Don  Kris

Don Kris

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ML-Agents 1.0 / Getting Started

ML-Agents 1.0 / Getting Started
Why NOW is the best time to get started with Machine Learning in Unity.
Unity’s Machine Learning framework ML-Agents has just released version 1.0.

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ML-Agents 1.0 / Getting Started

A Wrapper for Sembast and SQFlite to Enable Easy

FHIR_DB

This is really just a wrapper around Sembast_SQFLite - so all of the heavy lifting was done by Alex Tekartik. I highly recommend that if you have any questions about working with this package that you take a look at Sembast. He's also just a super nice guy, and even answered a question for me when I was deciding which sembast version to use. As usual, ResoCoder also has a good tutorial.

I have an interest in low-resource settings and thus a specific reason to be able to store data offline. To encourage this use, there are a number of other packages I have created based around the data format FHIR. FHIR® is the registered trademark of HL7 and is used with the permission of HL7. Use of the FHIR trademark does not constitute endorsement of this product by HL7.

Using the Db

So, while not absolutely necessary, I highly recommend that you use some sort of interface class. This adds the benefit of more easily handling errors, plus if you change to a different database in the future, you don't have to change the rest of your app, just the interface.

I've used something like this in my projects:

class IFhirDb {
  IFhirDb();
  final ResourceDao resourceDao = ResourceDao();

  Future<Either<DbFailure, Resource>> save(Resource resource) async {
    Resource resultResource;
    try {
      resultResource = await resourceDao.save(resource);
    } catch (error) {
      return left(DbFailure.unableToSave(error: error.toString()));
    }
    return right(resultResource);
  }

  Future<Either<DbFailure, List<Resource>>> returnListOfSingleResourceType(
      String resourceType) async {
    List<Resource> resultList;
    try {
      resultList =
          await resourceDao.getAllSortedById(resourceType: resourceType);
    } catch (error) {
      return left(DbFailure.unableToObtainList(error: error.toString()));
    }
    return right(resultList);
  }

  Future<Either<DbFailure, List<Resource>>> searchFunction(
      String resourceType, String searchString, String reference) async {
    List<Resource> resultList;
    try {
      resultList =
          await resourceDao.searchFor(resourceType, searchString, reference);
    } catch (error) {
      return left(DbFailure.unableToObtainList(error: error.toString()));
    }
    return right(resultList);
  }
}

I like this because in case there's an i/o error or something, it won't crash your app. Then, you can call this interface in your app like the following:

final patient = Patient(
    resourceType: 'Patient',
    name: [HumanName(text: 'New Patient Name')],
    birthDate: Date(DateTime.now()),
);

final saveResult = await IFhirDb().save(patient);

This will save your newly created patient to the locally embedded database.

IMPORTANT: this database will expect that all previously created resources have an id. When you save a resource, it will check to see if that resource type has already been stored. (Each resource type is saved in it's own store in the database). It will then check if there is an ID. If there's no ID, it will create a new one for that resource (along with metadata on version number and creation time). It will save it, and return the resource. If it already has an ID, it will copy the the old version of the resource into a _history store. It will then update the metadata of the new resource and save that version into the appropriate store for that resource. If, for instance, we have a previously created patient:

{
    "resourceType": "Patient",
    "id": "fhirfli-294057507-6811107",
    "meta": {
        "versionId": "1",
        "lastUpdated": "2020-10-16T19:41:28.054369Z"
    },
    "name": [
        {
            "given": ["New"],
            "family": "Patient"
        }
    ],
    "birthDate": "2020-10-16"
}

And we update the last name to 'Provider'. The above version of the patient will be kept in _history, while in the 'Patient' store in the db, we will have the updated version:

{
    "resourceType": "Patient",
    "id": "fhirfli-294057507-6811107",
    "meta": {
        "versionId": "2",
        "lastUpdated": "2020-10-16T19:45:07.316698Z"
    },
    "name": [
        {
            "given": ["New"],
            "family": "Provider"
        }
    ],
    "birthDate": "2020-10-16"
}

This way we can keep track of all previous version of all resources (which is obviously important in medicine).

For most of the interactions (saving, deleting, etc), they work the way you'd expect. The only difference is search. Because Sembast is NoSQL, we can search on any of the fields in a resource. If in our interface class, we have the following function:

  Future<Either<DbFailure, List<Resource>>> searchFunction(
      String resourceType, String searchString, String reference) async {
    List<Resource> resultList;
    try {
      resultList =
          await resourceDao.searchFor(resourceType, searchString, reference);
    } catch (error) {
      return left(DbFailure.unableToObtainList(error: error.toString()));
    }
    return right(resultList);
  }

You can search for all immunizations of a certain patient:

searchFunction(
        'Immunization', 'patient.reference', 'Patient/$patientId');

This function will search through all entries in the 'Immunization' store. It will look at all 'patient.reference' fields, and return any that match 'Patient/$patientId'.

The last thing I'll mention is that this is a password protected db, using AES-256 encryption (although it can also use Salsa20). Anytime you use the db, you have the option of using a password for encryption/decryption. Remember, if you setup the database using encryption, you will only be able to access it using that same password. When you're ready to change the password, you will need to call the update password function. If we again assume we created a change password method in our interface, it might look something like this:

class IFhirDb {
  IFhirDb();
  final ResourceDao resourceDao = ResourceDao();
  ...
    Future<Either<DbFailure, Unit>> updatePassword(String oldPassword, String newPassword) async {
    try {
      await resourceDao.updatePw(oldPassword, newPassword);
    } catch (error) {
      return left(DbFailure.unableToUpdatePassword(error: error.toString()));
    }
    return right(Unit);
  }

You don't have to use a password, and in that case, it will save the db file as plain text. If you want to add a password later, it will encrypt it at that time.

General Store

After using this for a while in an app, I've realized that it needs to be able to store data apart from just FHIR resources, at least on occasion. For this, I've added a second class for all versions of the database called GeneralDao. This is similar to the ResourceDao, but fewer options. So, in order to save something, it would look like this:

await GeneralDao().save('password', {'new':'map'});
await GeneralDao().save('password', {'new':'map'}, 'key');

The difference between these two options is that the first one will generate a key for the map being stored, while the second will store the map using the key provided. Both will return the key after successfully storing the map.

Other functions available include:

// deletes everything in the general store
await GeneralDao().deleteAllGeneral('password'); 

// delete specific entry
await GeneralDao().delete('password','key'); 

// returns map with that key
await GeneralDao().find('password', 'key'); 

FHIR® is a registered trademark of Health Level Seven International (HL7) and its use does not constitute an endorsement of products by HL7®

Use this package as a library

Depend on it

Run this command:

With Flutter:

 $ flutter pub add fhir_db

This will add a line like this to your package's pubspec.yaml (and run an implicit flutter pub get):

dependencies:
  fhir_db: ^0.4.3

Alternatively, your editor might support or flutter pub get. Check the docs for your editor to learn more.

Import it

Now in your Dart code, you can use:

import 'package:fhir_db/dstu2.dart';
import 'package:fhir_db/dstu2/fhir_db.dart';
import 'package:fhir_db/dstu2/general_dao.dart';
import 'package:fhir_db/dstu2/resource_dao.dart';
import 'package:fhir_db/encrypt/aes.dart';
import 'package:fhir_db/encrypt/salsa.dart';
import 'package:fhir_db/r4.dart';
import 'package:fhir_db/r4/fhir_db.dart';
import 'package:fhir_db/r4/general_dao.dart';
import 'package:fhir_db/r4/resource_dao.dart';
import 'package:fhir_db/r5.dart';
import 'package:fhir_db/r5/fhir_db.dart';
import 'package:fhir_db/r5/general_dao.dart';
import 'package:fhir_db/r5/resource_dao.dart';
import 'package:fhir_db/stu3.dart';
import 'package:fhir_db/stu3/fhir_db.dart';
import 'package:fhir_db/stu3/general_dao.dart';
import 'package:fhir_db/stu3/resource_dao.dart'; 

example/lib/main.dart

import 'package:fhir/r4.dart';
import 'package:fhir_db/r4.dart';
import 'package:flutter/material.dart';
import 'package:test/test.dart';

Future<void> main() async {
  WidgetsFlutterBinding.ensureInitialized();

  final resourceDao = ResourceDao();

  // await resourceDao.updatePw('newPw', null);
  await resourceDao.deleteAllResources(null);

  group('Playing with passwords', () {
    test('Playing with Passwords', () async {
      final patient = Patient(id: Id('1'));

      final saved = await resourceDao.save(null, patient);

      await resourceDao.updatePw(null, 'newPw');
      final search1 = await resourceDao.find('newPw',
          resourceType: R4ResourceType.Patient, id: Id('1'));
      expect(saved, search1[0]);

      await resourceDao.updatePw('newPw', 'newerPw');
      final search2 = await resourceDao.find('newerPw',
          resourceType: R4ResourceType.Patient, id: Id('1'));
      expect(saved, search2[0]);

      await resourceDao.updatePw('newerPw', null);
      final search3 = await resourceDao.find(null,
          resourceType: R4ResourceType.Patient, id: Id('1'));
      expect(saved, search3[0]);

      await resourceDao.deleteAllResources(null);
    });
  });

  final id = Id('12345');
  group('Saving Things:', () {
    test('Save Patient', () async {
      final humanName = HumanName(family: 'Atreides', given: ['Duke']);
      final patient = Patient(id: id, name: [humanName]);
      final saved = await resourceDao.save(null, patient);

      expect(saved.id, id);

      expect((saved as Patient).name?[0], humanName);
    });

    test('Save Organization', () async {
      final organization = Organization(id: id, name: 'FhirFli');
      final saved = await resourceDao.save(null, organization);

      expect(saved.id, id);

      expect((saved as Organization).name, 'FhirFli');
    });

    test('Save Observation1', () async {
      final observation1 = Observation(
        id: Id('obs1'),
        code: CodeableConcept(text: 'Observation #1'),
        effectiveDateTime: FhirDateTime(DateTime(1981, 09, 18)),
      );
      final saved = await resourceDao.save(null, observation1);

      expect(saved.id, Id('obs1'));

      expect((saved as Observation).code.text, 'Observation #1');
    });

    test('Save Observation1 Again', () async {
      final observation1 = Observation(
          id: Id('obs1'),
          code: CodeableConcept(text: 'Observation #1 - Updated'));
      final saved = await resourceDao.save(null, observation1);

      expect(saved.id, Id('obs1'));

      expect((saved as Observation).code.text, 'Observation #1 - Updated');

      expect(saved.meta?.versionId, Id('2'));
    });

    test('Save Observation2', () async {
      final observation2 = Observation(
        id: Id('obs2'),
        code: CodeableConcept(text: 'Observation #2'),
        effectiveDateTime: FhirDateTime(DateTime(1981, 09, 18)),
      );
      final saved = await resourceDao.save(null, observation2);

      expect(saved.id, Id('obs2'));

      expect((saved as Observation).code.text, 'Observation #2');
    });

    test('Save Observation3', () async {
      final observation3 = Observation(
        id: Id('obs3'),
        code: CodeableConcept(text: 'Observation #3'),
        effectiveDateTime: FhirDateTime(DateTime(1981, 09, 18)),
      );
      final saved = await resourceDao.save(null, observation3);

      expect(saved.id, Id('obs3'));

      expect((saved as Observation).code.text, 'Observation #3');
    });
  });

  group('Finding Things:', () {
    test('Find 1st Patient', () async {
      final search = await resourceDao.find(null,
          resourceType: R4ResourceType.Patient, id: id);
      final humanName = HumanName(family: 'Atreides', given: ['Duke']);

      expect(search.length, 1);

      expect((search[0] as Patient).name?[0], humanName);
    });

    test('Find 3rd Observation', () async {
      final search = await resourceDao.find(null,
          resourceType: R4ResourceType.Observation, id: Id('obs3'));

      expect(search.length, 1);

      expect(search[0].id, Id('obs3'));

      expect((search[0] as Observation).code.text, 'Observation #3');
    });

    test('Find All Observations', () async {
      final search = await resourceDao.getResourceType(
        null,
        resourceTypes: [R4ResourceType.Observation],
      );

      expect(search.length, 3);

      final idList = [];
      for (final obs in search) {
        idList.add(obs.id.toString());
      }

      expect(idList.contains('obs1'), true);

      expect(idList.contains('obs2'), true);

      expect(idList.contains('obs3'), true);
    });

    test('Find All (non-historical) Resources', () async {
      final search = await resourceDao.getAll(null);

      expect(search.length, 5);
      final patList = search.toList();
      final orgList = search.toList();
      final obsList = search.toList();
      patList.retainWhere(
          (resource) => resource.resourceType == R4ResourceType.Patient);
      orgList.retainWhere(
          (resource) => resource.resourceType == R4ResourceType.Organization);
      obsList.retainWhere(
          (resource) => resource.resourceType == R4ResourceType.Observation);

      expect(patList.length, 1);

      expect(orgList.length, 1);

      expect(obsList.length, 3);
    });
  });

  group('Deleting Things:', () {
    test('Delete 2nd Observation', () async {
      await resourceDao.delete(
          null, null, R4ResourceType.Observation, Id('obs2'), null, null);

      final search = await resourceDao.getResourceType(
        null,
        resourceTypes: [R4ResourceType.Observation],
      );

      expect(search.length, 2);

      final idList = [];
      for (final obs in search) {
        idList.add(obs.id.toString());
      }

      expect(idList.contains('obs1'), true);

      expect(idList.contains('obs2'), false);

      expect(idList.contains('obs3'), true);
    });

    test('Delete All Observations', () async {
      await resourceDao.deleteSingleType(null,
          resourceType: R4ResourceType.Observation);

      final search = await resourceDao.getAll(null);

      expect(search.length, 2);

      final patList = search.toList();
      final orgList = search.toList();
      patList.retainWhere(
          (resource) => resource.resourceType == R4ResourceType.Patient);
      orgList.retainWhere(
          (resource) => resource.resourceType == R4ResourceType.Organization);

      expect(patList.length, 1);

      expect(patList.length, 1);
    });

    test('Delete All Resources', () async {
      await resourceDao.deleteAllResources(null);

      final search = await resourceDao.getAll(null);

      expect(search.length, 0);
    });
  });

  group('Password - Saving Things:', () {
    test('Save Patient', () async {
      await resourceDao.updatePw(null, 'newPw');
      final humanName = HumanName(family: 'Atreides', given: ['Duke']);
      final patient = Patient(id: id, name: [humanName]);
      final saved = await resourceDao.save('newPw', patient);

      expect(saved.id, id);

      expect((saved as Patient).name?[0], humanName);
    });

    test('Save Organization', () async {
      final organization = Organization(id: id, name: 'FhirFli');
      final saved = await resourceDao.save('newPw', organization);

      expect(saved.id, id);

      expect((saved as Organization).name, 'FhirFli');
    });

    test('Save Observation1', () async {
      final observation1 = Observation(
        id: Id('obs1'),
        code: CodeableConcept(text: 'Observation #1'),
        effectiveDateTime: FhirDateTime(DateTime(1981, 09, 18)),
      );
      final saved = await resourceDao.save('newPw', observation1);

      expect(saved.id, Id('obs1'));

      expect((saved as Observation).code.text, 'Observation #1');
    });

    test('Save Observation1 Again', () async {
      final observation1 = Observation(
          id: Id('obs1'),
          code: CodeableConcept(text: 'Observation #1 - Updated'));
      final saved = await resourceDao.save('newPw', observation1);

      expect(saved.id, Id('obs1'));

      expect((saved as Observation).code.text, 'Observation #1 - Updated');

      expect(saved.meta?.versionId, Id('2'));
    });

    test('Save Observation2', () async {
      final observation2 = Observation(
        id: Id('obs2'),
        code: CodeableConcept(text: 'Observation #2'),
        effectiveDateTime: FhirDateTime(DateTime(1981, 09, 18)),
      );
      final saved = await resourceDao.save('newPw', observation2);

      expect(saved.id, Id('obs2'));

      expect((saved as Observation).code.text, 'Observation #2');
    });

    test('Save Observation3', () async {
      final observation3 = Observation(
        id: Id('obs3'),
        code: CodeableConcept(text: 'Observation #3'),
        effectiveDateTime: FhirDateTime(DateTime(1981, 09, 18)),
      );
      final saved = await resourceDao.save('newPw', observation3);

      expect(saved.id, Id('obs3'));

      expect((saved as Observation).code.text, 'Observation #3');
    });
  });

  group('Password - Finding Things:', () {
    test('Find 1st Patient', () async {
      final search = await resourceDao.find('newPw',
          resourceType: R4ResourceType.Patient, id: id);
      final humanName = HumanName(family: 'Atreides', given: ['Duke']);

      expect(search.length, 1);

      expect((search[0] as Patient).name?[0], humanName);
    });

    test('Find 3rd Observation', () async {
      final search = await resourceDao.find('newPw',
          resourceType: R4ResourceType.Observation, id: Id('obs3'));

      expect(search.length, 1);

      expect(search[0].id, Id('obs3'));

      expect((search[0] as Observation).code.text, 'Observation #3');
    });

    test('Find All Observations', () async {
      final search = await resourceDao.getResourceType(
        'newPw',
        resourceTypes: [R4ResourceType.Observation],
      );

      expect(search.length, 3);

      final idList = [];
      for (final obs in search) {
        idList.add(obs.id.toString());
      }

      expect(idList.contains('obs1'), true);

      expect(idList.contains('obs2'), true);

      expect(idList.contains('obs3'), true);
    });

    test('Find All (non-historical) Resources', () async {
      final search = await resourceDao.getAll('newPw');

      expect(search.length, 5);
      final patList = search.toList();
      final orgList = search.toList();
      final obsList = search.toList();
      patList.retainWhere(
          (resource) => resource.resourceType == R4ResourceType.Patient);
      orgList.retainWhere(
          (resource) => resource.resourceType == R4ResourceType.Organization);
      obsList.retainWhere(
          (resource) => resource.resourceType == R4ResourceType.Observation);

      expect(patList.length, 1);

      expect(orgList.length, 1);

      expect(obsList.length, 3);
    });
  });

  group('Password - Deleting Things:', () {
    test('Delete 2nd Observation', () async {
      await resourceDao.delete(
          'newPw', null, R4ResourceType.Observation, Id('obs2'), null, null);

      final search = await resourceDao.getResourceType(
        'newPw',
        resourceTypes: [R4ResourceType.Observation],
      );

      expect(search.length, 2);

      final idList = [];
      for (final obs in search) {
        idList.add(obs.id.toString());
      }

      expect(idList.contains('obs1'), true);

      expect(idList.contains('obs2'), false);

      expect(idList.contains('obs3'), true);
    });

    test('Delete All Observations', () async {
      await resourceDao.deleteSingleType('newPw',
          resourceType: R4ResourceType.Observation);

      final search = await resourceDao.getAll('newPw');

      expect(search.length, 2);

      final patList = search.toList();
      final orgList = search.toList();
      patList.retainWhere(
          (resource) => resource.resourceType == R4ResourceType.Patient);
      orgList.retainWhere(
          (resource) => resource.resourceType == R4ResourceType.Organization);

      expect(patList.length, 1);

      expect(patList.length, 1);
    });

    test('Delete All Resources', () async {
      await resourceDao.deleteAllResources('newPw');

      final search = await resourceDao.getAll('newPw');

      expect(search.length, 0);

      await resourceDao.updatePw('newPw', null);
    });
  });
} 

Download Details:

Author: MayJuun

Source Code: https://github.com/MayJuun/fhir/tree/main/fhir_db

#sqflite  #dart  #flutter 

伊藤  直子

伊藤 直子

1633693200

【 初心者向け】C言語でのマルチスレッド の概要

ニューヨークで働き、ウォール街中のプログラマーと話をしていると、ほとんどのリアルタイムプログラミングアプリケーションで期待される共通の知識の糸に気づきました。その知識はマルチスレッドとして知られています。私はプログラミングの世界を移動し、潜在的なプログラミング候補者にインタビューを行ったので、マルチスレッドについてほとんど知られていないことや、スレッドが適用される理由や方法に驚かされることは決してありません。Vance Morrisonによって書かれた一連の優れた記事で、MSDNはこの問題に対処しようとしました:(MSDNの8月号、すべての開発者がマルチスレッドアプリについて知っておくべきこと、および10月号はマルチスレッドでのローロック技術の影響を理解するを参照してください)。アプリ

この記事では、スレッド化、スレッド化が使用される理由、および.NETでのスレッド化の使用方法について紹介します。マルチスレッドの背後にある謎を完全に明らかにし、それを説明する際に、コード内の潜在的なスレッド障害を回避するのに役立つことを願っています。

スレッドとは何ですか?

すべてのアプリケーションは、少なくとも1つのスレッドで実行されます。では、スレッドとは何ですか?スレッドはプロセスにすぎません。私の推測では、糸という言葉は、織機で糸を織り上げる超自然的なミューズのギリシャ神話に由来していると思います。各糸は、誰かの人生の時間の道を表しています。あなたがその糸をいじると、あなたは人生の構造を乱したり、人生のプロセスを変えたりします。コンピューターでは、スレッドは時間の経過とともに移動するプロセスです。プロセスは一連の順次ステップを実行し、各ステップはコード行を実行します。ステップは連続しているため、各ステップには一定の時間がかかります。一連のステップを完了するのにかかる時間は、各プログラミングステップの実行にかかる時間の合計です。

マルチスレッドアプリケーションとは何ですか?

長い間、ほとんどのプログラミングアプリケーション(組み込みシステムプログラムを除く)はシングルスレッドでした。これは、アプリケーション全体でスレッドが1つしかないことを意味します。計算Bが完了するまで、計算Aを実行することはできません。プログラムはステップ1から始まり、最後のステップ(ステップ10と呼びます)に到達するまで順次続行します(ステップ2、ステップ3、ステップ4)。マルチスレッドアプリケーションを使用すると、複数のスレッドを実行できます。各スレッドは独自のプロセスで実行されます。したがって、理論的には、あるスレッドでステップ1を実行し、同時に別のスレッドでステップ2を実行できます。同時に、ステップ3を独自のスレッドで実行し、ステップ4を独自のスレッドで実行することもできます。したがって、ステップ1、ステップ2、ステップ3、およびステップ4は同時に実行されます。理論的には、4つのステップすべてがほぼ同時にかかった場合、シングルスレッドの実行にかかる時間の4分の1でプログラムを終了できます(4プロセッサマシンを使用していると仮定)。では、なぜすべてのプログラムがマルチスレッド化されていないのでしょうか。スピードとともに、あなたは複雑さに直面するからです。ステップ1がステップ2の情報に何らかの形で依存している場合を想像してみてください。ステップ1がステップ2の前に計算を終了した場合、またはその逆の場合、プログラムが正しく実行されない可能性があります。

珍しいアナロジー

マルチスレッドを考える別の方法は、人体を考慮することです。体の各器官(心臓、肺、肝臓、脳)はすべてプロセスに関与しています。各プロセスは同時に実行されています。各臓器がプロセスのステップとして実行された場合を想像してみてください。最初に心臓、次に脳、次に肝臓、次に肺です。私たちはおそらく死んでしまうでしょう。つまり、人体は1つの大きなマルチスレッドアプリケーションのようなものです。すべての臓器は同時に実行されるプロセスであり、これらのプロセスはすべて相互に依存しています。これらのプロセスはすべて、神経信号、血流、化学的トリガーを介して通信します。すべてのマルチスレッドアプリケーションと同様に、人体は非常に複雑です。一部のプロセスが他のプロセスから情報を取得しない場合、または特定のプロセスが遅くなったり速くなったりすると、医学的な問題が発生します。それか'

いつスレッド化するか

マルチスレッドは、プログラムをより効率的に実行したい状況で最もよく使用されます。たとえば、ウィンドウフォームプログラムの中に、実行に1秒以上かかり、繰り返し実行する必要のあるメソッド(method_Aと呼びます)が含まれているとします。プログラム全体が単一のスレッドで実行された場合、ボタンの押下が正しく機能しなかったり、入力が少し遅くなったりすることがあります。method_Aの計算量が多すぎると、ウィンドウフォームの特定の部分がまったく機能しないことに気付くかもしれません。この許容できないプログラムの動作は、プログラムにマルチスレッドが必要であることを示しています。スレッド化が必要になるもう1つの一般的なシナリオは、メッセージングシステムです。アプリケーションに多数のメッセージが送信されている場合は、メインの処理プログラムの実行と同時にそれらをキャプチャし、適切に配布する必要があります。重い処理を実行しているときに一連のメッセージを効率的にキャプチャすることはできません。そうしないと、メッセージを見逃す可能性があります。複数のスレッドは、複数のプロセスが同時に実行される組立ライン方式で使用することもできます。たとえば、プロセスがスレッドでデータを収集すると、1つのプロセスがデータをフィルタリングし、1つのプロセスがデータをデータベースと照合します。これらの各シナリオはマルチスレッドの一般的な使用法であり、シングルスレッドで実行されている同様のアプリケーションのパフォーマンスを大幅に向上させます。そうしないと、メッセージを見逃す可能性があるためです。複数のスレッドは、複数のプロセスが同時に実行される組立ライン方式で使用することもできます。たとえば、プロセスがスレッドでデータを収集すると、1つのプロセスがデータをフィルタリングし、1つのプロセスがデータをデータベースと照合します。これらの各シナリオはマルチスレッドの一般的な使用法であり、シングルスレッドで実行されている同様のアプリケーションのパフォーマンスを大幅に向上させます。そうしないと、メッセージを見逃す可能性があるためです。複数のスレッドは、複数のプロセスが同時に実行される組立ライン方式で使用することもできます。たとえば、プロセスがスレッドでデータを収集すると、1つのプロセスがデータをフィルタリングし、1つのプロセスがデータをデータベースと照合します。これらの各シナリオはマルチスレッドの一般的な使用法であり、シングルスレッドで実行されている同様のアプリケーションのパフォーマンスを大幅に向上させます。

スレッドしない場合

初心者のプログラマーが最初にスレッド化を学ぶとき、彼らはプログラムでスレッド化を使用する可能性に魅了される可能性があります。彼らは実際にスレッドハッピーになるかもしれません  詳しく説明させてください、

1日目)プログラマーは、スレッドを生成できることを学び、プログラムで1つの新しいスレッドCool!の作成を開始します 。

2日目)プログラマーは、「プログラムの一部で他のスレッドを生成することで、これをさらに効率的にすることができます!」と言います。

3日目)P:「わあ、スレッド内でスレッドをフォークすることもでき、本当に効率が向上します!!」

4日目)P:「奇妙な結果が出ているようですが、それは問題ありません。今は無視します。」

5日目)「うーん、widgetX変数に値がある場合もありますが、まったく設定されていないように見える場合もあります。コンピューターが機能していないため、デバッガーを実行するだけです」。

9日目)「このくそったれ(より強い言語)プログラムはあちこちでジャンプしています!!何が起こっているのか理解できません!」

2週目)時々、プログラムはただそこに座って、まったく何もしません!ヘルプ!!!!!

おなじみですか?マルチスレッドプログラムを初めて設計しようとしたほとんどの人は、スレッドの設計知識が豊富であっても、おそらくこれらの毎日の箇条書きの少なくとも1つまたは2つを経験したことがあります。スレッド化が悪いことだとほのめかしているわけではありません。プログラムでスレッド化の効率を上げるプロセスでは、非常に注意してください。  シングルスレッドプログラムとは異なり、同時に多くのプロセスを処理しているため、複数の従属変数を持つ複数のプロセスを追跡するのは非常に難しい場合があります。ジャグリングと同じようにマルチスレッドを考えてください。手で1つのボールをジャグリングするのは(退屈ではありますが)かなり簡単です。ただし、これらのボールのうち2つを空中に置くように挑戦された場合、その作業は少し難しくなります。3、4、および5の場合、ボールは次第に難しくなります。ボールの数が増えると、実際にボールを落とす可能性が高くなります。 一度にたくさんのボールをジャグリングするには、知識、スキル、正確なタイミングが必要です。マルチスレッドもそうです。 

マルチスレッド

図1-マルチスレッドはジャグリングプロセスのようなものです

 
スレッディングの問題

プログラム内のすべてのプロセスが相互に排他的である場合、つまり、プロセスが他のプロセスにまったく依存していない場合、複数のスレッド化は非常に簡単で、問題はほとんど発生しません。各プロセスは、他のプロセスに煩わされることなく、独自のハッピーコースで実行されます。ただし、複数のプロセスが他のプロセスによって使用されているメモリの読み取りまたは書き込みを行う必要がある場合、問題が発生する可能性があります。たとえば、プロセス#1とプロセス#2の2つのプロセスがあるとします。両方のプロセスが変数Xを共有します。スレッドプロセス#1が最初に値5の変数Xを書き込み、スレッドプロセス#2が次に値-3の変数Xを書き込む場合、Xの最終値は-3です。ただし、プロセス#2が最初に値-3の変数Xを書き込み、次にプロセス#1が値5の変数Xを書き込む場合、Xの最終値は5です。Xを設定できるプロセスがプロセス#1またはプロセス#2の知識を持っていない場合、Xは、最初にXに到達したスレッドに応じて異なる最終値になる可能性があります。シングルスレッドプログラムでは、すべてが順番に続くため、これが発生する可能性はありません。シングルスレッドプログラムでは、並列に実行されているプロセスがないため、Xは常に最初にメソッド#1によって設定され(最初に呼び出された場合)、次にメソッド#2によって設定されます。シングルスレッドプログラムには驚きはありません。それはステップバイステップです。マルチスレッドプログラムを使用すると、2つのスレッドが同時にコードを入力し、結果に大混乱をもたらす可能性があります。スレッドの問題は、同時に実行されている別のスレッドが同じコードを入力して共有データを操作できるようにしながら、共有メモリにアクセスする1つのスレッドを制御する何らかの方法が必要なことです。Xは、どのスレッドが最初にXに到達したかによって、最終的に異なる最終値になる可能性があります。シングルスレッドプログラムでは、すべてが順番に続くため、これが発生する可能性はありません。シングルスレッドプログラムでは、並列に実行されているプロセスがないため、Xは常に最初にメソッド#1によって設定され(最初に呼び出された場合)、次にメソッド#2によって設定されます。シングルスレッドプログラムには驚きはありません。それはステップバイステップです。マルチスレッドプログラムを使用すると、2つのスレッドが同時にコードを入力し、結果に大混乱をもたらす可能性があります。スレッドの問題は、同時に実行されている別のスレッドが同じコードを入力して共有データを操作できるようにしながら、共有メモリにアクセスする1つのスレッドを制御する何らかの方法が必要なことです。Xは、どのスレッドが最初にXに到達したかによって、最終的に異なる最終値になる可能性があります。シングルスレッドプログラムでは、すべてが順番に続くため、これが発生する可能性はありません。シングルスレッドプログラムでは、並列に実行されているプロセスがないため、Xは常に最初にメソッド#1によって設定され(最初に呼び出された場合)、次にメソッド#2によって設定されます。シングルスレッドプログラムには驚きはありません。それはステップバイステップです。マルチスレッドプログラムを使用すると、2つのスレッドが同時にコードを入力し、結果に大混乱をもたらす可能性があります。スレッドの問題は、同時に実行されている別のスレッドが同じコードを入力して共有データを操作できるようにしながら、共有メモリにアクセスする1つのスレッドを制御する何らかの方法が必要なことです。すべてが順番に続くため、これが発生する可能性はありません。シングルスレッドプログラムでは、並列に実行されているプロセスがないため、Xは常に最初にメソッド#1によって設定され(最初に呼び出された場合)、次にメソッド#2によって設定されます。シングルスレッドプログラムには驚きはありません。それはステップバイステップです。マルチスレッドプログラムを使用すると、2つのスレッドが同時にコードを入力し、結果に大混乱をもたらす可能性があります。スレッドの問題は、同時に実行されている別のスレッドが同じコードを入力して共有データを操作できるようにしながら、共有メモリにアクセスする1つのスレッドを制御する何らかの方法が必要なことです。すべてが順番に続くため、これが発生する可能性はありません。シングルスレッドプログラムでは、並列に実行されているプロセスがないため、Xは常に最初にメソッド#1によって設定され(最初に呼び出された場合)、次にメソッド#2によって設定されます。シングルスレッドプログラムには驚きはありません。それはステップバイステップです。マルチスレッドプログラムを使用すると、2つのスレッドが同時にコードを入力し、結果に大混乱をもたらす可能性があります。スレッドの問題は、同時に実行されている別のスレッドが同じコードを入力して共有データを操作できるようにしながら、共有メモリにアクセスする1つのスレッドを制御する何らかの方法が必要なことです。(最初に呼び出された場合)次に、メソッド#2で設定します。シングルスレッドプログラムには驚きはありません。それはステップバイステップです。マルチスレッドプログラムを使用すると、2つのスレッドが同時にコードを入力し、結果に大混乱をもたらす可能性があります。スレッドの問題は、同時に実行されている別のスレッドが同じコードを入力して共有データを操作できるようにしながら、共有メモリにアクセスする1つのスレッドを制御する何らかの方法が必要なことです。(最初に呼び出された場合)次に、メソッド#2で設定します。シングルスレッドプログラムには驚きはありません。それはステップバイステップです。マルチスレッドプログラムを使用すると、2つのスレッドが同時にコードを入力し、結果に大混乱をもたらす可能性があります。スレッドの問題は、同時に実行されている別のスレッドが同じコードを入力して共有データを操作できるようにしながら、共有メモリにアクセスする1つのスレッドを制御する何らかの方法が必要なことです。 

スレッドセーフ

3つのボールをジャグリングするたびに、空中のボールが、自然の異常によって、すでに右手に座っているボールが投げられるまで、右手に到達することが決して許されなかったと想像してみてください。少年、ジャグリングはずっと簡単でしょう!これがスレッドセーフのすべてです。私たちのプログラムでは、もう一方のスレッドがビジネスを終了している間、一方のスレッドをコードブロック内で待機させます。スレッドのブロックまたはスレッドの同期と呼ばれるこのアクティビティにより、プログラム内で実行される同時スレッドのタイミングを制御できます。C#では、メモリの特定の部分(通常はオブジェクトのインスタンス)をロックし、オブジェクトを使用して別のスレッドが完了するまで、スレッドがこのオブジェクトのメモリのコードを入力できないようにします。今ではおそらくコード例を渇望しているので、ここに行きます。

2スレッドのシナリオを見てみましょう。この例では、C#でスレッド1とスレッド2の2つのスレッドを作成します。どちらも、独自のwhileループで実行されます。スレッドは何の役にも立ちません。どのスレッドに属しているかを示すメッセージを出力するだけです。_threadOutputと呼ばれる共有メモリクラスメンバーを利用します。_threadOutputには、実行中のスレッドに基づいてメッセージが割り当てられます。リスト#1は、それぞれDisplayThread1とDisplayThread2に含まれる2つのスレッドを示しています。

リスト1-メモリ内で共通の変数を共有する2つのスレッドを作成する

// shared memory variable between the two threads  
// used to indicate which thread we are in  
private string _threadOutput = "";  
  
/// <summary>  
/// Thread 1: Loop continuously,  
/// Thread 1: Displays that we are in thread 1  
/// </summary>  
void DisplayThread1()  
{  
      while (_stopThreads == false)  
      {  
            Console.WriteLine("Display Thread 1");  
  
            // Assign the shared memory to a message about thread #1  
            _threadOutput = "Hello Thread1";  
  
  
            Thread.Sleep(1000);  // simulate a lot of processing   
  
            // tell the user what thread we are in thread #1, and display shared memory  
            Console.WriteLine("Thread 1 Output --> {0}", _threadOutput);  
  
      }  
}  

/// <summary>  
/// Thread 2: Loop continuously,  
/// Thread 2: Displays that we are in thread 2  
/// </summary>  
void DisplayThread2()  
{  
      while (_stopThreads == false)  
      {  
        Console.WriteLine("Display Thread 2");  
  
  
       // Assign the shared memory to a message about thread #2  
        _threadOutput = "Hello Thread2";  
  
  
        Thread.Sleep(1000);  // simulate a lot of processing  
  
       // tell the user we are in thread #2  
        Console.WriteLine("Thread 2 Output --> {0}", _threadOutput);  
  
      }  
}
Class1()  
{  
      // construct two threads for our demonstration;  
      Thread thread1 = new Thread(new ThreadStart(DisplayThread1));  
      Thread thread2 = new Thread(new ThreadStart(DisplayThread2));  
  
      // start them  
      thread1.Start();  
      thread2.Start();  
}

このコードの結果を図2に示します。結果を注意深く見てください。プログラムが驚くべき出力を提供することに気付くでしょう(これをシングルスレッドの考え方から見た場合)。_threadOutputを、それが属するスレッドに対応する番号の文字列に明確に割り当てましたが、コンソールでは次のように表示されます。

C#でのスレッド化

図2-2スレッドの例からの異常な出力。

私たちのコードから次のことが期待されます、

スレッド1の出力->ハロースレッド1とスレッド2の出力->ハロースレッド2ですが、ほとんどの場合、結果は完全に予測できません。 

スレッド2の出力->ハロースレッド1とスレッド1の出力->ハロースレッド2が表示されることがあります。スレッドの出力がコードと一致しません。コードを見て、それを目で追っていますが、_threadOutput = "Hello Thread 2"、Sleep、Write "Thread 2-> Hello Thread 2"ですが、このシーケンスで必ずしも最終結果が得られるとは限りません。 

説明

このようなマルチスレッドプログラムでは、理論的にはコードが2つのメソッドDisplayThread1とDisplayThread2を同時に実行しているためです。各メソッドは変数_threadOutputを共有します。したがって、_threadOutputにはスレッド#1で値 "Hello Thread1"が割り当てられ、2行後にコンソールに_threadOutputが表示されますが、スレッド#1がそれを割り当てて表示する時間の間のどこかで、スレッド#2が_threadOutputを割り当てる可能性があります。値「HelloThread2」。これらの奇妙な結果が発生する可能性があるだけでなく、図2に示す出力に見られるように、非常に頻繁に発生します。この痛みを伴うスレッドの問題は、競合状態として知られるスレッドプログラミングで非常に一般的なバグです。 この例は、よく知られているスレッドの問題の非常に単純な例です。この問題は、参照されている変数やスレッドセーフでない変数を指すコレクションなどを介して、プログラマーからはるかに間接的に隠されている可能性があります。図2では症状は露骨ですが、競合状態は非常にまれにしか現れず、1分に1回、1時間に1回、または3日後に断続的に現れる可能性があります。レースは、その頻度が低く、再現が非常に難しいため、おそらくプログラマーにとって最悪の悪夢です。

レースに勝つ

競合状態を回避する最善の方法は、スレッドセーフなコードを作成することです。コードがスレッドセーフである場合、いくつかの厄介なスレッドの問題が発生するのを防ぐことができます。スレッドセーフなコードを書くためのいくつかの防御策があります。1つは、メモリの共有をできるだけ少なくすることです。クラスのインスタンスを作成し、それが1つのスレッドで実行され、次に同じクラスの別のインスタンスを作成し、それが別のスレッドで実行される場合、静的変数が含まれていない限り、クラスはスレッドセーフです。 。2つのクラスはそれぞれ、独自のフィールド用に独自のメモリを作成するため、共有メモリはありません。クラスに静的変数がある場合、またはクラスのインスタンスが他の複数のスレッドによって共有されている場合は、他のクラスがその変数の使用を完了するまで、一方のスレッドがその変数のメモリを使用できないようにする方法を見つける必要があります。ロック。  C#を使用すると、Monitorクラスまたはlock {}構造のいずれかを使用してコードをロックできます。(lock構造は、実際にはtry-finallyブロックを介してMonitorクラスを内部的に実装しますが、プログラマーからこれらの詳細を隠します)。リスト1の例では、共有_threadOutput変数を設定した時点から、コンソールへの実際の出力まで、コードのセクションをロックできます。コードのクリティカルセクションを両方のスレッドでロックして、どちらか一方に競合が発生しないようにします。メソッド内をロックする最も速くて汚い方法は、このポインターをロックすることです。このポインタをロックすると、クラスインスタンス全体がロックされるため、ロック内でクラスのフィールドを変更しようとするスレッドはすべてブロックされます。。ブロッキングとは、変数を変更しようとしているスレッドが、ロックされたスレッドでロックが解除されるまで待機することを意味します。スレッドは、lock {}構造の最後のブラケットに到達すると、ロックから解放されます。

リスト2-2つのスレッドをロックして同期する

/// <summary>  
/// Thread 1, Displays that we are in thread 1 (locked)  
 /// </summary>  
 void DisplayThread1()  
 {  
       while (_stopThreads == false)  
       {  
          // lock on the current instance of the class for thread #1  
             lock (this)  
             {  
                   Console.WriteLine("Display Thread 1");  
                   _threadOutput = "Hello Thread1";  
                   Thread.Sleep(1000);  // simulate a lot of processing  
                   // tell the user what thread we are in thread #1  
                   Console.WriteLine("Thread 1 Output --> {0}", _threadOutput);  
             }// lock released  for thread #1 here  
       }   
 }  

/// <summary>  
/// Thread 1, Displays that we are in thread 1 (locked)  
 /// </summary>  
 void DisplayThread2()  
 {  
       while (_stopThreads == false)  
       {  
  
           // lock on the current instance of the class for thread #2  
             lock (this)  
             {  
                   Console.WriteLine("Display Thread 2");  
                   _threadOutput = "Hello Thread2";  
                   Thread.Sleep(1000);  // simulate a lot of processing  
                   // tell the user what thread we are in thread #1  
                   Console.WriteLine("Thread 2 Output --> {0}", _threadOutput);  
             } // lock released  for thread #2 here  
       }   
 }

2つのスレッドをロックした結果を図3に示します。すべてのスレッド出力が適切に同期されていることに注意してください。スレッド1の出力->ハロースレッド1とスレッド2の出力->ハロースレッド2という結果が常に表示されます。ただし、スレッドのロックにはコストがかかることに注意してください。スレッドをロックすると、ロックが解除されるまで他のスレッドを強制的に待機させます。本質的に、他のスレッドが共有メモリの使用を待機している間、最初のスレッドはプログラムで何もしていないため、プログラムの速度が低下しました。したがって、ロックは慎重に使用する必要があります。共有メモリに関与していない場合は、コード内にあるすべてのメソッドをロックするだけではいけません。また、ロックを使用するときは注意してください。スレッド#1がスレッド#2によってロックが解放されるのを待っている状況に陥りたくないからです。スレッド#2は、スレッド#1によってロックが解放されるのを待っています。この状況が発生すると、両方のスレッドがブロックされ、プログラムがフリーズしたように見えます。この状況はとして知られていますデッドロックが発生し、プログラム内の予測できない断続的な期間にも発生する可能性があるため、競合状態とほぼ同じくらい悪い状況です。 

  C#でのスレッド化

  図3-ロックを使用したデュアルスレッドプログラムの同期

代替ソリューション

.NETは、スレッドの制御に役立つ多くのメカニズムを提供します。別のスレッドが共有メモリの一部を処理している間、スレッドをブロックしたままにする別の方法は、AutoResetEventを使用することです。AutoResetEventクラスには、SetとWaitOneの2つのメソッドがあります。これらの2つの方法は、スレッドのブロックを制御するために一緒に使用できます。AutoResetEventがfalseで初期化されると、プログラムは、AutoResetEventでSetメソッドが呼び出されるまで、WaitOneを呼び出すコード行で停止します。AutoResetEventでSetメソッドが実行されると、スレッドのブロックが解除され、WaitOneを超えて続行できるようになります。次回WaitOneが呼び出されると、自動的にリセットされるため、プログラムは、WaitOneメソッドが実行されているコード行で再び待機(ブロック)します。この「停止とトリガー」を使用できます Setを呼び出して、別のスレッドがブロックされたスレッドを解放する準備ができるまで、あるスレッドをブロックするメカニズム。リスト3は、AutoResetEventを使用して、ブロックされたスレッドが待機し、ブロックされていないスレッドが実行されてコンソールに_threadOutputを表示している間に、互いにブロックする同じ2つのスレッドを示しています。最初に、_blockThread1はfalseを通知するように初期化され、_blockThread2はtrueを通知するように初期化されます。これは、_blockThread2がDisplayThread_2のループを最初に通過するときに、WaitOne呼び出しを続行できるようになる一方で、_blockThread1はDisplayThread_1のWaitOne呼び出しをブロックすることを意味します。_blockThread2がスレッド2のループの終わりに達すると、スレッド1をブロックから解放するためにSetを呼び出して_blockThread1に信号を送ります。次に、スレッド2は、スレッド1がループの終わりに到達して_blockThread2でSetを呼び出すまで、WaitOne呼び出しで待機します。スレッド1で呼び出されたセットはスレッド2のブロックを解放し、プロセスが再開されます。両方のAutoResetEvents(_blockThread1と_blockThread2)を最初にfalseを通知するように設定した場合、両方のスレッドが互いにトリガーする機会なしにループの進行を待機し、デッドロック。 

リスト3-あるいは、AutoResetEventでスレッドをブロックする

AutoResetEvent _blockThread1 = new AutoResetEvent(false);  
AutoResetEvent _blockThread2 = new AutoResetEvent(true);  
  
/// <summary>  
/// Thread 1, Displays that we are in thread 1  
/// </summary>  
void DisplayThread_1()  
{  
      while (_stopThreads == false)  
      {  
               // block thread 1  while the thread 2 is executing  
                _blockThread1.WaitOne();   
  
                // Set was called to free the block on thread 1, continue executing the code  
                  Console.WriteLine("Display Thread 1");  
  
                  _threadOutput = "Hello Thread 1";  
                  Thread.Sleep(1000);  // simulate a lot of processing  
  
                   // tell the user what thread we are in thread #1  
                  Console.WriteLine("Thread 1 Output --> {0}", _threadOutput);  
  
                // finished executing the code in thread 1, so unblock thread 2  
                  _blockThread2.Set();  
      }  
}  
  
/// <summary>  
/// Thread 2, Displays that we are in thread 2  
/// </summary>  
void DisplayThread_2()  
{  
      while (_stopThreads == false)  
      {  
            // block thread 2  while thread 1 is executing  
                  _blockThread2.WaitOne();   
  
            // Set was called to free the block on thread 2, continue executing the code  
                  Console.WriteLine("Display Thread 2");  
  
                  _threadOutput = "Hello Thread 2";  
                  Thread.Sleep(1000);  // simulate a lot of processing  
  
                   // tell the user we are in thread #2  
                  Console.WriteLine("Thread 2 Output --> {0}", _threadOutput);   
  
            // finished executing the code in thread 2, so unblock thread 1  
                _blockThread1.Set();  
      }  
} 

 

リスト3で生成される出力は、図3に示すロックコードと同じ出力ですが、AutoResetEventを使用すると、現在のスレッドが処理を完了したときに、あるスレッドが別のスレッドに通知する方法をより動的に制御できます。

結論

マイクロプロセッサの速度の理論的限界を押し上げているため、テクノロジは、コンピュータテクノロジの速度とパフォーマンスを最適化できる新しい方法を見つける必要があります。マルチプロセッサチップの発明と並列プログラミングへの侵入により、マルチスレッドを理解することで、ムーアの法則に挑戦し続けるために必要な利点をもたらすこれらのより最近のテクノロジーを処理するために必要なパラダイムに備えることができます。C#と.NETは、マルチスレッドと並列処理をサポートする機能を提供します。これらのツールを上手に活用する方法を理解すれば、私たち自身の日々のプログラミング活動において、将来のこれらのハードウェアの約束に備えることができます。一方、シャープなあなたができるので、スレッドのあなたの知識エン.NET可能性を。 

リンク:https://www.c-sharpcorner.com/article/introduction-to-multithreading-in-C-Sharp/

#csharp 

Best Review

1629825646

Design Beast Review & OTO Link

Design Beast Review & OTOs + $20k Bonuses

CHECK BONUSES & GRAB IT AT: https://bit.ly/3yhtcqi

Welcome to my Design Beast Review A Very warm welcome to my DesignBeast Review Here You Will Find Honest Opinion About The Design Beast Whether It is A Right Fit For You or not also I Have Covered All Working processes of DesignBeast, Live Video Demo, features Pros & Cons & All Design Beast OTO details.

Govind Rana Here Stay Till the End Of This Review I Have included $20k Bonuses At the end Of DesignBeast Review

DesignBeast Review – World finest graphic designing & animation software that will come into existence in some days. If you are searching for DesignBeast Review then this is the right platform to get in-depth information and the truth for Design Beast Review. An AI-based designing software that enables the 3D designing technology to you.

I am pretty much excited to share my point of view about the design beast. and this is because I want to meet you to the high technology graphics software.

This software is going to launch on 26 Aug. 2021 by the very famous vendor Paul Ponna and this time he is launching is 2 years of efforts on this amazing app. So do believe me without any doubt, here I only share the actual facts for Designbeast Review.

At this time the limited information is available on the web so I have included the creator of DesignBeast, Paul Ponna’s previous launches, what is DesignBeast, features & benefits, examples, who will best fit for this app, pros & cons, included with a huge bonuses.

Discount will be rolling out from 26th August

(fingers crossed till its launch because it is the launch beyond expectations)

Design Beast Review – Overview

  • Creator: Paul Ponna
  • Product Name: DesignBeast
  • Launch Date – 2021-Aug-24
  • Launch Timing – 11:00 EDT
  • Pricing – $67
  • Official Website – Visit
  • Money-Back Guarantee- Information Not Available
  • Category – Graphic Designing
  • Training – Yes, Available
  • Bonuses – Techevoke Special Bonuses Available

About Paul Ponna the vendor & Creator of DesignBeast

Paul Ponna is an entrepreneur and a digital geek in the internet marketing niche. His previous launches were hit the market products and were evergreen. No comparison of his products because he knows what is a need in today’s market and how online marketers will get benefited from online technologies.

So let’s have a look at Paul Ponna’s previous hits in the saas industry.

  1. DoodleMaker – This is the doodle video maker and the popular software on JVZoo that is the biggest launch in the history of internet marketing software. With a doodle maker, you can create studio-quality doodle videos with this application.
  2. VideoCreator – A readymade video editing app that is more authentic than existing video editing software. No more templates creation is required and no extra efforts to make and you can make exciting effects with videocreator.
  3. There is more software that has been launched by Paul Ponna…
  • DoodleMaker
  • Avatar Builder
  • VideoCreator
  • DesignBeast (available on 26th Aug)

Paul Ponna is a tech entrepreneur and he was started his journey from his 18 and with a website and hosting spending only $20. And he is a millionaire and frequently launches products that are really amazing and useful.

So not further delays let come to the designbeast review and let’s talk about what will be this software and how can you get benefited from this.

What is Design Beast?

Design beast is a software that comes with 6 world-class designing technology, and with those 6 modules, you can fulfill your graphics needs in just 1 price tag.

DesignBeast is a software that is responsible for multipurpose designs and better technology including these below-mentioned modules.

  1. Design Automation App #1– All in One Design and Mockup Engine
  2. Design Automation App #1– 3D Live Motion Photos
  3. Design Automation App #1– Magic Object Remover
  4. Design Automation App #1– 1-Click Background Removal
  5. Design Automation App #1– Slick Image Editor
  6. Design Automation App #1– AI Logo Creator

This is app bundle is fully loaded with advanced graphics features that are essential for making high-quality posts, infographics, motion pictures, 3D banners, and more.

Here are all modules explanations of DesignBeast

So this is clear this app has various technologies that are responsible for advanced editing and professional graphical designs. So here is the module’s explanation.

  1. All in One Design and mockup Engine

This is a designs library, not an ordinary image or premade design library. All elements are customizable and you can create any of your imagination with this design and mockup engine.

7000+ ready-to-use customizable designs and mockups are available in this module. Just head over to the DesignBeast software and you will get the professional DFY designs and mockups for your graphics need.

There are for all social apps, means available in various sizes.

2. 3D Live Motion Photos

Now you can convert a still, boring photo to a live, 3D effect photo with the A.I. technology of DesignBeast. With this effect, you can engage with your audience in a more effective manner.

And you all know that a moving object with a visual effect is 10x more engaging than an ordinary graphical image. with this technology, you can grab the attention of your customers and get more clicks on your sales platform.

3. Magic Object Removal Tool

Most of the time we need to remove some object or any person from any of the selected images and this module will give you access to select the required object or person and the remove that thing is just one click.

The feature Paul Ponna offers in his software is rarely available on any other software. With only one click the magic happens and the object will be removed.

4. 1-Click Background Removal

Because the software has technology that is based on AI and Machine Learning. So it auto-detects the edges and objects in your photos and automatically erases the background from any photo.

You don’t need to make extra effects just select the 1 click background removal option and click on the image background and it will vanish within seconds.

5. Slick Image Editor

This has the multi-feature of basic editing for any photo. Just like edit, crop, short, effects, blur, and more. You don’t need to go for different apps to perform different tasks every time.

You can convert any still normal photo to a high-class visual and ready-to-use, ready-to-print photo with this module.

6. Artificial Intelligence Logo Creator

An AI logo creator, not just a free tool that is available in the online market but it is quite effective and useful for you to generate any kind of logo. You can now bulk-create 50 logo variations for any brand in 3 easy steps.

All designs are fully customizable, also a single object is customizable with this app.

How DesignBeast will fire in the saas market?

In this section of DesignBeast Review, I am sharing its popularity, hype, and the vendor name-fame with you, so that you can evaluate its worth.

Just because you need a better, time-saving, authentic, graphic designing and animation software that will fulfill your professional graphics need for online marketing.

Because paul Ponna is a tech entrepreneur and he knows what is write to tab the market and what should be the next useful tool for every marketer.

DesignBeast is now going to be a popular one from the software list of its vendor. No matter what competitors of DesignBeast will say about this software. But as a consumer and a digital marketer, I am pretty much excited for its official launch.

DesignBeast Features & Benefits

If you want to create designs for Social media, websites, e-commerce sites, local businesses, promos, and advertising then focus on the features & benefits of DesignBeast Review, so that you can evaluate its actual strength.

 A.I. & Machine Learning Technology

This is the platform that suggests automatically the designs, objects, effects & more things that are based on your needs and the design frame you choose.

Automate design tasks with machine learning and artificial intelligence to leapfrog your competition and maximize revenues.

 6 Apps in the Price of One

There is no comparison of this app in the online market because the bundle of 6 apps and those apps are highly authentic useful in today’s competitive marketing world.

You can replace multiple graphics apps from one that is DesignBeast and you need to replace it if you want to save your money and time.

 Multilingual

This app is available in multi-languages, and with this feature, it doesn’t matter from where you are in this world.

It enables you to sell your service towards the globe and also give you the access to create graphical content in your local language.

 Commercial and resell rights available

Commercial licensing brings you to another stage of selling your services to clients. Now you can freely sell all generated content to your clients in the market. Also charge extra fees according to your skills and set your service on commercial platforms.

 Copywrite free assets and resources

Assets that are really expensive and everyone even I needs to purchase from the online market and those services are very expensive for all of us. But now all are available at one place that is design beast, you will get premium royalty-free images, icons, backgrounds & animations.

 Save Time and money

You can build world-class designs in minutes and all designs are professional, in starting you need to learn some lessons and practice to perform with DesignBeast membersarea.

 Dynamic Visual Effects

The effects offered by this software is so amazing and fully customizable so that I have given the term dynamic. All things are editable and ready to use.

Is there are any skills required to work with DesignBeast?

Designbeast is a DFY editable templates advanced graphic design software that will suggest to you the designs from its A.I. and machine learning technology. So I am sure you don’t need any advanced skills to use DesignBeast.

But to be honest, you need to work on these soft skills.

  1. Knowledge of using basic online apps.
  2. The mindset to Selecting the best
  3. Knowledge of colors
  4. Knowledge of graphics
  5. Understanding of designs
  6. Branding

And there are most soft skills required.

Design Beast Review – Who will be fit for this software?

So now in this series, it’s time to share the industry people who are best fit for this software that is Designbeast. And after lots of research and analysis, I decided to include these professionals in the DesignBeast audience. I am happy to share my point views in this DesignBeast Review.

  • Graphic Designers
  • Digital Marketers
  • Bloggers.
  • Vloggers
  • Youtubers
  • Media Agency
  • Advertising agency
  • Local Businesses
  • Ecommerce Players

DesignBeast Review – Pros & Cons

I have shared the sure short pros and cons for this revolutionary software. But there are some cons also available. After reviewing the product, as a marketer, I also realized this has lots of pros and some cons available in the market.

Pros

  • 6 modules in 1 app
  • 3d photo creation technology with AI and machine learning
  • Background and object removal technology.
  • Designs library over 7000
  • Kindly support team.
  • Trustable vendor
  • 30 Days money back gaurantee.
  • And more…

Cons

  • Some modules are more useful than 1 or 2 other modules.
  • You cannot download the software to your computer or on a desktop.
  • No more cons I have found for this software.

Design Beast OTOs/Upgrades

Here are the details of its upgrade, so that you can utilize all its advanced features. In this DesignBeast Review, I have mentioned the name and price of OTOs, and the rest of the details will be available soon.

Front End: DesignBeast Commercial

Price – $47 Onetime

  • Six Designs App For Price of One
  • Mockup Designer App
  • AI Logo Maker App
  • 1-Click Background Removal App
  • Live Motion Photos App
  • Multi-Purpose Image Editor App
  • Magic Object Removal App
  • 7000+ Ready-to-Use Templates
  • Millions of Royalty-Free Images
  • Copyright-Free Vectors & Icons
  • Hundreds of Fonts
  • Multi-Lingual Support
  • Step-by-Step Video Training
  • Commercial License
  • Sell The Designs For Profit
  • Facebook Group Access
  • Skype Mentorship Group Access
  • 8 Week Training Webinars

OTO#1: DesignBeast Elite

Price – $49 Onetime

Get access to additional features worth thousands. 10X your results, sales and profits and get ahead of the competition and other DesignBeast customers. 

  • Unlock 2,000 additional ready-to-use templates
  • Get 80 new templates added to your account each month for 1 year. (no monthly or yearly fees.)
  • Thousands of Premium Text Effects and Animations
  • Millions of Premium Royalty Free Design Assets, Icons and vectors.
  • Millions of Copyright-Free Image
  • Priority Future Software Updates

OTO#2: DesignBeast Agency

Price – $67

Sell videos for $300 to $500 each with the done-for-you agency package included. This upgrade makes it easy for everyone to find clients and sell their designs for top dollar. 

  • 5 sub accounts
  • Done-For-You Agency Marketing Bundle
  • Done-For-You Legal Client Contracts
  • Done-For-You Agency Website
  • Done-For-You Agency Sales Video

OTO#3: DesignBeast 4 in 1 Ultra.

Price – $39 OneTime

Customers get access to FOUR additional apps as part of this upgrade. 

  • Pixel Perfect
  • Instantly turn any image, even a low quality image, into ultra HD, high quality photo that can be blown up to any size – even billboard size – without any pixelation or distortion.
  • Animated Ads Builder 

Create animated ads in all languages, shapes and sizes using hundreds of ready to use design templates. Use animated ads to promote your products, create ads for clients or sell animated designs on freelancer websites like fiverr, upwork and freelancer to maximize profits. 

  • Video Resizer

With this powerful technology you can resize any video into multiple video sizes perfectly sized for all social platforms. Turn a single video into multiple dimensions and sizes within minutes and share the video onto different platforms to drive more traffic and sales!

  • Video Survey Pro

With this powerful app you can instantly collect:

* Video Testimonials

* Live video feedback from clients about your work

* Add video surveys on your websites to collect valuable information

* Have your team record video feedback about any project 

Streamline your workflows without any confusion or relying on old and outdated methods like email and text.  

OTO#4: DesignBeast Unlimited

Price $67 OneTime

With the DesignBeast basic license, you can create unlimited designs forever with one limit of 600 credits per month on each of the six apps included. 

The limits reset each month so you can continue creating amazing designs, graphics and animations forever without any monthly fees. 

This limit is put in place to prevent abuse and ensure all our customers are getting the best value for years to come at an unbeatable price.

As part of this special unlimited upgrade, you can remove all the monthly limits and restrictions for all the cutting-edge apps and technologies included. 

Design Beast Review Conclusion

From my take, this will be a good and useful tool for you if you belong to these above-mentioned professional categories. No matter you have advanced skills or not because everything will be DFY and ready to use. And the best thing is that you can customize and edit each and every pre-made effect, design, and more thing. According to my opinion, graphics designing software is ned for every marketer and business person, but everyone cannot go for photoshop, AI, and Coral, so for making it easy and useful there will be a choice in your hand that is DesignBeast.

CHECK BONUSES & GRAB IT AT: https://bit.ly/3yhtcqi

SOURCE: https://bit.ly/3Dch4KV

Dylan  Iqbal

Dylan Iqbal

1638243664

ElectroDB: A DynamoDB Library to Make Single Table Designs Easier

ElectroDB

 ElectroDB is a DynamoDB library to ease the use of having multiple entities and complex hierarchical relationships in a single DynamoDB table.


 

Introducing: The NEW ElectroDB Playground

 

Try out and share ElectroDB Models, Services, and Single Table Design at electrodb.fun


Features


Turn this

tasks
  .patch({ 
    team: "core",
    task: "45-662", 
    project: "backend"
  })
  .set({ status: "open" })
  .add({ points: 5 })
  .append({ 
    comments: [{
      user: "janet",
      body: "This seems half-baked."
    }] 
  })
  .where(( {status}, {eq} ) => eq(status, "in-progress"))
  .go();

Into This

{
    "UpdateExpression": "SET #status = :status_u0, #points = #points + :points_u0, #comments = list_append(#comments, :comments_u0), #updatedAt = :updatedAt_u0, #gsi1sk = :gsi1sk_u0",
    "ExpressionAttributeNames": {
        "#status": "status",
        "#points": "points",
        "#comments": "comments",
        "#updatedAt": "updatedAt",
        "#gsi1sk": "gsi1sk"
    },
    "ExpressionAttributeValues": {
        ":status0": "in-progress",
        ":status_u0": "open",
        ":points_u0": 5,
        ":comments_u0": [
            {
                "user": "janet",
                "body": "This seems half-baked."
            }
        ],
        ":updatedAt_u0": 1630977029015,
        ":gsi1sk_u0": "$assignments#tasks_1#status_open"
    },
    "TableName": "your_table_name",
    "Key": {
        "pk": "$taskapp#team_core",
        "sk": "$tasks_1#project_backend#task_45-662"
    },
    "ConditionExpression": "attribute_exists(pk) AND attribute_exists(sk) AND #status = :status0"
}

Table of Contents


Project Goals

ElectroDB focuses on simplifying the process of modeling, enforcing data constraints, querying across entities, and formatting complex DocumentClient parameters. Three important design considerations we're made with the development of ElectroDB:

  1. ElectroDB should be able to be useful without having to query the database itself [read more].
  2. ElectroDB should be able to be added to a project that already has been established tables, data, and access patterns [read more].
  3. ElectroDB should not require additional design considerations on top of those made for DynamoDB, and therefore should be able to be removed from a project at any time without sacrifice.

Installation

Install from NPM

npm install electrodb --save

Usage

Require/import Entity and/or Service from electrodb:

const {Entity, Service} = require("electrodb");
// or 
import {Entity, Service} from "electrodb";

Entities and Services

To see full examples of ElectroDB in action, go to the Examples section.

Entity allows you to create separate and individual business objects in a DynamoDB table. When queried, your results will not include other Entities that also exist the same table. This allows you to easily achieve single table design as recommended by AWS. For more detail, read Entities.

Service allows you to build relationships across Entities. A service imports Entity Models, builds individual Entities, and creates Collections to allow cross Entity querying. For more detail, read Services.

You can use Entities independent of Services, you do not need to import models into a Service to use them individually. However, If you intend to make queries that join or span multiple Entities you will need to use a Service.

Entities

In ElectroDB an Entity is represents a single business object. For example, in a simple task tracking application, one Entity could represent an Employee and or a Task that is assigned to an employee.

Require or import Entity from electrodb:

const {Entity} = require("electrodb");
// or
import {Entity} from "electrodb";

When using TypeScript, for strong type checking, be sure to either add your model as an object literal to the Entity constructor or create your model using const assertions with the as const syntax.

Services

In ElectroDB a Service represents a collection of related Entities. Services allow you to build queries span across Entities. Similar to Entities, Services can coexist on a single table without collision. You can use Entities independent of Services, you do not need to import models into a Service to use them individually. However, you do you need to use a Service if you intend make queries that join multiple Entities.

Require:

const {Service} = require("electrodb");
// or
import {Service} from "electrodb";

TypeScript Support

Previously it was possible to generate type definition files (.d.ts) for you Models, Entities, and Services with the Electro CLI. New with version 0.10.0 is TypeScript support for Entities and Services.

As of writing this, this functionality is still a work in progress, and enforcement of some of ElectroDB's query constraints have still not been written into the type checks. Most notably are the following constraints not yet enforced by the type checker, but are enforced at query runtime:

  • Sort Key Composite Attribute order is not strongly typed. Sort Key Composite Attributes must be provided in the order they are defined on the model to build the key appropriately. This will not cause an error at query runtime, be sure your partial Sort Keys are provided in accordance with your model to fully leverage Sort Key queries. For more information about composite attribute ordering see the section on Composite Attributes.
  • Put/Create/Update/Patch/Delete/Create operations that partially impact index composite attributes are not statically typed. When performing a put or update type operation that impacts a composite attribute of a secondary index, ElectroDB performs a check at runtime to ensure all composite attributes of that key are included. This is detailed more in the section Composite Attribute and Index Considerations.
  • Use of the params method does not yet return strict types.
  • Use of the raw or includeKeys query options do not yet impact the returned types.

If you experience any issues using TypeScript with ElectroDB, your feedback is very important, please create a GitHub issue, and it can be addressed.

See the section Exported TypeScript Types to read more about the useful types exported from ElectroDB.

TypeScript Services

New with version 0.10.0 is TypeScript support. To ensure accurate types with, TypeScript users should create their services by passing an Object literal or const object that maps Entity alias names to Entity instances.

const table = "my_table_name";
const employees = new Entity(EmployeesModel, { client, table });
const tasks = new Entity(TasksModel, { client, table });
const TaskApp = new Service({employees, tasks});

The property name you assign the entity will then be "alias", or name, you can reference that entity by through the Service. Aliases can be useful if you are building a service with multiple versions of the same entity or wish to change the reference name of an entity without impacting the schema/key names of that entity.

Services take an optional second parameter, similar to Entities, with a client and table. Using this constructor interface, the Service will utilize the values from those entities, if they were provided, or be passed values to override the client or table name on the individual entities.

Not yet available for TypeScript, this pattern will also accept Models, or a mix of Entities and Models, in the same object literal format.

Join

When using JavaScript, use join to add Entities or Models onto a Service.

NOTE: If using TypeScript, see Joining Entities at Service construction for TypeScript to learn how to "join" entities for use in a TypeScript project.

Independent Models

let table = "my_table_name";
let employees = new Entity(EmployeesModel, { client, table });
let tasks = new Entity(TasksModel, { client, table });

Joining Entity instances to a Service

// Joining Entity instances to a Service
let TaskApp = new Service("TaskApp", { client, table });
TaskApp
    .join(employees) // available at TaskApp.entities.employees
    .join(tasks);    // available at TaskApp.entities.tasks

Joining models to a Service

let TaskApp = new Service("TaskApp", { client, table });
TaskApp
    .join(EmployeesModel) // available at TaskApp.entities.employees (based on entity name in model)
    .join(TasksModel);    // available at TaskApp.entities.tasks (based on entity name in model)

Joining Entities or Models with an alias

let TaskApp = new Service("TaskApp", { client, table });
TaskApp
    .join("personnel", EmployeesModel) // available at TaskApp.entities.personnel
    .join("directives", TasksModel); // available at TaskApp.entities.directives

Joining Entities at Service construction for TypeScript

let TaskApp = new Service({
    personnel: EmployeesModel, // available at TaskApp.entities.personnel
    directives: TasksModel, // available at TaskApp.entities.directives
});

When joining a Model/Entity to a Service, ElectroDB will perform a number of validations to ensure that Entity conforms to expectations collectively established by all joined Entities.

  • Entity names must be unique across a Service.
  • Collection names must be unique across a Service.
  • All Collections map to on the same DynamoDB indexes with the same index field names. See Indexes.
  • Partition Key [Composite Attributes](#composite attribute-arrays) on a Collection must have the same attribute names and labels (if applicable). See Attribute Definitions.
  • The name of the Service in the Model must match the Name defined on the Service instance.
  • Joined instances must be type Model or Entity.
  • If the attributes of an Entity have overlapping names with other attributes in that service, they must all have compatible or matching attribute definitions.
  • All models conform to the same model format. If you created your model prior to ElectroDB version 0.9.19 see section Version 1 Migration.

Model

Create an Entity's schema. In the below example.

const DynamoDB = require("aws-sdk/clients/dynamodb");
const {Entity, Service} = require("electrodb");
const client = new DynamoDB.DocumentClient();
const EmployeesModel = {
    model: {
        entity: "employees",
        version: "1",
        service: "taskapp",
    },
    attributes: {
        employee: {
            type: "string",
            default: () => uuidv4(),
        },
        firstName: {
            type: "string",
            required: true,
        },
        lastName: {
            type: "string",
            required: true,
        },
        office: {
            type: "string",
            required: true,
        },
        title: {
            type: "string",
            required: true,
        },
        team: {
            type: ["development", "marketing", "finance", "product", "cool cats and kittens"],
            required: true,
        },
        salary: {
            type: "string",
            required: true,
        },
        manager: {
            type: "string",
        },
        dateHired: {
            type: "string",
            validate: /^\d{4}-\d{2}-\d{2}$/gi
        },
        birthday: {
            type: "string",
            validate: /^\d{4}-\d{2}-\d{2}$/gi
        },
    },
    indexes: {
        employee: {
            pk: {
                field: "pk",
                composite: ["employee"],
            },
            sk: {
                field: "sk",
                composite: [],
            },
        },
        coworkers: {
            index: "gsi1pk-gsi1sk-index",
            collection: "workplaces",
            pk: {
                field: "gsi1pk",
                composite: ["office"],
            },
            sk: {
                field: "gsi1sk",
                composite: ["team", "title", "employee"],
            },
        },
        teams: {
            index: "gsi2pk-gsi2sk-index",
            pk: {
                field: "gsi2pk",
                composite: ["team"],
            },
            sk: {
                field: "gsi2sk",
                composite: ["title", "salary", "employee"],
            },
        },
        employeeLookup: {
            collection: "assignments",
            index: "gsi3pk-gsi3sk-index",
            pk: {
                field: "gsi3pk",
                composite: ["employee"],
            },
            sk: {
                field: "gsi3sk",
                composite: [],
            },
        },
        roles: {
            index: "gsi4pk-gsi4sk-index",
            pk: {
                field: "gsi4pk",
                composite: ["title"],
            },
            sk: {
                field: "gsi4sk",
                composite: ["salary", "employee"],
            },
        },
        directReports: {
            index: "gsi5pk-gsi5sk-index",
            pk: {
                field: "gsi5pk",
                composite: ["manager"],
            },
            sk: {
                field: "gsi5sk",
                composite: ["team", "office", "employee"],
            },
        },
    },
};

const TasksModel = {
    model: {
        entity: "tasks",
        version: "1",
        service: "taskapp",
    },
    attributes: {
        task: {
            type: "string",
            default: () => uuid(),
        },
        project: {
            type: "string",
        },
        employee: {
            type: "string",
        },
        description: {
            type: "string",
        },
    },
    indexes: {
        task: {
            pk: {
                field: "pk",
                composite: ["task"],
            },
            sk: {
                field: "sk",
                composite: ["project", "employee"],
            },
        },
        project: {
            index: "gsi1pk-gsi1sk-index",
            pk: {
                field: "gsi1pk",
                composite: ["project"],
            },
            sk: {
                field: "gsi1sk",
                composite: ["employee", "task"],
            },
        },
        assigned: {
            collection: "assignments",
            index: "gsi3pk-gsi3sk-index",
            pk: {
                field: "gsi3pk",
                composite: ["employee"],
            },
            sk: {
                field: "gsi3sk",
                composite: ["project", "task"],
            },
        },
    },
};

Model Properties

PropertyDescription
model.serviceName of the application using the entity, used to namespace all entities
model.entityName of the entity that the schema represents
model.version(optional) The version number of the schema, used to namespace keys
attributesAn object containing each attribute that makes up the schema
indexesAn object containing table indexes, including the values for the table's default Partition Key and Sort Key

Service Options

Optional second parameter

PropertyDescription
tableThe name of the dynamodb table in aws.
client(optional) An instance of the docClient from the aws-sdk for use when querying a DynamoDB table. This is optional if you wish to only use the params functionality, but required if you actually need to query against a database.

Attributes

Attributes define an Entity record. The AttributeName represents the value your code will use to represent an attribute.

Pro-Tip: Using the field property, you can map an AttributeName to a different field name in your table. This can be useful to utilize existing tables, existing models, or even to reduce record sizes via shorter field names. For example, you may refer to an attribute as organization but want to save the attribute with a field name of org in DynamoDB.

Simple Syntax

Assign just the type of the attribute directly to the attribute name. Types currently supported options are "string", "number", "boolean", an array of strings representing a fixed set of possible values, or "any" which disables value type checking on that attribute.

attributes: {
    <AttributeName>: "string" | "number" | "boolean" | "list" | "map" | "set" | "any" | string[] | ReadonlyArray<string> 
}

Expanded Syntax

Use the expanded syntax build out more robust attribute options.

attributes: {
    <AttributeName>: {
        type: "string" | "number" | "boolean" | "list" | "map" | "set" | "any" | ReadonlyArray<string>;
        required?: boolean;
        default?: <type> | (() => <type>);
        validate?: RegExp | ((value: <type>) => void | string);
        field?: string;
        readOnly?: boolean;
        label?: string;
        cast?: "number"|"string"|"boolean";
        get?: (attribute: <type>, schema: any) => <type> | void | undefined;
        set?: (attribute?: <type>, schema?: any) => <type> | void | undefined; 
        watch: "*" | string[]
    }
}

NOTE: When using get/set in TypeScript, be sure to use the ?: syntax to denote an optional attribute on set

Attribute Definition

PropertyTypeRequiredTypesDescription
typestring, ReadonlyArray<string>, string[]yesallAccepts the values: "string", "number" "boolean", "map", "list", "set", an array of strings representing a finite list of acceptable values: ["option1", "option2", "option3"], or "any" which disables value type checking on that attribute.
requiredbooleannoallFlag an attribute as required to be present when creating a record. This attribute also acts as a type of NOT NULL flag, preventing it from being removed directly.
hiddenbooleannoallFlag an attribute as hidden to remove the property from results before they are returned.
defaultvalue, () => valuenoallEither the default value itself or a synchronous function that returns the desired value. Applied before set and before required check.
validateRegExp, (value: any) => void, (value: any) => stringnoallEither regex or a synchronous callback to return an error string (will result in exception using the string as the error's message), or thrown exception in the event of an error.
fieldstringnoallThe name of the attribute as it exists in DynamoDB, if named differently in the schema attributes. Defaults to the AttributeName as defined in the schema.
readOnlybooleannoallPrevents an attribute from being updated after the record has been created. Attributes used in the composition of the table's primary Partition Key and Sort Key are read-only by default. The one exception to readOnly is for properties that also use the watch property, read attribute watching for more detail.
labelstringnoallUsed in index composition to prefix key composite attributes. By default, the AttributeName is used as the label.
cast"number", "string", "boolean"noallOptionally cast attribute values when interacting with DynamoDB. Current options include: "number", "string", and "boolean".
set(attribute, schema) => valuenoallA synchronous callback allowing you to apply changes to a value before it is set in params or applied to the database. First value represents the value passed to ElectroDB, second value are the attributes passed on that update/put
get(attribute, schema) => valuenoallA synchronous callback allowing you to apply changes to a value after it is retrieved from the database. First value represents the value passed to ElectroDB, second value are the attributes retrieved from the database.
watchAttribute[], "*"noroot-onlyDefine other attributes that will always trigger your attribute's getter and setter callback after their getter/setter callbacks are executed. Only available on root level attributes.
properties{[key: string]: Attribute}yes*mapDefine the properties available on a "map" attribute, required if your attribute is a map. Syntax for map properties is the same as root level attributes.
itemsAttributeyes*listDefine the attribute type your list attribute will contain, required if your attribute is a list. Syntax for list items is the same as a single attribute.
items"string""number"yes*set

Enum Attributes

When using TypeScript, if you wish to also enforce this type make sure to us the as const syntax. If TypeScript is not told this array is Readonly, even when your model is passed directly to the Entity constructor, it will not resolve the unique values within that array.

This may be desirable, however, as enforcing the type value can require consumers of your model to do more work to resolve the type beyond just the type string.

NOTE: Regardless of using TypeScript or JavaScript, ElectroDB will enforce values supplied match the supplied array of values at runtime.

The following example shows the differences in how TypeScript may enforce your enum value:

attributes: {
  myEnumAttribute1: {
      type: ["option1", "option2", "option3"]        // TypeScript enforces as `string[]`
  },
  myEnumAttribute2: {
    type: ["option1", "option2", "option3"] as const // TypeScript enforces as `"option1" | "option2" | "option3" | undefined`
  },
  myEnumAttribute3: {
    required: true,
    type: ["option1", "option2", "option3"] as const // TypeScript enforces as `"option1" | "option2" | "option3"`
  }
}

Map Attributes

Map attributes leverage DynamoDB's native support for object-like structures. The attributes within a Map are defined under the properties property; a syntax that mirrors the syntax used to define root level attributes. You are not limited in the types of attributes you can nest inside a map attribute.

attributes: {
  myMapAttribute: {
    type: "map",
    properties: {
      myStringAttribute: {
        type: "string"
      },
      myNumberAttribute: {
        type: "number"
      }
    }
  }
}

List Attributes

List attributes model array-like structures with DynamoDB's List type. The elements of a List attribute are defined using the items property. Similar to Map properties, ElectroDB does not restrict the types of items that can be used with a list.

attributes: {
  myStringList: { 
    type: "list",
    items: {
      type: "string"
    },
  },
  myMapList: {
    myMapAttribute: {
      type: "map",
      properties: {
        myStringAttribute: {
          type: "string"
        },
        myNumberAttribute: {
          type: "number"
        }
      }
    }
  }
}

Set Attributes

The Set attribute is arguably DynamoDB's most powerful type. ElectroDB supports String and Number Sets using the items property set as either "string" or "number".

In addition to having the same modeling benefits you get with other attributes, ElectroDB also simplifies the use of Sets by removing the need to use DynamoDB's special createSet class to work with Sets. ElectroDB Set Attributes accept Arrays, JavaScript native Sets, and objects from createSet as values. ElectroDB will manage the casting of values to a DynamoDB Set value prior to saving and ElectroDB will also convert Sets back to JavaScript arrays on retrieval.

NOTE: If you are using TypeScript, Sets are currently typed as Arrays to simplify the type system. Again, ElectroDB will handle the conversion of these Arrays without the need to use client.createSet().

attributes: {
  myStringSet: {
    type: "set",
    items: "string"
  },
  myNumberSet: {
    type: "set",
    items: "number"
  }
}

Attribute Getters and Setters

Using get and set on an attribute can allow you to apply logic before and just after modifying or retrieving a field from DynamoDB. Both callbacks should be pure synchronous functions and may be invoked multiple times during one query.

The first argument in an attribute's get or set callback is the value received in the query. The second argument, called "item", in an attribute's is an object containing the values of other attributes on the item as it was given or retrieved. If your attribute uses watch, the getter or setter of attribute being watched will be invoked before your getter or setter and the updated value will be on the "item" argument instead of the original.

NOTE: Using getters/setters on Composite Attributes is not recommended without considering the consequences of how that will impact your keys. When a Composite Attribute is supplied for a new record via a put or create operation, or is changed via a patch or updated operation, the Attribute's set callback will be invoked prior to formatting/building your record's keys on when creating or updating a record.

ElectroDB invokes an Attribute's get method in the following circumstances:

  1. If a field exists on an item after retrieval from DynamoDB, the attribute associated with that field will have its getter method invoked.
  2. After a put or create operation is performed, attribute getters are applied against the object originally received and returned.
  3. When using ElectroDB's attribute watching functionality, an attribute will have its getter callback invoked whenever the getter callback of any "watched" attributes are invoked. Note: The getter of an Attribute Watcher will always be applied after the getters for the attributes it watches.

ElectroDB invokes an Attribute's set callback in the following circumstances:

  1. Setters for all Attributes will always be invoked when performing a create or put operation.
  2. Setters will only be invoked when an Attribute is modified when performing a patch or update operation.
  3. When using ElectroDB's attribute watching functionality, an attribute will have its setter callback invoked whenever the setter callback of any "watched" attributes are invoked. Note: The setter of an Attribute Watcher will always be applied after the setters for the attributes it watches.

NOTE: As of ElectroDB 1.3.0, the watch property is only possible for root level attributes. Watch is currently not supported for nested attributes like properties on a "map" or items of a "list".

Attribute Watching

Attribute watching is a powerful feature in ElectroDB that can be used to solve many unique challenges with DynamoDB. In short, you can define a column to have its getter/setter callbacks called whenever another attribute's getter or setter callbacks are called. If you haven't read the section on Attribute Getters and Setters, it will provide you with more context about when an attribute's mutation callbacks are called.

Because DynamoDB allows for a flexible schema, and ElectroDB allows for optional attributes, it is possible for items belonging to an entity to not have all attributes when setting or getting records. Sometimes values or changes to other attributes will require corresponding changes to another attribute. Sometimes, to fully leverage some advanced model denormalization or query access patterns, it is necessary to duplicate some attribute values with similar or identical values. This functionality has many uses; below are just a few examples of how you can use watch:

NOTE: Using the watch property impacts the order of which getters and setters are called. You cannot watch another attribute that also uses watch, so ElectroDB first invokes the getters or setters of attributes without the watch property, then subsequently invokes the getters or setters of attributes who use watch.

myAttr: { 
  type: "string",
  watch: ["otherAttr"],
  set: (myAttr, {otherAttr}) => {
    // Whenever "myAttr" or "otherAttr" are updated from an `update` or `patch` operation, this callback will be fired. 
    // Note: myAttr or otherAttr could be independently undefined because either attribute could have triggered this callback
  },
  get: (myAttr, {otherAttr}) => {
    // Whenever "myAttr" or "otherAttr" are retrieved from a `query` or `get` operation, this callback will be fired. 
    // Note: myAttr or otherAttr could be independently undefined because either attribute could have triggered this callback.
  } 
}

Attribute Watching: Watch All

If your attributes needs to watch for any changes to an item, you can model this by supplying the watch property a string value of "*"

myAttr: { 
  type: "string",
  watch: "*", // "watch all"
  set: (myAttr, allAttributes) => {
    // Whenever an `update` or `patch` operation is performed, this callback will be fired. 
    // Note: myAttr or the attributes under `allAttributes` could be independently undefined because either attribute could have triggered this callback
  },
  get: (myAttr, allAttributes) => {
    // Whenever a `query` or `get` operation is performed, this callback will be fired. 
    // Note: myAttr or the attributes under `allAttributes` could be independently undefined because either attribute could have triggered this callback
  } 
}

Attribute Watching Examples

Example 1 - A calculated attribute that depends on the value of another attribute:

In this example, we have an attribute "fee" that needs to be updated any time an item's "price" attribute is updated. The attribute "fee" uses watch to have its setter callback called any time "price" is updated via a put, create, update, or patch operation.

Try it out!

{
  model: {
    entity: "products",
    service: "estimator",
    version: "1"
  },
  attributes: {
    product: {
      type: "string"
    },
    price: {
      type: "number",
              required: true
    },
    fee: {
      type: "number",
              watch: ["price"],
              set: (_, {price}) => {
        return price * .2;
      }
    }
  },
  indexes: {
    pricing: {
      pk: {
        field: "pk",
                composite: ["product"]
      },
      sk: {
        field: "sk",
                composite: []
      }
    }
  }
}

Example 2 - Making a virtual attribute that never persists to the database:

In this example we have an attribute "displayPrice" that needs its getter called anytime an item's "price" attribute is retrieved. The attribute "displayPrice" uses watch to return a formatted price string based whenever an item with a "price" attribute is queried. Additionally, "displayPrice" always returns undefined from its setter callback to ensure that it will never write data back to the table.

{
  model: {
    entity: "services",
    service: "costEstimator",
    version: "1"
  },
  attributes: {
    service: {
      type: "string"
    },
    price: {
      type: "number",
      required: true
    },
    displayPrice: {
      type: "string",
      watch: ["price"],
      get: (_, {price}) => {
        return "$" + price;  
      },
      set: () => undefined
    }
  },
  indexes: {
    pricing: {
      pk: {
        field: "pk",
        composite: ["service"]
      },
      sk: {
        field: "sk",
        composite: []
      }
    }
  }
}

Example 3 - Creating a more filter-friendly version of an attribute without impacting the original attribute:

In this example we have an attribute "descriptionSearch" which will help our users easily filter for transactions by "description". To ensure our filters will not take into account a description's character casing, descriptionSearch duplicates the value of "description" so it can be used in filters without impacting the original "description" value. Without ElectroDB's watch functionality, to accomplish this you would either have to duplicate this logic or cause permanent modification to the property itself. Additionally, the "descriptionSearch" attribute has used hidden:true to ensure this value will not be presented to the user.

{
  model: {
    entity: "transaction",
    service: "bank",
    version: "1"
  },
  attributes: {
    accountNumber: {
      type: "string"
    },
    transactionId: {
      type: "string"
    },
    amount: {
      type: "number",
    },
    description: {
      type: "string",
    },
    descriptionSearch: {
      type: "string",
      hidden: true,
      watch: ["description"],
      set: (_, {description}) => {
        if (typeof description === "string") {
            return description.toLowerCase();
        }
      }
    }
  },
  indexes: {
    transactions: {
      pk: {
        field: "pk",
        composite: ["accountNumber"]
      },
      sk: {
        field: "sk",
        composite: ["transactionId"]
      }
    }
  }
}

Example 4 - Creating an updatedAt property:

In this example we can easily create both updatedAt and createdAt attributes on our model. createdAt will use ElectroDB's set and readOnly attribute properties, while updatedAt will make use of readOnly, and watch with the "watchAll" syntax: {watch: "*"}. By supplying an asterisk, instead of an array of attribute names, attributes can be defined to watch all changes to all attributes.

Using watch in conjunction with readOnly is another powerful modeling technique. This combination allows you to model attributes that can only be modified via the model and not via the user. This is useful for attributes that need to be locked down and/or strictly calculated.

Notable about this example is that both updatedAt and createdAt use the set property without using its arguments. The readOnly only prevents modification of an attributes on update, and patch. By disregarding the arguments passed to set, the updatedAt and createdAt attributes are then effectively locked down from user influence/manipulation.

{
  model: {
    entity: "transaction",
    service: "bank",
    version: "1"
  },
  attributes: {
    accountNumber: {
      type: "string"
    },
    transactionId: {
      type: "string"
    },
    description: {
      type: "string",
    },
    createdAt: {
      type: "number",
      readOnly: true,
      set: () => Date.now()
    },
    updatedAt: {
      type: "number",
      readOnly: true,
      watch: "*",
      set: () => Date.now()
    },
    
  },
  indexes: {
    transactions: {
      pk: {
        field: "pk",
        facets: ["accountNumber"]
      },
      sk: {
        field: "sk",
        facets: ["transactionId"]
      }
    }
  }
}

Calculated Attributes

See: Attribute Watching (Example 1).

Virtual Attributes

See: Attribute Watching (Example 2).

CreatedAt and UpdatedAt Attributes

See: Attribute Watching (Example 4).

Attribute Validation

The validation property allows for multiple function/type signatures. Here the different combinations ElectroDB supports: signature | behavior ----------------------- | -------- Regexp | ElectroDB will call .test(val) on the provided regex with the value passed to this attribute (value: T) => string | If a string value with length is returned, the text will be considered the reason the value is invalid. It will generate a new exception this text as the message. (value: T) => boolean | If a boolean value is returned, true or truthy values will signify than a value is invalid while false or falsey will be considered valid. (value: T) => void | A void or undefined value is returned, will be treated as successful, in this scenario you can throw an Error yourself to interrupt the query

Indexes

When using ElectroDB, indexes are referenced by their AccessPatternName. This allows you to maintain generic index names on your DynamoDB table, but reference domain specific names while using your ElectroDB Entity. These will often be referenced as "Access Patterns".

All DynamoDB table start with at least a PartitionKey with an optional SortKey, this can be referred to as the "Table Index". The indexes object requires at least the definition of this Table Index Partition Key and (if applicable) Sort Key.

In your model, the Table Index this is expressed as an Access Pattern without an index property. For Secondary Indexes, use the index property to define the name of the index as defined on your DynamoDB table.

Within these AccessPatterns, you define the PartitionKey and (optionally) SortKeys that are present on your DynamoDB table and map the key's name on the table with the field property.

indexes: {
    [AccessPatternName]: {
        pk: {
            field: string; 
            composite: AttributeName[];
            template?: string;
        },
        sk?: {
            field: string;
            composite: AttributesName[];
            template?: string;
        },
        index?: string
        collection?: string | string[]
    }
}
PropertyTypeRequiredDescription
pkobjectyesConfiguration for the pk of that index or table
pk.composite`stringstring[]`yes
pk.templatestringnoA string that represents the template in which attributes composed to form a key (see Composite Attribute Templates below for more on this functionality).
pk.fieldstringyesThe name of the attribute as it exists in DynamoDB, if named differently in the schema attributes.
pk.casingdefaultupperlower
skobjectnoConfiguration for the sk of that index or table
sk.composite`stringstring[]`no
sk.templatestringnoA string that represents the template in which attributes composed to form a key (see Composite Attribute Templates below for more on this functionality).
sk.fieldstringyesThe name of the attribute as it exists in DynamoDB, if named differently in the schema attributes.
pk.casingdefaultupperlower
indexstringnoRequired when the Index defined is a Secondary Index; but is left blank for the table's primary index.
collection`stringstring[]`no

Indexes Without Sort Keys

When using indexes without Sort Keys, that should be expressed as an index without an sk property at all. Indexes without an sk cannot have a collection, see Collections for more detail.

NOTE: It is generally recommended to always use Sort Keys when using ElectroDB as they allow for more advanced query opportunities. Even if your model doesn't need an additional property to define a unique record, having an sk with no defined composite attributes (e.g. an empty array) still opens the door to many more query opportunities like collections.

// ElectroDB interprets as index *not having* an SK.
{
  indexes: {
    myIndex: {
      pk: {
        field: "pk",
        composite: ["id"]
      }
    }
  }
}

Try it out!

Indexes With Sort Keys

When using indexes with Sort Keys, that should be expressed as an index with an sk property. If you don't wish to use the Sort Key in your model, but it does exist on the table, simply use an empty for the composite property. An empty array is still very useful, and opens the door to more query opportunities and access patterns like collections.

// ElectroDB interprets as index *having* SK, but this model doesnt assign any composite attributes to it.
{
  indexes: {
    myIndex: {
      pk: {
        field: "pk",
        composite: ["id"]
      },
      sk: {
        field: "sk",
        composite: []
      }
    }
  }
}

Try it out!

Numeric Keys

If you have an index where the Partition or Sort Keys are expected to be numeric values, you can accomplish this with the template property on the index that requires numeric keys. Define the attribute used in the composite template as type "number", and then create a template string with only the attribute's name.

For example, this model defines both the Partition and Sort Key as numeric:

const schema = {
  model: {
    entity: "numeric",
    service: "example",
    version: "1"
  },
  attributes: {
    number1: {
      type: "number" // defined as number
    },
    number2: {
      type: "number"  // defined as number
    }
  },
  indexes: {
    record: {
      pk: {
        field: "pk",
        template: "${number1}" // will build PK as numeric value 
      },
      sk: {
        field: "sk",
        template: "${number2}" // will build SK as numeric value
      }
    }
  }
}

Try it out!

Index Casing

DynamoDB is a case-sensitive data store, and therefore it is common to convert the casing of keys to uppercase or lowercase prior to saving, updating, or querying data to your table. ElectroDB, by default, will lowercase all keys when preparing query parameters. For those who are using ElectroDB with an existing dataset, have preferences on upper or lowercase, or wish to not convert case at all, this can be configured on an index key field basis.

In the example below, we are configuring the casing ElectroDB will use individually for the Partition Key and Sort Key on the GSI "gis1". For the index's PK, mapped to gsi1pk, we ElectroDB will convert this key to uppercase prior to its use in queries. For the index's SK, mapped to gsi1pk, we ElectroDB will not convert the case of this key prior to its use in queries.

{
  indexes: {
    myIndex: {
      index: "gsi1",
      pk: {
        field: "gsi1pk",
        casing: "upper", // Acct_0120 -> ACCT_0120
        composite: ["organizationId"]
      },
      sk: {
        field: "gsi1sk",
        casing: "none", // Acct_0120 -> Acct_0120 
        composite: ["accountId"]
      }
    }
  }
}

Try it out!

NOTE: Casing is a very important decision when modeling your data in DynamoDB. While choosing upper/lower is largely a personal preference, once you have begun loading records in your table it can be difficult to change your casing after the fact. Unless you have good reason, allowing for mixed case keys can make querying data difficult because it will require database consumers to always have a knowledge of their data's case.

Casing OptionEffect
defaultThe default for keys is lowercase, or lower
lowerWill convert the key to lowercase prior it its use
upperWill convert the key to uppercase prior it its use
noneWill not perform any casing changes when building keys

Facets

As of version 0.11.1, "Facets" have been renamed to "Composite Attributes", and all documentation has been updated to reflect that change.

Composite Attributes

A Composite Attribute is a segment of a key based on one of the attributes. Composite Attributes are concatenated together from either a Partition Key, or a Sort Key key, which define an index.

NOTE: Only attributes with a type of "string", "number", "boolean", or string[] (enum) can be used as composite attributes.

There are two ways to provide composite:

  1. As a Composite Attribute Array
  2. As a Composite Attribute Template

For example, in the following Access Pattern, "locations" is made up of the composite attributes storeId, mallId, buildingId and unitId which map to defined attributes in the model:

// Input
{
    storeId: "STOREVALUE",
    mallId: "MALLVALUE",
    buildingId: "BUILDINGVALUE",
    unitId: "UNITVALUE"
};

// Output:
{
    pk: '$mallstoredirectory_1#storeId_storevalue',
    sk: '$mallstores#mallid_mallvalue#buildingid_buildingvalue#unitid_unitvalue'
}

For PK values, the service and version values from the model are prefixed onto the key.

For SK values, the entity value from the model is prefixed onto the key.

Composite Attribute Arrays

Within a Composite Attribute Array, each element is the name of the corresponding Attribute defined in the Model. The attributes chosen, and the order in which they are specified, will translate to how your composite keys will be built by ElectroDB.

NOTE: If the Attribute has a label property, that will be used to prefix the composite attributes, otherwise the full Attribute name will be used.

attributes: {
    storeId: {
        type: "string",
        label: "sid",
    },
    mallId: {
        type: "string",
        label: "mid",
    },
    buildingId: {
        type: "string",
        label: "bid",
    },
    unitId: {
        type: "string",
        label: "uid",
    }
},
indexes: {
    locations: {
        pk: {
            field: "pk",
            composite: ["storeId"]
        },
        sk: {
            field: "sk",
            composite: ["mallId", "buildingId", "unitId"]
        }
    }
}
    
// Input
{
    storeId: "STOREVALUE",
    mallId: "MALLVALUE",
    buildingId: "BUILDINGVALUE",
    unitId: "UNITVALUE"
};

// Output:
{
    pk: '$mallstoredirectory_1#sid_storevalue',
    sk: '$mallstores#mid_mallvalue#bid_buildingvalue#uid_unitvalue'
}

Try it out!

Composite Attribute Templates

In a Composite Template, you provide a formatted template for ElectroDB to use when making keys. Composite Attribute Templates allow for potential ElectroDB adoption on already established tables and records.

Attributes are identified by surrounding the attribute with ${...} braces. For example, the syntax ${storeId} will match storeId attribute in the model.

Convention for a composing a key use the # symbol to separate attributes, and for labels to attach with underscore. For example, when composing both the mallId and buildingId would be expressed as mid_${mallId}#bid_${buildingId}.

NOTE: ElectroDB will not prefix templated keys with the Entity, Project, Version, or Collection. This will give you greater control of your keys but will limit ElectroDB's ability to prevent leaking entities with some queries.

ElectroDB will continue to always add a trailing delimiter to composite attributes with keys are partially supplied. The section on BeginsWith Queries goes into more detail about how ElectroDB builds indexes from composite attributes.

{
    model: {
        entity: "MallStoreCustom",
        version: "1",
        service: "mallstoredirectory"
    },
  attributes: {
      storeId: {
          type: "string"
      },
      mallId: {
          type: "string"
      },
      buildingId: {
          type: "string"
      },
      unitId: {
          type: "string"
      }
  },
  indexes: {
      locations: {
          pk: {
              field: "pk",
              template: "sid_${storeId}"
          },
          sk: {
              field: "sk",
              template: "mid_${mallId}#bid_${buildingId}#uid_${unitId}"
          }
      }
  }
}


// Input
{
    storeId: "STOREVALUE",
    mallId: "MALLVALUE",
    buildingId: "BUILDINGVALUE",
    unitId: "UNITVALUE"
};

// Output:
{
    pk: 'sid_storevalue',
    sk: 'mid_mallvalue#bid_buildingvalue#uid_unitvalue'
}

Try it out!

Templates and Composite Attribute Arrays

The example above shows indexes defined only with the template property. This property alone is enough to work with ElectroDB, however it can be useful to also include a composite array with the names of the Composite Attributes included in the template string. Doing so achieves the following benefits:

ElectroDB will enforce that the template you have supplied actually resolves to the composite attributes specified in the array.

If you use ElectroDB with TypeScript, supplying the composite array will ensure the indexes' Composite Attributes are typed just the same as if you had not used a composite template.

An example of using template while also using composite:

{
  indexes: {
    locations: {
      pk: {
        field: "pk",
        template: "sid_${storeId}"
        composite: ["storeId"]
      },
      sk: {
        field: "sk",
        template: "mid_${mallId}#bid_${buildingId}#uid_${unitId}",
        composite: ["mallId", "buildingId", "unitId"]
      }
    }
  }
}

Try it out!

Composite Attribute and Index Considerations

As described in the above two sections (Composite Attributes, Indexes), ElectroDB builds your keys using the attribute values defined in your model and provided on your query. Here are a few considerations to take into account when thinking about how to model your indexes:

Your table's primary Partition and Sort Keys cannot be changed after a record has been created. Be mindful of not to use Attributes that have values that can change as composite attributes for your primary table index.

When updating/patching an Attribute that is also a composite attribute for secondary index, ElectroDB will perform a runtime check that the operation will leave a key in a partially built state. For example: if a Sort Key is defined as having the Composite Attributes ["prop1", "prop2", "prop3"], than an update to the prop1 Attribute will require supplying the prop2 and prop3 Attributes as well. This prevents a loss of key fidelity because ElectroDB is not able to update a key partially in place with its existing values.

As described and detailed in [Composite Attribute Arrays](#composite attribute-arrays), you can use the label property on an Attribute shorten a composite attribute's prefix on a key. This can allow trim down the length of your keys.

Attributes as Indexes

It may be the case that an index field is also an attribute. For example, if a table was created with a Primary Index partition key of accountId, and that same field is used to store the accountId value used by the application. The following are a few examples of how to model that schema with ElectroDB:

NOTE: If you have the unique opportunity to use ElectroDB with a new project, it is strongly recommended to use generically named index fields that are separate from your business attributes.

Using composite

When your attribute's name, or field property on an attribute, matches the field property on an indexes' pk or sk ElectroDB will forego its usual index key prefixing.

{
  model: {
    entity: "your_entity_name",
    service: "your_service_name",
    version: "1"
  },
  attributes: {
    accountId: {
      type: "string"
    },
    productNumber: {
      type: "number"
    }
  },
  indexes: {
    products: {
      pk: {
        field: "accountId",
        composite: ["accountId"]
      },
      sk: {
        field: "productNumber",
        composite: ["productNumber"]
      }
    }
  }
}

Try it out!

Using template

Another approach allows you to use the template property, which allows you to format exactly how your key should be built when interacting with DynamoDB. In this case composite is optional when using template, but including it helps with TypeScript typing.

{
  model: {
    entity: "your_entity_name",
    service: "your_service_name",
    version: "1"
  },
  attributes: {
    accountId: {
      type: "string" // string and number types are both supported
    }      
  },
  indexes: {
    "your_access_pattern_name": {
      pk: {
        field: "accountId",
        composite: ["accountId"], // `composite` is optional when using `template` but is required when using TypeScript
        template: "${accountId}"
      },
      sk: {...}
    }
  }
}

Try it out!

Advanced use of template

When your string attribute is also an index key, and using key templates, you can also add static prefixes and postfixes to your attribute. Under the covers, ElectroDB will leverage this template while interacting with DynamoDB but will allow you to maintain a relationship with the attribute value itself.

For example, given the following model:

{
  model: {
    entity: "your_entity_name",
    service: "your_service_name",
    version: "1"
  },
  attributes: {
    accountId: {
      type: "string" // only string types are both supported for this example
    },
    organizationId: {
      type: "string"
    },
    name: {
      type: "string"
    }
  },
  indexes: {
    "your_access_pattern_name": {
      pk: {
        field: "accountId",
        composite: ["accountId"],
        template: "prefix_${accountId}_postfix"
      },
      sk: {
        field: "organizationId",
        composite: ["organizationId"]
      }
    }
  }
}

Try it out!

ElectroDB will accept a get request like this:

await myEntity.get({
  accountId: "1111-2222-3333-4444",
  organizationId: "AAAA-BBBB-CCCC-DDDD"
}).go()

Query DynamoDB with the following params (note the pre/postfix on accountId):

NOTE: ElectroDB defaults keys to lowercase, though this can be configured using Index Casing.

{
  Key: {
    accountId: "prefix_1111-2222-3333-4444_postfix",
    organizationId: `aaaa-bbbb-cccc-dddd`, 
  },
  TableName: 'your_table_name'
}

When returned from a query, however, ElectroDB will return the following and trim the key of it's prefix and postfix:

{
  accountId: "prefix_1111-2222-3333-4444_postfix",
  organizationId: `aaaa-bbbb-cccc-dddd`,
}
name: "your_item_name"

Collections

A Collection is a grouping of Entities with the same Partition Key and allows you to make efficient query across multiple entities. If your background is SQL, imagine Partition Keys as Foreign Keys, a Collection represents a View with multiple joined Entities.

NOTE: ElectroDB Collections use DynamoDB queries to retrieve results. One query is made to retrieve results for all Entities (the benefits of single table design), however like the query method, ElectroDB will paginate through all results for a given query.

Collections are defined on an Index, and the name of the collection should represent what the query would return as a pseudo Entity. Additionally, Collection names must be unique across a Service.

NOTE: A collection name should be unique to a single common index across entities.

const DynamoDB = require("aws-sdk/clients/dynamodb");
const table = "projectmanagement";
const client = new DynamoDB.DocumentClient();

const employees = new Entity({
  model: {
    entity: "employees",
    version: "1",
    service: "taskapp",
  },
  attributes: {
    employeeId: {
      type: "string"
    },
    organizationId: {
      type: "string"
    },
    name: {
      type: "string"
    },
    team: {
      type: ["jupiter", "mercury", "saturn"]
    }
  },
  indexes: {
    staff: {
      pk: {
        field: "pk",
        composite: ["organizationId"]
      },
      sk: {
        field: "sk",
        composite: ["employeeId"]
      }
    },
    employee: {
      collection: "assignments",
      index: "gsi2",
      pk: {
        field: "gsi2pk",
        composite: ["employeeId"],
      },
      sk: {
        field: "gsi2sk",
        composite: [],
      },
    }
  }
}, { client, table })

const tasks = new Entity({
  model: {
    entity: "tasks",
    version: "1",
    service: "taskapp",
  },
  attributes: {
    taskId: {
      type: "string"
    },
    employeeId: {
      type: "string"
    },
    projectId: {
      type: "string"
    },
    title: {
      type: "string"
    },
    body: {
      type: "string"
    }
  },
  indexes: {
    project: {
      pk: {
        field: "pk",
        composite: ["projectId"]
      },
      sk: {
        field: "sk",
        composite: ["taskId"]
      }
    },
    assigned: {
      collection: "assignments",
      index: "gsi2",
      pk: {
        field: "gsi2pk",
        composite: ["employeeId"],
      },
      sk: {
        field: "gsi2sk",
        composite: ["projectId"],
      },
    }
  }
}, { client, table });

const TaskApp = new Service({employees, tasks});

await TaskApp.collections
    .assignments({employeeId: "JExotic"})
    .go();

// Equivalent Parameters
{
  "TableName": 'projectmanagement',
  "ExpressionAttributeNames": { '#pk': 'gsi2pk', '#sk1': 'gsi2sk' },
  "ExpressionAttributeValues": { ':pk': '$taskapp_1#employeeid_joeexotic', ':sk1': '$assignments' },
  "KeyConditionExpression": '#pk = :pk and begins_with(#sk1, :sk1)',
  "IndexName": 'gsi2'
}

Try it out!

Collection Queries vs Entity Queries

To query across entities, collection queries make use of ElectroDB's Sort Key structure, which prefixes Sort Key fields with the collection name. Unlike an Entity Query, Collection Queries only leverage Composite Attributes from an access pattern's Partition Key.

To better explain how Collection Queries are formed, here is a juxtaposition of an Entity Query's parameters vs a Collection Query's parameters:

Entity Query

await TaskApp.entities
    .tasks.query
    .assigned({employeeId: "JExotic"})
    .go();

// Equivalent Parameters
{
  KeyConditionExpression: '#pk = :pk and begins_with(#sk1, :sk1)',
  TableName: 'projectmanagement',
  ExpressionAttributeNames: { '#pk': 'gsi2pk', '#sk1': 'gsi2sk' },
  ExpressionAttributeValues: {
    ':pk': '$taskapp#employeeid_jexotic',
    ':sk1': '$assignments#tasks_1'
  },
  IndexName: 'gsi2'
}

Try it out!

Collection Query

await TaskApp.collections
    .assignments({employeeId: "JExotic"})
    .go();

// Equivalent Parameters
{
  KeyConditionExpression: '#pk = :pk and begins_with(#sk1, :sk1)',
  TableName: 'projectmanagement',
  ExpressionAttributeNames: { '#pk': 'gsi2pk', '#sk1': 'gsi2sk' },
  ExpressionAttributeValues: { ':pk': '$taskapp#employeeid_jexotic', ':sk1': '$assignments' },
  IndexName: 'gsi2'
}

Try it out!

The notable difference between the two is how much of the Sort Key is specified at query time.

Entity Query:

ExpressionAttributeValues: { ':sk1': '$assignments#tasks_1' },

Collection Query:

ExpressionAttributeValues: { ':sk1': '$assignments' },

Collection Response Structure

Unlike Entity Queries which return an array, Collection Queries return an object. This object will have a key for every Entity name (or Entity Alias) associated with that Collection, and an array for all results queried that belong to that Entity.

For example, using the "TaskApp" models defined above, we would expect the following response from a query to the "assignments" collection:

let results = await TaskApp.collections
        .assignments({employeeId: "JExotic"})
        .go();

{
    tasks: [...],    // tasks for employeeId "JExotic" 
    employees: [...] // employee record(s) with employeeId "JExotic"
}

Because the Tasks and Employee Entities both associated their index (gsi2) with the same collection name (assignments), ElectroDB is able to associate the two entities via a shared Partition Key. As stated in the collections section, querying across Entities by PK can be comparable to querying across a foreign key in a traditional relational database.

Sub-Collections

Sub-Collections are an extension of Collection functionality that allow you to model more advanced access patterns. Collections and Sub-Collections are defined on Indexes via a property called collection, as either a string or string array respectively.

The following is an example of functionally identical collections, implemented as a string (referred to as a "collection") and then as a string array (referred to as sub-collections):

As a string (collection):

{
  collection: "assignments"
  pk: {
    field: "pk",
    composite: ["employeeId"]
  },
  sk: {
    field: "sk",
    composite: ["projectId"]
  }
}

As a string array (sub-collections):

{
  collection: ["assignments"]
  pk: {
    field: "pk",
            composite: ["employeeId"]
  },
  sk: {
    field: "sk",
            composite: ["projectId"]
  }
}

Both implementations above will create a "collections" method called assignments when added to a Service.

const results = await TaskApp.collections
    .assignments({employeeId: "JExotic"})
    .go();

The advantage to using a string array to define collections is the ability to express sub-collections. Below is an example of three entities using sub-collections, followed by an explanation of their sub-collection definitions:

Sub-Collection Entities

import {Entity, Service} from "electrodb"
import DynamoDB from "aws-sdk/clients/dynamodb";
const table = "projectmanagement";
const client = new DynamoDB.DocumentClient();

const employees = new Entity({
  model: {
    entity: "employees",
    version: "1",
    service: "taskapp",
  },
  attributes: {
    employeeId: {
      type: "string"
    },
    organizationId: {
      type: "string"
    },
    name: {
      type: "string"
    },
    team: {
      type: ["jupiter", "mercury", "saturn"] as const
    }
  },
  indexes: {
    staff: {
      pk: {
        field: "pk",
        composite: ["organizationId"]
      },
      sk: {
        field: "sk",
        composite: ["employeeId"]
      }
    },
    employee: {
      collection: "contributions",
      index: "gsi2",
      pk: {
        field: "gsi2pk",
        composite: ["employeeId"],
      },
      sk: {
        field: "gsi2sk",
        composite: [],
      },
    }
  }
}, { client, table })

const tasks = new Entity({
  model: {
    entity: "tasks",
    version: "1",
    service: "taskapp",
  },
  attributes: {
    taskId: {
      type: "string"
    },
    employeeId: {
      type: "string"
    },
    projectId: {
      type: "string"
    },
    title: {
      type: "string"
    },
    body: {
      type: "string"
    }
  },
  indexes: {
    project: {
      collection: "overview",
      pk: {
        field: "pk",
        composite: ["projectId"]
      },
      sk: {
        field: "sk",
        composite: ["taskId"]
      }
    },
    assigned: {
      collection: ["contributions", "assignments"] as const,
      index: "gsi2",
      pk: {
        field: "gsi2pk",
        composite: ["employeeId"],
      },
      sk: {
        field: "gsi2sk",
        composite: ["projectId"],
      },
    }
  }
}, { client, table });

const projectMembers = new Entity({
  model: {
    entity: "projectMembers",
    version: "1",
    service: "taskapp",
  },
  attributes: {
    employeeId: {
      type: "string"
    },
    projectId: {
      type: "string"
    },
    name: {
      type: "string"
    },
  },
  indexes: {
    members: {
      collection: "overview",
      pk: {
        field: "pk",
        composite: ["projectId"]
      },
      sk: {
        field: "sk",
        composite: ["employeeId"]
      }
    },
    projects: {
      collection: ["contributions", "assignments"] as const,
      index: "gsi2",
      pk: {
        field: "gsi2pk",
        composite: ["employeeId"],
      },
      sk: {
        field: "gsi2sk",
        composite: [],
      },
    }
  }
}, { client, table }); 

const TaskApp = new Service({employees, tasks, projectMembers});

Try it out!

TypeScript Note: Use as const syntax when defining collection as a string array for improved type support

The last line of the code block above creates a Service called TaskApp using the Entity instances created above its declaration. By creating a Service, ElectroDB will identify and validate the sub-collections defined across all three models. The result in this case are four unique collections: "overview", "contributions", and "assignments".

The simplest collection to understand is overview. This collection is defined on the table's Primary Index, composed of a projectId in the Partition Key, and is currently implemented by two Entities: tasks and projectMembers. If another entity were to be added to our service, it could "join" this collection by implementing an identical Partition Key composite (projectId) and labeling itself as part of the overview collection. The following is an example of using the overview collection:

// overview
const results = await TaskApp.collections
    .overview({projectId: "SD-204"})
    .go();

// results 
{ 
  tasks: [...],         // tasks associated with projectId "SD-204
  projectMembers: [...] // employees of project "SD-204"
}

// parameters
{
  KeyConditionExpression: '#pk = :pk and begins_with(#sk1, :sk1)',
  TableName: 'projectmanagement',
  ExpressionAttributeNames: { '#pk': 'pk', '#sk1': 'sk' },
  ExpressionAttributeValues: { ':pk': '$taskapp#projectid_sd-204', ':sk1': '$overview' }
}

Try it out!

Unlike overview, the collections contributions, and assignments are more complex.

In the case of contributions, all three entities implement this collection on the gsi2 index, and compose their Partition Key with the employeeId attribute. The assignments collection, however, is only implemented by the tasks and projectMembers Entities. Below is an example of using these collections:

NOTE: Collection values of collection: "contributions" and collection: ["contributions"] are interpreted by ElectroDB as being the same implementation.

// contributions
const results = await TaskApp.collections
        .contributions({employeeId: "JExotic"})
        .go();

// results 
{
  tasks: [...], // tasks assigned to employeeId "JExotic" 
  projectMembers: [...], // projects with employeeId "JExotic"
  employees: [...] // employee record(s) with employeeId "JExotic"
}

{
  KeyConditionExpression: '#pk = :pk and begins_with(#sk1, :sk1)',
  TableName: 'projectmanagement',
  ExpressionAttributeNames: { '#pk': 'gsi2pk', '#sk1': 'gsi2sk' },
  ExpressionAttributeValues: { ':pk': '$taskapp#employeeid_jexotic', ':sk1': '$contributions' },
  IndexName: 'gsi2'
}

Try it out!

// assignments
const results = await TaskApp.collections
        .assignments({employeeId: "JExotic"})
        .go();

// results 
{
  tasks: [...],          // tasks assigned to employeeId "JExotic" 
  projectMembers: [...], // projects with employeeId "JExotic"
}

{
  KeyConditionExpression: '#pk = :pk and begins_with(#sk1, :sk1)',
  TableName: 'projectmanagement',
  ExpressionAttributeNames: { '#pk': 'gsi2pk', '#sk1': 'gsi2sk' },
  ExpressionAttributeValues: {
    ':pk': '$taskapp#employeeid_jexotic',
    ':sk1': '$contributions#assignments'
  },
  IndexName: 'gsi2'
}

Try it out!

Looking above we can see that the assignments collection is actually a subset of the results that could be queried with the contributions collection. The power behind having the assignments sub-collection is the flexibility to further slice and dice your cross-entity queries into more specific and performant queries.

If you're interested in the naming used in the collection and access pattern definitions above, checkout the section on Naming Conventions

Index and Collection Naming Conventions

ElectroDB puts an emphasis on allowing users to define more domain specific naming. Instead of referring to indexes by their name on the table, ElectroDB allows users to define their indexes as Access Patterns.

Please refer to the Entities defined in the section Sub-Collection Entities as the source of examples within this section.

Index Naming Conventions

The following is an access pattern on the "employees" entity defined here:

staff: {
  pk: {
    field: "pk",
    composite: ["organizationId"]
  },
  sk: {
    field: "sk",
    composite: ["employeeId"]
  }
}

This Access Pattern is defined on the table's Primary Index (note the lack of an index property), is given the name staff, and is composed of an organiztionId and an employeeId.

When deciding on an Access Pattern name, ask yourself, "What would the array of items returned represent if I only supplied the Partition Key". In this example case, the entity defines an "Employee" by its organizationId and employeeId. If you performed a query against this index, and only provided organizationId you would then expect to receive all Employees for that Organization. From there, the name staff was chosen because the focus becomes "What are these Employees to that Organization?".

This convention also becomes evident when you consider Access Pattern name becomes the name of the method you use query that index.

await employee.query.staff({organizationId: "nike"}).go();

Collection Naming Conventions

The following are access patterns on entities defined here:

// employees entity
employee: {
  collection: "contributions",
  index: "gsi2",
  pk: {
    field: "gsi2pk",
    composite: ["employeeId"],
  },
  sk: {
    field: "gsi2sk",
    composite: [],
  },
}

// tasks entity
assigned: {
  collection: ["contributions", "assignments"],
  index: "gsi2",
  pk: {
    field: "gsi2pk",
    composite: ["employeeId"],
  },
  sk: {
    field: "gsi2sk",
    composite: ["projectId"],
  },
}

// projectMembers entity
projects: {
  collection: ["contributions", "assignments"] as const,
  index: "gsi2",
  pk: {
    field: "gsi2pk",
    composite: ["employeeId"],
  },
  sk: {
    field: "gsi2sk",
    composite: [],
  },
}

In the case of the entities above, we see an example of a sub-collection. ElectroDB will use the above definitions to generate two collections: contributions, assignments.

The considerations for naming a collection are nearly identical to the considerations for naming an index: What do the query results from supplying just the Partition Key represent? In the case of collections you must also consider what the results represent across all of the involved entities, and the entities that may be added in the future.

For example, the contributions collection is named such because when given an employeeId we receive the employee's details, the tasks the that employee, and the projects where they are currently a member.

In the case of assignments, we receive a subset of contributions when supplying an employeeId: Only the tasks and projects they are "assigned" are returned.

Filters

Filters are no longer the preferred way to add FilterExpressions. Checkout the Where section to find out about how to apply FilterExpressions and ConditionExpressions.

Building thoughtful indexes can make queries simple and performant. Sometimes you need to filter results down further. By adding Filters to your model, you can extend your queries with custom filters. Below is the traditional way you would add a filter to Dynamo's DocumentClient directly alongside how you would accomplish the same using a Filter function.

{
  "IndexName": "idx2",
  "TableName": "StoreDirectory",
  "ExpressionAttributeNames": {
    "#rent": "rent",
    "#discount": "discount",
    "#pk": "idx2pk",
    "#sk1": "idx2sk"
  },
  "ExpressionAttributeValues": {
    ":rent1": "2000.00",
    ":rent2": "5000.00",
    ":discount1": "1000.00",
    ":pk": "$mallstoredirectory_1#mallid_eastpointe",
    ":sk1": "$mallstore#leaseenddate_2020-04-01#rent_",
    ":sk2": "$mallstore#leaseenddate_2020-07-01#rent_"
  },
  "KeyConditionExpression": ",#pk = :pk and #sk1 BETWEEN :sk1 AND :sk2",
  "FilterExpression": "(#rent between :rent1 and :rent2) AND #discount <= :discount1"
}

Defined on the model

Deprecated but functional with 1.x

Filters can be defined on the model and used in your query chain.

/**
    * Filter by low rent a specific mall or a leaseEnd withing a specific range  
    * @param {Object} attributes - All attributes from the model with methods for each filter operation  
    * @param {...*} values - Values passed when calling the filter in a query chain.
**/
filters: {
    rentPromotions: function(attributes, minRent, maxRent, promotion)  {
        let {rent, discount} = attributes;
        return `
            ${rent.between(minRent, maxRent)} AND ${discount.lte(promotion)}
        `
    }
}


let StoreLocations  =  new Entity(model, {table: "StoreDirectory"});
let maxRent = "5000.00";
let minRent = "2000.00";
let promotion = "1000.00";
let stores = await MallStores.query
    .stores({ mallId: "EastPointe" })
    .between({ leaseEndDate:  "2020-04-01" }, { leaseEndDate:  "2020-07-01" })
    .rentPromotions(minRent, maxRent, promotion)
    .go();

// Equivalent Parameters
{
  IndexName: 'idx2',
  TableName: 'StoreDirectory',
  ExpressionAttributeNames: {
    '#rent': 'rent',
    '#discount': 'discount',
    '#pk': 'idx2pk',
    '#sk1': 'idx2sk'
  },
  ExpressionAttributeValues: {
    ':rent1': '2000.00',
    ':rent2': '5000.00',
    ':discount1': '1000.00',
    ':pk': '$mallstoredirectory_1#mallid_eastpointe',
    ':sk1': '$mallstore#leaseenddate_2020-04-01#rent_',
    ':sk2': '$mallstore#leaseenddate_2020-07-01#rent_'
  },
  KeyConditionExpression: '#pk = :pk and #sk1 BETWEEN :sk1 AND :sk2',
  FilterExpression: '(#rent between :rent1 and :rent2) AND #discount <= :discount1'
}

Defined via Filter method after query operators

Filters are no longer the preferred way to add FilterExpressions. Checkout the Where section to find out about how to apply FilterExpressions and ConditionExpressions.

The easiest way to use filters is to use them inline in your query chain.

let StoreLocations  =  new Entity(model, {table: "StoreDirectory"});
let maxRent = "5000.00";
let minRent = "2000.00";
let promotion = "1000.00";
let stores  =  await StoreLocations.query
    .leases({ mallId: "EastPointe" })
    .between({ leaseEndDate:  "2020-04-01" }, { leaseEndDate:  "2020-07-01" })
    .filter(({rent, discount}) => `
        ${rent.between(minRent, maxRent)} AND ${discount.lte(promotion)}
    `)
    .go();

// Equivalent Parameters
{
  IndexName: 'idx2',
  TableName: 'StoreDirectory',
  ExpressionAttributeNames: {
    '#rent': 'rent',
    '#discount': 'discount',
    '#pk': 'idx2pk',
    '#sk1': 'idx2sk'
  },
  ExpressionAttributeValues: {
    ':rent1': '2000.00',
    ':rent2': '5000.00',
    ':discount1': '1000.00',
    ':pk': '$mallstoredirectory_1#mallid_eastpointe',
    ':sk1': '$mallstore#leaseenddate_2020-04-01#rent_',
    ':sk2': '$mallstore#leaseenddate_2020-07-01#rent_'
  },
  KeyConditionExpression: '#pk = :pk and #sk1 BETWEEN :sk1 AND :sk2',
  FilterExpression: '(#rent between :rent1 and :rent2) AND #discount <= :discount1'
}

Filter functions allow you to write a FilterExpression without having to worry about the complexities of expression attributes. To accomplish this, ElectroDB injects an object attributes as the first parameter to all Filter Functions. This object contains every Attribute defined in the Entity's Model with the following operators as methods:

operator | example | result | ----------- | -------------------------------- |
gte | rent.gte(maxRent) | #rent >= :rent1 gt | rent.gt(maxRent) | #rent > :rent1 lte | rent.lte(maxRent) | #rent <= :rent1 lt | rent.lt(maxRent) | #rent < :rent1 eq | rent.eq(maxRent) | #rent = :rent1 ne | rent.ne(maxRent) | #rent <> :rent1 begins | rent.begins(maxRent) | begins_with(#rent, :rent1) exists | rent.exists() | attribute_exists(#rent) notExists | rent.notExists() | attribute_not_exists(#rent) contains | rent.contains(maxRent) | contains(#rent = :rent1) notContains | rent.notContains(maxRent) | not contains(#rent = :rent1) between | rent.between(minRent, maxRent) | (#rent between :rent1 and :rent2) name | rent.name() | #rent value | rent.value(maxRent) | :rent1

This functionality allows you to write the remaining logic of your FilterExpression with ease. Add complex nested and/or conditions or other FilterExpression logic while ElectroDB handles the ExpressionAttributeNames and ExpressionAttributeValues.

Multiple Filters

Filters are no longer the preferred way to add FilterExpressions. Checkout the Where section to find out about how to apply FilterExpressions and ConditionExpressions.

It is possible to chain together multiple filters. The resulting FilterExpressions are concatenated with an implicit AND operator.

let MallStores = new Entity(model, {table: "StoreDirectory"});
let stores = await MallStores.query
    .leases({ mallId: "EastPointe" })
    .between({ leaseEndDate: "2020-04-01" }, { leaseEndDate: "2020-07-01" })
    .filter(({ rent, discount }) => `
        ${rent.between("2000.00", "5000.00")} AND ${discount.eq("1000.00")}
    `)
    .filter(({ category }) => `
        ${category.eq("food/coffee")}
    `)
    .go();

// Equivalent Parameters
{
  TableName: 'StoreDirectory',
  ExpressionAttributeNames: {
    '#rent': 'rent',
    '#discount': 'discount',
    '#category': 'category',
    '#pk': 'idx2pk',
    '#sk1': 'idx2sk'
  },
  ExpressionAttributeValues: {
    ':rent1': '2000.00',
    ':rent2': '5000.00',
    ':discount1': '1000.00',
    ':category1': 'food/coffee',
    ':pk': '$mallstoredirectory_1#mallid_eastpointe',
    ':sk1': '$mallstore#leaseenddate_2020-04-01#storeid_',
    ':sk2': '$mallstore#leaseenddate_2020-07-01#storeid_'
  },
  KeyConditionExpression: '#pk = :pk and #sk1 BETWEEN :sk1 AND :sk2',
  IndexName: 'idx2',
  FilterExpression: '(#rent between :rent1 and :rent2) AND (#discount = :discount1 AND #category = :category1)'
}

Where

The where() method is an improvement on the filter() method. Unlike filter, where will be compatible with upcoming features related to complex types.

Building thoughtful indexes can make queries simple and performant. Sometimes you need to filter results down further or add conditions to an update/patch/put/create/delete/remove action.

FilterExpressions

Below is the traditional way you would add a FilterExpression to Dynamo's DocumentClient directly alongside how you would accomplish the same using the where method.

animals.query
  .exhibit({habitat: "Africa"})
  .where(({isPregnant, offspring}, {exists, eq}) => `
    ${eq(isPregnant, true)} OR ${exists(offspring)}
  `)
  .go()
{
  "KeyConditionExpression": "#pk = :pk and begins_with(#sk1, :sk1)",
  "TableName": "zoo_manifest",
  "ExpressionAttributeNames": {
    "#isPregnant": "isPregnant",
    "#offspring": "offspring",
    "#pk": "gsi1pk",
    "#sk1": "gsi1sk"
  },
  "ExpressionAttributeValues": {
    ":isPregnant0": true,
    ":pk": "$zoo#habitat_africa",
    ":sk1": "$animals_1#enclosure_"
  },
  "IndexName": "gsi1pk-gsi1sk-index",
  "FilterExpression": "#isPregnant = :isPregnant0 OR attribute_exists(#offspring)"
}

Try it out!

ConditionExpressions

Below is the traditional way you would add a ConditionExpression to Dynamo's DocumentClient directly alongside how you would accomplish the same using the where method.

animals.update({
    animal: "blackbear",
    name: "Isabelle"
  })
  // no longer pregnant because Ernesto was born!
  .set({
    isPregnant: false,
    lastEvaluation: "2021-09-12",
    lastEvaluationBy: "stephanie.adler"
  })
  // welcome to the world Ernesto!
  .append({
    offspring: [{
      name: "Ernesto",
      birthday: "2021-09-12",
      note: "healthy birth, mild pollen allergy"
    }]
  })
  // using the where clause can guard against making
  // updates against stale data
  .where(({isPregnant, lastEvaluation}, {lt, eq}) => `
    ${eq(isPregnant, true)} AND ${lt(lastEvaluation, "2021-09-12")}
  `)
  .go()
{
  "UpdateExpression": "SET #isPregnant = :isPregnant_u0, #lastEvaluation = :lastEvaluation_u0, #lastEvaluationBy = :lastEvaluationBy_u0, #offspring = list_append(#offspring, :offspring_u0)",
  "ExpressionAttributeNames": {
    "#isPregnant": "isPregnant",
    "#lastEvaluation": "lastEvaluation",
    "#lastEvaluationBy": "lastEvaluationBy",
    "#offspring": "offspring"
  },
  "ExpressionAttributeValues": {
    ":isPregnant0": true,
    ":lastEvaluation0": "2021-09-12",
    ":isPregnant_u0": false,
    ":lastEvaluation_u0": "2021-09-12",
    ":lastEvaluationBy_u0": "stephanie.adler",
    ":offspring_u0": [
      {
        "name": "Ernesto",
        "birthday": "2021-09-12",
        "note": "healthy birth, mild pollen allergy"
      }
    ]
  },
  "TableName": "zoo_manifest",
  "Key": {
    "pk": "$zoo#animal_blackbear",
    "sk": "$animals_1#name_isabelle"
  },
  "ConditionExpression": "#isPregnant = :isPregnant0 AND #lastEvaluation < :lastEvaluation0"
}

Try it out!

Where with Complex Attributes

ElectroDB supports using the where() method with DynamoDB's complex attribute types: map, list, and set. When using the injected attributes object, simply drill into the attribute itself to apply your update directly to the required object.

The following are examples on how to filter on complex attributes:

Example 1: Filtering on a map attribute

animals.query
    .farm({habitat: "Africa"})
    .where(({veterinarian}, {eq}) => eq(veterinarian.name, "Herb Peterson"))
    .go()

Try it out!

Example 1: Filtering on an element in a list attribute

animals.query
  .exhibit({habitat: "Tundra"})
  .where(({offspring}, {eq}) => eq(offspring[0].name, "Blitzen"))
  .go()

Try it out!

Attributes and Operations

Where functions allow you to write a FilterExpression or ConditionExpression without having to worry about the complexities of expression attributes. To accomplish this, ElectroDB injects an object attributes as the first parameter to all Filter Functions, and an object operations, as the second parameter. Pass the properties from the attributes object to the methods found on the operations object, along with inline values to set filters and conditions.

NOTE: where callbacks must return a string. All method on the operation object all return strings, so you can return the results of the operation method or use template strings compose an expression.

// A single filter operation 
animals.update({habitat: "Africa", enclosure: "5b"})
  .set({keeper: "Joe Exotic"})
  .where((attr, op) => op.eq(attr.dangerous, true))
  .go();

// A single filter operation w/ destructuring
animals.update({animal: "tiger", name: "janet"})
  .set({keeper: "Joe Exotic"})
  .where(({dangerous}, {eq}) => eq(dangerous, true))
  .go();

// Multiple conditions - `op`
animals.update({animal: "tiger", name: "janet"})
  .set({keeper: "Joe Exotic"})
  .where((attr, op) => `
    ${op.eq(attr.dangerous, true)} AND ${op.notExists(attr.lastFed)}
  `)
  .go();

// Multiple usages of `where` (implicit AND)
animals.update({animal: "tiger", name: "janet"})
  .set({keeper: "Joe Exotic"})
  .where((attr, op) => `
    ${op.eq(attr.dangerous, true)} OR ${op.notExists(attr.lastFed)}
  `)
  .where(({birthday}, {between}) => {
    const today = Date.now();
    const lastMonth = today - 1000 * 60 * 60 * 24 * 30;
    return between(birthday, lastMonth, today);
  })
  .go();

// "dynamic" filtering
function getAnimals(habitat, keepers) {
  const query = animals.query.exhibit({habitat});
  for (const name of keepers) {
    query.where(({keeper}, {eq}) => eq(keeper, name));
  }
  return query.go();
}

const keepers = [
  "Joe Exotic",
  "Carol Baskin"
];

getAnimals("RainForest", keepers);

Try it out!

The attributes object contains every Attribute defined in the Entity's Model. The operations object contains the following methods:

operatorexampleresult
eqeq(rent, maxRent)#rent = :rent1
neeq(rent, maxRent)#rent <> :rent1
gtegte(rent, value)#rent >= :rent1
gtgt(rent, maxRent)#rent > :rent1
ltelte(rent, maxRent)#rent <= :rent1
ltlt(rent, maxRent)#rent < :rent1
beginsbegins(rent, maxRent)begins_with(#rent, :rent1)
existsexists(rent)attribute_exists(#rent)
notExistsnotExists(rent)attribute_not_exists(#rent)
containscontains(rent, maxRent)contains(#rent = :rent1)
notContainsnotContains(rent, maxRent)not contains(#rent = :rent1)
betweenbetween(rent, minRent, maxRent)(#rent between :rent1 and :rent2)
namename(rent)#rent
valuevalue(rent, maxRent):rent1

Multiple Where Clauses

It is possible to include chain multiple where clauses. The resulting FilterExpressions (or ConditionExpressions) are concatenated with an implicit AND operator.

let MallStores = new Entity(model, {table: "StoreDirectory"});
let stores = await MallStores.query
    .leases({ mallId: "EastPointe" })
    .between({ leaseEndDate: "2020-04-01" }, { leaseEndDate: "2020-07-01" })
    .where(({ rent, discount }, {between, eq}) => `
        ${between(rent, "2000.00", "5000.00")} AND ${eq(discount, "1000.00")}
    `)
    .where(({ category }, {eq}) => `
        ${eq(category, "food/coffee")}
    `)
    .go();

// Equivalent Parameters
{
  TableName: 'StoreDirectory',
  ExpressionAttributeNames: {
    '#rent': 'rent',
    '#discount': 'discount',
    '#category': 'category',
    '#pk': 'idx2pk',
    '#sk1': 'idx2sk'
  },
  ExpressionAttributeValues: {
    ':rent1': '2000.00',
    ':rent2': '5000.00',
    ':discount1': '1000.00',
    ':category1': 'food/coffee',
    ':pk': '$mallstoredirectory_1#mallid_eastpointe',
    ':sk1': '$mallstore#leaseenddate_2020-04-01#storeid_',
    ':sk2': '$mallstore#leaseenddate_2020-07-01#storeid_'
  },
  KeyConditionExpression: '#pk = :pk and #sk1 BETWEEN :sk1 AND :sk2',
  IndexName: 'idx2',
  FilterExpression: '(#rent between :rent1 and :rent2) AND (#discount = :discount1 AND #category = :category1)'
}

Parse

The parse method can be given a DocClient response and return a typed and formatted ElectroDB item.

ElectroDB's parse() method accepts results from get, delete, put, update, query, and scan operations, applies all the same operations as though the item was retrieved by ElectroDB itself, and will return null (or empty array for query results) if the item could not be parsed.

const myEntity = new Entity({...});
const getResults = docClient.get({...}).promise();
const queryResults = docClient.query({...}).promise();
const updateResults = docClient.update({...}).promise(); 
const formattedGetResults = myEntity.parse(getResults);
const formattedQueryResults = myEntity.parse(formattedQueryResults);

Parse also accepts an optional options object as a second argument (see the section Query Options to learn more). Currently, the following query options are relevant to the parse() method:

Option | Default | Notes ----------------- : ------- | ----- ignoreOwnership | true | This property defaults to true here, unlike elsewhere in the application when it defaults to false. You can overwrite the default here with your own preference.

Building Queries

For hands-on learners: the following example can be followed along with and executed on runkit: https://runkit.com/tywalch/electrodb-building-queries

ElectroDB queries use DynamoDB's query method to find records based on your table's indexes.

NOTE: By default, ElectroDB will paginate through all items that match your query. To limit the number of items ElectroDB will retrieve, read more about the Query Options pages and limit, or use the ElectroDB Pagination API for fine-grain pagination support.

Forming a composite Partition Key and Sort Key is a critical step in planning Access Patterns in DynamoDB. When planning composite keys, it is crucial to consider the order in which they are composed. As of the time of writing this documentation, DynamoDB has the following constraints that should be taken into account when planning your Access Patterns:

  1. You must always supply the Partition Key in full for all queries to DynamoDB.
  2. You currently only have the following operators available on a Sort Key: begins_with, between, >, >=, <, <=, and Equals.
  3. To act on single record, you will need to know the full Partition Key and Sort Key for that record.

Using composite attributes to make hierarchical keys

Carefully considering your Composite Attribute order will allow ElectroDB to express hierarchical relationships and unlock more available Access Patterns for your application.

For example, let's say you have a StoreLocations Entity that represents Store Locations inside Malls:

Shopping Mall Stores

let schema = {  
    model: {
      service: "MallStoreDirectory",  
      entity: "MallStore",
      version: "1",    
    },  
    attributes: {
        cityId: {
            type: "string",
            required: true,
        }, 
        mallId: {  
            type: "string",  
            required: true,  
        },  
        storeId: {  
            type: "string",  
            required: true,  
        },  
        buildingId: {  
            type: "string",  
            required: true,  
        },  
        unitId: {  
            type: "string",  
            required: true,
        },  
        category: {  
            type: [
                "spite store",
                "food/coffee", 
                "food/meal", 
                "clothing", 
                "electronics", 
                "department", 
                "misc"
            ],  
            required: true  
        },  
        leaseEndDate: {  
            type: "string",  
            required: true  
        },
        rent: {
            type: "string",
            required: true,
            validate: /^(\d+\.\d{2})$/
        },
        discount: {
            type: "string",
            required: false,
            default: "0.00",
            validate: /^(\d+\.\d{2})$/
        }  
    },  
    indexes: {  
        stores: {  
            pk: {
                field: "pk",
                composite: ["cityId", "mallId"]
            }, 
            sk: {
                field: "sk",
                composite: ["buildingId", "storeId"]
            }  
        },  
        units: {  
            index: "gis1pk-gsi1sk-index",  
            pk: {
                field: "gis1pk",
                composite: ["mallId"]
            },  
            sk: {
                field: "gsi1sk",
                composite: ["buildingId", "unitId"]
            }  
        },
        leases: {
            index: "gis2pk-gsi2sk-index",
            pk: {
                field: "gis2pk",
                composite: ["storeId"]
            },  
            sk: {
                field: "gsi2sk",
                composite: ["leaseEndDate"]
            }  
        }
    }
};
const StoreLocations = new Entity(schema, {table: "StoreDirectory"});

Query App Records

Examples in this section using the MallStore schema defined above, and available for interacting with here: https://runkit.com/tywalch/electrodb-building-queries

All queries start from the Access Pattern defined in the schema.

const MallStore = new Entity(schema, {table: "StoreDirectory"}); 
// Each Access Pattern is available on the Entity instance
// MallStore.query.stores()
// MallStore.query.malls()

Partition Key Composite Attributes

All queries require (at minimum) the Composite Attributes included in its defined Partition Key. Composite Attributes you define on the Sort Key can be partially supplied, but must be supplied in the order they are defined.

Important: Composite Attributes must be supplied in the order they are composed when invoking the Access Pattern. This is because composite attributes are used to form a concatenated key string, and if attributes supplied out of order, it is not possible to fill the gaps in that concatenation.

const MallStore = new Entity({
  model: {
    service: "mallmgmt",
    entity: "store", 
    version: "1"
  },
  attributes: {
    cityId: "string",
    mallId: "string",
    storeId: "string",
    buildingId: "string",
    unitId: "string",
    name: "string",
    description: "string",
    category: "string"
  },
  indexes: {
    stores: {
      pk: {
        field: "pk",
        composite: ["cityId", "mallId"]
      },
      sk: {
        field: "sk",
        composite: ["storeId", "unitId"]
      }
    }
  }
}, {table: "StoreDirectory"});

const cityId = "Atlanta1";
const mallId = "EastPointe";
const storeId = "LatteLarrys";
const unitId = "B24";
const buildingId = "F34";

// Good: Includes at least the PK
StoreLocations.query.stores({cityId, mallId});

// Good: Includes at least the PK, and the first SK attribute
StoreLocations.query.stores({cityId, mallId, storeId});

// Good: Includes at least the PK, and the all SK attributes   
StoreLocations.query.stores({cityId, mallId, storeId, unitId});

// Bad: No PK composite attributes specified, will throw
StoreLocations.query.stores();

// Bad: Not All PK Composite Attributes included (cityId), will throw
StoreLocations.query.stores({mallId});

// Bad: Composite Attributes not included in order, will NOT throw, but will ignore `unitId` because `storeId` was not supplied as well
StoreLocations.query.stores({cityId, mallId, unitId});

Sort Key Operations

operatoruse case
beginsKeys starting with a particular set of characters.
betweenKeys between a specified range.
gtKeys less than some value
gteKeys less than or equal to some value
ltKeys greater than some value
lteKeys greater than or equal to some value

Each record represents one Store location. All Stores are located in Malls we manage.

To satisfy requirements for searching based on location, you could use the following keys: Each StoreLocations record would have a Partition Key with the store's storeId. This key alone is not enough to identify a particular store. To solve this, compose a Sort Key for the store's location attribute ordered hierarchically (mall/building/unit): ["mallId", "buildingId", "unitId"].

The StoreLocations entity above, using just the stores Index alone enables four Access Patterns:

  1. All LatteLarrys locations in all Malls
  2. All LatteLarrys locations in one Mall
  3. All LatteLarrys locations inside a specific Mall
  4. A specific LatteLarrys inside of a Mall and Building

Query Chains

Queries in ElectroDB are built around the Access Patterns defined in the Schema and are capable of using partial key Composite Attributes to create performant lookups. To accomplish this, ElectroDB offers a predictable chainable API.

Examples in this section using the StoreLocations schema defined above and can be directly experiment with on runkit: https://runkit.com/tywalch/electrodb-building-queries

The methods: Get (get), Create (put), Update (update), and Delete (delete) *require all composite attributes described in the Entities' primary PK and SK.

Query Method

ElectroDB queries use DynamoDB's query method to find records based on your table's indexes. To read more about queries checkout the section Building Queries

NOTE: By default, ElectroDB will paginate through all items that match your query. To limit the number of items ElectroDB will retrieve, read more about the Query Options pages and limit, or use the ElectroDB Pagination API for fine-grain pagination support.

Get Method

Provide all Table Index composite attributes in an object to the get method. In the event no record is found, a value of null will be returned.

NOTE: As part of ElectroDB's roll out of 1.0.0, a breaking change was made to the get method. Prior to 1.0.0, the get method would return an empty object if a record was not found. This has been changed to now return a value of null in this case.

let results = await StoreLocations.get({
    storeId: "LatteLarrys", 
    mallId: "EastPointe", 
    buildingId: "F34", 
    cityId: "Atlanta1"
}).go();

// Equivalent Params:
// {
//   Key: {
//     pk: "$mallstoredirectory#cityid_atlanta1#mallid_eastpointe",
//     sk: "$mallstore_1#buildingid_f34#storeid_lattelarrys"
//   },
//   TableName: 'StoreDirectory'
// }

Batch Get

Provide all Table Index composite attributes in an array of objects to the get method to perform a BatchGet query.

NOTE: Performing a BatchGet will return a response structure unique to BatchGet: a two-dimensional array with the results of the query and any unprocessed records. See the example below. Additionally, when performing a BatchGet the .params() method will return an array of parameters, rather than just the parameters for one docClient query. This is because ElectroDB BatchGet queries larger than the docClient's limit of 100 records.

If the number of records you are requesting is above the BatchGet threshold of 100 records, ElectroDB will make multiple requests to DynamoDB and return the results in a single array. By default, ElectroDB will make these requests in series, one after another. If you are confident your table can handle the throughput, you can use the Query Option concurrent. This value can be set to any number greater than zero, and will execute that number of requests simultaneously.

For example, 150 records (50 records over the DynamoDB maximum):

The default value of concurrent will be 1. ElectroDB will execute a BatchGet request of 100, then after that request has responded, make another BatchGet request for 50 records.

If you set the Query Option concurrent to 2, ElectroDB will execute a BatchGet request of 100 records, and another BatchGet request for 50 records without waiting for the first request to finish.

It is important to consider your Table's throughput considerations when setting this value.

let [results, unprocessed] = await StoreLocations.get([
    {
        storeId: "LatteLarrys", 
        mallId: "EastPointe", 
        buildingId: "F34", 
        cityId: "Atlanta1"
    },
    {
        storeId: "MochaJoes", 
        mallId: "WestEnd", 
        buildingId: "A21", 
        cityId: "Madison2"
    }   
]).go({concurrent: 1}); // `concurrent` value is optional and default's to `1`

// Equivalent Params:
// {
//   "RequestItems": {
//     "electro": {
//       "Keys": [
//         {
//           "pk": "$mallstoredirectory#cityid_atlanta1#mallid_eastpointe",
//           "sk": "$mallstore_1#buildingid_f34#storeid_lattelarrys"
//         },
//         {
//           "pk": "$mallstoredirectory#cityid_madison2#mallid_westend",
//           "sk": "$mallstore_1#buildingid_a21#storeid_mochajoes"
//         }
//       ]
//     }
//   }
// }

The two-dimensional array returned by batch get most easily used when deconstructed into two variables, in the above case: results and unprocessed.

The results array are records that were returned DynamoDB as Responses on the BatchGet query. They will appear in the same format as other ElectroDB queries.

Elements of the unprocessed array are unlike results received from a query. Instead of containing all the attributes of a record, an unprocessed record only includes the composite attributes defined in the Table Index. This is in keeping with DynamoDB's practice of returning only Keys in the case of unprocessed records. For convenience, ElectroDB will return these keys as composite attributes, but you can pass the query option {unprocessed:"raw"} override this behavior and return the Keys as they came from DynamoDB.

Delete Method

Provide all Table Index composite attributes in an object to the delete method to delete a record.

await StoreLocations.delete({
    storeId: "LatteLarrys", 
    mallId: "EastPointe", 
    buildingId: "F34", 
    cityId: "Atlanta1"
}).go();

// Equivalent Params:
// {
//   Key: {
//     pk: "$mallstoredirectory#cityid_atlanta1#mallid_eastpointe",
//     sk: "$mallstore_1#buildingid_f34#storeid_lattelarrys"
//   },
//   TableName: 'StoreDirectory'
// }

Batch Write Delete Records

Provide all table index composite attributes in an array of objects to the delete method to batch delete records.

NOTE: Performing a Batch Delete will return an array of "unprocessed" records. An empty array signifies all records were processed. If you want the raw DynamoDB response you can always use the option {raw: true}, more detail found here: Query Options. Additionally, when performing a BatchWrite the .params() method will return an array of parameters, rather than just the parameters for one docClient query. This is because ElectroDB BatchWrite queries larger than the docClient's limit of 25 records.

If the number of records you are requesting is above the BatchWrite threshold of 25 records, ElectroDB will make multiple requests to DynamoDB and return the results in a single array. By default, ElectroDB will make these requests in series, one after another. If you are confident your table can handle the throughput, you can use the Query Option concurrent. This value can be set to any number greater than zero, and will execute that number of requests simultaneously.

For example, 75 records (50 records over the DynamoDB maximum):

The default value of concurrent will be 1. ElectroDB will execute a BatchWrite request of 25, then after that request has responded, make another BatchWrite request for 25 records, and then another.

If you set the Query Option concurrent to 2, ElectroDB will execute a BatchWrite request of 25 records, and another BatchGet request for 25 records without waiting for the first request to finish. After those two have finished it will execute another BatchWrite request for 25 records.

It is important to consider your Table's throughput considerations when setting this value.

let unprocessed = await StoreLocations.delete([
    {
        storeId: "LatteLarrys", 
        mallId: "EastPointe", 
        buildingId: "F34", 
        cityId: "LosAngeles1"
    },
    {
        storeId: "MochaJoes", 
        mallId: "EastPointe", 
        buildingId: "F35", 
        cityId: "LosAngeles1"
    }
]).go({concurrent: 1}); // `concurrent` value is optional and default's to `1` 

// Equivalent Params:
{
  "RequestItems": {
    "StoreDirectory": [
      {
        "DeleteRequest": {
          "Key": {
            "pk": "$mallstoredirectory#cityid_losangeles1#mallid_eastpointe",
            "sk": "$mallstore_1#buildingid_f34#storeid_lattelarrys"
          }
        }
      },
      {
        "DeleteRequest": {
          "Key": {
            "pk": "$mallstoredirectory#cityid_losangeles1#mallid_eastpointe",
            "sk": "$mallstore_1#buildingid_f35#storeid_mochajoes"
          }
        }
      }
    ]
  }
}

Elements of the unprocessed array are unlike results received from a query. Instead of containing all the attributes of a record, an unprocessed record only includes the composite attributes defined in the Table Index. This is in keeping with DynamoDB's practice of returning only Keys in the case of unprocessed records. For convenience, ElectroDB will return these keys as composite attributes, but you can pass the query option {unprocessed:"raw"} override this behavior and return the Keys as they came from DynamoDB.

Put Record

Provide all required Attributes as defined in the model to create a new record. ElectroDB will enforce any defined validations, defaults, casting, and field aliasing. A Put operation will trigger the default, and set attribute callbacks when writing to DynamoDB. By default, after performing a put() or create() operation, ElectroDB will format and return the record through the same process as a Get/Query. This process will invoke the get callback on all included attributes. If this behaviour is not desired, use the Query Option response:"none" to return a null value.

This example includes an optional conditional expression

await StoreLocations
  .put({
      cityId: "Atlanta1",
      storeId: "LatteLarrys",
      mallId: "EastPointe",
      buildingId: "BuildingA1",
      unitId: "B47",
      category: "food/coffee",
      leaseEndDate: "2020-03-22",
      rent: "4500.00"
  })
  .where((attr, op) => op.eq(attr.rent, "4500.00"))
  .go()

// Equivalent Params:
{
  "Item": {
    "cityId": "Atlanta1",
    "mallId": "EastPointe",
    "storeId": "LatteLarrys",
    "buildingId": "BuildingA1",
    "unitId": "B47",
    "category": "food/coffee",
    "leaseEndDate": "2020-03-22",
    "rent": "4500.00",
    "discount": "0.00",
    "pk": "$mallstoredirectory#cityid_atlanta1#mallid_eastpointe",
    "sk": "$mallstore_1#buildingid_buildinga1#storeid_lattelarrys",
    "gis1pk": "$mallstoredirectory#mallid_eastpointe",
    "gsi1sk": "$mallstore_1#buildingid_buildinga1#unitid_b47",
    "gis2pk": "$mallstoredirectory#storeid_lattelarrys",
    "gsi2sk": "$mallstore_1#leaseenddate_2020-03-22",
    "__edb_e__": "MallStore",
    "__edb_v__": "1"
  },
  "TableName": "StoreDirectory",
  "ConditionExpression": "#rent = :rent_w1",
  "ExpressionAttributeNames": {
    "#rent": "rent"
  },
  "ExpressionAttributeValues": {
    ":rent_w1": "4500.00"
  }
}

Batch Write Put Records

Provide all required Attributes as defined in the model to create records as an array to .put(). ElectroDB will enforce any defined validations, defaults, casting, and field aliasing. Another convenience ElectroDB provides, is accepting BatchWrite arrays larger than the 25 record limit. This is achieved making multiple, "parallel", requests to DynamoDB for batches of 25 records at a time. A failure with any of these requests will cause the query to throw, so be mindful of your table's configured throughput.

NOTE: Performing a Batch Put will return an array of "unprocessed" records. An empty array signifies all records returned were processed. If you want the raw DynamoDB response you can always use the option {raw: true}, more detail found here: Query Options. Additionally, when performing a BatchWrite the .params() method will return an array of parameters, rather than just the parameters for one docClient query. This is because ElectroDB BatchWrite queries larger than the docClient's limit of 25 records.

If the number of records you are requesting is above the BatchWrite threshold of 25 records, ElectroDB will make multiple requests to DynamoDB and return the results in a single array. By default, ElectroDB will make these requests in series, one after another. If you are confident your table can handle the throughput, you can use the Query Option concurrent. This value can be set to any number greater than zero, and will execute that number of requests simultaneously.

For example, 75 records (50 records over the DynamoDB maximum):

The default value of concurrent will be 1. ElectroDB will execute a BatchWrite request of 25, then after that request has responded, make another BatchWrite request for 25 records, and then another.

If you set the Query Option concurrent to 2, ElectroDB will execute a BatchWrite request of 25 records, and another BatchGet request for 25 records without waiting for the first request to finish. After those two have finished it will execute another BatchWrite request for 25 records.

It is important to consider your Table's throughput considerations when setting this value.

let unprocessed = await StoreLocations.put([
    {
        cityId: "LosAngeles1",
        storeId: "LatteLarrys",
        mallId: "EastPointe",
        buildingId: "F34",
        unitId: "a1",
        category: "food/coffee",
        leaseEndDate: "2022-03-22",
        rent: "4500.00"
    },
    {
        cityId: "LosAngeles1",
        storeId: "MochaJoes",
        mallId: "EastPointe",
        buildingId: "F35",
        unitId: "a2",
        category: "food/coffee",
        leaseEndDate: "2021-01-22",
        rent: "1500.00"
    }
]).go({concurrent: 1}); // `concurrent` value is optional and default's to `1`

// Equivalent Params:
{
  "RequestItems": {
    "StoreDirectory": [
      {
        "PutRequest": {
          "Item": {
            "cityId": "LosAngeles1",
            "mallId": "EastPointe",
            "storeId": "LatteLarrys",
            "buildingId": "F34",
            "unitId": "a1",
            "category": "food/coffee",
            "leaseEndDate": "2022-03-22",
            "rent": "4500.00",
            "discount": "0.00",
            "pk": "$mallstoredirectory#cityid_losangeles1#mallid_eastpointe",
            "sk": "$mallstore_1#buildingid_f34#storeid_lattelarrys",
            "gis1pk": "$mallstoredirectory#mallid_eastpointe",
            "gsi1sk": "$mallstore_1#buildingid_f34#unitid_a1",
            "gis2pk": "$mallstoredirectory#storeid_lattelarrys",
            "gsi2sk": "$mallstore_1#leaseenddate_2022-03-22",
            "__edb_e__": "MallStore",
            "__edb_v__": "1"
          }
        }
      },
      {
        "PutRequest": {
          "Item": {
            "cityId": "LosAngeles1",
            "mallId": "EastPointe",
            "storeId": "MochaJoes",
            "buildingId": "F35",
            "unitId": "a2",
            "category": "food/coffee",
            "leaseEndDate": "2021-01-22",
            "rent": "1500.00",
            "discount": "0.00",
            "pk": "$mallstoredirectory#cityid_losangeles1#mallid_eastpointe",
            "sk": "$mallstore_1#buildingid_f35#storeid_mochajoes",
            "gis1pk": "$mallstoredirectory#mallid_eastpointe",
            "gsi1sk": "$mallstore_1#buildingid_f35#unitid_a2",
            "gis2pk": "$mallstoredirectory#storeid_mochajoes",
            "gsi2sk": "$mallstore_1#leaseenddate_2021-01-22",
            "__edb_e__": "MallStore",
            "__edb_v__": "1"
          }
        }
      }
    ]
  }
}

Elements of the unprocessed array are unlike results received from a query. Instead of containing all the attributes of a record, an unprocessed record only includes the composite attributes defined in the Table Index. This is in keeping with DynamoDB's practice of returning only Keys in the case of unprocessed records. For convenience, ElectroDB will return these keys as composite attributes, but you can pass the query option {unprocessed:"raw"} override this behavior and return the Keys as they came from DynamoDB.

Update Record

Update Methods are available after the method update() is called, and allow you to perform alter an item stored dynamodb. The methods can be used (and reused) in a chain to form update parameters, when finished with .params(), or an update operation, when finished with .go(). If your application requires the update method to return values related to the update (e.g. via the ReturnValues DocumentClient parameters), you can use the Query Option {response: "none" | "all_old" | "updated_old" | "all_new" | "updated_new"} with the value that matches your need. By default, the Update operation returns an empty object when using .go().

ElectroDB will validate an attribute's type when performing an operation (e.g. that the subtract() method can only be performed on numbers), but will defer checking the logical validity your update operation to the DocumentClient. If your query performs multiple mutations on a single attribute, or perform other illogical operations given nature of an item/attribute, ElectroDB will not validate these edge cases and instead will simply pass back any error(s) thrown by the Document Client.

Update MethodAttribute TypesParameter
setnumber string boolean enum map list set anyobject
removenumber string boolean enum map list set anyarray
addnumber any setobject
subtractnumberobject
appendany listobject
deleteany setobject
data*callback

Updates to Composite Attributes

ElectroDB adds some constraints to update calls to prevent the accidental loss of data. If an access pattern is defined with multiple composite attributes, then ElectroDB ensure the attributes cannot be updated individually. If an attribute involved in an index composite is updated, then the index key also must be updated, and if the whole key cannot be formed by the attributes supplied to the update, then it cannot create a composite key without overwriting the old data.

This example shows why a partial update to a composite key is prevented by ElectroDB:

{
  "index": "my-gsi",
  "pk": {
    "field": "gsi1pk",
    "composite": ["attr1"]
  },
  "sk": {
    "field": "gsi1sk",
    "composite": ["attr2", "attr3"]
  }
}

The above secondary index definition would generate the following index keys:

{
  "gsi1pk": "$service#attr1_value1",
  "gsi1sk": "$entity_version#attr2_value2#attr3_value6"
}

If a user attempts to update the attribute attr2, then ElectroDB has no way of knowing value of the attribute attr3 or if forming the composite key without it would overwrite its value. The same problem exists if a user were to update attr3, ElectroDB cannot update the key without knowing each composite attribute's value.

In the event that a secondary index includes composite values from the table's primary index, ElectroDB will draw from the values supplied for the update key to address index gaps in the secondary index. For example:

For the defined indexes:

{
  "accessPattern1": {
    "pk": {
      "field": "pk",
      "composite": ["attr1"]
    },
    "sk": {
      "field": "sk",
      "composite": ["attr2"]
    }
  },
  "accessPattern2": {
    "index": "my-gsi",
    "pk": {
      "field": "gsi1pk",
      "composite": ["attr3"]
    },
    "sk": {
      "field": "gsi1sk",
      "composite": ["attr2", "attr4"]
    }
  }
}

A user could update attr4 alone because ElectroDB is able to leverage the value for attr2 from values supplied to the update() method:

entity.update({ attr1: "value1", attr2: "value2" })
  .set({ attr4: "value4" })
  .go();

{
  "UpdateExpression": "SET #attr4 = :attr4_u0, #gsi1sk = :gsi1sk_u0, #attr1 = :attr1_u0, #attr2 = :attr2_u0",
  "ExpressionAttributeNames": {
    "#attr4": "attr4",
    "#gsi1sk": "gsi1sk",
    "#attr1": "attr1",
    "#attr2": "attr2"
  },
  "ExpressionAttributeValues": {
    ":attr4_u0": "value6",
    // This index was successfully built
    ":gsi1sk_u0": "$update-edgecases_1#attr2_value2#attr4_value6",
    ":attr1_u0": "value1",
    ":attr2_u0": "value2"
  },
  "TableName": "test_table",
  "Key": { 
    "pk": "$service#attr1_value1", 
    "sk": "$entity_version#attr2_value2" 
  }
}

Note: Included in the update are all attributes from the table's primary index. These values are automatically included on all updates in the event an update results in an insert.

Update Method: Set

The set() method will accept all attributes defined on the model. Provide a value to apply or replace onto the item.

await StoreLocations
    .update({cityId, mallId, storeId, buildingId})
    .set({category: "food/meal"})
    .where((attr, op) => op.eq(attr.category, "food/coffee"))
    .go()

// Equivalent Params:
{
  "UpdateExpression": "SET #category = :category",
  "ExpressionAttributeNames": {
    "#category": "category"
  },
  "ExpressionAttributeValues": {
    ":category_w1": "food/coffee",
    ":category": "food/meal"
  },
  "TableName": "StoreDirectory",
  "Key": {
    "pk": "$mallstoredirectory#cityid_atlanta1#mallid_eastpointe",
    "sk": "$mallstore_1#buildingid_f34#storeid_lattelarrys"
  },
  "ConditionExpression": "#category = :category_w1"
}

Update Method: Remove

The remove() method will accept all attributes defined on the model. Unlike most other update methods, the remove() method accepts an array with the names of the attributes that should be removed.

NOTE that the attribute property required functions as a sort of NOT NULL flag. Because of this, if a property exists as required:true it will not be possible to remove that property in particular. If the attribute is a property is on "map", and the "map" is not required, then the "map" can be removed.

await StoreLocations
    .update({cityId, mallId, storeId, buildingId})
    .remove(["category"])
    .where((attr, op) => op.eq(attr.category, "food/coffee"))
    .go()

// Equivalent Params:
{
  "UpdateExpression": "REMOVE #category",
  "ExpressionAttributeNames": {
    "#category": "category"
  },
  "ExpressionAttributeValues": {
    ":category0": "food/coffee"
  },
  "TableName": "StoreDirectory",
  "Key": {
    "pk": "$mallstoredirectory#cityid_atlanta#mallid_eastpointe",
    "sk": "$mallstore_1#buildingid_a34#storeid_lattelarrys"
  },
  "ConditionExpression": "#category = :category0"
}

Update Method: Add

The add() method will accept attributes with type number, set, and any defined on the model. In the case of a number attribute, provide a number to add to the existing attribute's value on the item.

If the attribute is defined as any, the syntax compatible with the attribute type set will be used. For this reason, do not use the attribute type any to represent a number.

const newTenant = client.createSet("larry");

await StoreLocations
    .update({cityId, mallId, storeId, buildingId})
    .add({
      rent: 100,         // "number" attribute
      tenant: ["larry"]  // "set" attribute
    })
    .where((attr, op) => op.eq(attr.category, "food/coffee"))
    .go()

// Equivalent Params:
{
  "UpdateExpression": "SET #rent = #rent + :rent0 ADD #tenant :tenant0",
  "ExpressionAttributeNames": {
    "#category": "category",
    "#rent": "rent",
    "#tenant": "tenant"
  },
  "ExpressionAttributeValues": {
    ":category0": "food/coffee",
    ":rent0": 100,
    ":tenant0": ["larry"]
  },
  "TableName": "StoreDirectory",
  "Key": {
    "pk": "$mallstoredirectory#cityid_atlanta#mallid_eastpointe",
    "sk": "$mallstore_1#buildingid_a34#storeid_lattelarrys"
  },
  "ConditionExpression": "#category = :category0"
}

Update Method: Subtract

The subtract() method will accept attributes with type number. In the case of a number attribute, provide a number to subtract from the existing attribute's value on the item.

await StoreLocations
    .update({cityId, mallId, storeId, buildingId})
    .subtract({deposit: 500})
    .where((attr, op) => op.eq(attr.category, "food/coffee"))
    .go()

// Equivalent Params:
{
  "UpdateExpression": "SET #deposit = #deposit - :deposit0",
  "ExpressionAttributeNames": {
    "#category": "category",
    "#deposit": "deposit"
  },
  "ExpressionAttributeValues": {
    ":category0": "food/coffee",
    ":deposit0": 500
  },
  "TableName": "StoreDirectory",
  "Key": {
    "pk": "$mallstoredirectory#cityid_atlanta#mallid_eastpointe",
    "sk": "$mallstore_1#buildingid_a34#storeid_lattelarrys"
  },
  "ConditionExpression": "#category = :category0"
}

Update Method: Append

The append() method will accept attributes with type any. This is a convenience method for working with DynamoDB lists, and is notably different that set because it will add an element to an existing array, rather than overwrite the existing value.

await StoreLocations
    .update({cityId, mallId, storeId, buildingId})
    .append({
      rentalAgreement: [{
        type: "ammendment", 
        detail: "no soup for you"
      }]
    })
    .where((attr, op) => op.eq(attr.category, "food/coffee"))
    .go()

// Equivalent Params:
{
  "UpdateExpression": "SET #rentalAgreement = list_append(#rentalAgreement, :rentalAgreement0)",
  "ExpressionAttributeNames": {
    "#category": "category",
    "#rentalAgreement": "rentalAgreement"
  },
  "ExpressionAttributeValues": {
    ":category0": "food/coffee",
    ":rentalAgreement0": [
      {
        "type": "ammendment",
        "detail": "no soup for you"
      }
    ]
  },
  "TableName": "StoreDirectory",
  "Key": {
    "pk": "$mallstoredirectory#cityid_atlanta#mallid_eastpointe",
    "sk": "$mallstore_1#buildingid_a34#storeid_lattelarrys"
  },
  "ConditionExpression": "#category = :category0"
}

Update Method: Delete

The delete() method will accept attributes with type any or set . This operation removes items from a the contract attribute, defined as a set attribute.

await StoreLocations
    .update({cityId, mallId, storeId, buildingId})
    .delete({contact: ['555-345-2222']})
    .where((attr, op) => op.eq(attr.category, "food/coffee"))
    .go()

// Equivalent Params:
{
  "UpdateExpression": "DELETE #contact :contact0",
  "ExpressionAttributeNames": {
    "#category": "category",
    "#contact": "contact"
  },
  "ExpressionAttributeValues": {
    ":category0": "food/coffee",
    ":contact0": "555-345-2222"
  },
  "TableName": "StoreDirectory",
  "Key": {
    "pk": "$mallstoredirectory#cityid_atlanta#mallid_eastpointe",
    "sk": "$mallstore_1#buildingid_a34#storeid_lattelarrys"
  },
  "ConditionExpression": "#category = :category0"
}

Update Method: Data

The data() allows for different approach to updating your item, by accepting a callback with a similar argument signature to the where clause.

The callback provided to the data method is injected with an attributes object as the first parameter, and an operations object as the second parameter. All operations accept an attribute from the attributes object as a first parameter, and optionally accept a second value parameter.

As mentioned above, this method is functionally similar to the where clause with one exception: The callback provided to data() is not expected to return a value. When you invoke an injected operation method, the side effects are applied directly to update expression you are building.

operationexampleresultdescription
setset(category, value)#category = :category0Add or overwrite existing value
addadd(tenant, name)#tenant :tenant1Add value to existing set attribute (used when provided attribute is of type any or set)
addadd(rent, amount)#rent = #rent + :rent0Mathematically add given number to existing number on record
subtractsubtract(deposit, amount)#deposit = #deposit - :deposit0Mathematically subtract given number from existing number on record
removeremove(petFee)#petFeeRemove attribute/property from item
appendappend(rentalAgreement, amendment)#rentalAgreement = list_append(#rentalAgreement, :rentalAgreement0)Add element to existing list attribute
deletedelete(tenant, name)#tenant :tenant1Remove item from existing set attribute
deldel(tenant, name)#tenant :tenant1Alias for delete operation
namename(rent)#rentReference another attribute's name, can be passed to other operation that allows leveraging existing attribute values in calculating new values
valuevalue(rent, value):rent1Create a reference to a particular value, can be passed to other operation that allows leveraging existing attribute values in calculating new values
await StoreLocations
    .update({cityId, mallId, storeId, buildingId})
    .data((a, o) => {
        const newTenant = a.value(attr.tenant, "larry");
        o.set(a.category, "food/meal");   // electrodb "enum"   -> dynamodb "string"
        o.add(a.tenant, newTenant);       // electrodb "set"    -> dynamodb "set"
        o.add(a.rent, 100);               // electrodb "number" -> dynamodb "number"
        o.subtract(a.deposit, 200);       // electrodb "number" -> dynamodb "number"
        o.remove(a.leaseEndDate);         // electrodb "string" -> dynamodb "string"
        o.append(a.rentalAgreement, [{    // electrodb "list"   -> dynamodb "list"
            type: "ammendment",           // electrodb "map"    -> dynamodb "map"
            detail: "no soup for you"
        }]);
        o.delete(a.tags, ['coffee']);     // electrodb "set"    -> dynamodb "set"
        o.del(a.contact, '555-345-2222'); // electrodb "string" -> dynamodb "string"
        o.add(a.fees, op.name(a.petFee)); // electrodb "number" -> dynamodb "number"
        o.add(a.leaseHolders, newTenant); // electrodb "set"    -> dynamodb "set"
    })
    .where((attr, op) => op.eq(attr.category, "food/coffee"))
    .go()

// Equivalent Params:
{
  "UpdateExpression": "SET #category = :category_u0, #rent = #rent + :rent_u0, #deposit = #deposit - :deposit_u0, #rentalAgreement = list_append(#rentalAgreement, :rentalAgreement_u0), #totalFees = #totalFees + #petFee REMOVE #leaseEndDate, #gsi2sk ADD #tenant :tenant_u0, #leaseHolders :tenant_u0 DELETE #tags :tags_u0, #contact :contact_u0",
  "ExpressionAttributeNames": {
  "#category": "category",
    "#tenant": "tenant",
    "#rent": "rent",
    "#deposit": "deposit",
    "#leaseEndDate": "leaseEndDate",
    "#rentalAgreement": "rentalAgreement",
    "#tags": "tags",
    "#contact": "contact",
    "#totalFees": "totalFees",
    "#petFee": "petFee",
    "#leaseHolders": "leaseHolders",
    "#gsi2sk": "gsi2sk"
  },
  "ExpressionAttributeValues": {
    ":category0": "food/coffee",
    ":category_u0": "food/meal",
    ":tenant_u0": ["larry"],
    ":rent_u0": 100,
    ":deposit_u0": 200,
    ":rentalAgreement_u0": [{
      "type": "amendment",
      "detail": "no soup for you"
    }],
    ":tags_u0": ["coffee"], // <- DynamoDB Set
    ":contact_u0": ["555-345-2222"], // <- DynamoDB Set 
    },
  "TableName": "electro",
  "Key": {
    "pk": `$mallstoredirectory#cityid_12345#mallid_eastpointe`,
    "sk": "$mallstore_1#buildingid_a34#storeid_lattelarrys"
  },
  "ConditionExpression": "#category = :category0"
}

Update Method: Complex Data Types

ElectroDB supports updating DynamoDB's complex types (list, map, set) with all of its Update Methods.

When using the chain methods set, add, subtract, remove, append, and delete, you can access map properties, list elements, and set items by supplying the json path of the property as the name of the attribute.

The data() method also allows for working with complex types. Unlike using the update chain methods, the data() method ensures type safety when using TypeScript. When using the injected attributes object, simply drill into the attribute itself to apply your update directly to the required object.

The following are examples on how update complex attributes, using both with chain methods and the data() method.

Example 1: Set property on a map attribute

Specifying a property on a map attribute is expressed with dot notation.

// via Chain Method
await StoreLocations
    .update({cityId, mallId, storeId, buildingId})
    .set({'mapAttribute.mapProperty':  "value"})
    .go();

// via Data Method 
await StoreLocations
    .update({cityId, mallId, storeId, buildingId})
    .data(({mapAttribute}, {set}) => set(mapAttribute.mapProperty, "value"))
    .go()

Example 2: Removing an element from a list attribute

Specifying an index on a list attribute is expressed with square brackets containing the element's index number.

// via Chain Method
await StoreLocations
    .update({cityId, mallId, storeId, buildingId})
    .remove(['listAttribute[0]'])
    .go();

// via Data Method 
await StoreLocations
    .update({cityId, mallId, storeId, buildingId})
    .data(({listAttribute}, {remove}) => remove(listAttribute[0]))
    .go();

Example 3: Adding an item to a set attribute, on a map attribute, that is an element of a list attribute

All other complex structures are simply variations on the above two examples.

// Set values must use the DocumentClient to create a `set`
const newSetValue = StoreLocations.client.createSet("setItemValue"); 

// via Data Method 
await StoreLocations
    .update({cityId, mallId, storeId, buildingId})
    .add({'listAttribute[1].setAttribute': newSetValue})
    .go();

await StoreLocations
    .update({cityId, mallId, storeId, buildingId})
    .data(({listAttribute}, {add}) => {
        add(listAttribute[1].setAttribute, newSetValue)
    })
    .go();

Scan Records

When scanning for rows, you can use filters the same as you would any query. For more information on filters, see the Where section.

Note: Scan functionality will be scoped to your Entity. This means your results will only include records that match the Entity defined in the model.

await StoreLocations.scan
    .where(({category}, {eq}) => `
        ${eq(category, "food/coffee")} OR ${eq(category, "spite store")}  
    `)
    .where(({leaseEndDate}, {between}) => `
        ${between(leaseEndDate, "2020-03", "2020-04")}
    `)
    .go()

// Equivalent Params:
{
  "TableName": "StoreDirectory",
  "ExpressionAttributeNames": {
    "#category": "category",
    "#leaseEndDate": "leaseEndDate",
    "#pk": "pk",
    "#sk": "sk",
    "#__edb_e__": "__edb_e__",
    "#__edb_v__": "__edb_v__"
  },
  "ExpressionAttributeValues": {
    ":category_w1": "food/coffee",
    ":category_w2": "spite store",
    ":leaseEndDate_w1": "2020-03",
    ":leaseEndDate_w2": "2020-04",
    ":pk": "$mallstoredirectory#cityid_",
    ":sk": "$mallstore_1#buildingid_",
    ":__edb_e__": "MallStore",
    ":__edb_v__": "1"
  },
  "FilterExpression": "begins_with(#pk, :pk) AND #__edb_e__ = :__edb_e__ AND #__edb_v__ = :__edb_v__ AND begins_with(#sk, :sk) AND (#category = :category_w1 OR #category = :category_w2) AND (#leaseEndDate between :leaseEndDate_w1 and :leaseEndDate_w2)"
}

Remove Method

A convenience method for delete with ConditionExpression that the item being deleted exists. Provide all Table Index composite attributes in an object to the remove method to remove the record.

await StoreLocations.remove({
    storeId: "LatteLarrys", 
    mallId: "EastPointe", 
    buildingId: "F34", 
    cityId: "Atlanta1"
}).go();

// Equivalent Params:
// {
//   Key: {
//     pk: "$mallstoredirectory#cityid_atlanta1#mallid_eastpointe",
//     sk: "$mallstore_1#buildingid_f34#storeid_lattelarrys"
//   },
//   TableName: 'StoreDirectory'
//   ConditionExpression: 'attribute_exists(pk) AND attribute_exists(sk)'
// }

Patch Record

In DynamoDB, update operations by default will insert a record if record being updated does not exist. In ElectroDB, the patch method will utilize the attribute_exists() parameter dynamically to ensure records are only "patched" and not inserted when updating.

For more detail on how to use the patch() method, see the section Update Record to see all the transferable requirements and capabilities available to patch().

Create Record

In DynamoDB, put operations by default will overwrite a record if record being updated does not exist. In ElectroDB, the patch method will utilize the attribute_not_exists() parameter dynamically to ensure records are only "created" and not overwritten when inserting new records into the table.

A Put operation will trigger the default, and set attribute callbacks when writing to DynamoDB. By default, after writing to DynamoDB, ElectroDB will format and return the record through the same process as a Get/Query, which will invoke the get callback on all included attributes. If this behaviour is not desired, use the Query Option response:"none" to return a null value.

await StoreLocations
  .create({
      cityId: "Atlanta1",
      storeId: "LatteLarrys",
      mallId: "EastPointe",
      buildingId: "BuildingA1",
      unitId: "B47",
      category: "food/coffee",
      leaseEndDate: "2020-03-22",
      rent: "4500.00"
  })
  .where((attr, op) => op.eq(attr.rent, "4500.00"))
  .go()

// Equivalent Params:
{
  "Item": {
    "cityId": "Atlanta1",
    "mallId": "EastPointe",
    "storeId": "LatteLarrys",
    "buildingId": "BuildingA1",
    "unitId": "B47",
    "category": "food/coffee",
    "leaseEndDate": "2020-03-22",
    "rent": "4500.00",
    "discount": "0.00",
    "pk": "$mallstoredirectory#cityid_atlanta1#mallid_eastpointe",
    "sk": "$mallstore_1#buildingid_buildinga1#storeid_lattelarrys",
    "gis1pk": "$mallstoredirectory#mallid_eastpointe",
    "gsi1sk": "$mallstore_1#buildingid_buildinga1#unitid_b47",
    "gis2pk": "$mallstoredirectory#storeid_lattelarrys",
    "gsi2sk": "$mallstore_1#leaseenddate_2020-03-22",
    "__edb_e__": "MallStore",
    "__edb_v__": "1"
  },
  "TableName": "StoreDirectory",
  "ConditionExpression": "attribute_not_exists(pk) AND attribute_not_exists(sk) AND #rent = :rent_w1",
  "ExpressionAttributeNames": {
    "#rent": "rent"
  },
  "ExpressionAttributeValues": {
    ":rent_w1": "4500.00"
  }
}

Find Records

DynamoDB offers three methods to query records: get, query, and scan. In ElectroDB, there is a fourth type: find. Unlike get and query, the find method does not require you to provide keys, but under the covers it will leverage the attributes provided to choose the best index to query on. Provide the find method will all properties known to match a record and ElectroDB will generate the most performant query it can to locate the results. This can be helpful with highly dynamic querying needs. If an index cannot be satisfied with the attributes provided, scan will be used as a last resort.

NOTE: The Find method is similar to the Match method with one exception: The attributes you supply directly to the .find() method will only be used to identify and fulfill your index access patterns. Any values supplied that do not contribute to a composite key will not be applied as query filters. Furthermore, if the values you provide do not resolve to an index access pattern, then a table scan will be performed. Use the where() chain method to further filter beyond keys, or use Match for the convenience of automatic filtering based on the values given directly to that method.

await StoreLocations.find({
    mallId: "EastPointe",
    buildingId: "BuildingA1",
}).go()

// Equivalent Params:
{
  "KeyConditionExpression": "#pk = :pk and begins_with(#sk1, :sk1)",
  "TableName": "StoreDirectory",
  "ExpressionAttributeNames": {
    "#mallId": "mallId",
    "#buildingId": "buildingId",
    "#pk": "gis1pk",
    "#sk1": "gsi1sk"
  },
  "ExpressionAttributeValues": {
    ":mallId1": "EastPointe",
    ":buildingId1": "BuildingA1",
    ":pk": "$mallstoredirectory#mallid_eastpointe",
    ":sk1": "$mallstore_1#buildingid_buildinga1#unitid_"
  },
  "IndexName": "gis1pk-gsi1sk-index",
}

Match Records

Match is a convenience method based off of ElectroDB's find method. Similar to Find, Match does not require you to provide keys, but under the covers it will leverage the attributes provided to choose the best index to query on.

Match differs from Find in that it will also include all supplied values into a query filter.

await StoreLocations.find({
    mallId: "EastPointe",
    buildingId: "BuildingA1",
    leaseEndDate: "2020-03-22",
    rent: "1500.00"
}).go()

// Equivalent Params:
{
  "KeyConditionExpression": "#pk = :pk and begins_with(#sk1, :sk1)",
  "TableName": "StoreDirectory",
  "ExpressionAttributeNames": {
    "#mallId": "mallId",
    "#buildingId": "buildingId",
    "#leaseEndDate": "leaseEndDate",
    "#rent": "rent",
    "#pk": "gis1pk",
    "#sk1": "gsi1sk"
  },
  "ExpressionAttributeValues": {
    ":mallId1": "EastPointe",
    ":buildingId1": "BuildingA1",
    ":leaseEndDate1": "2020-03-22",
    ":rent1": "1500.00",
    ":pk": "$mallstoredirectory#mallid_eastpointe",
    ":sk1": "$mallstore_1#buildingid_buildinga1#unitid_"
  },
  "IndexName": "gis1pk-gsi1sk-index",
  "FilterExpression": "#mallId = :mallId1 AND#buildingId = :buildingId1 AND#leaseEndDate = :leaseEndDate1 AND#rent = :rent1"
}

After invoking the Access Pattern with the required Partition Key Composite Attributes, you can now choose what Sort Key Composite Attributes are applicable to your query. Examine the table in Sort Key Operations for more information on the available operations on a Sort Key.

Access Pattern Queries

When you define your indexes in your model, you are defining the Access Patterns of your entity. The composite attributes you choose, and their order, ultimately define the finite set of index queries that can be made. The more you can leverage these index queries the better from both a cost and performance perspective.

Unlike Partition Keys, Sort Keys can be partially provided. We can leverage this to multiply our available access patterns and use the Sort Key Operations: begins, between, lt, lte, gt, and gte. These queries are more performant and cost-effective than filters. The costs associated with DynamoDB directly correlate to how effectively you leverage Sort Key Operations.

For a comprehensive and interactive guide to build queries please visit this runkit: https://runkit.com/tywalch/electrodb-building-queries.

Begins With Queries

One important consideration when using Sort Key Operations to make is when to use and not to use "begins".

It is possible to supply partially supply Sort Key composite attributes. Sort Key attributes must be provided in the order they are defined, but it's possible to provide only a subset of the Sort Key Composite Attributes to ElectroDB. By default, when you supply a partial Sort Key in the Access Pattern method, ElectroDB will create a beginsWith query. The difference between that and using .begins() is that, with a .begins() query, ElectroDB will not post-pend the next composite attribute's label onto the query.

The difference is nuanced and makes better sense with an example, but the rule of thumb is that data passed to the Access Pattern method should represent values you know strictly equal the value you want.

The following examples will use the following Access Pattern definition for units:

{
  "units": {
    "index": "gis1pk-gsi1sk-index",
    "pk": {
      "field": "gis1pk",
      "composite attributes": [
        "mallId"
      ]
    },
    "sk": {
      "field": "gsi1sk",
      "composite attributes": [
        "buildingId",
        "unitId"
      ]
    }
  }
}

The names you have given to your indexes on your entity model/schema express themselves as "Access Pattern" methods on your Entity's query object:

// Example #1, access pattern `units`
StoreLocations.query.units({mallId, buildingId}).go();
// -----------------------^^^^^^^^^^^^^^^^^^^^^^

Data passed to the Access Pattern method is considered to be full, known, data. In the above example, we are saying we know the mallId, buildingId and unitId.

Alternatively, if you only know the start of a piece of data, use .begins():

// Example #2
StoreLocations.query.units({mallId}).begins({buildingId}).go();
// ---------------------------------^^^^^^^^^^^^^^^^^^^^^

Data passed to the .begins() method is considered to be partial data. In the second example, we are saying we know the mallId and buildingId, but only know the beginning of unitId.

For the above queries we see two different sort keys:

  1. "$mallstore_1#buildingid_f34#unitid_"
  2. "$mallstore_1#buildingid_f34"

The first example shows how ElectroDB post-pends the label of the next composite attribute (unitId) on the Sort Key to ensure that buildings such as "f340" are not included in the query. This is useful to prevent common issues with overloaded sort keys like accidental over-querying.

The second example allows you to make queries that do include buildings such as "f340" or "f3409" or "f340356346".

For these reasons it is important to consider that attributes passed to the Access Pattern method are considered to be full, known, data.

Collection Chains

Collections allow you to query across Entities. They can be used on Service instance.

const DynamoDB = require("aws-sdk/clients/dynamodb");
const table = "projectmanagement";
const client = new DynamoDB.DocumentClient();

const employees = new Entity({
  model: {
    entity: "employees",
    version: "1",
    service: "taskapp",
  },
  attributes: {
    employeeId: {
      type: "string"
    },
    organizationId: {
      type: "string"
    },
    name: {
      type: "string"
    },
    team: {
      type: ["jupiter", "mercury", "saturn"]
    }
  },
  indexes: {
    staff: {
      pk: {
        field: "pk",
        composite: ["organizationId"]
      },
      sk: {
        field: "sk",
        composite: ["employeeId"]
      }
    },
    employee: {
      collection: "assignments",
      index: "gsi2",
      pk: {
        field: "gsi2pk",
        composite: ["employeeId"],
      },
      sk: {
        field: "gsi2sk",
        composite: [],
      },
    }
  }
}, { client, table })

const tasks = new Entity({
  model: {
    entity: "tasks",
    version: "1",
    service: "taskapp",
  },
  attributes: {
    taskId: {
      type: "string"
    },
    employeeId: {
      type: "string"
    },
    projectId: {
      type: "string"
    },
    title: {
      type: "string"
    },
    body: {
      type: "string"
    }
  },
  indexes: {
    project: {
      pk: {
        field: "pk",
        composite: ["projectId"]
      },
      sk: {
        field: "sk",
        composite: ["taskId"]
      }
    },
    assigned: {
      collection: "assignments",
      index: "gsi2",
      pk: {
        field: "gsi2pk",
        composite: ["employeeId"],
      },
      sk: {
        field: "gsi2sk",
        composite: [],
      },
    }
  }
}, { client, table });

const TaskApp = new Service({employees, tasks});

Available on your Service are two objects: entites and collections. Entities available on entities have the same capabilities as they would if created individually. When a Model added to a Service with join however, its Collections are automatically added and validated with the other Models joined to that Service. These Collections are available on collections.

TaskApp.collections.assignments({employeeId: "JExotic"}).params();  

// Results
{
  TableName: 'projectmanagement',
  ExpressionAttributeNames: { '#pk': 'gsi2pk', '#sk1': 'gsi2sk' },
  ExpressionAttributeValues: { ':pk': '$taskapp_1#employeeid_joeexotic', ':sk1': '$assignments' },
  KeyConditionExpression: '#pk = :pk and begins_with(#sk1, :sk1)',
  IndexName: 'gsi3'
}

Collections do not have the same query functionality and as an Entity, though it does allow for inline filters like an Entity. The attributes available on the filter object include all attributes across entities.

TaskApp.collections
    .assignments({employee: "CBaskin"})
    .filter((attributes) => `
        ${attributes.project.notExists()} OR ${attributes.project.contains("murder")}
    `)

// Results
{
  TableName: 'projectmanagement',
  ExpressionAttributeNames: { '#project': 'project', '#pk': 'gsi2pk', '#sk1': 'gsi2sk' },
  ExpressionAttributeValues: {
    ':project1': 'murder',
    ':pk': '$taskapp_1#employeeid_carolbaskin',
    ':sk1': '$assignments'
  },
  KeyConditionExpression: '#pk = :pk and begins_with(#sk1, :sk1)',
  IndexName: 'gsi2',
  FilterExpression: '\n\t\tattribute_not_exists(#project) OR contains(#project, :project1)\n\t'
}

Execute Queries

Lastly, all query chains end with either a .go() or a .params() method invocation. These will either execute the query to DynamoDB (.go()) or return formatted parameters for use with the DynamoDB docClient (.params()).

Both .params() and .go() take a query configuration object which is detailed more in the section Query Options.

Params

The params method ends a query chain, and synchronously formats your query into an object ready for the DynamoDB docClient.

For more information on the options available in the config object, checkout the section Query Options.

let config = {};
let stores = MallStores.query
    .leases({ mallId })
    .between(
      { leaseEndDate:  "2020-06-01" }, 
      { leaseEndDate:  "2020-07-31" })
    .filter(attr) => attr.rent.lte("5000.00"))
    .params(config);

// Results:
{
  IndexName: 'idx2',
  TableName: 'electro',
  ExpressionAttributeNames: { '#rent': 'rent', '#pk': 'idx2pk', '#sk1': 'idx2sk' },
  ExpressionAttributeValues: {
    ':rent1': '5000.00',
    ':pk': '$mallstoredirectory_1#mallid_eastpointe',
    ':sk1': '$mallstore#leaseenddate_2020-06-01#rent_',
    ':sk2': '$mallstore#leaseenddate_2020-07-31#rent_'
  },
  KeyConditionExpression: '#pk = :pk and #sk1 BETWEEN :sk1 AND :sk2',
  FilterExpression: '#rent <= :rent1'
}

Go

The go method ends a query chain, and asynchronously queries DynamoDB with the client provided in the model.

For more information on the options available in the config object, check out the section Query Options.

let config = {};
let stores = MallStores.query
    .leases({ mallId })
    .between(
        { leaseEndDate:  "2020-06-01" }, 
        { leaseEndDate:  "2020-07-31" })
    .filter(({rent}) => rent.lte("5000.00"))
    .go(config);

Page

NOTE: By Default, ElectroDB queries will paginate through all results with the go() method. ElectroDB's page() method can be used to manually iterate through DynamoDB query results.

The page method ends a query chain, and asynchronously queries DynamoDB with the client provided in the model. Unlike the .go(), the .page() method returns a tuple.

The first element for a page query is the "pager": an object contains the composite attributes that make up the ExclusiveStartKey that is returned by the DynamoDB client. This is very useful in multi-tenant applications where only some composite attributes are exposed to the client, or there is a need to prevent leaking keys between entities. If there is no ExclusiveStartKey this value will be null. On subsequent calls to .page(), pass the results returned from the previous call to .page() or construct the composite attributes yourself.

The "pager" includes the associated entity's Identifiers.

NOTE: It is highly recommended to use the query option pager: "raw"" flag when using .page() with scan operations. This is because when using scan on large tables the docClient may return an ExclusiveStartKey for a record that does not belong to entity making the query (regardless of the filters set). In these cases ElectroDB will return null (to avoid leaking the keys of other entities) when further pagination may be needed to find your records.

The second element is the results of the query, exactly as it would be returned through a query operation.

NOTE: When calling .page() the first argument is reserved for the "page" returned from a previous query, the second parameter is for Query Options. For more information on the options available in the config object, check out the section Query Options.

Entity Pagination

let [next, stores] = await MallStores.query
    .leases({ mallId })
    .page(); // no "pager" passed to `.page()`

let [pageTwo, moreStores] = await MallStores.query
    .leases({ mallId })
    .page(next, {}); // the "pager" from the first query (`next`) passed to the second query

// page:
// { 
//   storeId: "LatteLarrys", 
//   mallId: "EastPointe", 
//   buildingId: "BuildingA1", 
//   unitId: "B47"
//   __edb_e__: "MallStore",
//   __edb_v__: "version" 
// }

// stores
// [{
//   mall: '3010aa0d-5591-4664-8385-3503ece58b1c',
//   leaseEnd: '2020-01-20',
//   sector: '7d0f5c19-ec1d-4c1e-b613-a4cc07eb4db5',
//   store: 'MNO',
//   unit: 'B5',
//   id: 'e0705325-d735-4fe4-906e-74091a551a04',
//   building: 'BuildingE',
//   category: 'food/coffee',
//   rent: '0.00'
// },
// {
//   mall: '3010aa0d-5591-4664-8385-3503ece58b1c',
//   leaseEnd: '2020-01-20',
//   sector: '7d0f5c19-ec1d-4c1e-b613-a4cc07eb4db5',
//   store: 'ZYX',
//   unit: 'B9',
//   id: 'f201a1d3-2126-46a2-aec9-758ade8ab2ab',
//   building: 'BuildingI',
//   category: 'food/coffee',
//   rent: '0.00'
// }]

Service Pagination

NOTE: By Default, ElectroDB will paginate through all results with the query() method. ElectroDB's page() method can be used to manually iterate through DynamoDB query results.

Pagination with services is also possible. Similar to Entity Pagination, calling the .page() method returns a [pager, results] tuple. Also, similar to pagination on Entities, the pager object returned by default is a deconstruction of the returned LastEvaluatedKey.

Pager Query Options

The .page() method also accepts Query Options just like the .go() and .params() methods. Unlike those methods, however, the .page() method accepts Query Options as the second parameter (the first parameter is reserved for the "pager").

A notable Query Option, that is available only to the .page() method, is an option called pager. This property defines the post-processing ElectroDB should perform on a returned LastEvaluatedKey, as well as how ElectroDB should interpret an incoming pager, to use as an ExclusiveStartKey.

NOTE: Because the "pager" object is destructured from the keys DynamoDB returns as the LastEvaluatedKey, these composite attributes differ from the record's actual attribute values in one important way: Their string values will all be lowercase. If you intend to use these attributes in ways where their casing will matter (e.g. in a where filter), keep in mind this may result in unexpected outcomes.

The three options for the query option pager are as follows:

// LastEvaluatedKey
{
  pk: '$taskapp#country_united states of america#state_oregon',
  sk: '$offices_1#city_power#zip_34706#office_mobile branch',
  gsi1pk: '$taskapp#office_mobile branch',
  gsi1sk: '$workplaces#offices_1'
}

"named" (default): By default, ElectroDB will deconstruct the LastEvaluatedKey returned by the DocClient into it's individual composite attribute parts. The "named" option, chosen by default, also includes the Entity's column "identifiers" -- this is useful with Services where destructured pagers may be identical between more than one Entity in that Service.

// {pager: "named"} | {pager: undefined} 
{  
  "city": "power",
  "country": "united states of america",
  "state": "oregon",
  "zip": "34706",
  "office": "mobile branch",
  "__edb_e__": "offices",
  "__edb_v__": "1"
}

"item": Similar to "named", however without the Entity's "identifiers". If two Entities with a service have otherwise identical index definitions, using the "item" pager option can result in errors while paginating a Collection. If this is not a concern with your Service, or you are paginating with only an Entity, this option could be preferable because it has fewer properties.

// {pager: "item"} 
{  
  "city": "power",
  "country": "united states of america",
  "state": "oregon",
  "zip": "34706",
  "office": "mobile branch",
}

"raw": The "raw" option returns the LastEvaluatedKey as it was returned by the DynamoDB DocClient.

// {pager: "raw"} 
{
  pk: '$taskapp#country_united states of america#state_oregon',
  sk: '$offices_1#city_power#zip_34706#office_mobile branch',
  gsi1pk: '$taskapp#office_mobile branch',
  gsi1sk: '$workplaces#offices_1'
}

Pagination Example

Simple pagination example:

async function getAllStores(mallId) {
  let stores = [];
  let pager = null;

  do {
    let [next, results] = await MallStores.query
      .leases({ mallId })
      .page(pager);
    stores = [...stores, ...results]; 
    pager = next;
  } while(pager !== null);
  
  return stores;
} 

Query Examples

For a comprehensive and interactive guide to build queries please visit this runkit: https://runkit.com/tywalch/electrodb-building-queries.

const cityId = "Atlanta1";
const mallId = "EastPointe";
const storeId = "LatteLarrys";
const unitId = "B24";
const buildingId = "F34";
const june = "2020-06";
const july = "2020-07"; 
const discount = "500.00";
const maxRent = "2000.00";
const minRent = "5000.00";

// Lease Agreements by StoreId
await StoreLocations.query.leases({storeId}).go()

// Lease Agreement by StoreId for March 22nd 2020
await StoreLocations.query.leases({storeId, leaseEndDate: "2020-03-22"}).go()

// Lease agreements by StoreId for 2020
await StoreLocations.query.leases({storeId}).begins({leaseEndDate: "2020"}).go()

// Lease Agreements by StoreId after March 2020
await StoreLocations.query.leases({storeId}).gt({leaseEndDate: "2020-03"}).go()

// Lease Agreements by StoreId after, and including, March 2020
await StoreLocations.query.leases({storeId}).gte({leaseEndDate: "2020-03"}).go()

// Lease Agreements by StoreId before 2021
await StoreLocations.query.leases({storeId}).lt({leaseEndDate: "2021-01"}).go()

// Lease Agreements by StoreId before February 2021
await StoreLocations.query.leases({storeId}).lte({leaseEndDate: "2021-02"}).go()

// Lease Agreements by StoreId between 2010 and 2020
await StoreLocations.query
    .leases({storeId})
    .between(
        {leaseEndDate: "2010"}, 
        {leaseEndDate: "2020"})
    .go()

// Lease Agreements by StoreId after, and including, 2010 in the city of Atlanta and category containing food
await StoreLocations.query
    .leases({storeId})
    .gte({leaseEndDate: "2010"})
    .where((attr, op) => `
        ${op.eq(attr.cityId, "Atlanta1")} AND ${op.contains(attr.category, "food")}
    `)
    .go()
    
// Rents by City and Store who's rent discounts match a certain rent/discount criteria
await StoreLocations.query
    .units({mallId})
    .begins({leaseEndDate: june})
    .rentDiscount(discount, maxRent, minRent)
    .go()

// Stores by Mall matching a specific category
await StoreLocations.query
    .units({mallId})
    .byCategory("food/coffee")
    .go()

Query Options

Query options can be added the .params(), .go() and .page() to change query behavior or add customer parameters to a query.

By default, ElectroDB enables you to work with records as the names and properties defined in the model. Additionally, it removes the need to deal directly with the docClient parameters which can be complex for a team without as much experience with DynamoDB. The Query Options object can be passed to both the .params() and .go() methods when building you query. Below are the options available:

{
  params?: object;
  table?: string;
  raw?: boolean;
  includeKeys?: boolean;
  pager?: "raw" | "named" | "item";
  originalErr?: boolean;
  concurrent?: number;
  unprocessed?: "raw" | "item";
  response?: "default" | "none" | "all_old" | "updated_old" | "all_new" | "updated_new";
  ignoreOwnership?: boolean;
  limit?: number;
  pages?: number;
};
OptionDefaultDescription
params{}Properties added to this object will be merged onto the params sent to the document client. Any conflicts with ElectroDB will favor the params specified here.
table(from constructor)Use a different table than the one defined in the Service Options
rawfalseReturns query results as they were returned by the docClient.
includeKeysfalseBy default, ElectroDB does not return partition, sort, or global keys in its response.
pager"named"Used in with pagination (.pages()) calls to override ElectroDBs default behaviour to break apart LastEvaluatedKeys records into composite attributes. See more detail about this in the sections for Pager Query Options.
originalErrfalseBy default, ElectroDB alters the stacktrace of any exceptions thrown by the DynamoDB client to give better visibility to the developer. Set this value equal to true to turn off this functionality and return the error unchanged.
concurrent1When performing batch operations, how many requests (1 batch operation == 1 request) to DynamoDB should ElectroDB make at one time. Be mindful of your DynamoDB throughput configurations
unprocessed"item"Used in batch processing to override ElectroDBs default behaviour to break apart DynamoDBs Unprocessed records into composite attributes. See more detail about this in the sections for BatchGet, BatchDelete, and BatchPut.
response"default"Used as a convenience for applying the DynamoDB parameter ReturnValues. The options here are the same as the parameter values for the DocumentClient except lowercase. The "none" option will cause the method to return null and will bypass ElectroDB's response formatting -- useful if formatting performance is a concern.
ignoreOwnershipfalseBy default, ElectroDB interrogates items returned from a query for the presence of matching entity "identifiers". This helps to ensure other entities, or other versions of an entity, are filtered from your results. If you are using ElectroDB with an existing table/dataset you can turn off this feature by setting this property to true.
limitnoneA target for the number of items to return from DynamoDB. If this option is passed, Queries on entities and through collections will paginate DynamoDB until this limit is reached or all items for that query have been returned.
pagesHow many DynamoDB pages should a query iterate through before stopping. By default ElectroDB paginate through all results for your query.

Errors:

Error CodeDescription
1000sConfiguration Errors
2000sInvalid Queries
3000sUser Defined Errors
4000sDynamoDB Errors
5000sUnexpected Errors

No Client Defined On Model

Code: 1001

Why this occurred: If a DynamoDB DocClient is not passed to the constructor of an Entity or Service (client), ElectroDB will be unable to query DynamoDB. This error will only appear when a query(using go()) is made because ElectroDB is still useful without a DocClient through the use of it's params() method.

What to do about it: For an Entity be sure to pass the DocClient as the second param to the constructor:

new Entity(schema, {client})

For a Service, the client is passed the same way, as the second param to the constructor:

new Service("", {client});

Invalid Identifier

Code: 1002

Why this occurred: You tried to modify the entity identifier on an Entity.

What to do about it: Make sure you have spelled the identifier correctly or that you actually passed a replacement.

Invalid Key Composite Attribute Template

Code: 1003

Why this occurred: You are trying to use the custom Key Composite Attribute Template, and the format you passed is invalid.

What to do about it: Checkout the section on [Composite Attribute Templates](#composite attribute-templates) and verify your template conforms to the rules detailed there.

Duplicate Indexes

Code: 1004

Why this occurred: Your model contains duplicate indexes. This could be because you accidentally included an index twice or even forgot to add an index name on a secondary index, which would be interpreted as "duplicate" to the Table's Primary index.

What to do about it: Double-check the index names on your model for duplicate indexes. The error should specify which index has been duplicated. It is also possible that you have forgotten to include an index name. Each table must have at least one Table Index (which does not include an index property in ElectroDB), but all Secondary and Local indexes must include an index property with the name of that index as defined on the table.

{
  indexes: {
    index1: {
      index: "idx1", // <-- duplicate "idx1"
      pk: {},
      sk: {}
    },
    index2: {
      index: "idx1", // <-- duplicate "idx1"
      pk: {},
      sk: {}
    }
  }
}

Collection Without An SK

Code: 1005

Why this occurred: You have added a collection to an index that does not have an SK. Because Collections are used to help query across entities via the Sort Key, not having a Sort Key on an index defeats the purpose of a Collection.

What to do about it: If your index does have a Sort Key, but you are unsure of how to inform electro without setting composite attributes to the SK, add the SK object to the index and use an empty array for Composite Attributes:

// ElectroDB interprets as index *not having* an SK.
{
  indexes: {
    myIndex: {
      pk: {
        field: "pk",
        composite: ["id"]
      }
    }
  }
}

// ElectroDB interprets as index *having* SK, but this model doesnt attach any composite attributes to it.
{
  indexes: {
    myIndex: {
      pk: {
        field: "pk",
        composite: ["id"]
      },
      sk: {
        field: "sk",
        composite: []
      }
    }
  }
}

Duplicate Collections

Code: 1006

Why this occurred: You have assigned the same collection name to multiple indexes. This is not allowed because collection names must be unique.

What to do about it: Determine a new naming scheme

Missing Primary Index

Code: 1007

Why this occurred: DynamoDB requires the definition of at least one Primary Index on the table. In Electro this is defined as an Index without an index property. Each model needs at least one, and the composite attributes used for this index must ensure each composite represents a unique record.

What to do about it: Identify the index you're using as the Primary Index and ensure it does not have an index property on its definition.

// ElectroDB interprets as the Primary Index because it lacks an `index` property.
{
  indexes: {
    myIndex: {
      pk: {
        field: "pk",
        composite: ["org"]
      },
      sk: {
        field: "sk",
        composite: ["id"]
      }
    }
  }
}

// ElectroDB interprets as a Global Secondary Index because it has an `index` property.
{
  indexes: {
    myIndex: {
      index: "gsi1"
      pk: {
        field: "gsipk1",
        composite: ["org"]
      },
      sk: {
        field: "gsisk1",
        composite: ["id"]
      }
    }
  }
}

Invalid Attribute Definition

Code: 1008

Why this occurred: Some attribute on your model has an invalid configuration.

What to do about it: Use the error to identify which column needs to examined, double-check the properties on that attribute. Checkout the section on Attributes for more information on how they are structured.

Invalid Model

Code: 1009

Why this occurred: Some properties on your model are missing or invalid.

What to do about it: Checkout the section on Models to verify your model against what is expected.

Invalid Options

Code: 1010

Why this occurred: Some properties on your options object are missing or invalid.

What to do about it: Checkout the section on Model/Service Options to verify your model against what is expected.

Duplicate Index Fields

Code: 1014

Why this occurred: An Index in your model references the same field twice across indexes. The field property in the definition of an index is a mapping to the name of the field assigned to the PK or SK of an index.

What to do about it: This is likely a typo, if not double-check the names of the fields you assigned to be the PK and SK of your index, these field names must be unique.

Duplicate Index Composite Attributes

Code: 1015

Why this occurred: Within one index you tried to use the same composite attribute in both the PK and SK. A composite attribute may only be used once within an index. With ElectroDB it is not uncommon to use the same value as both the PK and SK when a Sort Key exists on a table -- this usually is done because some value is required in that column but for that entity it is not necessary. If this is your situation remember that ElectroDB does put a value in the SortKey even if does not include a composite attribute, checkout this section for more information.

What to do about it: Determine how you can change your access pattern to not duplicate the composite attribute. Remember that an empty array for an SK is valid.

Incompatible Key Composite Attribute Template

Code: 1017

Why this occurred: You are trying to use the custom Key Composite Attribute Template, and a Composite Attribute Array on your model, and they do not contain identical composite attributes.

What to do about it: Checkout the section on [Composite Attribute Templates](#composite attribute-templates) and verify your template conforms to the rules detailed there. Both properties must contain the same attributes and be provided in the same order.

Invalid Index With Attribute Name

Code: 1018

Why this occurred: ElectroDB's design revolves around best practices related to modeling in single table design. This includes giving indexed fields generic names. If the PK and SK fields on your table indexes also match the names of attributes on your Entity you will need to make special considerations to make sure ElectroDB can accurately map your data.

What to do about it: Checkout the section Using ElectroDB with existing data to learn more about considerations to make when using attributes as index fields.

Invalid Collection on Index With Attribute Field Names

Code: 1019

Why this occurred: Collections allow for unique access patterns to be modeled between entities. It does this by appending prefixes to your key composites. If an Entity leverages an attribute field as an index key, ElectroDB will be unable to prefix your value because that would result in modifying the value itself.

What to do about it: Checkout the section Collections to learn more about collections, as well as the section Using ElectroDB with existing data to learn more about considerations to make when using attributes as index fields.

Missing Composite Attributes

Code: 2002

Why this occurred: The current request is missing some composite attributes to complete the query based on the model definition. Composite Attributes are used to create the Partition and Sort keys. In DynamoDB Partition keys cannot be partially included, and Sort Keys can be partially include they must be at least passed in the order they are defined on the model.

What to do about it: The error should describe the missing composite attributes, ensure those composite attributes are included in the query or update the model to reflect the needs of the access pattern.

Missing Table

Code: 2003f

Why this occurred: You never specified a Table for DynamoDB to use.

What to do about it: Tables can be defined on the Service Options object when you create an Entity or Service, or if that is not known at the time of creation, it can be supplied as a Query Option and supplied on each query individually. If can be supplied on both, in that case the Query Option will override the Service Option.

Invalid Concurrency Option

Code: 2004

Why this occurred: When performing a bulk operation (Batch Get, Batch Delete Records, Batch Put Records) you can pass a Query Options called concurrent, which impacts how many batch requests can occur at the same time. Your value should pass the test of both, !isNaN(parseInt(value)) and parseInt(value) > 0.

What to do about it:
Expect this error only if you're providing a concurrency option. Double-check the value you are providing is the value you expect to be passing, and that the value passes the tests listed above.

Invalid Pages Option

Code: 2005

Why this occurred: When performing a query Query you can pass a Query Options called pages, which impacts how many DynamoDB pages a query should iterate through. Your value should pass the test of both, !isNaN(parseInt(value)) and parseInt(value) > 0.

What to do about it: Expect this error only if you're providing a pages option. Double-check the value you are providing is the value you expect to be passing, and that the value passes the tests listed above.

Invalid Limit Option

Code: 2006

Why this occurred: When performing a query Query you can pass a Query Options called limit, which impacts how many DynamoDB items a query should return. Your value should pass the test of both, !isNaN(parseInt(value)) and parseInt(value) > 0.

What to do about it: Expect this error only if you're providing a limit option. Double-check the value you are providing is the value you expect to be passing, and that the value passes the tests listed above.

Invalid Attribute

Code: 3001

Why this occurred: The value received for a validation either failed type expectations (e.g. a "number" instead of a "string"), or the user provided "validate" callback on an attribute rejected a value.

What to do about it: Examine the error itself for more precise detail on why the failure occurred. The error object itself should have a property called "fields" which contains an array of every attribute that failed validation, and a reason for each. If the failure originated from a "validate" callback, the originally thrown error will be accessible via the cause property the corresponding element within the fields array.1

Below is the type definition for an ElectroValidationError:

ElectroValidationError<T extends Error = Error> extends ElectroError {
    readonly name: "ElectroValidationError"
    readonly code: number;
    readonly date: number;
    readonly isElectroError: boolean;
    ref: {
        readonly code: number;
        readonly section: string;
        readonly name: string;
        readonly sym: unique symbol;
    }
    readonly fields: ReadonlyArray<{
        /**
         * The json path to the attribute that had a validation error
         */
        readonly field: string;

        /**
         * A description of the validation error for that attribute
         */
        readonly reason: string;

        /**
         * Index of the value passed (present only in List attribute validation errors)
         */
        readonly index: number | undefined;

        /**
         * The error thrown from the attribute's validate callback (if applicable)
         */
        readonly cause: T | undefined;
    }>
}

AWS Error

Code: 4001

Why this occurred: DynamoDB did not like something about your query.

What to do about it: By default ElectroDB tries to keep the stack trace close to your code, ideally this can help you identify what might be going on. A tip to help with troubleshooting: use .params() to get more insight into how your query is converted to DocClient params.

Unknown Errors

Invalid Last Evaluated Key

Code: 5003

Why this occurred: Likely you were calling .page() on a scan. If you weren't please make an issue and include as much detail about your query as possible.

What to do about it: When paginating with scan queries, it is highly recommended that the query option, {pager: "raw"}. This is because when using scan on large tables the docClient may return an ExclusiveStartKey for a record that does not belong to entity making the query (regardless of the filters set). In these cases ElectroDB will return null (to avoid leaking the keys of other entities) when further pagination may be needed to find your records.

// example
myModel.scan.page(null, {pager: "raw"});

No Owner For Pager

Code: 5004

Why this occurred: When using pagination with a Service, ElectroDB will try to identify which Entity is associated with the supplied pager. This error can occur when you supply an invalid pager, or when you are using a different pager option to a pager than what was used when retrieving it. Consult the section on Pagination to learn more.

What to do about it: If you are sure the pager you are passing to .page() is the same you received from .page() this could be an unexpected error. To mitigate the issue use the Query Option {pager: "raw"} and please open a support issue.

Pager Not Unique

Code: 5005

Why this occurred: When using pagination with a Service, ElectroDB will try to identify which Entity is associated with the supplied pager option. This error can occur when you supply a pager that resolves to more than one Entity. This can happen if your entities share the same composite attributes for the index you are querying on, and you are using the Query Option {pager: "item""}.

What to do about it: Because this scenario is possible with otherwise well considered/thoughtful entity models, the default pager type used by ElectroDB is "named". To avoid this error, you will need to use either the "raw" or "named" pager options for any index that could result in an ambiguous Entity owner.

Examples

Want to just play with ElectroDB instead of read about it? Try it out for yourself! https://runkit.com/tywalch/electrodb-building-queries

Employee App

For an example, lets look at the needs of application used to manage Employees. The application Looks at employees, offices, tasks, and projects.

Employee App Requirements

  1. As a Project Manager, I need to find all tasks and details on a specific employee.
  2. As a Regional Manager, I need to see all details about an office and its employees
  3. As an Employee, I need to see all my Tasks.
  4. As a Product Manager, I need to see all the tasks for a project.
  5. As a Client, I need to find a physical office close to me.
  6. As a Hiring manager, I need to find employees with comparable salaries.
  7. As HR, I need to find upcoming employee birthdays/anniversaries
  8. As HR, I need to find all the employees that report to a specific manager

App Entities

const EmployeesModel = {
    model: {
      entity: "employees",
      version: "1",
      service: "taskapp",  
    },
    attributes: {
        employee: "string",
        firstName: "string",
        lastName: "string",
        office: "string",
        title: "string",
        team: ["development", "marketing", "finance", "product"],
        salary: "string",
        manager: "string",
        dateHired: "string",
        birthday: "string",
    },
    indexes: {
        employee: {
            pk: {
                field: "pk",
                composite: ["employee"],
            },
            sk: {
                field: "sk",
                composite: [],
            },
        },
        coworkers: {
            index: "gsi1pk-gsi1sk-index",
            collection: "workplaces",
            pk: {
                field: "gsi1pk",
                composite: ["office"],
            },
            sk: {
                field: "gsi1sk",
                composite: ["team", "title", "employee"],
            },
        },
        teams: {
            index: "gsi2pk-gsi2sk-index",
            pk: {
                field: "gsi2pk",
                composite: ["team"],
            },
            sk: {
                field: "gsi2sk",
                composite: ["title", "salary", "employee"],
            },
        },
        employeeLookup: {
            collection: "assignements",
            index: "gsi3pk-gsi3sk-index",
            pk: {
                field: "gsi3pk",
                composite: ["employee"],
            },
            sk: {
                field: "gsi3sk",
                composite: [],
            },
        },
        roles: {
            index: "gsi4pk-gsi4sk-index",
            pk: {
                field: "gsi4pk",
                composite: ["title"],
            },
            sk: {
                field: "gsi4sk",
                composite: ["salary", "employee"],
            },
        },
        directReports: {
            index: "gsi5pk-gsi5sk-index",
            pk: {
                field: "gsi5pk",
                composite: ["manager"],
            },
            sk: {
                field: "gsi5sk",
                composite: ["team", "office", "employee"],
            },
        },
    },
    filters: {
        upcomingCelebrations: (attributes, startDate, endDate) => {
            let { dateHired, birthday } = attributes;
            return `${dateHired.between(startDate, endDate)} OR ${birthday.between(
                startDate,
                endDate,
            )}`;
        },
    },
};

const TasksModel = {
    model: {
        entity: "tasks",
        version: "1",
        service: "taskapp",  
    }, 
    attributes: {
        task: "string",
        project: "string",
        employee: "string",
        description: "string",
    },
    indexes: {
        task: {
            pk: {
                field: "pk",
                composite: ["task"],
            },
            sk: {
                field: "sk",
                composite: ["project", "employee"],
            },
        },
        project: {
            index: "gsi1pk-gsi1sk-index",
            pk: {
                field: "gsi1pk",
                composite: ["project"],
            },
            sk: {
                field: "gsi1sk",
                composite: ["employee", "task"],
            },
        },
        assigned: {
            collection: "assignements",
            index: "gsi3pk-gsi3sk-index",
            pk: {
                field: "gsi3pk",
                composite: ["employee"],
            },
            sk: {
                field: "gsi3sk",
                composite: ["project", "task"],
            },
        },
    },
};

const OfficesModel = {
    model: {
          entity: "offices",
          version: "1",
          service: "taskapp",  
      }, 
    attributes: {
        office: "string",
        country: "string",
        state: "string",
        city: "string",
        zip: "string",
        address: "string",
    },
    indexes: {
        locations: {
            pk: {
                field: "pk",
                composite: ["country", "state"],
            },
            sk: {
                field: "sk",
                composite: ["city", "zip", "office"],
            },
        },
        office: {
            index: "gsi1pk-gsi1sk-index",
            collection: "workplaces",
            pk: {
                field: "gsi1pk",
                composite: ["office"],
            },
            sk: {
                field: "gsi1sk",
                composite: [],
            },
        },
    },
};

Join models on a new Service called EmployeeApp

const DynamoDB = require("aws-sdk/clients/dynamodb");
const client = new DynamoDB.DocumentClient({region: "us-east-1"});
const { Service } = require("electrodb");
const table = "projectmanagement";
const EmployeeApp = new Service("EmployeeApp", { client, table });

EmployeeApp
    .join(EmployeesModel) // EmployeeApp.entities.employees
    .join(TasksModel)     // EmployeeApp.entities.tasks
    .join(OfficesModel);  // EmployeeApp.entities.tasks

Query Records

All tasks and employee information for a given employee

Fulfilling Requirement #1.

EmployeeApp.collections.assignements({employee: "CBaskin"}).go();

Returns the following:

{
    employees: [{
        employee: "cbaskin",
        firstName: "carol",
        lastName: "baskin",
        office: "big cat rescue",
        title: "owner",
        team: "cool cats and kittens",
        salary: "1,000,000",
        manager: "",
        dateHired: "1992-11-04",
        birthday: "1961-06-06",
    }],
    tasks: [{
        task: "Feed tigers",
        description: "Prepare food for tigers to eat",
        project: "Keep tigers alive",
        employee: "cbaskin"
    }, {
        task: "Fill water bowls",
        description: "Ensure the tigers have enough water",
        project: "Keep tigers alive",
        employee: "cbaskin"
    }]
}

Find all employees and office details for a given office

Fulfilling Requirement #2.

EmployeeApp.collections.workplaces({office: "big cat rescue"}).go()

Returns the following:

{
    employees: [{
        employee: "cbaskin",
        firstName: "carol",
        lastName: "baskin",
        office: "big cat rescue",
        title: "owner",
        team: "cool cats and kittens",
        salary: "1,000,000",
        manager: "",
        dateHired: "1992-11-04",
        birthday: "1961-06-06",
    }],
    offices: [{
        office: "big cat rescue",
        country: "usa",
        state: "florida",
        city: "tampa",
        zip: "12345",
        address: "123 Kitty Cat Lane"
    }]
}

Tasks for a given employee

Fulfilling Requirement #3.

EmployeeApp.entities.tasks.query.assigned({employee: "cbaskin"}).go();

Returns the following:

[
    {
        task: "Feed tigers",
        description: "Prepare food for tigers to eat",
        project: "Keep tigers alive",
        employee: "cbaskin"
    }, {
        task: "Fill water bowls",
        description: "Ensure the tigers have enough water",
        project: "Keep tigers alive",
        employee: "cbaskin"
    }
]

Tasks for a given project

Fulfilling Requirement #4.

EmployeeApp.entities.tasks.query.project({project: "Murder Carol"}).go();

Returns the following:

[
    {
        task: "Hire hitman",
        description: "Find someone to murder Carol",
        project: "Murder Carol",
        employee: "jexotic"
    }
];

Find office locations

Fulfilling Requirement #5.

EmployeeApp.entities.office.locations({country: "usa", state: "florida"}).go()

Returns the following:

[
    {
        office: "big cat rescue",
        country: "usa",
        state: "florida",
        city: "tampa",
        zip: "12345",
        address: "123 Kitty Cat Lane"
    }
]

Find employee salaries and titles

Fulfilling Requirement #6.

EmployeeApp.entities.employees
    .roles({title: "animal wrangler"})
    .lte({salary: "150.00"})
    .go()

Returns the following:

[
    {
        employee: "ssaffery",
        firstName: "saff",
        lastName: "saffery",
        office: "gw zoo",
        title: "animal wrangler",
        team: "keepers",
        salary: "105.00",
        manager: "jexotic",
        dateHired: "1999-02-23",
        birthday: "1960-07-11",
    }
]

Find employee birthdays or anniversaries

Fulfilling Requirement #7.

EmployeeApp.entities.employees
    .workplaces({office: "gw zoo"})
    .upcomingCelebrations("2020-05-01", "2020-06-01")
    .go()

Returns the following:

[
    {
        employee: "jexotic",
        firstName: "joe",
        lastName: "maldonado-passage",
        office: "gw zoo",
        title: "tiger king",
        team: "founders",
        salary: "10000.00",
        manager: "jlowe",
        dateHired: "1999-02-23",
        birthday: "1963-03-05",
    }
]

Find direct reports

Fulfilling Requirement #8.

EmployeeApp.entities.employees
    .reports({manager: "jlowe"})
    .go()

Returns the following:

[
    {
        employee: "jexotic",
        firstName: "joe",
        lastName: "maldonado-passage",
        office: "gw zoo",
        title: "tiger king",
        team: "founders",
        salary: "10000.00",
        manager: "jlowe",
        dateHired: "1999-02-23",
        birthday: "1963-03-05",
    }
]

Shopping Mall Property Management App

For an example, lets look at the needs of application used to manage Shopping Mall properties. The application assists employees in the day-to-day operations of multiple Shopping Malls.

Shopping Mall Requirements

  1. As a Maintenance Worker, I need to know which stores are currently in each Mall down to the Building they are located.
  2. As a Helpdesk Employee, I need to locate related stores in Mall locations by Store Category.
  3. As a Property Manager, I need to identify upcoming leases in need of renewal.

Create a new Entity using the StoreLocations schema defined above

const DynamoDB = require("aws-sdk/clients/dynamodb");
const client = new DynamoDB.DocumentClient();
const StoreLocations = new Entity(model, {client, table: "StoreLocations"});

Access Patterns are accessible on the StoreLocation

PUT Record

Add a new Store to the Mall

await StoreLocations.create({
    mallId: "EastPointe",
    storeId: "LatteLarrys",
    buildingId: "BuildingA1",
    unitId: "B47",
    category: "spite store",
    leaseEndDate: "2020-02-29",
    rent: "5000.00",
}).go();

Returns the following:

{
    "mallId": "EastPointe",
    "storeId": "LatteLarrys",
    "buildingId": "BuildingA1",
    "unitId": "B47",
    "category": "spite store",
    "leaseEndDate": "2020-02-29",
    "rent": "5000.00",
    "discount": "0.00"
}

UPDATE Record

Change the Stores Lease Date

When updating a record, you must include all Composite Attributes associated with the table's primary PK and SK.

let storeId = "LatteLarrys";
let mallId = "EastPointe";
let buildingId = "BuildingA1";
let unitId = "B47";
await StoreLocations.update({storeId, mallId, buildingId, unitId}).set({
    leaseEndDate: "2021-02-28"
}).go();

Returns the following:

{
    "leaseEndDate": "2021-02-28"
}

GET Record

Retrieve a specific Store in a Mall

When retrieving a specific record, you must include all Composite Attributes associated with the table's primary PK and SK.

let storeId = "LatteLarrys";
let mallId = "EastPointe";
let buildingId = "BuildingA1";
let unitId = "B47";
await StoreLocations.get({storeId, mallId, buildingId, unitId}).go();

Returns the following:

{
    "mallId": "EastPointe",
    "storeId": "LatteLarrys",
    "buildingId": "BuildingA1",
    "unitId": "B47",
    "category": "spite store",
    "leaseEndDate": "2021-02-28",
    "rent": "5000.00",
    "discount": "0.00"
}

DELETE Record

Remove a Store location from the Mall

When removing a specific record, you must include all Composite Attributes associated with the table's primary PK and SK.

let storeId = "LatteLarrys";
let mallId = "EastPointe";
let buildingId = "BuildingA1";
let unitId = "B47";
let storeId = "LatteLarrys";
await StoreLocations.delete({storeId, mallId, buildingId, unitId}).go();

Returns the following:

{}

Query Mall Records

All Stores in a particular mall

Fulfilling Requirement #1.


let mallId = "EastPointe";
let stores = await StoreLocations.malls({mallId}).query().go();

All Stores in a particular mall building

Fulfilling Requirement #1.

let mallId = "EastPointe";
let buildingId = "BuildingA1";
let stores = await StoreLocations.malls({mallId}).query({buildingId}).go();

Find the store located in unit B47

Fulfilling Requirement #1.

let mallId = "EastPointe";
let buildingId = "BuildingA1";
let unitId = "B47";
let stores = await StoreLocations.malls({mallId}).query({buildingId, unitId}).go();

Stores by Category at Mall

Fulfilling Requirement #2.

let mallId = "EastPointe";
let category = "food/coffee";
let stores = await StoreLocations.malls({mallId}).byCategory(category).go();

Stores by upcoming lease

Fulfilling Requirement #3.

let mallId = "EastPointe";
let q2StartDate = "2020-04-01";
let stores = await StoreLocations.leases({mallId}).lt({leaseEndDate: q2StateDate}).go();

Stores will renewals for Q4

Fulfilling Requirement #3.

let mallId = "EastPointe";
let q4StartDate = "2020-10-01";
let q4EndDate = "2020-12-31";
let stores = await StoreLocations.leases(mallId)
    .between (
      {leaseEndDate: q4StartDate}, 
      {leaseEndDate: q4EndDate})
    .go();

Spite-stores with release renewals this year

Fulfilling Requirement #3.

let mallId = "EastPointe";
let yearStarDate = "2020-01-01";
let yearEndDate = "2020-12-31";
let storeId = "LatteLarrys";
let stores = await StoreLocations.leases(mallId)
    .between (
      {leaseEndDate: yearStarDate}, 
      {leaseEndDate: yearEndDate})
    .filter(attr => attr.category.eq("Spite Store"))
    .go();

All Latte Larrys in a particular mall building

let mallId = "EastPointe";
let buildingId = "BuildingA1";
let unitId = "B47";
let storeId = "LatteLarrys";
let stores = await StoreLocations.malls({mallId}).query({buildingId, storeId}).go();

Exported TypeScript Types

The following types are exported for easier use while using ElectroDB with TypeScript:

EntityRecord Type

The EntityRecord type is an object containing every attribute an Entity's model.

Definition:

type EntityRecord<E extends Entity<any, any, any, any>> =
    E extends Entity<infer A, infer F, infer C, infer S>
        ? Item<A,F,C,S,S["attributes"]>
        : never;

Use:

type EntiySchema = EntityRecord<typeof MyEntity>

EntityItem Type

This type represents an item as it is returned from a query. This is different from the EntityRecord in that this type reflects the required, hidden, default, etc properties defined on the attribute.

Definition:

export type EntityItem<E extends Entity<any, any, any, any>> =
  E extends Entity<infer A, infer F, infer C, infer S>
  ? ResponseItem<A, F, C, S>
  : never;

Use:

type Thing = EntityItem<typeof MyEntityInstance>;

CollectionItem Type

This type represents the value returned from a collection query, and is similar to EntityItem.

Use:

type CollectionResults = CollectionItem<typeof MyServiceInstance, "collectionName">

CreateEntityItem Type

This type represents an item that you would pass your entity's put or create method

Definition:

export type CreateEntityItem<E extends Entity<any, any, any, any>> =
  E extends Entity<infer A, infer F, infer C, infer S>
  ? PutItem<A, F, C, S>
  : never;

Use:

type NewThing = CreateEntityItem<typeof MyEntityInstance>;

UpdateEntityItem Type

This type represents an item that you would pass your entity's set method when using create or update.

Definition:

export type UpdateEntityItem<E extends Entity<any, any, any, any>> =
  E extends Entity<infer A, infer F, infer C, infer S>
  ? SetItem<A, F, C, S>
  : never;

Use:

type UpdateProperties = UpdateEntityItem<typeof MyEntityInstance>;

UpdateAddEntityItem Type

This type represents an item that you would pass your entity's add method when using create or update.

Definition:

export type UpdateAddEntityItem<E extends Entity<any, any, any, any>> =
    E extends Entity<infer A, infer F, infer C, infer S>
        ? AddItem<A, F, C, S>
        : never;

UpdateSubtractEntityItem Type

This type represents an item that you would pass your entity's subtract method when using create or update.

Definition:

export type UpdateSubtractEntityItem<E extends Entity<any, any, any, any>> =
    E extends Entity<infer A, infer F, infer C, infer S>
        ? SubtractItem<A, F, C, S>
        : never;

UpdateAppendEntityItem Type

This type represents an item that you would pass your entity's append method when using create or update.

Definition:

export type UpdateAppendEntityItem<E extends Entity<any, any, any, any>> =
    E extends Entity<infer A, infer F, infer C, infer S>
        ? AppendItem<A, F, C, S>
        : never;

UpdateRemoveEntityItem Type

This type represents an item that you would pass your entity's remove method when using create or update.

Definition:

export type UpdateRemoveEntityItem<E extends Entity<any, any, any, any>> =
    E extends Entity<infer A, infer F, infer C, infer S>
        ? RemoveItem<A, F, C, S>
        : never;

UpdateDeleteEntityItem Type

This type represents an item that you would pass your entity's delete method when using create or update.

Definition:

export type UpdateDeleteEntityItem<E extends Entity<any, any, any, any>> =
    E extends Entity<infer A, infer F, infer C, infer S>
        ? DeleteItem<A, F, C, S>
        : never;

Using ElectroDB With Existing Data

When using ElectroDB with an existing table and/or data model, there are a few configurations you may need to make to your ElectroDB model. Read the sections below to see if any of the following cases fits your particular needs.

Whenever using ElectroDB with existing tables/data, it is best to use the Query Option ignoreOwnership. ElectroDB leaves some meta-data on items to help ensure data queried and returned from DynamoDB does not leak between entities. Because your data was not made by ElectroDB, these checks could impede your ability to return data.

// when building params
.params({ignoreOwnership: true})
// when querying the table
.go({ignoreOwnership: true})
// when using pagination
.page(null, {ignoreOwnership: true})

Your existing index fields have values with mixed case:

DynamoDB is case-sensitive, and ElectroDB will lowercase key values by default. In the case where you modeled your data with uppercase, or did not apply case modifications, ElectroDB can be configured to match this behavior. Checkout the second on Index Casing to read more.

You have index field names that match attribute names:

With Single Table Design, it is encouraged to give index fields a generic name, like pk, sk, gsi1pk, etc. In reality, it is also common for tables to have index fields that are named after the domain itself, like accountId, organizationId, etc.

ElectroDB tries to abstract away your when working with DynamoDB, so instead of defining pk or sk in your model's attributes, you define them as indexes and map other attributes onto those fields as a composite. Using separate item fields for keys, then for the actual attributes you use in your application, you can leverage more advanced modeling techniques in DynamoDB.

If your existing table uses non-generic fields that also function as attributes, checkout the section Attributes as Indexes to learn more about how ElectroDB handles these types of indexes.

Electro CLI

NOTE: The ElectroCLI is currently in a beta phase and subject to change.

Electro is a CLI utility toolbox for extending the functionality of ElectroDB. Current functionality of the CLI allows you to:

  1. Execute queries against your Entities, Services, Models directly from the command line.
  2. Dynamically stand up an HTTP Service to interact with your Entities, Services, Models.

For usage and installation details you can learn more here.

Version 1 Migration

This section is to detail any breaking changes made on the journey to a stable 1.0 product.

New schema format/breaking key format change

It became clear when I added the concept of a Service that the "version" paradigm of having the version in the PK wasn't going to work. This is because collection queries use the same PK for all entities and this would prevent some entities in a Service to change versions without impacting the service as a whole. The better more is the place the version in the SK after the entity name so that all version of an entity can be queried. This will work nicely into the migration feature I have planned that will help migrate between model versions.

To address this change, I decide it would be best to change the structure for defining a model, which is then used as heuristic to determine where to place the version in the key (PK or SK). This has the benefit of not breaking existing models, but does increase some complexity in the underlying code.

Additionally, a change was made to the Service class. New Services would take a string of the service name instead of an object as before.

In the old scheme, version came after the service name (see ^).

pk: $mallstoredirectory_1#mall_eastpointe
                        ^
sk: $mallstores#building_buildinga#store_lattelarrys

In the new scheme, version comes after the entity name (see ^).

pk: $mallstoredirectory#mall_eastpointe

sk: $mallstores_1#building_buildinga#store_lattelarrys
                ^

In practice the change looks like this for use of Entity:

const  DynamoDB  =  require("aws-sdk/clients/dynamodb");
const {Entity} = require("electrodb");
const client = new DynamoDB.DocumentClient();
const table = "dynamodb_table_name";

// old way
let old_schema = {
  entity: "model_name",
  service: "service_name",
  version: "1",
  table: table,
  attributes: {...},
  indexes: {...}
};
new Entity(old_schema, {client});

// new way
let new_schema = {
  model: {
    entity: "model_name",
    service: "service_name",
    version: "1",
  },
  attributes: {...},
  indexes: {...}
};
new Entity(new_schema, {client, table});

Changes to usage of Service would look like this:

const  DynamoDB  =  require("aws-sdk/clients/dynamodb");
const {Service} = require("electrodb");
const client = new DynamoDB.DocumentClient();
const table = "dynamodb_table_name";

// old way
new Service({
  service: "service_name",
  version: "1",
  table: table,
}, {client});

// new way
new Service("service_name", {client, table});

// new way (for better TypeScript support)
new Service({entity1, entity2, ...})

The renaming of index property Facets to Composite and Template

In preparation of moving the codebase to version 1.0, ElectroDB will now accept the facets property as either the composite and/or template properties. Using the facets property is still accepted by ElectroDB but will be deprecated sometime in the future (tbd).

This change stems from the fact the facets is already a defined term in the DynamoDB space and that definition does not fit the use-case of how ElectroDB uses the term. To avoid confusion from new developers, the facets property shall now be called composite (as in Composite Attributes) when supplying an Array of attributes, and template while supplying a string. These are two independent fields for two reasons:

ElectroDB will validate the Composite Attributes provided map to those in the template (more validation is always nice).

Allowing for the composite array to be supplied independently will allow for Composite Attributes to remained typed even when using a Composite Attribute Template.

Get Method to Return null

1.0.0 brings back a null response from the get() method when a record could not be found. Prior to 1.0.0 ElectroDB returned an empty object.

Coming Soon

  • Default query options defined on the model to give more general control of interactions with the Entity.

Download Details:
Author: tywalch
Official Website: https://github.com/tywalch/electrodb 
License: MIT
 

#electrodb #dynamodb

渚  直樹

渚 直樹

1635917640

ループを使用して、Rustのデータを反復処理します

このモジュールでは、Rustでハッシュマップ複合データ型を操作する方法について説明します。ハッシュマップのようなコレクション内のデータを反復処理するループ式を実装する方法を学びます。演習として、要求された注文をループし、条件をテストし、さまざまなタイプのデータを処理することによって車を作成するRustプログラムを作成します。

さび遊び場

錆遊び場は錆コンパイラにブラウザインタフェースです。言語をローカルにインストールする前、またはコンパイラが利用できない場合は、Playgroundを使用してRustコードの記述を試すことができます。このコース全体を通して、サンプルコードと演習へのPlaygroundリンクを提供します。現時点でRustツールチェーンを使用できない場合でも、コードを操作できます。

Rust Playgroundで実行されるすべてのコードは、ローカルの開発環境でコンパイルして実行することもできます。コンピューターからRustコンパイラーと対話することを躊躇しないでください。Rust Playgroundの詳細については、What isRust?をご覧ください。モジュール。

学習目標

このモジュールでは、次のことを行います。

  • Rustのハッシュマップデータ型、およびキーと値にアクセスする方法を確認してください
  • ループ式を使用してRustプログラムのデータを反復処理する方法を探る
  • Rustプログラムを作成、コンパイル、実行して、ループを使用してハッシュマップデータを反復処理します

Rustのもう1つの一般的なコレクションの種類は、ハッシュマップです。このHashMap<K, V>型は、各キーKをその値にマッピングすることによってデータを格納しますV。ベクトル内のデータは整数インデックスを使用してアクセスされますが、ハッシュマップ内のデータはキーを使用してアクセスされます。

ハッシュマップタイプは、オブジェクト、ハッシュテーブル、辞書などのデータ項目の多くのプログラミング言語で使用されます。

ベクトルのように、ハッシュマップは拡張可能です。データはヒープに格納され、ハッシュマップアイテムへのアクセスは実行時にチェックされます。

ハッシュマップを定義する

次の例では、書評を追跡するためのハッシュマップを定義しています。ハッシュマップキーは本の名前であり、値は読者のレビューです。

use std::collections::HashMap;
let mut reviews: HashMap<String, String> = HashMap::new();

reviews.insert(String::from("Ancient Roman History"), String::from("Very accurate."));
reviews.insert(String::from("Cooking with Rhubarb"), String::from("Sweet recipes."));
reviews.insert(String::from("Programming in Rust"), String::from("Great examples."));

このコードをさらに詳しく調べてみましょう。最初の行に、新しいタイプの構文が表示されます。

use std::collections::HashMap;

このuseコマンドは、Rust標準ライブラリの一部HashMapからの定義をcollectionsプログラムのスコープに取り込みます。この構文は、他のプログラミング言語がインポートと呼ぶものと似ています。

HashMap::newメソッドを使用して空のハッシュマップを作成します。reviews必要に応じてキーと値を追加または削除できるように、変数を可変として宣言します。この例では、ハッシュマップのキーと値の両方がStringタイプを使用しています。

let mut reviews: HashMap<String, String> = HashMap::new();

キーと値のペアを追加します

このinsert(<key>, <value>)メソッドを使用して、ハッシュマップに要素を追加します。コードでは、構文は<hash_map_name>.insert()次のとおりです。

reviews.insert(String::from("Ancient Roman History"), String::from("Very accurate."));

キー値を取得する

ハッシュマップにデータを追加した後、get(<key>)メソッドを使用してキーの特定の値を取得できます。

// Look for a specific review
let book: &str = "Programming in Rust";
println!("\nReview for \'{}\': {:?}", book, reviews.get(book));

出力は次のとおりです。

Review for 'Programming in Rust': Some("Great examples.")

ノート

出力には、書評が単なる「すばらしい例」ではなく「Some( "すばらしい例。")」として表示されていることに注意してください。getメソッドはOption<&Value>型を返すため、Rustはメソッド呼び出しの結果を「Some()」表記でラップします。

キーと値のペアを削除します

この.remove()メソッドを使用して、ハッシュマップからエントリを削除できます。get無効なハッシュマップキーに対してメソッドを使用すると、getメソッドは「なし」を返します。

// Remove book review
let obsolete: &str = "Ancient Roman History";
println!("\n'{}\' removed.", obsolete);
reviews.remove(obsolete);

// Confirm book review removed
println!("\nReview for \'{}\': {:?}", obsolete, reviews.get(obsolete));

出力は次のとおりです。

'Ancient Roman History' removed.
Review for 'Ancient Roman History': None

このコードを試して、このRustPlaygroundでハッシュマップを操作できます。

演習:ハッシュマップを使用して注文を追跡する
この演習では、ハッシュマップを使用するように自動車工場のプログラムを変更します。

ハッシュマップキーと値のペアを使用して、車の注文に関する詳細を追跡し、出力を表示します。繰り返しになりますが、あなたの課題は、サンプルコードを完成させてコンパイルして実行することです。

この演習のサンプルコードで作業するには、次の2つのオプションがあります。

  • コードをコピーして、ローカル開発環境で編集します。
  • 準備されたRustPlaygroundでコードを開きます。

ノート

サンプルコードで、todo!マクロを探します。このマクロは、完了するか更新する必要があるコードを示します。

現在のプログラムをロードする

最初のステップは、既存のプログラムコードを取得することです。

  1. 編集のために既存のプログラムコードを開きます。コードは、データ型宣言、および定義のため含みcar_qualitycar_factoryおよびmain機能を。

次のコードをコピーしてローカル開発環境で編集する
か、この準備されたRustPlaygroundでコードを開きます。

#[derive(PartialEq, Debug)]
struct Car { color: String, motor: Transmission, roof: bool, age: (Age, u32) }

#[derive(PartialEq, Debug)]
enum Transmission { Manual, SemiAuto, Automatic }

#[derive(PartialEq, Debug)]
enum Age { New, Used }

// Get the car quality by testing the value of the input argument
// - miles (u32)
// Return tuple with car age ("New" or "Used") and mileage
fn car_quality (miles: u32) -> (Age, u32) {

    // Check if car has accumulated miles
    // Return tuple early for Used car
    if miles > 0 {
        return (Age::Used, miles);
    }

    // Return tuple for New car, no need for "return" keyword or semicolon
    (Age::New, miles)
}

// Build "Car" using input arguments
fn car_factory(order: i32, miles: u32) -> Car {
    let colors = ["Blue", "Green", "Red", "Silver"];

    // Prevent panic: Check color index for colors array, reset as needed
    // Valid color = 1, 2, 3, or 4
    // If color > 4, reduce color to valid index
    let mut color = order as usize;
    if color > 4 {        
        // color = 5 --> index 1, 6 --> 2, 7 --> 3, 8 --> 4
        color = color - 4;
    }

    // Add variety to orders for motor type and roof type
    let mut motor = Transmission::Manual;
    let mut roof = true;
    if order % 3 == 0 {          // 3, 6, 9
        motor = Transmission::Automatic;
    } else if order % 2 == 0 {   // 2, 4, 8, 10
        motor = Transmission::SemiAuto;
        roof = false;
    }                            // 1, 5, 7, 11

    // Return requested "Car"
    Car {
        color: String::from(colors[(color-1) as usize]),
        motor: motor,
        roof: roof,
        age: car_quality(miles)
    }
}

fn main() {
    // Initialize counter variable
    let mut order = 1;
    // Declare a car as mutable "Car" struct
    let mut car: Car;

    // Order 6 cars, increment "order" for each request
    // Car order #1: Used, Hard top
    car = car_factory(order, 1000);
    println!("{}: {:?}, Hard top = {}, {:?}, {}, {} miles", order, car.age.0, car.roof, car.motor, car.color, car.age.1);

    // Car order #2: Used, Convertible
    order = order + 1;
    car = car_factory(order, 2000);
    println!("{}: {:?}, Hard top = {}, {:?}, {}, {} miles", order, car.age.0, car.roof, car.motor, car.color, car.age.1);    

    // Car order #3: New, Hard top
    order = order + 1;
    car = car_factory(order, 0);
    println!("{}: {:?}, Hard top = {}, {:?}, {}, {} miles", order, car.age.0, car.roof, car.motor, car.color, car.age.1);

    // Car order #4: New, Convertible
    order = order + 1;
    car = car_factory(order, 0);
    println!("{}: {:?}, Hard top = {}, {:?}, {}, {} miles", order, car.age.0, car.roof, car.motor, car.color, car.age.1);

    // Car order #5: Used, Hard top
    order = order + 1;
    car = car_factory(order, 3000);
    println!("{}: {:?}, Hard top = {}, {:?}, {}, {} miles", order, car.age.0, car.roof, car.motor, car.color, car.age.1);

    // Car order #6: Used, Hard top
    order = order + 1;
    car = car_factory(order, 4000);
    println!("{}: {:?}, Hard top = {}, {:?}, {}, {} miles", order, car.age.0, car.roof, car.motor, car.color, car.age.1);
}

2. プログラムをビルドします。次のセクションに進む前に、コードがコンパイルされて実行されることを確認してください。

次の出力が表示されます。

1: Used, Hard top = true, Manual, Blue, 1000 miles
2: Used, Hard top = false, SemiAuto, Green, 2000 miles
3: New, Hard top = true, Automatic, Red, 0 miles
4: New, Hard top = false, SemiAuto, Silver, 0 miles
5: Used, Hard top = true, Manual, Blue, 3000 miles
6: Used, Hard top = true, Automatic, Green, 4000 miles

注文の詳細を追跡するためのハッシュマップを追加する

現在のプログラムは、各車の注文を処理し、各注文が完了した後に要約を印刷します。car_factory関数を呼び出すたびにCar、注文の詳細を含む構造体が返され、注文が実行されます。結果はcar変数に格納されます。

お気づきかもしれませんが、このプログラムにはいくつかの重要な機能がありません。すべての注文を追跡しているわけではありません。car変数は、現在の注文の詳細のみを保持しています。関数carの結果で変数が更新されるたびcar_factoryに、前の順序の詳細が上書きされます。

ファイリングシステムのようにすべての注文を追跡するために、プログラムを更新する必要があります。この目的のために、<K、V>ペアでハッシュマップを定義します。ハッシュマップキーは、車の注文番号に対応します。ハッシュマップ値は、Car構造体で定義されているそれぞれの注文の詳細になります。

  1. ハッシュマップを定義するには、main関数の先頭、最初の中括弧の直後に次のコードを追加します{
// Initialize a hash map for the car orders
    // - Key: Car order number, i32
    // - Value: Car order details, Car struct
    use std::collections::HashMap;
    let mut orders: HashMap<i32, Car> = HashMap;

2. ordersハッシュマップを作成するステートメントの構文の問題を修正します。

ヒント

ハッシュマップを最初から作成しているので、おそらくこのnew()メソッドを使用することをお勧めします。

3. プログラムをビルドします。次のセクションに進む前に、コードがコンパイルされていることを確認してください。コンパイラからの警告メッセージは無視してかまいません。

ハッシュマップに値を追加する

次のステップは、履行された各自動車注文をハッシュマップに追加することです。

このmain関数では、car_factory車の注文ごとに関数を呼び出します。注文が履行された後、println!マクロを呼び出して、car変数に格納されている注文の詳細を表示します。

// Car order #1: Used, Hard top
    car = car_factory(order, 1000);
    println!("{}: {}, Hard top = {}, {:?}, {}, {} miles", order, car.age.0, car.roof, car.motor, car.color, car.age.1);

    ...

    // Car order #6: Used, Hard top
    order = order + 1;
    car = car_factory(order, 4000);
    println!("{}: {}, Hard top = {}, {:?}, {}, {} miles", order, car.age.0, car.roof, car.motor, car.color, car.age.1);

新しいハッシュマップで機能するように、これらのコードステートメントを修正します。

  • car_factory関数の呼び出しは保持します。返された各Car構造体は、ハッシュマップの<K、V>ペアの一部として格納されます。
  • println!マクロの呼び出しを更新して、ハッシュマップに保存されている注文の詳細を表示します。
  1. main関数で、関数の呼び出しcar_factoryとそれに伴うprintln!マクロの呼び出しを見つけます。
// Car order #1: Used, Hard top
    car = car_factory(order, 1000);
    println!("{}: {}, Hard top = {}, {:?}, {}, {} miles", order, car.age.0, car.roof, car.motor, car.color, car.age.1);

    ...

    // Car order #6: Used, Hard top
    order = order + 1;
    car = car_factory(order, 4000);
    println!("{}: {}, Hard top = {}, {:?}, {}, {} miles", order, car.age.0, car.roof, car.motor, car.color, car.age.1);

2. すべての自動車注文のステートメントの完全なセットを次の改訂されたコードに置き換えます。

// Car order #1: Used, Hard top
    car = car_factory(order, 1000);
    orders(order, car);
    println!("Car order {}: {:?}", order, orders.get(&order));

    // Car order #2: Used, Convertible
    order = order + 1;
    car = car_factory(order, 2000);
    orders(order, car);
    println!("Car order {}: {:?}", order, orders.get(&order));

    // Car order #3: New, Hard top
    order = order + 1;
    car = car_factory(order, 0);
    orders(order, car);
    println!("Car order {}: {:?}", order, orders.get(&order));

    // Car order #4: New, Convertible
    order = order + 1;
    car = car_factory(order, 0);
    orders(order, car);
    println!("Car order {}: {:?}", order, orders.get(&order));

    // Car order #5: Used, Hard top
    order = order + 1;
    car = car_factory(order, 3000);
    orders(order, car);
    println!("Car order {}: {:?}", order, orders.get(&order));

    // Car order #6: Used, Hard top
    order = order + 1;
    car = car_factory(order, 4000);
    orders(order, car);
    println!("Car order {}: {:?}", order, orders.get(&order));

3. 今すぐプログラムをビルドしようとすると、コンパイルエラーが表示されます。<K、V>ペアをordersハッシュマップに追加するステートメントに構文上の問題があります。問題がありますか?先に進んで、ハッシュマップに順序を追加する各ステートメントの問題を修正してください。

ヒント

ordersハッシュマップに直接値を割り当てることはできません。挿入を行うにはメソッドを使用する必要があります。

プログラムを実行する

プログラムが正常にビルドされると、次の出力が表示されます。

Car order 1: Some(Car { color: "Blue", motor: Manual, roof: true, age: ("Used", 1000) })
Car order 2: Some(Car { color: "Green", motor: SemiAuto, roof: false, age: ("Used", 2000) })
Car order 3: Some(Car { color: "Red", motor: Automatic, roof: true, age: ("New", 0) })
Car order 4: Some(Car { color: "Silver", motor: SemiAuto, roof: false, age: ("New", 0) })
Car order 5: Some(Car { color: "Blue", motor: Manual, roof: true, age: ("Used", 3000) })
Car order 6: Some(Car { color: "Green", motor: Automatic, roof: true, age: ("Used", 4000) })

改訂されたコードの出力が異なることに注意してください。println!マクロディスプレイの内容Car各値を示すことによって、構造体と対応するフィールド名。

次の演習では、ループ式を使用してコードの冗長性を減らします。

for、while、およびloop式を使用します


多くの場合、プログラムには、その場で繰り返す必要のあるコードのブロックがあります。ループ式を使用して、繰り返しの実行方法をプログラムに指示できます。電話帳のすべてのエントリを印刷するには、ループ式を使用して、最初のエントリから最後のエントリまで印刷する方法をプログラムに指示できます。

Rustは、プログラムにコードのブロックを繰り返させるための3つのループ式を提供します。

  • loop:手動停止が発生しない限り、繰り返します。
  • while:条件が真のままで繰り返します。
  • for:コレクション内のすべての値に対して繰り返します。

この単元では、これらの各ループ式を見ていきます。

ループし続けるだけ

loop式は、無限ループを作成します。このキーワードを使用すると、式の本文でアクションを継続的に繰り返すことができます。ループを停止させるための直接アクションを実行するまで、アクションが繰り返されます。

次の例では、「We loopforever!」というテキストを出力します。そしてそれはそれ自体で止まりません。println!アクションは繰り返し続けます。

loop {
    println!("We loop forever!");
}

loop式を使用する場合、ループを停止する唯一の方法は、プログラマーとして直接介入する場合です。特定のコードを追加してループを停止したり、Ctrl + Cなどのキーボード命令を入力してプログラムの実行を停止したりできます。

loop式を停止する最も一般的な方法は、breakキーワードを使用してブレークポイントを設定することです。

loop {
    // Keep printing, printing, printing...
    println!("We loop forever!");
    // On the other hand, maybe we should stop!
    break;                            
}

プログラムがbreakキーワードを検出すると、loop式の本体でアクションの実行を停止し、次のコードステートメントに進みます。

breakキーワードは、特別な機能を明らかにするloop表現を。breakキーワードを使用すると、式本体でのアクションの繰り返しを停止することも、ブレークポイントで値を返すこともできます。

次の例はbreakloop式でキーワードを使用して値も返す方法を示しています。

let mut counter = 1;
// stop_loop is set when loop stops
let stop_loop = loop {
    counter *= 2;
    if counter > 100 {
        // Stop loop, return counter value
        break counter;
    }
};
// Loop should break when counter = 128
println!("Break the loop at counter = {}.", stop_loop);

出力は次のとおりです。

Break the loop at counter = 128.

私たちのloop表現の本体は、これらの連続したアクションを実行します。

  1. stop_loop変数を宣言します。
  2. 変数値をloop式の結果にバインドするようにプログラムに指示します。
  3. ループを開始します。loop式の本体でアクションを実行します:
    ループ本体
    1. counter値を現在の値の2倍にインクリメントします。
    2. counter値を確認してください。
    3. もしcounter値が100以上です。

ループから抜け出し、counter値を返します。

4. もしcounter値が100以上ではありません。

ループ本体でアクションを繰り返します。

5. stop_loop値を式のcounter結果である値に設定しますloop

loop式本体は、複数のブレークポイントを持つことができます。式に複数のブレークポイントがある場合、すべてのブレークポイントは同じタイプの値を返す必要があります。すべての値は、整数型、文字列型、ブール型などである必要があります。ブレークポイントが明示的に値を返さない場合、プログラムは式の結果を空のタプルとして解釈します()

しばらくループする

whileループは、条件式を使用しています。条件式が真である限り、ループが繰り返されます。このキーワードを使用すると、条件式がfalseになるまで、式本体のアクションを実行できます。

whileループは、ブール条件式を評価することから始まります。条件式がと評価されるtrueと、本体のアクションが実行されます。アクションが完了すると、制御は条件式に戻ります。条件式がと評価されるfalseと、while式は停止します。

次の例では、「しばらくループします...」というテキストを出力します。ループを繰り返すたびに、「カウントが5未満である」という条件がテストされます。条件が真のままである間、式本体のアクションが実行されます。条件が真でなくなった後、whileループは停止し、プログラムは次のコードステートメントに進みます。

while counter < 5 {
    println!("We loop a while...");
    counter = counter + 1;
}

これらの値のループ

forループは、項目のコレクションを処理するためにイテレータを使用しています。ループは、コレクション内の各アイテムの式本体のアクションを繰り返します。このタイプのループの繰り返しは、反復と呼ばれます。すべての反復が完了すると、ループは停止します。

Rustでは、配列、ベクトル、ハッシュマップなど、任意のコレクションタイプを反復処理できます。Rustはイテレータを使用して、コレクション内の各アイテムを最初から最後まで移動します

forループはイテレータとして一時変数を使用しています。変数はループ式の開始時に暗黙的に宣言され、現在の値は反復ごとに設定されます。

次のコードでは、コレクションはbig_birds配列であり、イテレーターの名前はbirdです。

let big_birds = ["ostrich", "peacock", "stork"];
for bird in big_birds

iter()メソッドを使用して、コレクション内のアイテムにアクセスします。for式は結果にイテレータの現在の値をバインドするiter()方法。式本体では、イテレータ値を操作できます。

let big_birds = ["ostrich", "peacock", "stork"];
for bird in big_birds.iter() {
    println!("The {} is a big bird.", bird);
}

出力は次のとおりです。

The ostrich is a big bird.
The peacock is a big bird.
The stork is a big bird.

イテレータを作成するもう1つの簡単な方法は、範囲表記を使用することですa..b。イテレータはa値から始まりb、1ステップずつ続きますが、値を使用しませんb

for number in 0..5 {
    println!("{}", number * 2);
}

このコードは、0、1、2、3、および4の数値をnumber繰り返し処理します。ループの繰り返しごとに、値を変数にバインドします。

出力は次のとおりです。

0
2
4
6
8

このコードを実行して、このRustPlaygroundでループを探索できます。

演習:ループを使用してデータを反復処理する


この演習では、自動車工場のプログラムを変更して、ループを使用して自動車の注文を反復処理します。

main関数を更新して、注文の完全なセットを処理するためのループ式を追加します。ループ構造は、コードの冗長性を減らすのに役立ちます。コードを簡素化することで、注文量を簡単に増やすことができます。

このcar_factory関数では、範囲外の値での実行時のパニックを回避するために、別のループを追加します。

課題は、サンプルコードを完成させて、コンパイルして実行することです。

この演習のサンプルコードで作業するには、次の2つのオプションがあります。

  • コードをコピーして、ローカル開発環境で編集します。
  • 準備されたRustPlaygroundでコードを開きます。

ノート

サンプルコードで、todo!マクロを探します。このマクロは、完了するか更新する必要があるコードを示します。

プログラムをロードする

前回の演習でプログラムコードを閉じた場合は、この準備されたRustPlaygroundでコードを再度開くことができます。

必ずプログラムを再構築し、コンパイラエラーなしで実行されることを確認してください。

ループ式でアクションを繰り返す

より多くの注文をサポートするには、プログラムを更新する必要があります。現在のコード構造では、冗長ステートメントを使用して6つの注文をサポートしています。冗長性は扱いにくく、維持するのが困難です。

ループ式を使用してアクションを繰り返し、各注文を作成することで、構造を単純化できます。簡略化されたコードを使用すると、多数の注文をすばやく作成できます。

  1. ではmain機能、削除次の文を。このコードブロックは、order変数を定義および設定し、自動車の注文のcar_factory関数とprintln!マクロを呼び出し、各注文をordersハッシュマップに挿入します。
// Order 6 cars
    // - Increment "order" after each request
    // - Add each order <K, V> pair to "orders" hash map
    // - Call println! to show order details from the hash map

    // Initialize order variable
    let mut order = 1;

    // Car order #1: Used, Hard top
    car = car_factory(order, 1000);
    orders.insert(order, car);
    println!("Car order {}: {:?}", order, orders.get(&order));

    ...

    // Car order #6: Used, Hard top
    order = order + 1;
    car = car_factory(order, 4000);
    orders.insert(order, car);
    println!("Car order {}: {:?}", order, orders.get(&order));

2. 削除されたステートメントを次のコードブロックに置き換えます。

// Start with zero miles
    let mut miles = 0;

    todo!("Add a loop expression to fulfill orders for 6 cars, initialize `order` variable to 1") {

        // Call car_factory to fulfill order
        // Add order <K, V> pair to "orders" hash map
        // Call println! to show order details from the hash map        
        car = car_factory(order, miles);
        orders.insert(order, car);
        println!("Car order {}: {:?}", order, orders.get(&order));

        // Reset miles for order variety
        if miles == 2100 {
            miles = 0;
        } else {
            miles = miles + 700;
        }
    }

3. アクションを繰り返すループ式を追加して、6台の車の注文を作成します。order1に初期化された変数が必要です。

4. プログラムをビルドします。コードがエラーなしでコンパイルされることを確認してください。

次の例のような出力が表示されます。

Car order 1: Some(Car { color: "Blue", motor: Manual, roof: true, age: ("New", 0) })
Car order 2: Some(Car { color: "Green", motor: SemiAuto, roof: false, age: ("Used", 700) })
Car order 3: Some(Car { color: "Red", motor: Automatic, roof: true, age: ("Used", 1400) })
Car order 4: Some(Car { color: "Silver", motor: SemiAuto, roof: false, age: ("Used", 2100) })
Car order 5: Some(Car { color: "Blue", motor: Manual, roof: true, age: ("New", 0) })
Car order 6: Some(Car { color: "Green", motor: Automatic, roof: true, age: ("Used", 700) })

車の注文を11に増やす

 プログラムは現在、ループを使用して6台の車の注文を処理しています。6台以上注文するとどうなりますか?

  1. main関数のループ式を更新して、11台の車を注文します。
    todo!("Update the loop expression to create 11 cars");

2. プログラムを再構築します。実行時に、プログラムはパニックになります!

Compiling playground v0.0.1 (/playground)
    Finished dev [unoptimized + debuginfo] target(s) in 1.26s
    Running `target/debug/playground`
thread 'main' panicked at 'index out of bounds: the len is 4 but the index is 4', src/main.rs:34:29

この問題を解決する方法を見てみましょう。

ループ式で実行時のパニックを防ぐ

このcar_factory関数では、if / else式を使用colorして、colors配列のインデックスの値を確認します。

// Prevent panic: Check color index for colors array, reset as needed
    // Valid color = 1, 2, 3, or 4
    // If color > 4, reduce color to valid index
    let mut color = order as usize;
    if color > 4 {        
        // color = 5 --> index 1, 6 --> 2, 7 --> 3, 8 --> 4
        color = color - 4;
    }

colors配列には4つの要素を持ち、かつ有効なcolor場合は、インデックスの範囲は0〜3の条件式をチェックしているcolor私たちはをチェックしません(インデックスが4よりも大きい場合color、その後の関数で4に等しいインデックスへのときに我々のインデックスを車の色を割り当てる配列では、インデックス値から1を減算しますcolor - 1color値4はcolors[3]、配列と同様に処理されます。)

現在のif / else式は、8台以下の車を注文するときの実行時のパニックを防ぐためにうまく機能します。しかし、11台の車を注文すると、プログラムは9番目の注文でパニックになります。より堅牢になるように式を調整する必要があります。この改善を行うために、別のループ式を使用します。

  1. ではcar_factory機能、ループ式であれば/他の条件文を交換してください。colorインデックス値が4より大きい場合に実行時のパニックを防ぐために、次の擬似コードステートメントを修正してください。
// Prevent panic: Check color index, reset as needed
    // If color = 1, 2, 3, or 4 - no change needed
    // If color > 4, reduce to color to a valid index
    let mut color = order as usize;
    todo!("Replace `if/else` condition with a loop to prevent run-time panic for color > 4");

ヒント

この場合、if / else条件からループ式への変更は実際には非常に簡単です。

2. プログラムをビルドします。コードがエラーなしでコンパイルされることを確認してください。

次の出力が表示されます。

Car order 1: Some(Car { color: "Blue", motor: Manual, roof: true, age: ("New", 0) })
Car order 2: Some(Car { color: "Green", motor: SemiAuto, roof: false, age: ("Used", 700) })
Car order 3: Some(Car { color: "Red", motor: Automatic, roof: true, age: ("Used", 1400) })
Car order 4: Some(Car { color: "Silver", motor: SemiAuto, roof: false, age: ("Used", 2100) })
Car order 5: Some(Car { color: "Blue", motor: Manual, roof: true, age: ("New", 0) })
Car order 6: Some(Car { color: "Green", motor: Automatic, roof: true, age: ("Used", 700) })
Car order 7: Some(Car { color: "Red", motor: Manual, roof: true, age: ("Used", 1400) })
Car order 8: Some(Car { color: "Silver", motor: SemiAuto, roof: false, age: ("Used", 2100) })
Car order 9: Some(Car { color: "Blue", motor: Automatic, roof: true, age: ("New", 0) })
Car order 10: Some(Car { color: "Green", motor: SemiAuto, roof: false, age: ("Used", 700) })
Car order 11: Some(Car { color: "Red", motor: Manual, roof: true, age: ("Used", 1400) })

概要

このモジュールでは、Rustで使用できるさまざまなループ式を調べ、ハッシュマップの操作方法を発見しました。データは、キーと値のペアとしてハッシュマップに保存されます。ハッシュマップは拡張可能です。

loop手動でプロセスを停止するまでの式は、アクションを繰り返します。while式をループして、条件が真である限りアクションを繰り返すことができます。このfor式は、データ収集を反復処理するために使用されます。

この演習では、自動車プログラムを拡張して、繰り返されるアクションをループし、すべての注文を処理しました。注文を追跡するためにハッシュマップを実装しました。

このラーニングパスの次のモジュールでは、Rustコードでエラーと障害がどのように処理されるかについて詳しく説明します。

 リンク: https://docs.microsoft.com/en-us/learn/modules/rust-loop-expressions/

#rust #Beginners