Patch A Single Record to A Table in PowerApps

In this blog, we are going to see how to use the patch function to create and update single records in a table. 

Create A New Record Using Patch Function

Syntax

Patch(Datasource, BaseRecord, NewRecord)

Code

Patch(
    GrosseryInventory,
    Defaults(GrosseryInventory),
    {
        Name: "Butter",
        ProductID: 1003,
        ExpiryDate: Date(2023,12,11),
        Price: 120
    }
)

Output

GrosseryInventory in SharePoint.

IDNameProductIDExpiryDatePrice
10Pasta100112/01/2023110
11Rice100212/01/202399
12Butter100312/11/2023120


Update An Existing Record Using Patch Function

Patch(Datasource, BaseRecord, ChangeRecord)

Code

Patch(
    GrosseryInventory,
    LookUp(
        GrosseryInventory,
        ID=12
    ),
    {
        ExpiryDate: Date(2023,6,6),
        Price: 145
    }
)

Output

GrosseryInventory in SharePoint.

IDNameProductIDExpiryDatePrice
10Pasta100112/01/2023110
11Rice100212/01/202399
12Butter100306/06/2023145

That’s it, you have seen how to use the patch function to create and update single records in a table. Feel free to fill up the comment box below if you need any further assistance.

Original article source at: https://www.c-sharpcorner.com/

#powerapp #table 

What is GEEK

Buddha Community

Patch A Single Record to A Table in PowerApps

Patch A Single Record to A Table in PowerApps

In this blog, we are going to see how to use the patch function to create and update single records in a table. 

Create A New Record Using Patch Function

Syntax

Patch(Datasource, BaseRecord, NewRecord)

Code

Patch(
    GrosseryInventory,
    Defaults(GrosseryInventory),
    {
        Name: "Butter",
        ProductID: 1003,
        ExpiryDate: Date(2023,12,11),
        Price: 120
    }
)

Output

GrosseryInventory in SharePoint.

IDNameProductIDExpiryDatePrice
10Pasta100112/01/2023110
11Rice100212/01/202399
12Butter100312/11/2023120


Update An Existing Record Using Patch Function

Patch(Datasource, BaseRecord, ChangeRecord)

Code

Patch(
    GrosseryInventory,
    LookUp(
        GrosseryInventory,
        ID=12
    ),
    {
        ExpiryDate: Date(2023,6,6),
        Price: 145
    }
)

Output

GrosseryInventory in SharePoint.

IDNameProductIDExpiryDatePrice
10Pasta100112/01/2023110
11Rice100212/01/202399
12Butter100306/06/2023145

That’s it, you have seen how to use the patch function to create and update single records in a table. Feel free to fill up the comment box below if you need any further assistance.

Original article source at: https://www.c-sharpcorner.com/

#powerapp #table 

Fredy  Larson

Fredy Larson

1595209620

How to alter tables in production when records are in millions

As a developer, I have experienced changes in app when it is in production and the records have grown up to millions. In this specific case if you want to alter a column using simple migrations that will not work because of the following reasons:

It is not so easy if your production servers are under heavy load and the database tables have 100 million rows. Because such a migration will run for some seconds or even minutes and the database table can be locked for this time period – a no-go on a zero-downtime environment.

In this specific case you can use MySQL’s algorithms: Online DDL operations. That’s how you can do it in Laravel.

First of all create migration. For example I want to modify a column’s name the traditional migration will be:

Schema::table('users', function (Blueprint $table) {
            $table->renameColumn('name', 'first_name');
        });

Run the following command php artisan migrate –pretend this command will not run the migration rather it will print out it’s raw sql:

ALTER TABLE users CHANGE name first_name VARCHAR(191) NOT NULL

Copy that raw sql, remove following code:

Schema::table('users', function (Blueprint $table) {
            $table->renameColumn('name', 'first_name');
        });

Replace it with following in migrations up method:

\DB::statement('ALTER TABLE users CHANGE name first_name VARCHAR(191) NOT NULL');

Add desired algorithm, in my case query will look like this:

\DB::statement('ALTER TABLE users CHANGE name first_name VARCHAR(191) NOT NULL, ALGORITHM=INPLACE, LOCK=NONE;');

#laravel #mysql #php #alter heavy tables in production laravel #alter table in production laravel #alter tables with million of records in laravel #how to alter heavy table in production laravel #how to alter table in production larave #mysql online ddl operations

Patch Multiple Records to A Table in Power Apps

In this article, we are going to see how to use the patch function to create and edit multiple records in a table.

Create Multiple Records Using Patch Function

Syntax

Patch(Datasource, BaseRecordsTable, NewRecordsTable)

Code

ClearCollect(
    colGrosseryInventory,
    Table(
        {
            Name: "Pasta",
        	ProductID: 1001,
        	ExpiryDate: Date(2023,12,11),
        	Price: 120
        },
        {
            Name: "Rice",
        	ProductID: 1002,
        	ExpiryDate: Date(2024,12,08),
        	Price: 110
        },
        {
            Name: "Butter",
        	ProductID: 1003,
        	ExpiryDate: Date(2025,12,07),
        	Price: 130
        }
    )
);

Patch(
    GrosseryInventory,
    ForAll(
        Sequence(CountRows(colGrosseryInventory)),
        Defaults(GrosseryInventory)
    ),
    colGrosseryInventory
);

JavaScript

Copy

Output

GrosseryInventory in SharePoint.

IDNameProductIDExpiryDatePrice
10Pasta100112/01/2023120
11Rice100208/01/2024110
12Butter100307/11/2025130


Edit Multiple Existing Records Using Patch Function

Syntax

Patch(Datasource, BaseRecordsTable, UpdateRecordsTable)

Code

ClearCollect(
    colUpdateGrosseryInventory,
    Table(
        {
		    ID: 10,
        	Price: 140
        },
        {
		    ID: 11,
        	ExpiryDate: Date(2024,12,11),
        	Price: 130
        },
        {
            ID: 12,
        	Price: 160
        }
    )
);

Patch(
    GrosseryInventory,
    ShowColumns(
        colUpdateGrosseryInventory,
        "ID"
    ),
   colUpdateGrosseryInventory
);

Output

GrosseryInventory in SharePoint.

IDNameProductIDExpiryDatePrice
10Pasta100112/01/2023140
11Rice100212/11/2024130
12Butter100307/11/2025160

That’s it, you have seen how to use the patch function to create and edit multiple records in a table. Feel free to fill up the comment box below if you need any further assistance.

Original article source at: https://www.c-sharpcorner.com/

#powerapp #table 

Bhakti Rane

1625057623

Click2Undo - 1 Click App to restore Dynamics 365 CRM data to its last known state

Undo changes & restore records in Dynamics 365 CRM with a single click

Click2Undo is a productivity app that helps you to undo changes in the data in Dynamics 365 CRM with a single click. Be it the last change that you’d want to restore, or the changes that were done in the past which you would like to get back, Click2Undo can do it without any hassle. This provides a safety net within which users can conduct day-to-day activities without fear of losing data due to human or technical errors.
Click2Undo is available for Dynamics CRM 8.2 and above, Dataverse (Power Apps). It supports deployment models - On-Premises and Online.
Features
• Entity Support: Click2Undo provides support to all OOB as well as Custom Entities
• Undo Last Changes: Ability to restore the last changes done to a Dynamics 365 CRM record by clicking the Click2Undo button
• Undo Past Changes: Ability to undo past changes made to multiple fields on Dynamics 365 CRM records in one go using History button
• Undo Bulk Changes: Ability to undo changes on multiple records at one go.

#restore last state of dynamics 365 records #restoring deleted dynamics 365 records #recovering deleted dynamics 365 records #recover deleted dynamics crm records #dynamics 365 online recover deleted records #restore records dynamics crm

Julie  Donnelly

Julie Donnelly

1596495120

Beginner’s Guide to Table Partitioning In PostgreSQL

Table partitioning in SQL, as the name suggests, is a process of dividing large data tables into small manageable parts, such that each part has its own name and characteristics.

Table partitioning helps in significantly improving database server performance as less number of rows have to be read, processed and returned. We can also use partitioning techniques for dividing indexes and index-organized tables.

Table partitioning can be of two types, namely, vertical partitioning or horizontal partitioning. In vertical partitioning, we divide the table column wise. While in horizontal partitioning, we divide the table row wise on the basis of range of values in a certain column.

Syntax and parameters

The basic syntax for partitioning a table using range is as follows :

Main table creation :

CREATE TABLE main_table_name (

column_1 data type,

column_2 data type,

.

.

. ) PARTITION BY RANGE (column_2);

Partition table creation :

CREATE TABLE partition_name

PARTITION OF main_table_name FOR VALUES FROM (start_value) TO (end_value);

The parameters used in the above mentioned syntax are similar to CREATE TABLE statement, except these :

PARTITION BY RANGE (column_2) : column_2 is the field on the basis of which partitions will be created.

partition_name : name of the partition table

FROM (start_value) TO (end_value) : The range of values in column_2, which forms the part of this partition. Note that start_value is inclusive, while end_value is exclusive.

Here is an example to illustrate it further.

Example

Imagine that you are working as a data engineer for an e-com firm that gets a huge number of orders on a daily basis. You usually store data such as order_id, order_at, customer_id etc. in a SQL table called “e-transactions’’. Since, the table has a humongous amount of data in it, the low load speed and high return time etc. have become a problem for data analysts, who use this table for preparing KPIs on a daily basis.

What will you do to improvise this table, so that data analysts can run queries quickly?

A logical step would be partitioning the table into smaller parts. Let’s say we create partitions such that the partition stores data pertaining to specified order dates only. This way, we will have less data in each partition and working on it will be more fun.

We can partition the table using declarative partitioning i.e. by using a PARTITION BY RANGE (column_name) function as shown below.

#postgresql #drop-table #sql #alter-table #table-partitioning