Laravel 6 Full Text Search Using Scout Example

hii guys,

In this example,I will show you how to add full text search using scout in your laravel 6 application.Here we will use scout ans algolia to perform full text search.

You just need to create an account in algolia.com and create one index where your data will store.

Follow below step to add full text search in your application :

Link: https://www.nicesnippets.com/blog/full-text-search-using-scout-and-algolia-in-laravel-6

#laravel #laravel6

What is GEEK

Buddha Community

Laravel 7 Full Text Search MySQL

Here, I will show you how to create full text search in laravel app. You just follow the below easy steps and create full text search with mysql db in laravel.

Laravel 7 Full Text Search Mysql

Let’s start laravel full-text search implementation in laravel 7, 6 versions:

1. Step 1: Install Laravel New App
2. Step 2: Configuration DB .evn file
3. Step 3: Run Migration
4. Step 4: Install Full Text Search Package
5. Step 5: Add Fake Records in DB
6. Step 6: Add Routes,
7. Step 7: Create Controller
8. Step 8: Create Blade View
9. Step 9: Start Development Server

https://www.tutsmake.com/laravel-full-text-search-tutorial/

#laravel full text search mysql #laravel full text search query #mysql full text search in laravel #full text search in laravel 6 #full text search in laravel 7 #using full text search in laravel

Text Analysis Within a Full-Text Search Engine

Full-Text Search refers to techniques for searching text content within a document or a collection of documents that hold textual content. A Full-Text search engine examines all the textual content within documents as it tries to match a single search term or several terms, text analysis being a pivotal component.

You’ve probably heard of the most well-known Full-Text Search engine: Lucene with Elasticsearch built on top of it. Couchbase’s Full-Text Search (FTS) Engine is powered by Bleve, and this article will showcase the various ways to analyze text within this engine.

Bleve is an open-sourced text indexing and search library implemented in Go, developed in-house at Couchbase.

Couchbase’s FTS engine supports indexes that subscribe to data residing within a Couchbase Server and indexes data that it ingests from the server. It’s a distributed system – meaning it can partition data across multiple nodes in a cluster and searches involve scattering the request and gathering responses from across all nodes within the cluster before responding to the application.

The FTS engine distributes documents ingested for an index across a configurable number of partitions and these partitions could reside across multiple nodes within a cluster. Each partition follows the same set of rules that the FTS index is configured with – to analyze and index text into the full-text search database.

The text analysis component of a Full-Text search engine is responsible for breaking down the raw text into a list of words – which we’ll refer to as tokens. These tokens are more suitable for indexing in the database and searching.

Couchbase’s FTS Engine handles text indexing for JSON documents. It builds an index for the content that is analyzed and stores into the database – the index along with all the relevant metadata needed to link the tokens generated to the original documents within which they reside.

An Inverted index is the data structure chosen to index the tokens generated from text, to make search queries faster. This index links every token generated to documents that contain the token.

For example, take the following documents …

The inverted index for the tokens generated from the 2 documents above would resemble this…

Here’s a diagram highlighting the components of the full-text search engine …

A Text Analyzer

The components of a text analyzer can broadly be classified into 2 categories:

• Tokenizer
• Filters

Couchbase’s engine further categorizes filters into:

• Character filters
• Token filters

Before we dive into the function of each of these components, here’s an overview of a text analyzer …

Tokenizer

A tokenizer is the first component to which the documents are subjected to. As the name suggests, it breaks the raw text into a list of tokens. This conversion will depend on a rule-set defined for the tokenizer.

Stock tokenizers…

Take this sample text for an example: “_this is my email ID: _abhi123@cb.com”

A couple of configurable tokenizers…

• Exception … This tokenizer allows the user to enter exception patterns (regular expressions) over the stock tokenizers.
• Regexp … This tokenizer extracts text that matches the pattern (a regular expression) as tokens.

For example:

#json #couchbase #search #go #text analysis #full-text search #bleve #full-text #full-text-indexing

Basic and Full-text Search with Django and Postgres

Unlike relational databases, full-text search is not standardized. There are a number of open-source options like ElasticSearch, Solr, and Xapian. ElasticSearch is probably the most popular solution; however, it’s complicated to set up and maintain. Further, if you’re not taking advantage of some of the advanced features that ElasticSearch offers, you should stick with the full-text search capabilities that many relational (like Postgres, MySQL, SQLite) and non-relational databases (like MongoDB and CouchDB) offer. Postgres in particular is well-suited for full-text search. Django supports it out-of-the-box as well.

For the vast majority of your Django apps, you should, at the very least, start out with leveraging full-text search from Postgres before looking to a more powerful solution like ElasticSearch or Solr.

In this article, we’ll add basic and full-text search to a Django app with Postgres.

Objectives

By the end of this article, you should be able to:

1. Set up basic search functionality in a Django app with the Q object
2. Add full-text search to a Django app
3. Sort full-text search results by relevance using stemming, ranking, and weighting

#basic and full-text search with django and postgres #django #search lookup #postgres #full-text search #postgres full text search

Php how to delete multiple rows through checkbox using ajax in laravel

First thing, we will need a table and i am creating products table for this example. So run the following query to create table.

CREATE TABLE `products` (
 `id` int(10) unsigned NOT NULL AUTO_INCREMENT,
 `name` varchar(255) COLLATE utf8mb4_unicode_ci NOT NULL,
 `description` varchar(255) COLLATE utf8mb4_unicode_ci DEFAULT NULL,
 `created_at` timestamp NULL DEFAULT CURRENT_TIMESTAMP,
 `updated_at` datetime DEFAULT NULL,
 PRIMARY KEY (`id`)
) ENGINE=InnoDB AUTO_INCREMENT=7 DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_unicode_ci

Next, we will need to insert some dummy records in this table that will be deleted.

INSERT INTO `products` (`name`, `description`) VALUES

('Test product 1', 'Product description example1'),

('Test product 2', 'Product description example2'),

('Test product 3', 'Product description example3'),

('Test product 4', 'Product description example4'),

('Test product 5', 'Product description example5');

Now we are redy to create a model corresponding to this products table. Here we will create Product model. So let’s create a model file Product.php file under app directory and put the code below.

<?php

namespace App;

use Illuminate\Database\Eloquent\Model;

class Product extends Model
{
    protected $fillable = [
        'name','description'
    ];
}

Step 2: Create Route

Now, in this second step we will create some routes to handle the request for this example. So opeen routes/web.php file and copy the routes as given below.

routes/web.php

Route::get('product', 'ProductController@index');
Route::delete('product/{id}', ['as'=>'product.destroy','uses'=>'ProductController@destroy']);
Route::delete('delete-multiple-product', ['as'=>'product.multiple-delete','uses'=>'ProductController@deleteMultiple']);

#laravel #delete multiple rows in laravel using ajax #laravel ajax delete #laravel ajax multiple checkbox delete #laravel delete multiple rows #laravel delete records using ajax #laravel multiple checkbox delete rows #laravel multiple delete

Laravel AJAX CRUD Example Tutorial

Hello Guys,

Today I will show you how to create laravel AJAX CRUD example tutorial. In this tutorial we are implements ajax crud operation in laravel. Also perform insert, update, delete operation using ajax in laravel 6 and also you can use this ajax crud operation in laravel 6, laravel 7. In ajax crud operation we display records in datatable.

Read More : Laravel AJAX CRUD Example Tutorial

https://www.techsolutionstuff.com/post/laravel-ajax-crud-example-tutorial

---

Read Also : Read Also : Laravel 6 CRUD Tutorial with Example

https://techsolutionstuff.com/post/laravel-6-crud-tutorial-with-example

#laravel ajax crud example tutorial #ajax crud example in laravel #laravel crud example #laravel crud example with ajax #laravel #php