Laravel Scout vs. ElasticSearch case

Elasticsearch is referred to as ES for short below

To use ES as a search engine, first we need to install it

Elastic requires the Java 8 environment. Check the Java environment before installing the software

The installation

$ wget https://artifacts.elastic.co/downloads/elasticsearch/elasticsearch-5.5.1.zip
$ unzip elasticsearch-5.5.1.zip
$ cdElasticsearch 5.5.1 /Copy the code

Next, go to the unzipped directory and run the following command to try to start Elastic

$ ./bin/elasticsearch
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Note:

It is very likely that the following error will occur during the initial installation:

max virtual memory areas vm.maxmapcount [65530] is too low
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To resolve the problem, run the following command:

$ sudo sysctl -w vm.max_map_count=262144
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If all is well, elastic will be running on port 9200 of the machine by default. Requesting this port will give you the following information

$ curl localhost:9200

{
  "name" : "atntrTf",
  "cluster_name" : "elasticsearch",
  "cluster_uuid" : "tf9250XhQ6ee4h7YI11anA",
  "version" : {
    "number" : "5.5.1",
    "build_hash" : "19c13d0",
    "build_date" : "2017-07-18T20:44:24.823Z",
    "build_snapshot" : false,
    "lucene_version" : "6.6.0"
  },
  "tagline" : "You Know, for Search"
}
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By default, elastic only allows local access. If remote access is required, modify the config/ Elasticserach. yml file in the Elastic installation directory to uncomment netword.host and change it to 0.0.0.0. And then restart Elastic

Network. The host: 0.0.0.0Copy the code

In the code above, set it to 0.0.0.0 so that anyone can access it. Don’t do this for online services. Set it to a specific IP address

The basic concept

Elastic is essentially a distributed database that allows multiple servers to work together. Each server can allow multiple Elastic instances. A single Elastic instance is called a node, and a group of nodes forms a cluster

It has some important concepts

1. Index = Index
2. Type (Type)
3. Document
4. Shards
5. Replicasedit

Shards and replicas are not needed at the moment, so this is a brief explanation

- Copies are multiplications, more is more wasteful, but also more safe. - Sharding is a division method. The more shards there are, the smaller and more fragmented the single shard data is.Copy the code

Since there are many concepts in it, I have posted two very good blogs:

1. Ruan Yifeng
2. Technical analysis of ElastSearch

After that, we can use a comparison to understand the important concepts

- Relational Databases -> Databases -> Tables -> Rows -> Columns - Elasticsearch -> Indeces -> Types -> Documents -> FieldsCopy the code

An Elasticsearch cluster can contain multiple indexes, each index can contain multiple Types, each type can contain multiple documents, then each document can contain multiple Fields.

Although the analogy is so, they are two different products after all, and it has been mentioned above that Types may be deleted in the later version, so generally we create an index for each type. Fresh creates an index for groceries, and groceries creates an index for groceries, rather than creating an index for groceries that includes both fresh and groceries.

Laravel scout and es

Install the Scout package first

composer require laravel/scout
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Generates a configuration file

php artisan vendor:publish --provider="Laravel\Scout\ScoutServiceProvider"
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In provider of config/app.php, add

Laravel\Scout\ScoutServiceProvider::class,
ScoutEngines\Elasticsearch\ElasticsearchProvider::class,
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Then we also need to add the es configuration information in scoute.php after algolia

'elasticsearch'= > ['index' => env('ELASTICSEARCH_INDEX'.'dongdianyi'),
        'hosts' => [
            env('ELASTICSEARCH_HOST'.'http://127.0.0.1:9200'),]],Copy the code

We also need to use GuzzleHttp

Install the

composer require guzzlehttp/guzzle
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To start writing code, use Command to get ES to initialize some data

php artisan make:command InitEs
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Post my code

      

namespace App\Console\Commands;

use GuzzleHttp\Client;
use Illuminate\Console\Command;

class ESInit extends Command
{

    protected $signature = 'es:init';

    protected $description = 'Initialize the ES library';

    public function __construct(a)
    {
        parent::__construct();
    }

    public function handle(a)
    {
        $client = new Client();
        try {
            $this->createTemplate($client);
            $this->createIndex($client);
        } catch (\Exception$ex) { $ex->message(); }}public function createTemplate(Client $client)
    {
        $url = config('scout.elasticsearch.hosts') [0].'/_template/tmp';
        // Ensure that template does not exist
        // $client->delete($url);
        $param = [
            'json'= > ['template'= >The '*'.'settings'= > ['number_of_shards'= >1,].'mappings'= > ['_default_'= > ['_all'= > ['enabled'= >true,].'dynamic_templates' => [
                            [
                                'strings'= > ['match_mapping_type'= >'string'.'mapping'= > ['type'= >'text'.'analyzer'= >'ik_smart'.'ignore_above'= >256.'fields'= > ['keyword'= > ['type'= >'keyword'[,], [,], [,],]; $client->put($url, $param);$this->info('elasticsearch template created done');
    }

    public function createIndex(Client $client)
    {
        / / create the index
        $url = config('scout.elasticsearch.hosts') [0].'/' . config('scout.elasticsearch.index');
        // Make sure index does not exist
        // $client->delete($url);
        $param = [
            'json'= > ['settings'= > ['refresh_interval'= >'5s'.'number_of_shards'= >1.'number_of_replicas'= >0,].'mappings'= > ['_default_'= > ['_all'= > ['enabled'= >false[,] [,],]; $client->put($url, $param);$this->info('elasticsearch index created done'); }}Copy the code

Then, we specify which model needs to be searched

      

namespace App;

use Illuminate\Database\Eloquent\Model;
use Laravel\Scout\Searchable;


class Article extends Model
{
    use Searchable;
    protected $table = 'posts';

    protected $fillable = [
        'url'.'author'.'title'.'content'.'post_date'
    ];

    public function toSearchableArray(a)
    {
        return [
            'title'= >$this->title,
            'content'= >$this->content ]; }}Copy the code

Inside the model, use Searchable and override the toSearchableArray function

Then use the command

php artisan scout:import "App\Article"
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The current database data, according to toSearchableArray rules import, import complete can

The verification results

The ES and Scout steps are complete and ready to use

Start by defining the GraphQL interface

searchArticles(keyWord: String!). : [Article!] ! @paginate(defaultCount:10.builder: "App\\Article@searchArticles")
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And then parse it

public function searchArticles($rootValue, array $args, GraphQLContext $context, ResolveInfo $resolveInfo)
    {
        $query = $args['keyWord'];
        return Article::search($query);
    }
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Done! In this example, I use IK_smart, which will automatically match according to the maximum granularity of Chinese word segmentation