承接 belyys7/elasticsearch-its-easy 相关项目开发

从需求分析到上线部署,全程专人跟进,保证项目质量与交付效率

邮箱:yvsm@zunyunkeji.com | QQ:316430983 | 微信:yvsm316

belyys7/elasticsearch-its-easy

最新稳定版本:1.1.1

Composer 安装命令:

composer require belyys7/elasticsearch-its-easy

包简介

Simple search with elasticsearch

关键字:

README 文档

README

Elasticsearch it`s easy SDK for working with Elasticsearch like with constructor

Documentation

The documentation for the Elasticsearch REST API can be found here.

Installation

The preferred way to install this extension is through composer.

Either run

composer require idapgroup/elasticsearch-its-easy

or add

{
  "require": {
    "idapgroup/elasticsearch-its-easy": "^1.0.0"
  }
}

to the requirement section of your composer.json file.

Quickstart

Prepare the data you want to store in elasticsearch

$data = [
    [
        'user' => [
            'id' => 100,
            'email' => 'stepan21@gmail.com',
            'name' => 'Stepan',
            'age' => 21,
            'birthday' => '2001-06-15',
        ],
        'work' => [
            'position' => [
                'id' => 25,
                'name' => 'php developer',
            ],
            'skills' => [
                [
                    'id' => 36,
                    'name' => 'php'
                ],
                [
                    'id' => 40,
                    'name' => 'mysql'
                ],
                [
                    'id' => 56,
                    'name' => 'js'
                ],
            ],
            'salary' => 4000
        ],
        'location' => [
            'lat' => 50.445077,
            'lon' => 30.521215
        ],
    ],
    [
        'user' => [
            'id' => 101,
            'email' => 'luigi@gmail.com',
            'name' => 'Luigi',
            'age' => 29,
            'birthday' => '2005-03-20',
        ],
        'work' => [
            'position' => [
                'id' => 12,
                'name' => 'js developer',
            ],
            'skills' => [
                [
                    'id' => 56,
                    'name' => 'js'
                ],
                [
                    'id' => 70,
                    'name' => 'mongodb'
                ],
                [
                    'id' => 1,
                    'name' => 'html'
                ],
                [
                    'id' => 2,
                    'name' => 'css'
                ],
            ],
            'salary' => 2700
        ],
        'location' => [
            'lat' => 47.454589,
            'lon' => 32.915673
        ],
    ],
];

Create your class to be expanded by basic search

use IdapGroup\ElasticsearchItsEasy\ModelSearchBase;

class StaffModelSearch extends ModelSearchBase
{   
    public function setRules() : void
    {
        $this->rules = [
            self::GROUP_MUST => [
                self::RULE_EQUAL => [
                    'userId' => 'user.id',
                ],
            ],
            self::GROUP_SHOULD => [
                self::RULE_LIKE => [
                    'userEmail' => 'user.email',
                    'userName' => 'user.name',
                ],
                self::RULE_IN => [
                    'workSkillsId' => 'work.skills.id',
                ],
            ],
            self::GROUP_FILTER => [
                self::RULE_EQUAL => [
                    'workPositionId' => 'work.position.id'
                ],
                self::RULE_RANGE_NUMBER => [
                    'userAge' => 'user.age',
                    'workSalary' => 'work.salary',
                ],
                self::RULE_RANGE_DATE => [
                    'birthday' => 'user.birthday',
                ],
            ],
            self::GROUP_LOCATION => [
                'location' => self::SORT_DESC,
            ],
        ];
    }
   
    public function setSort() : void
    {
        $this->sort = [
            'user.id' => self::SORT_DESC,
        ];
    }

}

Create model based on elasticsearch configuration

$staffModelSearch = new StaffModelSearch('es01', '9200', 'staff_search');

Indexing Documents in Elasticsearch

$staffModelSearch->reCreateIndex();

foreach ($data as $item) {
    $staffModelSearch->addDocument($item, 'user.id', $item['user']['id']);
}

Example #1: search as list with pagination

Specify search keys and their values

$params = [
    'userId' => 100,
    'workPositionId' => 25,
    'userEmail' => 'stepan21@gmail.com',
    'userName' => 'Stepan',
    'workSkillsId' => [36, 40],
    'userAge' => ['min' => 18, 'max' => 65],
    'workSalary' => ['min' => 500, 'max' => 5000],
    'location' => [
        'point' => [
            'lat' => 48.454589,
            'lon' => 33.915673,
            'distance' => 100000
        ],
        'rectangle' => [
            'topLeftLat' => 55.710929,
            'topLeftLng' => 14.090451,
            'bottomRightLat' => 41.830140,
            'bottomRightLng' => 41.802791
        ],
    ],
    'page' => 1,
    'limit' => 20
];

Set data output limits if required and search

//$staffModelSearch->enableFixLimitResult(50);
$result = $staffModelSearch->searchList($params);

The result of the response will be in the format

[
    'result' => [
        [
            'user' => [
                'id' => 100,
                'email' => 'stepan21@gmail.com',
                'name' => 'Stepan',
                'age' => 21
            ],
            'work' => [
                'position' => [
                    'id' => 25,
                    'name' => 'php developer',
                ],
                'skills' => [
                    [
                        'id' => 36,
                        'name' => 'php'
                    ],
                    [
                        'id' => 40,
                        'name' => 'mysql'
                    ],
                    [
                        'id' => 56,
                        'name' => 'js'
                    ],
                ],
                'salary' => 4000
            ],
            'location' => [
                'lat' => 50.445077,
                'lon' => 30.521215
            ],
        ],
        //... etc.
    ],
    'pagination' => [
        'totalCount' => (int),
        'pageCount' => (int),
        'currentPage' => (int)
    ]
]

Example #2: search for map

Specify search keys and their values

$params = [
    'userId' => 100,
    'workPositionId' => 25,
    'userEmail' => 'stepan21@gmail.com',
    'userName' => 'Stepan',
    'workSkillsId' => [36, 40],
    'userAge' => ['min' => 18, 'max' => 65],
    'workSalary' => ['min' => 500, 'max' => 5000],
    'location' => [
        'point' => [
            'lat' => 48.454589,
            'lon' => 33.915673,
            'distance' => 100000
        ],
        'rectangle' => [
            'topLeftLat' => 55.710929,
            'topLeftLng' => 14.090451,
            'bottomRightLat' => 41.830140,
            'bottomRightLng' => 41.802791
        ],       
    ],
];

Execute search

$result = $staffModelSearch->searchMap($params);

The result of the response will be in the format

[
    [
        'user' => [
            'id' => 100,
            'email' => 'stepan21@gmail.com',
            'name' => 'Stepan',
            'age' => 21
        ],
        'work' => [
            'position' => [
                'id' => 25,
                'name' => 'php developer',
            ],
            'skills' => [
                [
                    'id' => 36,
                    'name' => 'php'
                ],
                [
                    'id' => 40,
                    'name' => 'mysql'
                ],
                [
                    'id' => 56,
                    'name' => 'js'
                ],
            ],
            'salary' => 4000
        ],
        'location' => [
            'lat' => 50.445077,
            'lon' => 30.521215
        ],
    ],
    //... etc.
]

Additional settings

Custom clustering (useful when markers on the map overlap each other and the maximum zoom does not solve the problem)

$params = [
    //...
    'location' => [
        'point' => [
            'lat' => 48.454589,
            'lon' => 33.915673,
            'distance' => 100000
        ],
        'rectangle' => [
            'topLeftLat' => 55.710929,
            'topLeftLng' => 14.090451,
            'bottomRightLat' => 41.830140,
            'bottomRightLng' => 41.802791
        ],
        'clustering' => true,
        'zoom' => 1,
    ],
    //...
];

Response structure example

[
    // Cluster 1
    [
        [
            // data
        ],
        [
            // data
        ],
        //...
    ],
    // Cluster 2
    [
        [
            // data
        ],
        [
            // data
        ],
        //...
    ],
    //... etc.
]

Overwrite rules

// Describe the rules in the associative array as required by the ES documentation
$overWriteRules = [
    'must' => [
        [
            'term' => [
                'user.name.keyword' => 'Stepan',
            ],
        ],
        [
            'term' => [
                'user.age' => 21,
            ],
        ],
        //...
    ],
    //...
];

// Use a Method to Set Your Rules
$staffModelSearch->setOverWriteRules($overWriteRules);

统计信息

  • 总下载量: 6
  • 月度下载量: 0
  • 日度下载量: 0
  • 收藏数: 0
  • 点击次数: 0
  • 依赖项目数: 0
  • 推荐数: 0

GitHub 信息

  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • 开发语言: PHP

其他信息

  • 授权协议: MIT
  • 更新时间: 2023-04-09