上一篇扯了一大通都只是 Elasticsearch 的安装配置, 现在扯点集成到 Rails 上的东西.

elasticsearch-rails 这个 Repository 是由三个 Gem 组成,

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gem 'elasticsearch-model'
gem 'elasticsearch-rails'
gem 'elasticsearch-persistence'

总觉得这里起名略蛋疼 = . = 一般用到前两个较多.

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class Post < ActiveRecord::Base
  include Elasticsearch::Model
  include Elasticsearch::Model::Callbacks

  # settings do
  #   mappings dynamic: 'false' do
  #     indexes :title, type: 'string', analyzer: 'ik_smart'
  #     indexes :keywords, type: 'string', analyzer: 'ik_smart'
  #     indexes :body, type: 'string', analyzer: 'ik_smart'
  #     indexes :user_name, type: 'string', analyzer: 'ik_smart'
  #   end
  # end

  # def as_indexed_json(options={})
  #   as_json(
  #     only: ['title', 'body', 'keywords'],
  #     methods: [:user_name]
  #   )
  # end
end

Elasticsearch::Model::Callbacks 这个模块主要是当 model 更新以后回调更新索引. 对于厂里的 CRM 来说, 因为是数据仓库, 更多是做一些查询, 分析之类的应用, 而不是主要应用于增删改查, 所以, 其实我们没有 include 这个模块. 手工执行一下 Post.import 基本工作就完成了.

也可以只 import 特定 scope 或者查询下面的记录.

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Post.import scope: 'published'
#
Post.import query: -> { where(user_id: user_id) }

title, keywords, body 是 posts 表的字段, user_name 是 Post 类的一个方法.

上面用了 settings 设置映射以后还要定义 as_indexed_json, 否则该方法来自 Elasticsearch::Model::Serializing 默认实现(只)会序列化所有原有字段(比如包括 created_at, updated_at 等). settings 设置也不会起作用.

mappings 方法的参数 dynamic: 'false' 是对文档新增 field 的处理, 默认为 true, 也就是会动态判断该 field 的类型, 并添加这个 field, 而设置为 false 的话, 如果有新的 field 被传进来, 则会被无视之. 不会改变文档的 _source. _source 仍然是只包含已经索引的整个 JSON 文档, 任何新来的 field 都不会被添加到映射, 也不会被搜索到.

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[5] pry(main)> Post.search('blahblahblah').records.all
  Post Search (11.9ms) {index: "posts", type: "post", q: "blahblahblah"}
  Post Load (0.2ms)  SELECT `posts`.* FROM `posts` WHERE 1=0
=> []
[6] pry(main)> Post.search('cool').records.all
  Post Search (12.8ms) {index: "posts", type: "post", q: "cool"}
  Post Load (0.4ms)  SELECT `posts`.* FROM `posts` WHERE `posts`.`id` IN (13, 108)
=> [#<Post:0x007f8819c2d690
  id: 13,
  title: "Peanut and Peach nut",
  body:
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[10] pry(main)> resp = Post.search('一张照片')
=> #<Elasticsearch::Model::Response::Response:0x007fcc13200008
@klass=[PROXY] Post (call 'Post.connection' to establish a connection),
@search=
  #<Elasticsearch::Model::Searching::SearchRequest:0x007fcc13200238
   @definition={:index=>"posts", :type=>"post", :q=>"一张照片"},
   @klass=[PROXY] Post (call 'Post.connection' to establish a connection),
   @options={}>>

[11] pry(main)> resp.records
=> #<Elasticsearch::Model::Response::Records:0x007fcc11719ca8
@klass=[PROXY] Post (call 'Post.connection' to establish a connection),
@response=
 #<Elasticsearch::Model::Response::Response:0x007fcc117c93b0
  @klass=[PROXY] Post (call 'Post.connection' to establish a connection),
  @records=#<Elasticsearch::Model::Response::Records:0x007fcc11719ca8 ...>,
  @search=
   #<Elasticsearch::Model::Searching::SearchRequest:0x007fcc117c8578
    @definition={:index=>"posts", :type=>"post", :q=>"一张照片"},
    @klass=[PROXY] Post (call 'Post.connection' to establish a connection),
    @options={}>>>
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[9] pry(main)> resp.records.first
  Post Load (0.8ms)  SELECT `posts`.* FROM `posts` WHERE `posts`.`id` IN (61, 4, 82, 15, 90, 72, 114, 112, 28, 17)
=> #<Post:0x007fcc18c23238
 id: 61,
 title: "让布列松看不顺眼的摄影师",
 body: "BlahBlahBlahBlah...........",
 user_id: 1,
 slug: "bdgh2Lyf4z3jF",
 created_at: Mon, 10 Feb 2015 12:51:04 CST +08:00,
 updated_at: Tue, 09 Aug 2015 08:00:07 CST +08:00,
 comments_count: 0,
 keywords: "Photo 摄影 布列松",
 popular: false>
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[12] pry(main)> resp.results
=> #<Elasticsearch::Model::Response::Results:0x007fcc11693568
@klass=[PROXY] Post (call 'Post.connection' to establish a connection),
@response=
  #<Elasticsearch::Model::Response::Response:0x007fcc117c93b0
   @klass=[PROXY] Post (call 'Post.connection' to establish a connection),
   @records=
    #<Elasticsearch::Model::Response::Records:0x007fcc11719ca8
     @klass=[PROXY] Post (call 'Post.connection' to establish a connection),
     @response=#<Elasticsearch::Model::Response::Response:0x007fcc117c93b0 ...>>,
   @results=#<Elasticsearch::Model::Response::Results:0x007fcc11693568 ...>,
   @search=
    #<Elasticsearch::Model::Searching::SearchRequest:0x007fcc117c8578
     @definition={:index=>"posts", :type=>"post", :q=>"一张照片"},
     @klass=[PROXY] Post (call 'Post.connection' to establish a connection),
     @options={}>>>

[8] pry(main)> resp.results.first
 Post Search (39.4ms) {index: "posts", type: "post", q: "一张照片"}
=> #<Elasticsearch::Model::Response::Result:0x007fcc18d44270
@result=
 {"_index"=>"posts",
  "_type"=>"post",
  "_id"=>"61",
  "_score"=>0.21295425,
  "_source"=>
   {"title"=>"让布列松看不顺眼的摄影师",
    "body"=> "BlahBlahBlahBlah...........",
    "keywords"=>"Photo 摄影 布列松",
    "user_name"=>"XguoX"}}>

results 返回的是对应的 JSON, 而用 records 返回的则是经过数据库查询的记录. 毫无疑问, 使用 results 的话性能会好一些.

查看某个 model, 比如 Post 的映射配置 curl 'http://localhost:9200/posts?pretty'

返回结果

对比一下, 同样的关键词使用 ik, ik_smart 以及使用标准 anlayser 之间分词区别.

索引文档之间的关联关系, 假设 Post has_many Comments. 可以像下面这样进行序列化:

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def as_indexed_json(options={})
  as_json(
    only: ['title', 'body', 'keywords'],
    methods: [:user_name],
    include: {comments: {only: :content}}
  )
end
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[19] pry(main)> Post.last.__elasticsearch__.as_indexed_json
  Post Load (0.3ms)  SELECT  `posts`.* FROM `posts`  ORDER BY `posts`.`id` DESC LIMIT 1
  User Load (0.2ms)  SELECT  `users`.* FROM `users` WHERE `users`.`id` = 1 LIMIT 1
  Comment Load (0.2ms)  SELECT `comments`.* FROM `comments` WHERE `comments`.`post_id` = 61
=> {"title"=>"让布列松看不顺眼的摄影师",
 "body"=>"blahblahblah.......",
 "keywords"=>"Photo 摄影 布列松",
 "user_name"=>"XguoX",
 "comments"=>[{"content"=>"Here is 评论..."}]}

更改了映射设置以后要更新索引,

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Post.__elasticsearch__.create_index! force: true
Post.__elasticsearch__.refresh_index!

手动更新单个文档

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[8] pry(main)> Post.first.__elasticsearch__.index_document
  Post Load (0.4ms)  SELECT  `posts`.* FROM `posts`  ORDER BY `posts`.`id` ASC LIMIT 1
  User Load (0.4ms)  SELECT  `users`.* FROM `users` WHERE `users`.`id` = 2 LIMIT 1
=> {"_index"=>"posts", "_type"=>"post", "_id"=>"1", "_version"=>2, "created"=>false}

Elasticsearch 开箱笔记

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Upgrade Elasticsearch to 2.3

Elasticsearch Scroll (Ruby)

Elasticsearch analysis & 自定义 analyzers

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