一、Term Suggester

1、概念

搜索推荐或者搜索建议，不光是根据用户输入的文本，找到对应的内容，还要根据用户输入的文本进行一定的纠错、改错。

搜索引擎中这样的功能，在Elasticsearch中是通过Suggester API实现的，它的原理是通过将输入的文本分解为Token，然后在索引的字典里查找相似的Term并返回。

"suggest": {
    "term-suggester": {
      "text": "汉包",
      "term": {
        "suggest_mode": "title_completion",
        "field": "body"
      }
    }
  }

• Suggester就是一种特殊类型的搜索，其中“text”是调用时候提供的文本，也就是用户页面上输入的文本
• 用户输入的文本如果是一个错误的拼写，会到指定的字段“body”上搜索，当无法搜索的结果时，返回建议的词。

2、案例

数据准备

DELETE articles

POST articles/_bulk
{ "index" : { } }
{ "body": "lucene is very cool"}
{ "index" : { } }
{ "body": "Elasticsearch builds on top of lucene"}
{ "index" : { } }
{ "body": "Elasticsearch rocks"}
{ "index" : { } }
{ "body": "elastic is the company behind ELK stack"}
{ "index" : { } }
{ "body": "Elk stack rocks"}
{ "index" : {} }
{  "body": "elasticsearch is rock solid"}

查询

POST /articles/_search
{
  "size": 1,
  "query": {
    "match": {
      "body": "lucen rock"
    }
  },
  "suggest": {
    "term-suggestion": {
      "text": "lucen rock",
      "term": {
        "suggest_mode": "missing",
        "field": "body"
      }
    }
  }
}

suggest_mode有如下几种：

• Missing - 如索引中已经存在，就不提供建议
• Popular - 推荐出现频率更加高的词
• Always - 无论是否存在，都提供建议

{
  "took" : 20,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 1,
      "relation" : "eq"
    },
    "max_score" : 1.5904956,
    "hits" : [
      {
        "_index" : "articles",
        "_type" : "_doc",
        "_id" : "QPlkjogB1hYm8koHEygM",
        "_score" : 1.5904956,
        "_source" : {
          "body" : "elasticsearch is rock solid"
        }
      }
    ]
  },
  "suggest" : {
    "term-suggestion" : [
      {
        "text" : "lucen",
        "offset" : 0,
        "length" : 5,
        "options" : [
          {
            "text" : "lucene",
            "score" : 0.8,
            "freq" : 2
          }
        ]
      },
      {
        "text" : "rock",
        "offset" : 6,
        "length" : 4,
        "options" : [ ]
      }
    ]
  }
}

由服务端返回的结果可以发现，lucen给出了推荐的内容lucene，而rock并没有给出推荐，因为rock在搜索中已经存在了。

popular

POST /articles/_search
{

  "suggest": {
    "term-suggestion": {
      "text": "lucen rock",
      "term": {
        "suggest_mode": "popular",
        "field": "body"
      }
    }
  }
}

{
  "took" : 32,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 0,
      "relation" : "eq"
    },
    "max_score" : null,
    "hits" : [ ]
  },
  "suggest" : {
    "term-suggestion" : [
      {
        "text" : "lucen",
        "offset" : 0,
        "length" : 5,
        "options" : [
          {
            "text" : "lucene",
            "score" : 0.8,
            "freq" : 2
          }
        ]
      },
      {
        "text" : "rock",
        "offset" : 6,
        "length" : 4,
        "options" : [
          {
            "text" : "rocks",
            "score" : 0.75,
            "freq" : 2
          }
        ]
      }
    ]
  }
}

由于是popular，所以推荐出现频率更加高的词，除了lucen进行了推荐，rock推荐了出现频率更高的rocks。

三、Phrase Suggester

Phrase Suggester在Term Suggester上增加了一些额外的逻辑：

• Suggest Mode: missing、popular、always
• Max Erros：最多可以拼错的Terms数
• Confidence：限制返回结果数

POST /articles/_search
{
  "suggest": {
    "my-suggestion": {
      "text": "lucne and elasticsear rock hello world ",
      "phrase": {
        "field": "body",
        "max_errors":2,
        "confidence":0,
        "direct_generator":[{
          "field":"body",
          "suggest_mode":"always"
        }],
        "highlight": {
          "pre_tag": "<em>",
          "post_tag": "</em>"
        }
      }
    }
  }
}

参考

Elasticsearch 核心技术与实战 (opens new window)