search（7）- elastic4s-search-filter模式

现在我们可以开始探讨ES的核心环节：搜索search了。search又分filter,query两种模式。filter模式即筛选模式：将符合筛选条件的记录作为结果找出来。query模式则分两个步骤：先筛选，然后对每条符合条件记录进行相似度计算。就是多了个评分过程。如果我们首先要实现传统数据库的查询功能的话，那么用filter模式就足够了。filter模式同样可以利用搜索引擎的分词功能产生高质量的查询结果，而且filter是可以进缓存的，执行起来效率更高。这些功能数据库管理系统是无法达到的。ES的filter模式是在bool查询框架下实现的，如下：

GET /_search
{
  "query": {
    "bool": {
      "filter": [
        { "term":  { "status": "published" }},
        { "range": { "publish_date": { "gte": "2015-01-01" }}}
      ]
    }
  }
}

下面是一个最简单的示范：

  val filterTerm = search("bank")
    .query(
      boolQuery().filter(termQuery("city.keyword","Brogan")))

产生的请求json如下：

POST /bank/_search
{
  "query":{
    "bool":{
      "filter":[
       {
        "term":{"city.keyword":{"value":"Brogan"}}
       }
      ]
    }
  }
}

先说明一下这个查询请求：这是一个词条查询termQuery，要求条件完全匹配，包括大小写，肯定无法用经过分词器分析过的字段，所以用city.keyword。

返回查询结果json：

{
  "took" : 1,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 1,
      "relation" : "eq"
    },
    "max_score" : 0.0,
    "hits" : [
      {
        "_index" : "bank",
        "_type" : "_doc",
        "_id" : "1",
        "_score" : 0.0,
        "_source" : {
          "account_number" : 1,
          "balance" : 39225,
          "firstname" : "Amber",
          "lastname" : "Duke",
          "age" : 32,
          "gender" : "M",
          "address" : "880 Holmes Lane",
          "employer" : "Pyrami",
          "email" : "amberduke@pyrami.com",
          "city" : "Brogan",
          "state" : "IL"
        }
      }
    ]
  }
}

我们来看看elasitic4s是怎样表达上面json结果的：首先，返回的类型是 Reponse[SearchResponse]。Response类定义如下：

sealed trait Response[+U] {
  def status: Int                  // the http status code of the response
  def body: Option[String]         // the http response body if the response included one
  def headers: Map[String, String] // any http headers included in the response
  def result: U                    // returns the marshalled response U or throws an exception
  def error: ElasticError          // returns the error or throw an exception
  def isError: Boolean             // returns true if this is an error response
  final def isSuccess: Boolean = !isError // returns true if this is a success
  def map[V](f: U => V): Response[V]
  def flatMap[V](f: U => Response[V]): Response[V]
  final def fold[V](ifError: => V)(f: U => V): V = if (isError) ifError else f(result)
  final def fold[V](onError: RequestFailure => V, onSuccess: U => V): V = this match {
    case failure: RequestFailure => onError(failure)
    case RequestSuccess(_, _, _, result) => onSuccess(result)
  }
  final def foreach[V](f: U => V): Unit          = if (!isError) f(result)
  final def toOption: Option[U] = if (isError) None else Some(result)
}

Response[+U]是个高阶类，如果把U替换成SearchResponse, 那么返回的结果值可以用def result: SearchResponse来获取。status代表标准HTTP返回状态，isError,isSuccess代表执行情况，error是确切的异常消息。返回结果的头部信息在headers内。我们再看看这个SearchResponse类的定义：

case class SearchResponse(took: Long,
                          @JsonProperty("timed_out") isTimedOut: Boolean,
                          @JsonProperty("terminated_early") isTerminatedEarly: Boolean,
                          private val suggest: Map[String, Seq[SuggestionResult]],
                          @JsonProperty("_shards") private val _shards: Shards,
                          @JsonProperty("_scroll_id") scrollId: Option[String],
                          @JsonProperty("aggregations") private val _aggregationsAsMap: Map[String, Any],
                          hits: SearchHits) {...}
case class SearchHits(total: Total,
                      @JsonProperty("max_score") maxScore: Double,
                      hits: Array[SearchHit]) {
  def size: Long = hits.length
  def isEmpty: Boolean = hits.isEmpty
  def nonEmpty: Boolean = hits.nonEmpty
}
case class SearchHit(@JsonProperty("_id") id: String,
                     @JsonProperty("_index") index: String,
                     @JsonProperty("_type") `type`: String,
                     @JsonProperty("_version") version: Long,
                     @JsonProperty("_seq_no") seqNo: Long,
                     @JsonProperty("_primary_term") primaryTerm: Long,
                     @JsonProperty("_score") score: Float,
                     @JsonProperty("_parent") parent: Option[String],
                     @JsonProperty("_shard") shard: Option[String],
                     @JsonProperty("_node") node: Option[String],
                     @JsonProperty("_routing") routing: Option[String],
                     @JsonProperty("_explanation") explanation: Option[Explanation],
                     @JsonProperty("sort") sort: Option[Seq[AnyRef]],
                     private val _source: Map[String, AnyRef],
                     fields: Map[String, AnyRef],
                     @JsonProperty("highlight") private val _highlight: Option[Map[String, Seq[String]]],
                     private val inner_hits: Map[String, Map[String, Any]],
                     @JsonProperty("matched_queries") matchedQueries: Option[Set[String]])
  extends Hit {...}

返回结果的重要部分如 _score, _source,fields都在SearchHit里。完整的返回结果处理示范如下：

 val filterTerm  = client.execute(search("bank")
    .query(
      boolQuery().filter(termQuery("city.keyword","Brogan")))).await
  if (filterTerm.isSuccess) {
    if (filterTerm.result.nonEmpty)
      filterTerm.result.hits.hits.foreach {hit => println(hit.sourceAsMap)}
  } else println(s"Error: ${filterTerm.error.reason}")

传统查询方式中前缀查询用的比较多：

POST /bank/_search
{
  "query":{
    "bool":{
      "filter":[
       {
        "prefix":{"city.keyword":{"value":"Bro"}}
       }
      ]
    }
  }
}
  val filterPrifix  = client.execute(search("bank")
    .query(
      boolQuery().filter(prefixQuery("city.keyword","Bro")))
      .sourceInclude("address","city","state")
  ).await
  if (filterPrifix.isSuccess) {
    if (filterPrifix.result.nonEmpty)
      filterPrifix.result.hits.hits.foreach {hit => println(hit.sourceAsMap)}
  } else println(s"Error: ${filterPrifix.error.reason}")
....
Map(address -> 880 Holmes Lane, city -> Brogan, state -> IL)
Map(address -> 810 Nostrand Avenue, city -> Brooktrails, state -> GA)
Map(address -> 295 Whitty Lane, city -> Broadlands, state -> VT)
Map(address -> 511 Heath Place, city -> Brookfield, state -> OK)
Map(address -> 918 Bridge Street, city -> Brownlee, state -> HI)
Map(address -> 806 Pierrepont Place, city -> Brownsville, state -> MI)

正则表达式查询也有：

POST /bank/_search
{
  "query":{
    "bool":{
      "filter":[
       {
        "regexp":{"address.keyword":{"value":".*bridge.*"}}
       }
      ]
    }
  }
}
  val filterRegex  = client.execute(search("bank")
    .query(
      boolQuery().filter(regexQuery("address.keyword",".*bridge.*")))
    .sourceInclude("address","city","state")
  ).await
  if (filterRegex.isSuccess) {
    if (filterRegex.result.nonEmpty)
      filterRegex.result.hits.hits.foreach {hit => println(hit.sourceAsMap)}
  } else println(s"Error: ${filterRegex.error.reason}")
....
Map(address -> 384 Bainbridge Street, city -> Elizaville, state -> MS)
Map(address -> 721 Cambridge Place, city -> Efland, state -> ID)

当然，ES用bool查询来实现复合式查询，我们可以把一个bool查询放进filter框架，如下：

POST /bank/_search
{
  "query":{
    "bool":{
      "filter":[
       {
        "regexp":{"address.keyword":{"value":".*bridge.*"}}
       },
       {
         "bool": {
         "must": [
           { "match" : {"lastname" : "lane"}}
           ]
         }
       }
      ]
    }
  }
}

elastic4s QueryDSL 语句和返回结果如下：

  val filterBool  = client.execute(search("bank")
    .query(
      boolQuery().filter(regexQuery("address.keyword",".*bridge.*"),
        boolQuery().must(matchQuery("lastname","lane"))))
    .sourceInclude("lastname","address","city","state")
  ).await
  if (filterBool.isSuccess) {
    if (filterBool.result.nonEmpty)
      filterBool.result.hits.hits.foreach {hit => println(s"score: ${hit.score}, ${hit.sourceAsMap}")}
  } else println(s"Error: ${filterBool.error.reason}")
...
score: 0.0, Map(address -> 384 Bainbridge Street, city -> Elizaville, state -> MS, lastname -> Lane)

score: 0.0 ，说明filter不会进行评分。可能执行效率会有所提高吧。

本文链接：https://www.cnblogs.com/tiger-xc/p/12782333.html

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