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search(14)- elastic4s-统计范围:global, filter,post-filter bucket
来源:cnblogs  作者:雪川大虫  时间:2020/5/18 8:50:32  对本文有异议

  聚合一般作用在query范围内。不带query的aggregation请求实际上是在match_all{}查询范围内进行统计的:

GET /cartxns/_search
{
  "aggs": {
    "all_colors": {
      "terms": {"field" : "color.keyword"}
    }
  }
 }
}

GET /cartxns/_search
{
  "query": {
    "match_all": {}
  }, 
  "aggs": {
    "all_colors": {
      "terms": {"field" : "color.keyword"}
    }
  }
 }
}

上面这两个请求结果相同:

  "aggregations" : {
    "all_colors" : {
      "doc_count_error_upper_bound" : 0,
      "sum_other_doc_count" : 0,
      "buckets" : [
        {
          "key" : "red",
          "doc_count" : 4
        },
        {
          "key" : "blue",
          "doc_count" : 2
        },
        {
          "key" : "green",
          "doc_count" : 2
        }
      ]
    }
  }

虽然很多时候我们都希望在query作用域下进行统计,但也会碰到需要统计不含任何query条件的汇总数。比如在统计某个车款平价售价的同时又需要知道全部车款的平均售价。这里全部车款平价售价就是一种global bucket统计:

GET /cartxns/_search
{
  "query" : {
    "match" : {"make.keyword": "ford"}
  }
  , "aggs": {
    "avg_ford": {
      "avg": {
        "field": "price"
      }
    },
    "avg_all" : {
      "global": {},
      "aggs": {
        "avg_price": {
          "avg": {"field": "price"}
        }
      }
    }
    
  }

}

搜索结果和聚合结果如下:

 "hits" : {
    "total" : {
      "value" : 2,
      "relation" : "eq"
    },
    "max_score" : 1.2809337,
    "hits" : [
      {
        "_index" : "cartxns",
        "_type" : "_doc",
        "_id" : "NGVXAnIBSDa1Wo5UqLc3",
        "_score" : 1.2809337,
        "_source" : {
          "price" : 30000,
          "color" : "green",
          "make" : "ford",
          "sold" : "2014-05-18"
        }
      },
      {
        "_index" : "cartxns",
        "_type" : "_doc",
        "_id" : "OWVYAnIBSDa1Wo5UTrf8",
        "_score" : 1.2809337,
        "_source" : {
          "price" : 25000,
          "color" : "blue",
          "make" : "ford",
          "sold" : "2014-02-12"
        }
      }
    ]
  },
  "aggregations" : {
    "avg_all" : {
      "doc_count" : 8,
      "avg_price" : {
        "value" : 26500.0
      }
    },
    "avg_ford" : {
      "value" : 27500.0
    }
  }

用elastic4s来表达:

 val aggGlob = search("cartxns").query(
    matchQuery("make.keyword","ford")
  ).aggregations(
    avgAggregation("single_avg").field("price"),
    globalAggregation("all_avg").subaggs(
        avgAggregation("avg_price").field("price")
    )
  )
  println(aggGlob.show)

  val globResult = client.execute(aggGlob).await

  if (globResult.isSuccess) {
    val gavg = globResult.result.aggregations.global("all_avg").avg("avg_price")
    val savg = globResult.result.aggregations.avg("single_avg")
    println(s"${savg.value},${gavg.value}")
    globResult.result.hits.hits.foreach(h => println(s"${h.sourceAsMap}"))
  } else println(s"error: ${globResult.error.causedBy.getOrElse("unknown")}")

...

POST:/cartxns/_search?
StringEntity({"query":{"match":{"make.keyword":{"query":"ford"}}},"aggs":{"single_avg":{"avg":{"field":"price"}},"all_avg":{"global":{},"aggs":{"avg_price":{"avg":{"field":"price"}}}}}},Some(application/json))
27500.0,26500.0
Map(price -> 30000, color -> green, make -> ford, sold -> 2014-05-18)
Map(price -> 25000, color -> blue, make -> ford, sold -> 2014-02-12)

filter-bucket的作用是:在query结果内再进行筛选后统计。比如:查询所有honda车款交易,但只统计honda某个月销售: 

GET /cartxns/_search
{
    "query": {
      "match": {
        "make.keyword": "honda"
      }
    },
    "aggs": {
      "sales_this_month": {
        "filter": {
          "range" : {"sold" : { "from" : "2014-10-01", "to" : "2014-11-01" }}
        },
        "aggs": {
          "month_total": {
            "sum": {"field": "price"}
          }
        }
      }
    }
}

首先,查询结果应该不受影响。同时还得到查询结果车款某个月的销售额:

 "hits" : {
    "total" : {
      "value" : 3,
      "relation" : "eq"
    },
    "max_score" : 0.9444616,
    "hits" : [
      {
        "_index" : "cartxns",
        "_type" : "_doc",
        "_id" : "MmVXAnIBSDa1Wo5UqLc3",
        "_score" : 0.9444616,
        "_source" : {
          "price" : 10000,
          "color" : "red",
          "make" : "honda",
          "sold" : "2014-10-28"
        }
      },
      {
        "_index" : "cartxns",
        "_type" : "_doc",
        "_id" : "M2VXAnIBSDa1Wo5UqLc3",
        "_score" : 0.9444616,
        "_source" : {
          "price" : 20000,
          "color" : "red",
          "make" : "honda",
          "sold" : "2014-11-05"
        }
      },
      {
        "_index" : "cartxns",
        "_type" : "_doc",
        "_id" : "N2VXAnIBSDa1Wo5UqLc3",
        "_score" : 0.9444616,
        "_source" : {
          "price" : 20000,
          "color" : "red",
          "make" : "honda",
          "sold" : "2014-11-05"
        }
      }
    ]
  },
  "aggregations" : {
    "sales_this_month" : {
      "doc_count" : 1,
      "month_total" : {
        "value" : 10000.0
      }
    }
  }

elastic4s示范如下: 

  val aggfilter = search("cartxns").query(
    matchQuery("make.keyword","honda")
  ).aggregations(
    filterAgg("sales_the_month",rangeQuery("sold").gte("2014-10-01").lte("2014-11-01"))
    .subaggs(sumAggregation("monthly_sales").field("price"))
  )
  println(aggfilter.show)

  val filterResult = client.execute(aggfilter).await

  if (filterResult.isSuccess) {
    val ms = filterResult.result.aggregations.filter("sales_the_month")
              .sum("monthly_sales").value
    println(s"${ms}")
    filterResult.result.hits.hits.foreach(h => println(s"${h.sourceAsMap}"))
  } else println(s"error: ${filterResult.error.causedBy.getOrElse("unknown")}")

...

POST:/cartxns/_search?
StringEntity({"query":{"match":{"make.keyword":{"query":"honda"}}},"aggs":{"sales_the_month":{"filter":{"range":{"sold":{"gte":"2014-10-01","lte":"2014-11-01"}}},"aggs":{"monthly_sales":{"sum":{"field":"price"}}}}}},Some(application/json))
10000.0
Map(price -> 10000, color -> red, make -> honda, sold -> 2014-10-28)
Map(price -> 20000, color -> red, make -> honda, sold -> 2014-11-05)
Map(price -> 20000, color -> red, make -> honda, sold -> 2014-11-05)

最后一个是post-filter。post-filter同样是对query结果的筛选,但是在完成了整个query后对结果的筛选。也就是说如果query还涉及到聚合,那么聚合不受筛选影响:

GET /cartxns/_search
{
  "query": {
    "match": {
      "make.keyword": "ford"
    }
  },
  "post_filter": {
    "match" : {
      "color.keyword" : "blue"
    }
  }
  ,"aggs": {
    "colors": {
      "terms": {
        "field": "color.keyword",
        "size": 10
      }
    }
  }
}

查询和聚合结果如下:

  "hits" : {
    "total" : {
      "value" : 1,
      "relation" : "eq"
    },
    "max_score" : 1.2809337,
    "hits" : [
      {
        "_index" : "cartxns",
        "_type" : "_doc",
        "_id" : "OWVYAnIBSDa1Wo5UTrf8",
        "_score" : 1.2809337,
        "_source" : {
          "price" : 25000,
          "color" : "blue",
          "make" : "ford",
          "sold" : "2014-02-12"
        }
      }
    ]
  },
  "aggregations" : {
    "colors" : {
      "doc_count_error_upper_bound" : 0,
      "sum_other_doc_count" : 0,
      "buckets" : [
        {
          "key" : "blue",
          "doc_count" : 1
        },
        {
          "key" : "green",
          "doc_count" : 1
        }
      ]
    }
  }
}

可以看到:查询结果显示了经过post-filter筛选的结果,但聚合并没有受到filter影响。

elastic4s示范代码:

 val aggPost = search("cartxns").query(
    matchQuery("make.keyword","ford")
  ).postFilter(matchQuery("color.keyword","blue"))
      .aggregations(
        termsAgg("colors","color.keyword")
      )

  println(aggPost.show)

  val postResult = client.execute(aggPost).await

  if (postResult.isSuccess) {
    postResult.result.hits.hits.foreach(h => println(s"${h.sourceAsMap}"))
    postResult.result.aggregations.terms("colors").buckets
      .foreach(b => println(s"${b.key},${b.docCount}"))
  } else println(s"error: ${postResult.error.causedBy.getOrElse("unknown")}")

...

POST:/cartxns/_search?
StringEntity({"query":{"match":{"make.keyword":{"query":"ford"}}},"post_filter":{"match":{"color.keyword":{"query":"blue"}}},"aggs":{"colors":{"terms":{"field":"color.keyword"}}}},Some(application/json))
Map(price -> 25000, color -> blue, make -> ford, sold -> 2014-02-12)
blue,1
green,1

 

原文链接:http://www.cnblogs.com/tiger-xc/p/12902536.html

 友情链接: NPS  问卷模板