ElasticSearch聚合查询Restful语法和JavaApi详解（基于ES7.6）

作者:鱼仔
博客首页: https://codeease.top
公众号:Java鱼仔

# （一）概述

在前面关于ES的一系列文章中，已经介绍了ES的概念、常用操作、JavaAPI以及实际的一个小demo，但是在真实的应用场景中，还有可能会有更高阶的一些用法，今天主要介绍两种相对来说会更难一些的操作，聚合查询。该文档基于ElasticSearch7.6，将介绍restful查询语法以及JavaApi。

阅读本文需要你有ElasticSearch的基础。

# （二）前期数据准备

这里准备了包含姓名、年龄、教室、性别和成绩五个字段的数据

PUT /test4
{
    "mappings" : {
      "properties" : {
        "name" : {
          "type" : "text"
        },
        "age":{
          "type": "integer"
        },
        "classroom":{
          "type": "keyword"
        },
        "gender":{
          "type": "keyword"
        },
        "grade":{
          "type": "integer"
        }
      }
    }
}

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22

PUT /test4/_bulk
{"index": {"_id": 1}}
{"name":"张三","age":18,"classroom":"1","gender":"男","grade":80}
{"index": {"_id": 2}}
{"name":"李四","age":20,"classroom":"2","gender":"男","grade":60}
{"index": {"_id": 3}}
{"name":"王五","age":20,"classroom":"2","gender":"女","grade":70}
{"index": {"_id": 4}}
{"name":"赵六","age":19,"classroom":"1","gender":"女","grade":90}
{"index": {"_id": 5}}
{"name":"毛七","age":20,"classroom":"1","gender":"男","grade":90}

1
2
3
4
5
6
7
8
9
10
11

# （三）聚合查询

ES中的聚合操作提供了强大的分组及数理计算的能力，ES中聚合从大体上可以分为四种方式：

1、Metrics Aggregation 提供了诸如Max，Min，Avg的数值计算能力

2、Bucket Aggregation 提供了分桶的能力，简单来讲就是将一类相同的数据聚合到一起

3、Pipeline Aggregation 管道聚合，对其他聚合进行二次聚合

4、Matrix Aggregation 对多个字段进行操作并返回矩阵结果

ES官网提供了全部聚合查询文档，这篇文章将介绍常用的几种聚合查询的语法以及JavaApi：

https://www.elastic.co/guide/en/elasticsearch/client/java-rest/7.6/java-rest-high-aggregation-builders.html#_metrics_aggregations

# （四）Metrics Aggregation

# 4.1 AVG

avg用于计算聚合文档中提取的数值的平均值，restful查询语法如下：

POST /test4/_search
{
  "aggs": {
    "avg_grade": {
      "avg": {
        "field": "grade"
      }
    }
  }
}

1
2
3
4
5
6
7
8
9
10

查询得到的结果如下:

接着是JavaApi，核心在于使用AggregationBuilders的avg方法，第七行代码对应于上面的操作。

@Test
public void testAvg() throws Exception {
    //封装了获取RestHighLevelClient的方法
    RestHighLevelClient client=ElasticSearchClient.getClient();
    SearchRequest request = new SearchRequest("test4");
    SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
    searchSourceBuilder.aggregation(AggregationBuilders.avg("agg_grade").field("grade")).size(0);
    request.source(searchSourceBuilder);
    SearchResponse search = client.search(request, RequestOptions.DEFAULT);
    //注意这里要把Aggregation类型转化为ParsedAvg类型
    ParsedAvg aggregation = search.getAggregations().get("agg_grade");
    System.out.println(aggregation.getValue()); //返回78.0
}

1
2
3
4
5
6
7
8
9
10
11
12
13

接下来就直接贴代码了

# 4.2 Min

获取聚合数据的最小值：

POST /test4/_search
{
  "aggs": {
    "min_grade": {
      "min": {
        "field": "grade"
      }
    }
  }
}

1
2
3
4
5
6
7
8
9
10

@Test
public void testMin() throws Exception {
    //封装了获取RestHighLevelClient的方法
    RestHighLevelClient client=ElasticSearchClient.getClient();
    SearchRequest request = new SearchRequest("test4");
    SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
    searchSourceBuilder.aggregation(AggregationBuilders.min("min_grade").field("grade")).size(0);
    request.source(searchSourceBuilder);
    SearchResponse search = client.search(request, RequestOptions.DEFAULT);
    ParsedMin aggregation = search.getAggregations().get("min_grade");
    System.out.println(aggregation.getValue());
}

1
2
3
4
5
6
7
8
9
10
11
12

# 4.3 Max

获取聚合数据的最大值：

POST /test4/_search
{
  "aggs": {
    "max_grade": {
      "max": {
        "field": "grade"
      }
    }
  }
}

1
2
3
4
5
6
7
8
9
10

@Test
public void testMax() throws Exception {
    //封装了获取RestHighLevelClient的方法
    RestHighLevelClient client=ElasticSearchClient.getClient();
    SearchRequest request = new SearchRequest("test4");
    SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
    searchSourceBuilder.aggregation(AggregationBuilders.max("max_grade").field("grade")).size(0);
    request.source(searchSourceBuilder);
    SearchResponse search = client.search(request, RequestOptions.DEFAULT);
    ParsedMax aggregation = search.getAggregations().get("max_grade");
    System.out.println(aggregation.getValue());
}

1
2
3
4
5
6
7
8
9
10
11
12

# 4.4 Sum

获取聚合数据的和：

POST /test4/_search
{
  "aggs": {
    "sum_grade": {
      "sum": {
        "field": "grade"
      }
    }
  }
}

1
2
3
4
5
6
7
8
9
10

@Test
public void testSum() throws Exception {
    //封装了获取RestHighLevelClient的方法
    RestHighLevelClient client=ElasticSearchClient.getClient();
    SearchRequest request = new SearchRequest("test4");
    SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
    searchSourceBuilder.aggregation(AggregationBuilders.sum("sum_grade").field("grade")).size(0);
    request.source(searchSourceBuilder);
    SearchResponse search = client.search(request, RequestOptions.DEFAULT);
    ParsedSum aggregation = search.getAggregations().get("sum_grade");
    System.out.println(aggregation.getValue());
}

1
2
3
4
5
6
7
8
9
10
11
12

# 4.5 Stats

stats集成了上面的所有计算操作。

POST /test4/_search
{
  "aggs": {
    "stats_grade": {
      "stats": {
        "field": "grade"
      }
    }
  }
}

1
2
3
4
5
6
7
8
9
10

@Test
public void testStats() throws Exception {
    //封装了获取RestHighLevelClient的方法
    RestHighLevelClient client=ElasticSearchClient.getClient();
    SearchRequest request = new SearchRequest("test4");
    SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
    searchSourceBuilder.aggregation(AggregationBuilders.stats("sum_grade").field("grade")).size(0);
    request.source(searchSourceBuilder);
    SearchResponse search = client.search(request, RequestOptions.DEFAULT);
    ParsedStats aggregation = search.getAggregations().get("sum_grade");
    System.out.println(aggregation.getMax());
    System.out.println(aggregation.getAvg());
    System.out.println(aggregation.getCount());
    System.out.println(aggregation.getMin());
    System.out.println(aggregation.getSum());
}

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16

# （五）Bucket Aggregation

桶聚合是按照某个字段将同类型的数据聚合为一类，最常用对桶聚合就是terms聚合了。

# 5.1 terms

terms查询类似于group by，返回查询字段分组后的值以及数量，比如我对classroom字段terms查询

POST /test4/_search
{
  "aggs": {
    "classroom_term": {
      "terms": {
        "field": "classroom"
      }
    }
  }
}

1
2
3
4
5
6
7
8
9
10

返回值就是classroom的分组后的值以及每个组的数量：classroom是1的有3条记录，classroom是2的有2条记录

"aggregations" : {
    "classroom_term" : {
      "doc_count_error_upper_bound" : 0,
      "sum_other_doc_count" : 0,
      "buckets" : [
        {
          "key" : "1",
          "doc_count" : 3
        },
        {
          "key" : "2",
          "doc_count" : 2
        }
      ]
    }

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15

我们也可以对多个字段进行terms分组，比如我现在对classroom和gender两个字段进行分组：

POST /test4/_search
{
  "aggs": {
    "classroom_term": {
      "terms": {
        "field": "classroom"
      },
      "aggs": {
        "gender": {
          "terms": {
            "field": "gender"
          }
        }
      }
    }
  }
}

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17

最后对返回值就是classroom和gender分组后的值和数量：

classroom是1，gender是男有两条；

classroom是1，gender是女有一条；

classroom是2，gender是男有一条；

classroom是2，gender是女有一条；

"aggregations" : {
    "classroom_term" : {
      "doc_count_error_upper_bound" : 0,
      "sum_other_doc_count" : 0,
      "buckets" : [
        {
          "key" : "1",
          "doc_count" : 3,
          "gender" : {
            "doc_count_error_upper_bound" : 0,
            "sum_other_doc_count" : 0,
            "buckets" : [
              {
                "key" : "男",
                "doc_count" : 2
              },
              {
                "key" : "女",
                "doc_count" : 1
              }
            ]
          }
        },
        {
          "key" : "2",
          "doc_count" : 2,
          "gender" : {
            "doc_count_error_upper_bound" : 0,
            "sum_other_doc_count" : 0,
            "buckets" : [
              {
                "key" : "女",
                "doc_count" : 1
              },
              {
                "key" : "男",
                "doc_count" : 1
              }
            ]
          }
        }
      ]
    }

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43

对应的JavaApi使用如下：

@Test
public void testTerms() throws Exception {
    //封装了获取RestHighLevelClient的方法
    RestHighLevelClient client=ElasticSearchClient.getClient();
    SearchRequest request = new SearchRequest("test4");
    SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
    searchSourceBuilder.aggregation(AggregationBuilders.terms("classroom_term").field("classroom")
                        .subAggregation(AggregationBuilders.terms("gender").field("gender")));
    request.source(searchSourceBuilder);
    SearchResponse search = client.search(request, RequestOptions.DEFAULT);
    //获取数据时首先对classroom分桶，再对gender分桶
    Terms classroomTerm = search.getAggregations().get("classroom_term");
    for(Terms.Bucket classroomBucket:classroomTerm.getBuckets()){
        Terms genderTerm=classroomBucket.getAggregations().get("gender");
        for (Terms.Bucket genderBucket:genderTerm.getBuckets()){
            System.out.println("classRoom:"+classroomBucket.getKeyAsString()+"gender:"+genderBucket.getKeyAsString()+"count:"+genderBucket.getDocCount());
        }
    }
}

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19

这里比较难理解对是获取数据时的处理，聚合查询时有个桶的概念，在获取数据时需要遍历获取桶，以上面的代码为例，先获取到classroom的桶，再遍历classroom的桶获取gender的桶，从桶中获取到具体的内容。看下图：

# 5.2 range

range查询可以统计出每个数据区间内的数量：比如我要统计分数为*～70，70～85，80～*的数据，就可以通过下面的方式：

POST /test4/_search
{
  "aggs": {
    "grade_range": {
      "range": {
        "field": "grade",
        "ranges": [
          {"to":70},
          {"from":70,"to":85},
          {"from":85}
        ]
      }
    }
  }
}

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15

JavaAPI如下：

@Test
public void testRange() throws Exception {
    //封装了获取RestHighLevelClient的方法
    RestHighLevelClient client=ElasticSearchClient.getClient();
    SearchRequest request = new SearchRequest("test4");
    SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
    searchSourceBuilder.aggregation(AggregationBuilders.range("grade_range").field("grade")
                                    .addUnboundedTo(70).addRange(70,85).addUnboundedFrom(85));
    request.source(searchSourceBuilder);
    SearchResponse search = client.search(request, RequestOptions.DEFAULT);
    //获取数据时首先对classroom分桶，再对gender分桶
    Range gradeRange = search.getAggregations().get("grade_range");
    for(Range.Bucket gradeBucket:gradeRange.getBuckets()){
        System.out.println("key:"+gradeBucket.getKey()+"count:"+gradeBucket.getDocCount());
    }
}

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16

# （六）总结

至此，关于ES的聚合查询一些常用方法就讲解完毕了，ES提供的其他更多方法可以直接在官方文档中看，讲解的十分详细。我是鱼仔，我们下期再见！

上次更新: 2024/07/31, 14:01:52

← 如何在自己的项目中引入ElasticSearch搜索引擎？深入了解ElasticSearch的Nested数据类型→