Elasticsearch：使用 Java 来对 Elasticsearch 索引进行聚合

Posted 2021-10-22 中国社区官方博客

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聚合是 Elasticsearch 中一个强大的工具，它允许你计算字段的最小值、最大值、平均值等等。在我之前的文章中，我许多介绍 Elasticsearch 聚合的文章，比如 Elasticsearch: aggregation 介绍。更多关于 aggregation 的介绍，请参阅 “Elastic：菜鸟上手指南” 文章中的 “Aggregations” 章节。

有不同类型的聚合，每一种都有自己的目的。本章将详细讨论它们。在今天的例子中，我将简单地介绍像我们在 SQL 中的那些简单的聚合：

在这里，我就不详述每个聚合的具体意义了。我们着重于介绍如何使用 Jave client API 来访问并且计算相应的聚合。关于 Java client API 的介绍，你可以到 Elastic 的官方网站链接去查看。

安装

如果你还没有安装好自己的 Elasticsearch 及 Kibana，请参照如下的文章来进行安装：

创建 Java 客户端

我们首先使用一个自己的喜欢的 Java 开发工具，比如 eclipse 或者 InteliJ 来创建一个简单的 Maven 项目：

pom.xml

<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0"
         xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
         xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
    <modelVersion>4.0.0</modelVersion>

    <groupId>org.liuxg.demo</groupId>
    <artifactId>elasticjava</artifactId>
    <version>1.0-SNAPSHOT</version>

    <properties>
        <maven.compiler.source>15</maven.compiler.source>
        <maven.compiler.target>15</maven.compiler.target>
    </properties>

    <dependencies>
        <dependency>
            <groupId>org.elasticsearch.client</groupId>
            <artifactId>elasticsearch-rest-high-level-client</artifactId>
            <version>7.11.2</version>
        </dependency>
        <dependency>
            <groupId>org.elasticsearch.client</groupId>
            <artifactId>elasticsearch-rest-client</artifactId>
            <version>7.11.2</version>
        </dependency>
        <dependency>
            <groupId>org.elasticsearch</groupId>
            <artifactId>elasticsearch</artifactId>
            <version>7.11.2</version><!--$NO-MVN-MAN-VER$-->
        </dependency>
        <dependency>
            <groupId>com.fasterxml.jackson.core</groupId>
            <artifactId>jackson-databind</artifactId>
            <version>2.11.1</version>
        </dependency>
    </dependencies>

</project>

你需要添加相应的 dependency。

接下来，我们可以直接在 Kibana 中输入如下的命令来创建一个简单的 classindex 的索引：

POST coachingclass/_bulk
{ "index" : {"_id": 1} }
{ "classname" : "Galaxy", "cource" : "Physics","instructor":"Sheldon Kooper","language":"English","seats available":18,"fees" : 6000 }
{ "index" : {"_id": 2} }
{ "classname" : "Galaxy", "cource" : "Chemistry","instructor":"Tom Nelson","language":"English","seats available":20,"fees" : 4000}
{ "index" : {"_id": 3} }
{ "classname" : "Galaxy","cource" : "Maths","instructor":"Smith Ray","language":"English","seats available":25,"fees" : 3000 }
{ "index" : {"_id": 4} }
{ "classname" : "Galaxy", "cource" : "Biology","instructor":"Tom Nelson","language":"English","seats available":12,"fees" : 2000 }
{ "index" : {"_id": 5} }
{ "classname" : "Galaxy", "cource" : "Social Science","instructor":"Ric Johanson","language":"English","seats available":10,"fees" : 3000 }

如果你对手动创建不感兴趣，你可以参考我之前的文章 “Elasticsearch：Java 运用示例” 来通过客户端应用来进行创建。

我们接下来实现一个如下的一个聚合查询：

GET classindex/_search
{
  "size": 0,
  "aggs": {
    "sum": {
      "sum": {
        "field": "fees"
      }
    },
    "avg": {
      "avg": {
        "field": "fees"
      }
    },
    "min": {
      "min": {
        "field": "fees"
      }
    },
    "max": {
      "max": {
        "field": "fees"
      }
    },
    "cardinality": {
      "cardinality": {
        "field": "fees"
      }
    },
    "count": {
      "value_count": {
        "field": "fees"
      }
    }
  }
}

上面显示的结果为：

{
  "took" : 4,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 5,
      "relation" : "eq"
    },
    "max_score" : null,
    "hits" : [ ]
  },
  "aggregations" : {
    "min" : {
      "value" : 2000.0
    },
    "avg" : {
      "value" : 3600.0
    },
    "max" : {
      "value" : 6000.0
    },
    "count" : {
      "value" : 5
    },
    "sum" : {
      "value" : 18000.0
    },
    "cardinality" : {
      "value" : 4
    }
  }
}

如果你对这些 min, max, avg 等聚合还不是很清楚的话，请参考我的另外一篇文章 “开始使用 Elasticsearch （3）”。

我们紧接着来创建一个叫做 Aggregation 的类：

它的内容如下：

Aggregation.java

import java.io.IOException;
import java.util.Arrays;
import java.util.Map;

import org.apache.http.HttpHost;
import org.elasticsearch.action.search.SearchRequest;
import org.elasticsearch.action.search.SearchResponse;
import org.elasticsearch.client.RequestOptions;
import org.elasticsearch.client.RestClient;
import org.elasticsearch.client.RestHighLevelClient;
import org.elasticsearch.index.query.QueryBuilders;
import org.elasticsearch.search.SearchHit;
import org.elasticsearch.search.aggregations.AggregationBuilders;
import org.elasticsearch.search.aggregations.metrics.Avg;
import org.elasticsearch.search.aggregations.metrics.Cardinality;
import org.elasticsearch.search.aggregations.metrics.Max;
import org.elasticsearch.search.aggregations.metrics.Min;
import org.elasticsearch.search.aggregations.metrics.Sum;
import org.elasticsearch.search.aggregations.metrics.ValueCount;
import org.elasticsearch.search.builder.SearchSourceBuilder;

public class Aggregation {
    @SuppressWarnings("resource")
    public static void main(String[] args) {

        RestHighLevelClient client = new RestHighLevelClient(
                RestClient.builder(new HttpHost("localhost", 9200, "http")));

        SearchRequest searchRequest = new SearchRequest();
        searchRequest.indices("classindex");
        SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
        searchSourceBuilder.query(QueryBuilders.matchAllQuery());

        searchSourceBuilder.aggregation(AggregationBuilders.sum("sum").field("fees"));
        searchSourceBuilder.aggregation(AggregationBuilders.avg("avg").field("fees"));
        searchSourceBuilder.aggregation(AggregationBuilders.min("min").field("fees"));
        searchSourceBuilder.aggregation(AggregationBuilders.max("max").field("fees"));
        searchSourceBuilder.aggregation(AggregationBuilders.cardinality("cardinality").field("fees"));
        searchSourceBuilder.aggregation(AggregationBuilders.count("count").field("fees"));

        searchRequest.source(searchSourceBuilder);
        Map<String, Object> map = null;

        try {
            SearchResponse searchResponse = null;
            searchResponse = client.search(searchRequest, RequestOptions.DEFAULT);
            if (searchResponse.getHits().getTotalHits().value > 0) {
                SearchHit[] searchHit = searchResponse.getHits().getHits();
                for (SearchHit hit : searchHit) {
                    map = hit.getSourceAsMap();
                    System.out.println("Index data:" + Arrays.toString(map.entrySet().toArray()));

                }
            }

            Sum sum = searchResponse.getAggregations().get("sum");
            double result = sum.getValue();
            System.out.println("aggs Sum: " + result);
            Avg aggAvg = searchResponse.getAggregations().get("avg");
            double valueAvg = aggAvg.getValue();
            System.out.println("aggs Avg::" + valueAvg);
            Min aggMin = searchResponse.getAggregations().get("min");
            double minOutput = aggMin.getValue();
            System.out.println("aggs Min::" + minOutput);
            Max aggMax = searchResponse.getAggregations().get("max");
            double maxOutput = aggMax.getValue();
            System.out.println("aggs Max::" + maxOutput);
            Cardinality aggCadinality = searchResponse.getAggregations().get("cardinality");
            long valueCadinality = aggCadinality.getValue();
            System.out.println("aggs Cadinality::" + valueCadinality);
            ValueCount aggCount = searchResponse.getAggregations().get("count");
            long valueCount = aggCount.getValue();
            System.out.println("aggs Count::" + valueCount);
        } catch (IOException ex) {
            ex.printStackTrace();
        }
    }
}

请注意在上面：

        RestHighLevelClient client = new RestHighLevelClient(
                RestClient.builder(new HttpHost("localhost", 9200, "http")));

我们需要根据自己的 Elasticsearch 的地址和端口地址进行相应的修改。上面的代码复制和 Elasticsearch 进行连接。

在上面，我们使用了 searchRequest.indices("classindex"); 来设置我们的索引。我们对 fee 这个字段进行了如下的聚合：

sum
avg
min
max
cardinality
count

编译并运行上面的代码，我们可以看到如下的输出：

Index data:[fees=6000, classname=Galaxy, instructor=Sheldon Kooper, seats available=18, cource=Physics, language=English]
Index data:[fees=4000, classname=Galaxy, instructor=Tom Nelson, seats available=20, cource=Chemistry, language=English]
Index data:[fees=3000, classname=Galaxy, instructor=Smith Ray, seats available=25, cource=Maths, language=English]
Index data:[fees=2000, classname=Galaxy, instructor=Tom Nelson, seats available=12, cource=Biology, language=English]
Index data:[fees=3000, classname=Galaxy, instructor=Ric Johanson, seats available=10, cource=Social Science, language=English]
aggs Sum: 18000.0
aggs Avg::3600.0
aggs Min::2000.0
aggs Max::6000.0
aggs Cadinality::4
aggs Count::5

你可以在地址 https://github.com/liu-xiao-guo/elasticjavaaggr 下载源码。

使用 Java 程序实现 terms 桶聚合

如果你对 Bucket aggregation 还不是很熟的话，建议你阅读我之前的文章 “Elasticsearch：透彻理解 Elasticsearch 中的 Bucket aggregation”。

我们接下来实现如下的一个聚合：

GET classindex/_search
{
  "size": 0, 
  "query": {
    "match_all": {}
  },
  "aggs": {
    "DISTINCT_VALUES": {
      "terms": {
        "field": "instructor.keyword",
        "size": 10
      }
    }
  }
}

我们使用 Kibana 进行查询，它显示的结果为：

{
  "took" : 1,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 5,
      "relation" : "eq"
    },
    "max_score" : null,
    "hits" : [ ]
  },
  "aggregations" : {
    "DISTINCT_VALUES" : {
      "doc_count_error_upper_bound" : 0,
      "sum_other_doc_count" : 0,
      "buckets" : [
        {
          "key" : "Tom Nelson",
          "doc_count" : 2
        },
        {
          "key" : "Ric Johanson",
          "doc_count" : 1
        },
        {
          "key" : "Sheldon Kooper",
          "doc_count" : 1
        },
        {
          "key" : "Smith Ray",
          "doc_count" : 1
        }
      ]
    }
  }
}

就像在上节中显示的那样，我们修改 Aggregation.java 如下：

Aggregation.java

import java.io.IOException;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.List;
import java.util.Map;

import org.apache.http.HttpHost;
import org.elasticsearch.action.search.SearchRequest;
import org.elasticsearch.action.search.SearchResponse;
import org.elasticsearch.client.RequestOptions;
import org.elasticsearch.client.RestClient;
import org.elasticsearch.client.RestHighLevelClient;
import org.elasticsearch.index.query.QueryBuilders;
import org.elasticsearch.search.SearchHit;
import org.elasticsearch.search.aggregations.AggregationBuilders;
import org.elasticsearch.search.aggregations.Aggregations;
import org.elasticsearch.search.aggregations.bucket.terms.Terms;
import org.elasticsearch.search.builder.SearchSourceBuilder;

public class Aggregation {
    public static void main(String[] args) {

        RestHighLevelClient client = new RestHighLevelClient(
                RestClient.builder(new HttpHost("localhost", 9200, "http")));


        SearchRequest searchRequest = new SearchRequest();
        searchRequest.indices("classindex");
        SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
        searchSourceBuilder.query(QueryBuilders.matchAllQuery());
        searchSourceBuilder.aggregation(AggregationBuilders.terms("DISTINCT_VALUES").field("instructor.keyword"));
        searchRequest.source(searchSourceBuilder);
        Map<String, Object> map = null;

        try {
            SearchResponse searchResponse = null;
            searchResponse = client.search(searchRequest, RequestOptions.DEFAULT);
            if (searchResponse.getHits().getTotalHits().value > 0) {
                SearchHit[] searchHit = searchResponse.getHits().getHits();
                for (SearchHit hit : searchHit) {
                    map = hit.getSourceAsMap();
                    System.out.println("map:" + Arrays.toString(map.entrySet().toArray()));
                }
            }
            Aggregations aggregations = searchResponse.getAggregations();
            List<String> list = new ArrayList<String>();
            Terms aggTerms = aggregations.get("DISTINCT_VALUES");
            List<? extends Terms.Bucket> buckets = aggTerms.getBuckets();
            for (Terms.Bucket bucket : buckets) {
                list.add(bucket.getKeyAsString());
            }
            System.out.println("DISTINCT list values:" + list.toString());
        } catch (IOException e) {
            e.printStackTrace();
        }
    }
}

我们编译并运行程序，它显示的结果如下：

map:[fees=6000, classname=Galaxy, instructor=Sheldon Kooper, seats available=18, cource=Physics, language=English]
map:[fees=4000, classname=Galaxy, instructor=Tom Nelson, seats available=20, cource=Chemistry, language=English]
map:[fees=3000, classname=Galaxy, instructor=Smith Ray, seats available=25, cource=Maths, language=English]
map:[fees=2000, classname=Galaxy, instructor=Tom Nelson, seats available=12, cource=Biology, language=English]
map:[fees=3000, classname=Galaxy, instructor=Ric Johanson, seats available=10, cource=Social Science, language=English]
DISTINCT list values:[Tom Nelson, Ric Johanson, Sheldon Kooper, Smith Ray]

从上面我们可以看出来和在 Kibana 中显示的结果是一样的。

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