elasticsearch笔记(8)聚合查询

聚合查询: 也就是类似mysql的count，max，avg等查询，但要更为强大

聚合查询语法

POST /index/type/_search
{
    "aggs":{
        "名字":{
            "agg_type":{
                "属性":"值"
            }
        }
    }
}

一.  去重计数查询:Cardinality

去掉重复的数据，然后算出总数，也就是Cardinality; 如查询总共几个省.

 java 中的重复计数查询

//重复计数查询
    @Test
    public void cardinalityQuery() throws IOException {
        //        1. 创建查询对象
        String index = "sms-logs-index";
        String type = "sms-logs-type";
        SearchRequest searchRequest = new SearchRequest(index);//指定索引
        searchRequest.types(type);//指定类型
//    2. 封装查询条件
        String aggName = "agg";
        SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
        searchSourceBuilder.aggregation(AggregationBuilders.cardinality(aggName).field("province"));
        searchRequest.source(searchSourceBuilder);

        //        3.执行查询
        // client执行
        HttpHost httpHost = new HttpHost("192.168.43.30", 9200);
        RestClientBuilder restClientBuilder = RestClient.builder(httpHost);
        RestHighLevelClient restHighLevelClient = new RestHighLevelClient(restClientBuilder);
        SearchResponse search = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);

//        4.获取数据(source中的数据)
        Cardinality aggregation = search.getAggregations().get(aggName); //用Cardinality接收
        System.out.println(aggregation.getValue());
    }

 二. 范围统计

根据某个属性的范围，统计文档的个数，(from 包含, to不包含)

针对不同的类型指定不同的方法，

数值：range

时间：date_range

ip：ip_range

数值统计:

日期型范围查询(data_range):加一个format来规定格式

 ip范围统计(ip_range)

 

java中用range查询

    @Test
    public void rangeQuery() throws IOException {
        //        1. 创建查询对象
        String index = "sms-logs-index";
        String type = "sms-logs-type";
        SearchRequest searchRequest = new SearchRequest(index);//指定索引
        searchRequest.types(type);//指定类型
//    2. 封装查询条件
        String aggName = "agg";
        SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
        searchSourceBuilder.aggregation(AggregationBuilders.range(aggName).field("fee").addUnboundedTo(3)
12                 .addRange(3,4)
13                 .addUnboundedFrom(4));
        searchRequest.source(searchSourceBuilder);

        //        3.执行查询
        // client执行
        HttpHost httpHost = new HttpHost("192.168.43.30", 9200);
        RestClientBuilder restClientBuilder = RestClient.builder(httpHost);
        RestHighLevelClient restHighLevelClient = new RestHighLevelClient(restClientBuilder);
        SearchResponse search = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);

//        4.获取数据(source中的数据)
        Range range = search.getAggregations().get(aggName);//用Range接收
25         List<? extends Range.Bucket> buckets = range.getBuckets();
        for(  Range.Bucket bucket : buckets ){
            System.out.println(bucket.getDocCount());

        }


    }

 3. 统计聚合查询

可以查询属性(field)的最大值，最小值，平均值，平方和.......

  @Test
    public void extended_status_Query() throws IOException {
        //        1. 创建查询对象
        String index = "sms-logs-index";
        String type = "sms-logs-type";
        SearchRequest searchRequest = new SearchRequest(index);//指定索引
        searchRequest.types(type);//指定类型
//    2. 封装查询条件
        String aggName = "agg";
        SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
        searchSourceBuilder.aggregation(AggregationBuilders.extendedStats(aggName).field("fee"));
        searchRequest.source(searchSourceBuilder);

        //        3.执行查询
        // client执行
        HttpHost httpHost = new HttpHost("192.168.43.30", 9200);
        RestClientBuilder restClientBuilder = RestClient.builder(httpHost);
        RestHighLevelClient restHighLevelClient = new RestHighLevelClient(restClientBuilder);
        SearchResponse search = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);

//        4.获取数据(source中的数据)
        ExtendedStats aggregation = search.getAggregations().get(aggName);//用Range接收
        System.out.println(aggregation.getMax());
        System.out.println(aggregation.getSum());
        System.out.println(aggregation.getAvg());
    }

https://www.elastic.co/guide/en/elasticsearch/reference/6.5/getting-started.html