开封网站建设流程与步骤,网站开发发送短信,wap网站建设管理制度,云南建设厅网站一、说明 在项目中使用Elasticsearch的聚合与分组查询后,对于返回结果一脸懵逼,查阅各资料后,自己总结了一下参数取值的含义,不一定全面,只含常见参数 二、分组查询
2.1 参数解释
SearchResponseMap searchResponse null;try {searchResponse client.search(s -Map searchResponse null;try {searchResponse client.search(s - s.index(tbanalyzelist).query(q - q.bool(t - {t.must(m - m.match(b - b.field(machineType.keyword).query(FieldValue.of(machineType))));if (ToolUtil.isNotEmpty(bizCodes))t.must(m - m.terms(b - b.field(bizCode.keyword).terms(f - f.value(values))));t.must(a - a.range(r - r.field(duration).gt(JsonData.of(0))));t.must(a - a.range(r - r.field(open_time).gt(JsonData.of(startTime)).lte(JsonData.of(endTime1))));return t;}))//.size(2000000) 数据太多暂且注释.from(1) //分页查询 起始位置.size(2) // 每页两条数据 .aggregations(byOpenTime, aggregationBuilder -aggregationBuilder.terms(termsAggregationBuilder -termsAggregationBuilder.field(openTime))),Map.class);} catch (IOException e) {e.printStackTrace();}//查询结果System.out.println(searchResponse);System.out.println(耗时 searchResponse.took());HitsMetadataMap hits searchResponse.hits();System.out.println(hits.total());System.out.println(符合条件的总文档数量 hits.total().value());//注意第一个hits() 与 第二个hits()含义不一样ListHitMap hitList searchResponse.hits().hits(); //获取分组结果MapString, Aggregate aggregations searchResponse.aggregations();System.out.println(aggregations aggregations);Aggregate aggregate aggregations.get(byOpenTime);System.out.println(byOpenTime分组结果 aggregate);LongTermsAggregate lterms aggregate.lterms();BucketsLongTermsBucket buckets lterms.buckets();for (LongTermsBucket b : buckets.array()) {System.out.println(b.key() : b.docCount());} searchResponse输出结果转JSON
{took:190, //执行整个搜索请求耗费了多少毫秒timed_out:false,//查询是否超时。默认情况下搜索请求不会超时。_shards:{ // 在查询中参与分片情况failed:0, //失败分片数量 successful:1,//成功total:1,//总计skipped:0//跳过},hits:{ //结果命中数据 total:{ //匹配到的文档总数relation:gte,//是否是我们的实际的满足条件的所有文档数 value:10000 //文档总数},hits:[//每一个命中数据{_index:tbanalyzelist, //索引名相当于数据库的表名_id:QF2THIQBzxpesqmRtMpw,_score:3.0470734,//分数_type:_doc,//类型//资源,这里才是存储的我们想要的数据_source:{duration317.0, //每个字段的值相当于mysql中的字段machineIdZFB007422, bizNamewangyf, bizCode221026172721ZBTQ, open_time1664296386000, openTime2022-09-27, machineTypeDEV-HL}},{_index:tbanalyzelist,_id:QV2THIQBzxpesqmRtMpw,_score:3.0470734,_type:_doc,_source:{duration313.0, machineIdZFB007422, bizNamewangyf, bizCode221026172721ZBTQ, open_time1664383009000, openTime2022-09-28, machineTypeDEV-HL}}],max_score:3.0470734 //查询所匹配文档的 _score 的最大值},aggregations:{//聚合结果lterms#byOpenTime:{//分组的桶名称buckets:[ //分组桶结果{doc_count:20144,//key:1664150400000,key_as_string:2022-09-26T00:00:00.000Z},{doc_count:19724,key:1664409600000,key_as_string:2022-09-29T00:00:00.000Z},{doc_count:19715,key:1664236800000,key_as_string:2022-09-27T00:00:00.000Z},{doc_count:19653,key:1664323200000,key_as_string:2022-09-28T00:00:00.000Z},{doc_count:19376,key:1664496000000,key_as_string:2022-09-30T00:00:00.000Z},{doc_count:331,key:1664064000000,key_as_string:2022-09-25T00:00:00.000Z}],doc_count_error_upper_bound:0,sum_other_doc_count:0}}
}
doc_count_error_upper_bound表示没有在这次聚合中返回、但是可能存在的潜在聚合结果sum_other_doc_count表示这次聚合中没有统计到的文档数。因为ES为分布式部署不同文档分散于多个分片这样当聚合时会在每个分片上分别聚合然后由协调节点汇总结果后返回。doc_count每个桶的文档数量。key: 分组后的key值 2.2 获取桶数据方式
BucketsLongTermsBucket longBuckets aggregate.lterms().buckets();
BucketsStringTermsBucket stringBuckets aggregate.sterms().buckets();
BucketsDoubleTermsBucket doubleBuckets aggregate.dterms().buckets();
三、聚合查询 查询条件先忽略,这里聚合后的条件可以直接取到max,count,min,avg,sum等值 String cinemaId 15989;SearchResponseMap searchResponse null;try {searchResponse client.search(s - s.index(tbmaoyan).query(q - q.bool(t - {t.must(m - m.match(f - f.field(cinemaId.keyword).query(FieldValue.of(cinemaId))));//t.must(m - m.term(f - f.field(cinemaId.keyword).value(cinemaId)));//t.must(m - m.match(f - f.field(cinemaId).query(36924)));// t.must(m - m.match(f - f.field(bizCode).query(FieldValue.of(220104182434IIZF))));//220104182434IIZF 220120143442CB4Creturn t;}))
// .sort(o - o.field(f - f.field(openTime).order(SortOrder.Asc)))//对viewInfo进行统计.aggregations(sumViewInfo, aggregationBuilder - aggregationBuilder.stats(statsAggregationBuilder - statsAggregationBuilder.field(viewInfo)))//对showInfo进行统计.aggregations(aggregateShowInfo, aggregationBuilder - aggregationBuilder.stats(statsAggregationBuilder - statsAggregationBuilder.field(showInfo))).from(0).size(10000), Map.class);} catch (IOException e) {e.printStackTrace();}//查询结果System.out.println(searchResponse);System.out.println(耗时 searchResponse.took());HitsMetadataMap hits searchResponse.hits();System.out.println(hits.total());System.out.println(符合条件的总文档数量 hits.total().value());//注意第一个hits() 与 第二个hits()的区别ListHitMap hitList searchResponse.hits().hits(); ListMap hitListCopy new ArrayList();for (HitMap mapHit : hitList) {String source mapHit.source().toString();System.out.println(文档原生信息 source);Map map mapHit.source();hitListCopy.add(map);}//获取聚合结果MapString, Aggregate aggregations searchResponse.aggregations();System.out.println(aggregations aggregations);Aggregate aggregateViewInfo aggregations.get(sumViewInfo);Aggregate aggregateShowInfo aggregations.get(aggregateShowInfo);System.out.println(viewInfo aggregateViewInfo);System.out.println(showInfo aggregateShowInfo);System.out.println(统计个数 aggregateViewInfo.stats().count());System.out.println(最高分账票房 aggregateViewInfo.stats().max());System.out.println(最低分账票房 aggregateViewInfo.stats().min());System.out.println(平均分账票房 aggregateViewInfo.stats().avg());System.out.println(聚合查询的分账票房 aggregateViewInfo.stats().sum());Double sumViewInfoCopy hitListCopy.stream().mapToDouble(h - Double.parseDouble(h.get(viewInfo).toString())).sum();System.out.println(********************);System.out.println(聚合查询的分账票房 aggregateViewInfo.stats().sum());System.out.println(stream流查询的分账票房: sumViewInfoCopy);
searchResponse.aggregations()的结果跟上面分组查询类似,不过赘述了aggregations.get(sumViewInfo)的取值 aggregations.get(aggregateShowInfo)的取值 比对一下聚合查询跟我们自己算的数据是否一致
