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ES使用聚合aggregations实战（自用：2025.04.03更新）

article 2026/2/4 7:50:51

ES使用聚合aggregations实战

聚合模板
- 桶聚合：Bucket Aggregations
- 指标聚合：Metrics Aggregations
- 管道聚合：Pipeline Aggregations
- 嵌套聚合
- 日期直方图：date-histogram
接口实战
- 接口一：根据stu_id分组统计时间段内的各个签到率出勤率迟到率等
- 接口二：某一stu_id去统计时间段内的课程签到情况
- 接口三：根据课程分组筛选获取满勤数和非满勤数
- 接口四：根据stu_id分组筛选获取满勤数和非满勤数
- 接口五：根据学院分组筛选获取top5和各学院学生平均出勤率
- 接口六：时间端筛选统计时间段内每一天的学生签到率

聚合模板

一般思路是先写出对应的es语句，再写java代码，首先介绍一下聚合的模板，具体细节可看
开源社区-伯乐马科技 ---- 第九章：聚合搜索（Aggregations）

桶聚合：Bucket Aggregations

GET <index_name>/_search
{"aggs": {"<aggs_name>": { // 聚合名称需要自己定义"<agg_type>": {"field": "<field_name>"}}}
}

aggs_name：聚合函数的名称
agg_type：聚合种类，比如是桶聚合（terms）或者是指标聚合（avg、sum、min、max等）
field_name：字段名称或者叫域名。
多字段聚合Multi Terms

GET /<index_name>/_search
{"aggs": {"agg_name": {"multi_terms": {"terms": [{"field": "field_1"},{"field": "field_2"}]}}}
}

指标聚合：Metrics Aggregations

将上述的trems换成指标聚合的函数，有下：
平均值：Avg
最大值：Max
最小值：Min
求和：Sum
详细信息：Stats
数量：Value count

管道聚合：Pipeline Aggregations

GET <index_name>/_search
{"aggs": {"my_aggs": {"<function>": {...},"aggs": {"my_price_bucket": {...}}},"my_min_bucket":{"<pip_function>": {"buckets_path": "my_aggs>price_bucket"}}}
}

注：buckets_path：路径相对于管道聚合的位置，不是绝对路径，路径不能返回“向上”的路径

Min bucket：最小桶
Max bucket：最大桶
Avg bucket：桶平均值
Sum bucket：桶求和
Stats bucket：桶信息
注意：buckets_path 为管道聚合的关键字，其值从当前聚合统计的聚合函数开始计算为第一级。比如下面例子中，my_aggs 和 my_min_bucket 同级，my_aggs 就是buckets_path 值的起始值。

嵌套聚合

GET <index_name>/_search
{"aggs": {"<agg_name>": {"<agg_type>": {"field": "<field_name>"},"aggs": {"<agg_name_child>": {"<agg_type>": {"field": "<field_name>"}}}}}
}

用途：用于在某种聚合的计算结果之上再次聚合，如统计不同类型商品的平均价格，就是在按照商品类型桶聚合之后，在其结果之上计算平均价格

日期直方图：date-histogram

GET product/_search?size=0
{"aggs": {"my_date_histogram": {"date_histogram": {"field": "createtime",					#字段需为date类型"<interval_type>": "month",			#时间间隔的参数可选项"format": "yyyy-MM", 						#日期的格式化输出"extended_bounds": {						#输出空桶"min": "2020-01","max": "2020-12"}}}}
}

interval_type：时间间隔的参数可选项

fixed_interval：ms（毫秒）、s（秒）、 m（分钟）、h（小时）、d（天），注意单位需要带上具体的数值，如2d为两天。需要当心当单位过小，会导致输出桶过多而导致服务崩溃。

calendar_interval：year、quarter、month、week、day、hour、minute
在 8.x 版本中 interval 已弃用

missing：指定在日期字段缺失时，如何处理该时间段。

min_doc_count：指定在时间段内至少需要满足的文档数量才会包含在结果中。默认值为0，表示即使时间段内没有文档，也会返回结果。

time_zone：指定聚合操作中使用的时区。默认情况下，Elasticsearch使用服务器的时区设置。如：“time_zone”: “Asia/Shanghai”,

offset：指定聚合结果中时间段的偏移量。可以通过提供时间单位和数量来指定偏移量。例如，"+1h"表示时间段向后偏移1小时。

keyed：指定是否将结果按时间段的键值对形式返回。如果设置为true，每个时间段的结果将以键值对的形式返回，默认为false。

extended_bounds：指定自定义的时间范围。可以通过提供"min"和"max"参数来限制聚合操作的时间范围。

接口实战

**前提：**本文环境-

elasticsearch-7.16.3
kibana-7.16.3
elasticsearch-analysis-ik-7.16.3
logstash-7.16.3

pom.xml文件引入

<!-- Java Low Level REST Client -->
<dependency><groupId>org.elasticsearch.client</groupId><artifactId>elasticsearch-rest-client</artifactId><version>7.16.3</version>
</dependency><!-- Java High Level REST Client -->
<dependency><groupId>org.elasticsearch.client</groupId><artifactId>elasticsearch-rest-high-level-client</artifactId><version>7.16.3</version>
</dependency>

同步表数据stu_sign学生签到记录表结构为

CREATE TABLE `stu_sign` (`id` int(11) NOT NULL AUTO_INCREMENT,`create_date` datetime DEFAULT NULL,`modify_date` datetime DEFAULT NULL,`class_num_begin` varchar(32) DEFAULT NULL,`class_num_end` varchar(32) DEFAULT NULL,`classroom` varchar(128) DEFAULT NULL,`classroom_id` int(11) DEFAULT NULL,`course_id` int(11) DEFAULT NULL,`course_name` varchar(256) DEFAULT NULL,`course_sched_id` int(11) DEFAULT NULL,`roll_call_date` datetime DEFAULT NULL,`semester_id` int(11) DEFAULT NULL,`sign_status` int(11) DEFAULT NULL,`sing_date` datetime DEFAULT NULL,`stu_id` int(11) DEFAULT NULL,`stu_name` varchar(256) DEFAULT NULL,`teach_time` datetime DEFAULT NULL,`teach_time_str` varchar(32) DEFAULT NULL,`teacher_id` int(11) DEFAULT NULL,`teacher_name` varchar(256) DEFAULT NULL,`roll_call_status` int(11) DEFAULT NULL,`stu_num` varchar(64) DEFAULT NULL,`stu_sign_status` int(11) DEFAULT NULL,`academy_id` int(11) DEFAULT NULL,`academy_superior_id` int(11) DEFAULT NULL,`class_id` int(11) DEFAULT NULL,`grade_id` varchar(50) DEFAULT NULL,`class_begin_time` varchar(100) DEFAULT '',`class_end_time` varchar(100) DEFAULT '',`sign_type` int(11) DEFAULT NULL,`appeal_msg` varchar(255) DEFAULT NULL,`appeal_status` int(11) DEFAULT NULL,`appeal_time` varchar(255) DEFAULT NULL,`late_status` int(11) DEFAULT NULL,`leave_status` int(11) DEFAULT NULL,`absence_status` int(11) DEFAULT NULL COMMENT '1、事假    2、病假   3、公假',`modify_userId` varchar(255) DEFAULT NULL COMMENT '修改人id',`modify_userName` varchar(256) DEFAULT NULL COMMENT '修改人姓名',`modify_time` varchar(100) DEFAULT NULL COMMENT '修改时间',PRIMARY KEY (`id`),KEY `schedIdIndex` (`course_sched_id`) USING BTREE,KEY `index_course_id` (`course_id`) USING BTREE,KEY `index_course_sched_id` (`course_sched_id`) USING BTREE,KEY `index_semester_id` (`semester_id`) USING BTREE,KEY `index_sign_status` (`sign_status`) USING BTREE,KEY `index_stu_id` (`stu_id`) USING BTREE,KEY `index_teacher_id` (`teacher_id`) USING BTREE,KEY `index_stu_num` (`stu_num`) USING BTREE,KEY `index_class_num_begin` (`class_num_begin`) USING BTREE,KEY `index_class_num_end` (`class_num_end`) USING BTREE,KEY `class_begin_time_index` (`class_begin_time`),KEY `class_end_time_index` (`class_end_time`),KEY `class_id_index` (`class_id`),KEY `teach_time_index` (`teach_time`),KEY `class_begin_end_time_index` (`class_begin_time`,`class_end_time`,`teach_time`),KEY `course_sched_id_stu_id_index` (`course_sched_id`,`stu_id`),KEY `idx_stu_sign_class_begin_time_course_id_stu_id` (`class_begin_time`,`course_id`,`stu_id`)
) ENGINE=InnoDB AUTO_INCREMENT=7923 DEFAULT CHARSET=utf8;

在es中的kibana执行创建索引对应mapping，由于很多查询基于class_begin_time字段去做，但是在表结构中该字段存储为varchar，特殊的设置其mapping的type为date和format时间格式
稍微解释一下下面的配置文件：根据追踪日志的文件last_run_stu_login.txt中记录的时间，并根据字段modify_date去增量同步stu_sign表中的数据，并设置每五分钟同步一次

input {jdbc {# 配置数据库信息jdbc_connection_string => "jdbc:mysql://188.18.66.185:3306/eschool?useUnicode=true&characterEncoding=UTF-8&serverTimezone=Asia/Shanghai"jdbc_driver_class => "com.mysql.cj.jdbc.Driver"jdbc_user => "root"jdbc_password => "JYD.2015.internet"jdbc_paging_enabled => "true"jdbc_page_size => "50000"jdbc_default_timezone => "UTC"# mysql驱动所在位置jdbc_driver_library => "D:\environment\apache-maven-3.8.8\maven_repository\mysql\mysql-connector-java\8.0.27\mysql-connector-java-8.0.27.jar"#sql执行语句statement => "SELECT * FROM `stu_sign` WHERE modify_date > :sql_last_value AND modify_date < NOW() "use_column_value => truetracking_column => "modify_date"tracking_column_type => "timestamp"last_run_metadata_path => "E:\software\logstash\logstash-7.16.3\conf\metadata\last_run_stu_login.txt"schedule => "*/5 * * * *"lowercase_column_names => false}
}
output {elasticsearch {hosts => ["127.0.0.1:9200"]index => "stu_sign"document_id => "%{id}"}stdout {codec => json_lines}
}

在logstash文件下bin目录下启动命令

logstash.bat -f E:\software\logstash\logstash-7.16.3\conf\stu_sign.conf

接口一：根据stu_id分组统计时间段内的各个签到率出勤率迟到率等

需求：根据stu_id分组统计时间段内的各个签到率出勤率迟到率等
完成分页操作和统计结果按照缺勤率降序排序
在这里插入图片描述
对应mapper.xml方法中的sql代码为

<select id="getStuAttendanceListJson" resultType="java.util.Map">SELECTifnull(a.NAME,'') AS college_name,s.stu_id,s.stu_num,s.stu_name,count( s.id ) AS total_num,(ifnull( sum( sign_status ), 0 )- ifnull( sum( late_status ), 0 )) AS yes_num,ifnull( sum( late_status ), 0 ) AS late_num,(count( s.id )- ifnull( sum( sign_status ), 0 )) AS no_num,FORMAT((( ifnull( sum( sign_status ), 0 )- ifnull( sum( late_status ), 0 ))/ count( s.id )* 100 ), 1 ) ASyes_lv,FORMAT(( ifnull( sum( late_status ), 0 )/ count( s.id )* 100 ), 1 ) AS late_lv,FORMAT((( count( s.id )- ifnull( sum( sign_status ), 0 ))/ count( s.id )* 100 ), 1 ) AS no_lvFROMeschool.stu_sign sLEFT JOIN eschool.USER u ON s.stu_id = u.idLEFT JOIN eschool.academy a ON a.id = u.academy_idWHEREs.class_begin_time &lt; now()<if test="t.collegeId!=null and t.collegeId!=''">and u.academy_id = #{t.collegeId}</if><if test="t.beginDate!=null and t.beginDate!=''">and s.class_begin_time &gt; CONCAT(#{t.beginDate},' 00:00:01')</if><if test="t.endDate!=null and t.endDate!=''">and s.class_begin_time &lt; CONCAT(#{t.endDate},' 23:59:59')</if><if test="t.keyWord!=null and t.keyWord!=''">and (s.stu_num like concat('%',#{t.keyWord},'%') or s.stu_name like concat('%',#{t.keyWord},'%'))</if>GROUP BY s.stu_id ORDER BY (( ifnull(sum(sign_status), 0) - ifnull(sum(late_status), 0)) / count(s.id)) DESC
</select>

java实现代码如下：(待优化：使用bucket_sort进行桶排序然后再from size)

public BaseResponse getStuAttendanceListJson(UserSignRequest requestParam) {Map<String, Object> result = new HashMap<>();try {SearchRequest searchRequest = new SearchRequest("stu_sign");SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();BoolQueryBuilder boolQueryBuilder = QueryBuilders.boolQuery();RangeQueryBuilder timeRangeQuery = QueryBuilders.rangeQuery("class_begin_time").lt("now");if (requestParam.getBeginDate() != null && requestParam.getEndDate() != null) {timeRangeQuery.gte(requestParam.getBeginDate()+" 00:00:00").lte(requestParam.getEndDate()+" 23:59:59");}boolQueryBuilder.must(timeRangeQuery);if (requestParam.getCollegeId() != null) {boolQueryBuilder.must(QueryBuilders.termQuery("academy_id", requestParam.getCollegeId()));}// 关键词查询if (StringUtils.isNotBlank(requestParam.getKeyWord())) {BoolQueryBuilder keywordQuery = QueryBuilders.boolQuery().should(QueryBuilders.wildcardQuery("stu_name.keyword", "*"+requestParam.getKeyWord()+"*")).should(QueryBuilders.wildcardQuery("stu_num.keyword", "*"+requestParam.getKeyWord()+"*")).minimumShouldMatch(1);boolQueryBuilder.must(keywordQuery);}searchSourceBuilder.query(boolQueryBuilder);TopHitsAggregationBuilder topHits = AggregationBuilders.topHits("student_info").size(1).fetchField("stu_num").fetchField("stu_name").fetchField("academy_id");// 构建聚合TermsAggregationBuilder aggregation = AggregationBuilders.terms("group_by_stu_id").field("stu_id").size(10000)  // 根据实际情况调整.subAggregation(AggregationBuilders.sum("sum_sign").field("sign_status")).subAggregation(AggregationBuilders.sum("sum_late").field("late_status")).subAggregation(topHits);searchSourceBuilder.aggregation(aggregation);searchSourceBuilder.size(0);// 执行查询searchRequest.source(searchSourceBuilder);SearchResponse response = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);// 处理聚合结果Map<String, Object> academyNameMap = getAcademyNameMap();List<Map<String, Object>> attendanceList = new ArrayList<>();Terms terms = response.getAggregations().get("group_by_stu_id");for (Terms.Bucket bucket : terms.getBuckets()) {Map<String, Object> item = new HashMap<>();item.put("stu_id", bucket.getKeyAsString());SearchHit student_info = ((ParsedTopHits) bucket.getAggregations().get("student_info")).getHits().getHits()[0];item.put("stu_num", student_info.getDocumentFields().get("stu_num").getValue());item.put("stu_name", student_info.getDocumentFields().get("stu_name").getValue());if(student_info.getDocumentFields().get("academy_id") != null){String academyId = student_info.getDocumentFields().get("academy_id").getValue().toString();item.put("college_id", academyId);item.put("college_name",academyNameMap.getOrDefault(academyId,""));}item.put("total_num", bucket.getDocCount());Sum sumSign = bucket.getAggregations().get("sum_sign");Sum sumLate = bucket.getAggregations().get("sum_late");double sign = sumSign.getValue();double late = sumLate.getValue();item.put("yes_num", (int) (sign - late));item.put("late_num", (int) late);item.put("no_num", (int) (bucket.getDocCount() - sign));BigDecimal yesLv = new BigDecimal((sign - late) / bucket.getDocCount() * 100);BigDecimal lateLv = new BigDecimal(late / bucket.getDocCount() * 100);BigDecimal noLv = new BigDecimal((bucket.getDocCount() - sign) / bucket.getDocCount() * 100);DecimalFormat df = new DecimalFormat("#.0");item.put("yes_lv", yesLv.compareTo(BigDecimal.ZERO) == 0 ? "0.0" : df.format(yesLv));item.put("late_lv", lateLv.compareTo(BigDecimal.ZERO) == 0 ? "0.0" : df.format(lateLv));item.put("no_lv", noLv.compareTo(BigDecimal.ZERO) == 0 ? "0.0" : df.format(noLv));attendanceList.add(item);}// 按正常签到率排序,如果正常签到率一样，按照stu_id升序attendanceList = attendanceList.stream().sorted((o1, o2) -> {double yesLv1 = Double.parseDouble(o1.get("yes_lv").toString());double yesLv2 = Double.parseDouble(o2.get("yes_lv").toString());if (yesLv1 != yesLv2) {return Double.compare(yesLv2, yesLv1);} else {return ((String) o1.get("stu_id")).compareTo((String) o2.get("stu_id"));}}).collect(Collectors.toList());result.put("total_count", attendanceList.size());int pages = (int) Math.ceil((double) attendanceList.size() / requestParam.getPageSize());result.put("total_pages",pages);result.put("size",requestParam.getPageSize());//截取listattendanceList = attendanceList.subList((requestParam.getPage() - 1) * requestParam.getPageSize(), Math.min(requestParam.getPage() * requestParam.getPageSize(), attendanceList.size()));result.put("list", attendanceList);return BaseResponseBuilder.success(result);} catch (Exception e) {return BaseResponseBuilder.failure("查询失败",e.getMessage());}
}

在这里插入图片描述

接口二：某一stu_id去统计时间段内的课程签到情况

相比1已经简单许多了

SELECT
count( 1 ) AS total_num,(
ifnull( sum( sign_status ), 0 )- ifnull( sum( late_status ), 0 )) AS yes_num,
ifnull( sum( late_status ), 0 ) AS late_num,
(
count( s.id )- ifnull( sum( sign_status ), 0 )) AS no_num,
FORMAT((( ifnull( sum( sign_status ), 0 )- ifnull( sum( late_status ), 0 ))/ count( s.id )* 100 ), 1 ) AS
yes_lv,
FORMAT(( ifnull( sum( late_status ), 0 )/ count( s.id )* 100 ), 1 ) AS late_lv,
FORMAT((( count( s.id )- ifnull( sum( sign_status ), 0 ))/ count( s.id )* 100 ), 1 ) AS no_lv
FROM
eschool.stu_sign s
WHERE
s.stu_id = #{t.userId}
AND s.class_begin_time &lt; now()
<if test="t.beginDate!=null and t.beginDate!=''">and s.class_begin_time &gt; CONCAT(#{t.beginDate},' 00:00:01')
</if>
<if test="t.endDate!=null and t.endDate!=''">and s.class_begin_time &lt; CONCAT(#{t.endDate},' 23:59:59')
</if>

java代码如下

public BaseResponse getStuAttendanceDeatilsByStudentId(UserSignDetailRequest requestParam) {Map<String, Object> result = new HashMap<>();try {SearchRequest searchRequest = new SearchRequest("stu_sign");CountRequest countRequest = new CountRequest("stu_sign");SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();BoolQueryBuilder boolQueryBuilder = QueryBuilders.boolQuery();RangeQueryBuilder timeRangeQuery = QueryBuilders.rangeQuery("class_begin_time").lte("now");if (requestParam.getBeginDate() != null && requestParam.getEndDate() != null) {// 添加日期格式化，匹配yyyy-MM-dd HH:mm:ss格式String gte = requestParam.getBeginDate() + " 00:00:00";String lte = requestParam.getEndDate() + " 23:59:59";timeRangeQuery.gte(gte).lte(lte);}boolQueryBuilder.must(timeRangeQuery);boolQueryBuilder.must(QueryBuilders.termQuery("stu_id", requestParam.getUserId()));searchSourceBuilder.query(boolQueryBuilder);countRequest.source(searchSourceBuilder);CountResponse countResponse = restHighLevelClient.count(countRequest, RequestOptions.DEFAULT);long total = countResponse.getCount();// 指定返回字段searchSourceBuilder.fetchSource(new String[]{"course_name", "class_begin_time", "class_end_time", "sign_status", "late_status", "sign_type" ,"sing_date"}, null);// 分页参数if (requestParam.getPage() != 0 && requestParam.getPageSize() != 0) {searchSourceBuilder.from((requestParam.getPage() - 1) * requestParam.getPageSize());searchSourceBuilder.size(requestParam.getPageSize());}searchSourceBuilder.sort("class_begin_time", SortOrder.DESC);searchRequest.source(searchSourceBuilder);SearchResponse response = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);List<Map<String, Object>> details = new ArrayList<>();for (SearchHit hit : response.getHits().getHits()) {Map<String, Object> item = new HashMap<>();item.put("course_name", hit.getSourceAsMap().get("course_name"));item.put("class_begin_time", hit.getSourceAsMap().get("class_begin_time"));item.put("class_end_time", hit.getSourceAsMap().get("class_end_time"));//完善sing_date、sing_status、sign_typeif(hit.getSourceAsMap().get("sign_status")!=null && hit.getSourceAsMap().get("sign_status").equals("1")){item.put("sing_date", hit.getSourceAsMap().get("sing_date"));}if(hit.getSourceAsMap().get("late_status")!=null && hit.getSourceAsMap().get("late_status").equals("1")){item.put("sing_status", 2+"");}else{item.put("sing_status", hit.getSourceAsMap().get("sing_status"));}item.put("sign_type", hit.getSourceAsMap().get("sign_type")==null?"":hit.getSourceAsMap().get("sign_type"));details.add(item);}result.put("total_count", response.getHits().getTotalHits().value);//注：这个值最大为10000int pages = (int) Math.ceil((double) response.getHits().getTotalHits().value / requestParam.getPageSize());result.put("total_pages",pages);result.put("size",requestParam.getPageSize());result.put("list", details);Map<String, Object> stuAttendanceListJsonByStuIdMap = getStuAttendanceListJsonByStuIdMap(requestParam);result.put("stu_id", stuAttendanceListJsonByStuIdMap.get("stu_id"));result.put("total_num", stuAttendanceListJsonByStuIdMap.get("total_num"));result.put("yes_num", stuAttendanceListJsonByStuIdMap.get("yes_num"));result.put("late_num", stuAttendanceListJsonByStuIdMap.get("late_num"));result.put("no_num", stuAttendanceListJsonByStuIdMap.get("no_num"));result.put("yes_lv", stuAttendanceListJsonByStuIdMap.get("yes_lv"));result.put("late_lv", stuAttendanceListJsonByStuIdMap.get("late_lv"));result.put("no_lv", stuAttendanceListJsonByStuIdMap.get("no_lv"));return BaseResponseBuilder.success(result);} catch (Exception e) {return BaseResponseBuilder.failure("查询失败", e.getMessage());}
}

接口三：根据课程分组筛选获取满勤数和非满勤数

对应的sql（满勤数）（也可以使用case操作用一条sql统计出两个数）

SELECT
count( 1 ) AS course_yes_num
FROM
(
SELECT
FORMAT( ifnull((( ifnull( sum( sign_status ), 0 ))/ count( s.id )* 100 ), 0 ), 1 ) AS yes_lv
FROM
eschool.stu_sign s
<where>AND s.class_begin_time &lt; now()<if test="t.beginDate!=null and t.beginDate!=''">and s.class_begin_time &gt; CONCAT(#{t.beginDate},' 00:00:01')</if><if test="t.endDate!=null and t.endDate!=''">and s.class_begin_time &lt; CONCAT(#{t.endDate},' 23:59:59')</if><if test="t.dormId!=null and t.dormId!=''">and s.classroom_id in (select id from eschool.class_room where uuid in(${t.dormId}))</if>
</where>
GROUP BY s.course_id ) t
where t.yes_lv='100.0'

java代码

public Long getCourseYesNumByES(SchoolReportRequest requestParam){try {SearchRequest searchRequest = new SearchRequest("stu_sign");SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();BoolQueryBuilder boolQueryBuilder = QueryBuilders.boolQuery();RangeQueryBuilder timeRangeQuery = QueryBuilders.rangeQuery("class_begin_time").lte("now");if (requestParam.getBeginDate() != null && requestParam.getEndDate() != null) {// 添加日期格式化，匹配yyyy-MM-dd HH:mm:ss格式String gte = requestParam.getBeginDate() + " 00:00:00";String lte = requestParam.getEndDate() + " 23:59:59";timeRangeQuery.gte(gte).lte(lte);}boolQueryBuilder.must(timeRangeQuery);if(StringUtils.isNotBlank(requestParam.getDormId())){List<String> classroomIds = attendanceMapper.getClassroomIdByDormId(requestParam.getDormId());boolQueryBuilder.must(QueryBuilders.termsQuery("classroom_id.keyword", classroomIds));}searchSourceBuilder.query(boolQueryBuilder);searchSourceBuilder.size(0);// 聚合：统计课程出勤百分比Map<String, String> bucketsPathsMap = new HashMap<>();bucketsPathsMap.put("sum_sign", "sum_sign");bucketsPathsMap.put("count_total", "count_total");TermsAggregationBuilder courseAgg = AggregationBuilders.terms("perfect_courses").field("course_id").size(10000)  // 根据实际课程数量调整.subAggregation(AggregationBuilders.sum("sum_sign").field("sign_status")).subAggregation(AggregationBuilders.sum("sum_late").field("late_status")).subAggregation(AggregationBuilders.count("count_total").field("id")).subAggregation(PipelineAggregatorBuilders.bucketScript("attendance_percentage",bucketsPathsMap,new Script(" params.sum_sign  / params.count_total * 100")));Map<String, String> pipelineBucketsPathsMap = new HashMap<>();pipelineBucketsPathsMap.put("attendance_percent", "attendance_percentage");//管道聚合筛选courseAgg.subAggregation(PipelineAggregatorBuilders.bucketSelector("attendance_percentage_100_filter",pipelineBucketsPathsMap,new Script("params.attendance_percent == 100.0")));searchSourceBuilder.aggregation(courseAgg);//管道聚合（最大值、平均值、最小值。。。）searchSourceBuilder.aggregation(PipelineAggregatorBuilders.statsBucket("attendance_percentage_100_count","perfect_courses._count"));searchRequest.source(searchSourceBuilder);SearchResponse response = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);Aggregations aggregations = response.getAggregations();ParsedStatsBucket attendancePercentage100Count = aggregations.get("attendance_percentage_100_count");return attendancePercentage100Count.getCount();} catch (Exception e) {throw new RuntimeException(e);}
}
public Long getCourseNoNumByES(SchoolReportRequest requestParam){try {SearchRequest searchRequest = new SearchRequest("stu_sign");SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();BoolQueryBuilder boolQueryBuilder = QueryBuilders.boolQuery();RangeQueryBuilder timeRangeQuery = QueryBuilders.rangeQuery("class_begin_time").lte("now");if (requestParam.getBeginDate() != null && requestParam.getEndDate() != null) {// 添加日期格式化，匹配yyyy-MM-dd HH:mm:ss格式String gte = requestParam.getBeginDate() + " 00:00:00";String lte = requestParam.getEndDate() + " 23:59:59";timeRangeQuery.gte(gte).lte(lte);}boolQueryBuilder.must(timeRangeQuery);if(StringUtils.isNotBlank(requestParam.getDormId())){List<String> classroomIds = attendanceMapper.getClassroomIdByDormId(requestParam.getDormId());boolQueryBuilder.must(QueryBuilders.termsQuery("classroom_id", classroomIds));}searchSourceBuilder.query(boolQueryBuilder);searchSourceBuilder.size(0);// 聚合：统计课程出勤百分比Map<String, String> bucketsPathsMap = new HashMap<>();bucketsPathsMap.put("sum_sign", "sum_sign");bucketsPathsMap.put("count_total", "count_total");TermsAggregationBuilder courseAgg = AggregationBuilders.terms("perfect_courses").field("course_id").size(10000)  // 根据实际课程数量调整.subAggregation(AggregationBuilders.sum("sum_sign").field("sign_status")).subAggregation(AggregationBuilders.sum("sum_late").field("late_status")).subAggregation(AggregationBuilders.count("count_total").field("id")).subAggregation(PipelineAggregatorBuilders.bucketScript("attendance_percentage",bucketsPathsMap,new Script(" params.sum_sign  / params.count_total * 100")));//管道聚合筛选Map<String, String> pipelineBucketsPathsMap = new HashMap<>();pipelineBucketsPathsMap.put("attendance_percent", "attendance_percentage");//管道聚合筛选courseAgg.subAggregation(PipelineAggregatorBuilders.bucketSelector("attendance_percentage_100_filter",pipelineBucketsPathsMap,new Script("params.attendance_percent < 100.0")));searchSourceBuilder.aggregation(courseAgg);//管道聚合（最大值、平均值、最小值。。。）searchSourceBuilder.aggregation(PipelineAggregatorBuilders.statsBucket("attendance_percentage_no_100_count","perfect_courses._count"));searchRequest.source(searchSourceBuilder);SearchResponse response = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);Aggregations aggregations = response.getAggregations();ParsedStatsBucket attendancePercentageNo100Count = aggregations.get("attendance_percentage_no_100_count");return attendancePercentageNo100Count.getCount();} catch (Exception e) {throw new RuntimeException(e);}
}

接口四：根据stu_id分组筛选获取满勤数和非满勤数

sql如下：

SELECT
count( 1 ) AS stu_yes_num
FROM
(
SELECT
FORMAT( ifnull((( ifnull( sum( sign_status ), 0 ))/ count( s.id )* 100 ), 0 ), 1 ) AS yes_lv
FROM
eschool.stu_sign s
<where>AND s.class_begin_time &lt; now()<if test="t.beginDate!=null and t.beginDate!=''">and s.class_begin_time &gt; CONCAT(#{t.beginDate},' 00:00:01')</if><if test="t.endDate!=null and t.endDate!=''">and s.class_begin_time &lt; CONCAT(#{t.endDate},' 23:59:59')</if><if test="t.dormId!=null and t.dormId!=''">and s.classroom_id in (select id from eschool.class_room where uuid in(${t.dormId}))</if>
</where>
GROUP BY s.stu_id ) t
where t.yes_lv ='100.0'