ElasticSearch 聚合查询 JavaApi
ES 聚合查询Java Api
分页查询，按照时间进行分组查询求平均(多平均)，按照某一字段分组求聚合等等
- 分页查询
SysUser loginUser = SecurityUtils.getLoginUser().getUser();
Long userId = loginUser.getUserId();
LambdaQueryChainWrapper<Warning> query = warningService.lambdaQuery();
if (req.getStatus()!=null && req.getStatus().size() > 0){
if (req.getStatus().contains(null)){
throw new BaseException("错误的'处理状态'字段信息！");
}else {
query.in(Warning::getProcessStatus, req.getStatus());
}
}
//query.in(req.getStatus()!=null && req.getStatus().size() > 0,Warning::getProcessStatus, req.getStatus());
query.eq(StringUtils.isNotEmpty(req.getSiteId()), Warning::getDeptId, req.getSiteId());
query.like(StringUtils.isNotEmpty(req.getDevCode()), Warning::getDevCode, req.getDevCode());
query.like(StringUtils.isNotEmpty(req.getDevName()), Warning::getDevName, req.getDevName());
List<WarningProcess> processes = warningProcessService.getWarningProcess(userId);
if (processes == null || processes.size() == 0)// return new TableDataInfo();//没有处理人的话，就按照当前登录人的站点权限过滤
{
List<Long> userDepts = userService.queryUserDepts(userId);
query.in(Warning::getDeptId, userDepts);
}
else{
List<Long> warnIds = processes.stream().map(m -> m.getWarnId()).collect(Collectors.toList());
query.in(CollectionUtils.isNotEmpty(warnIds), Warning::getId, warnIds);
}
query.orderByDesc(Warning::getWarnTime);
TableDataInfo data = warningService.page(req, query);
List<SysDept> depts = sysDeptService.list();
data.getRows().stream().forEach(item -> {
Warning warnItem = (Warning) item;
SysDept dept = depts.stream().filter(m -> m.getDeptId().equals(warnItem.getDeptId())).findFirst().orElse(null);
if (null != dept) {
warnItem.setDeptName(dept.getDeptName());
}
});
return data;
mybatisPlus 转换成es查询的JavaApi
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder()
//从哪到哪
.from((req.getPageNum() - 1) * req.getPageSize())
//数量
.size(req.getPageSize())
//按照warn_time 倒序排序
.sort("warn_time", SortOrder.DESC)
.trackTotalHits(true);
BoolQueryBuilder boolQueryBuilder = QueryBuilders.boolQuery();
//相当于sql 的 in 操作
if (req.getStatus()!=null && req.getStatus().size() > 0){
boolQueryBuilder.filter(QueryBuilders.termsQuery("process_status",req.getStatus()));
}
//term 精确匹配
if (StringUtils.isNotEmpty(req.getSiteId())){
boolQueryBuilder.filter(QueryBuilders.termQuery("dept_id",req.getSiteId()));
}
//模糊查询
if (StringUtils.isNotEmpty(req.getDevCode())){
boolQueryBuilder.filter(QueryBuilders.wildcardQuery("dev_code.keyword","*"+req.getDevCode()+"*"));
}
if (StringUtils.isNotEmpty(req.getDevName())){
boolQueryBuilder.filter(QueryBuilders.wildcardQuery("dev_name.keyword","*"+req.getDevName()+"*"));
}
List<WarningProcess> processes = warningProcessService.getWarningProcess(userId);
if (processes == null || processes.size() == 0)// return new TableDataInfo();//没有处理人的话，就按照当前登录人的站点权限过滤
{
List<Long> userDepts = userService.queryUserDepts(userId);
boolQueryBuilder.filter(QueryBuilders.termsQuery("dept_id.keyword",userDepts));
}
else{
List<Long> warnIds = processes.stream().map(m -> m.getWarnId()).collect(Collectors.toList());
if (CollectionUtils.isNotEmpty(warnIds)){
//ES in操作 termsQuery
boolQueryBuilder.filter(QueryBuilders.termsQuery("id",warnIds));
}
}
//进行查询
searchSourceBuilder.query(boolQueryBuilder);
//返回结果
SearchResponse searchResponse = EsClintUtil.execSearch(restHighLevelClient,searchSourceBuilder, index);
//返回总数
long total = searchResponse.getHits().getTotalHits();
List<Warning> list = new ArrayList<>();
final SearchHit[] searchHits = searchResponse.getHits().getHits();
for (SearchHit searchHit : searchHits) {
list.add(JSON.parseObject(searchHit.getSourceAsString(), Warning.class));
}
//返回自定义表格信息
TableDataInfo info = new TableDataInfo(list, (int) total);
- 桶聚合
SELECT
dept_name,
count(d1.id) as imgcount,
count(distinct d1.device_code) as imgcount1,
sum(case d1.`status` when '1' then 1 ELSE 0 END) as warningCount
FROM sys_dept s1
LEFT JOIN dev_shock_data d1 ON s1.dept_id = d1.dept_id
where s1.dept_id!=100
GROUP BY s1.dept_name
数据库的sql对应的Java代码
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
BoolQueryBuilder boolQueryBuilder = QueryBuilders.boolQuery();
boolQueryBuilder.mustNot(QueryBuilders.termQuery("dept_id", 100));
searchSourceBuilder.query(boolQueryBuilder);
searchSourceBuilder.size(0);//不输出原始数据
//按照站点分组
TermsAggregationBuilder aggregationBuilder = AggregationBuilders
.terms("deptgroup").field("dept_id") //桶分组
.subAggregation(AggregationBuilders.terms("statusgroup").field("status.keyword"))
//设备个数去重数量
.subAggregation(AggregationBuilders.cardinality("imgcount1").field("device_code.keyword"))
.size(5000);
searchSourceBuilder.aggregation(aggregationBuilder);
SearchResponse searchResponse = EsClintUtil.execSearch(restHighLevelClient,searchSourceBuilder, "dev_shock_data");
// 遍历封装列表对象
List<ImageStatisticRes> resList=new ArrayList<>();
Terms parsedStringTerms =searchResponse.getAggregations().get("deptgroup");
List<? extends Terms.Bucket> buckets = parsedStringTerms.getBuckets();
Map<String,String> deptMap= EsClintUtil.getDepts(restHighLevelClient);
List<String> list = new ArrayList<>();
for (Terms.Bucket bucket : buckets) {
//key的数据
String key = bucket.getKey().toString();
long docCount = bucket.getDocCount();
//获取数据
ImageStatisticRes res = new ImageStatisticRes();
res.setSiteName(deptMap.get(key));
res.setImageCount((int) docCount);
//获取设备个数
Cardinality imagecount1 = bucket.getAggregations().get("imgcount1");
res.setImageCount1((int) imagecount1.getValue());
Terms statusgroupTearms = bucket.getAggregations().get("statusgroup");
for (Terms.Bucket statusBucket : statusgroupTearms.getBuckets()) {
if (statusBucket.getKey().equals("1")) {
res.setImageWarningCount((int) statusBucket.getDocCount());
}
}
resList.add(res);
list.add(key);
}
//获取到总的站台数据
final List<String> deptIds = deptMap.keySet().stream().collect(Collectors.toList());
//获取差集
final List<String> collect = deptIds.stream()
.filter(item -> !list.contains(item))
.collect(Collectors.toList());
//遍历得到的差集就是不存在站台数据的
for (String s : collect) {
ImageStatisticRes res = new ImageStatisticRes();
res.setSiteName(deptMap.get(s));
res.setImageCount(0);
res.setImageWarningCount(0);
resList.add(res);
}
return resList;
- 时间聚合分组
SELECT HOUR (create_time) khour ,avg(angle_x) averageX, avg(angle_y) averageY, avg(angle_z) averageZ from dev_shock_data
where device_id=#{deviceId} and create_time >#{startTime} and create_time <#{endTime}
group by HOUR (create_time)
order by khour
数据库的sql转换成es对应的JavaApi
final ArrayList<GroupByHour> groupByHours = new ArrayList<>();
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder()
.sort("create_time", SortOrder.ASC)
.trackTotalHits(true);
BoolQueryBuilder boolQueryBuilder = QueryBuilders.boolQuery();
boolQueryBuilder.must(QueryBuilders.termQuery("device_id",deviceId));
boolQueryBuilder.filter(QueryBuilders.rangeQuery("create_time").gt(startTime).lt(endTime));
searchSourceBuilder.size(0);
searchSourceBuilder.query(boolQueryBuilder);
AvgAggregationBuilder averageX = AggregationBuilders.avg("averageX").field(x);
AvgAggregationBuilder averageY = AggregationBuilders.avg("averageY").field(y);
AvgAggregationBuilder averageZ = AggregationBuilders.avg("averageZ").field(z);
AggregationBuilder groupTime = AggregationBuilders.dateHistogram("khour")
.field("create_time") // 根据date字段值，对数据进行分组
// 时间分组间隔：DateHistogramInterval.* 序列常量，支持每月，每年，每天等等时间间隔
.dateHistogramInterval(DateHistogramInterval.HOUR)
// 设置返回结果中桶key的时间格式
.format("HH")
// .timeZone(DateTimeZone.forTimeZone(TimeZone.getTimeZone("GMT%2B8")))
// .timeZone(DateTimeZone.forTimeZone(TimeZone.getTimeZone("GMT+8:00")))
.minDocCount(0L)
.subAggregation(averageX)
.subAggregation(averageY)
.subAggregation(averageZ);
searchSourceBuilder.aggregation(groupTime);
final SearchResponse dev_shock_data = EsClintUtil.execSearch(restHighLevelClient, searchSourceBuilder, "dev_shock_data");
ParsedDateHistogram khour = dev_shock_data.getAggregations().get("khour");
final List<? extends Histogram.Bucket> buckets1 = khour.getBuckets();
for (Histogram.Bucket bucket : buckets1) {
final GroupByHour groupByHour = new GroupByHour();
if(bucket.getDocCount()>0){
groupByHour.setHour(Integer.parseInt(bucket.getKeyAsString()));
Avg xAvg = bucket.getAggregations().get("averageX");
Avg yAvg = bucket.getAggregations().get("averageY");
Avg zAvg = bucket.getAggregations().get("averageZ");
groupByHour.setAverageX(xAvg.getValue());
groupByHour.setAverageY(yAvg.getValue());
groupByHour.setAverageZ(zAvg.getValue());
groupByHours.add(groupByHour);
}
}
return groupByHours;