1、条件查询 bool
must：返回的文档必须满足子句的条件，并且参与计算分值
filter：返回的文档必须满足filter子句的条件，不会参与计算分值
should：返回的文档可能满足should子句的条件。
must_nout：返回的文档必须不满足must_not定义的条件。
注意：如果一个查询既有filter又有should，那么至少包含一个should子句。
bool 查询
user 值为kimchy tag 值为tech
"query": {
"bool" : {
"must" : {
"term" : { "user" : "kimchy" }
},
"filter": {
"term" : { "tag" : "tech" }
},
"must_not" : {
"range" : {
"age" : { "from" : 10, "to" : 20 }
}
},
"should" : [
{"term" : { "tag" : "wow" }},
{"term" : { "tag" : "elasticsearch" }}
]
}
过滤不存在数据
"query": {
"bool":{
"filter":{
"exists":{
"field":"subject" }
}
}
}
统计某个字段出现的次数
size 0 不需要返回文档数据，只需要值
"size": 0,
"query": {
"bool":{
"filter":{
"exists":{
"field":"proofreadresult" }
}
}
}
返回 某个字段 ischeck值为false 的数量
"size": 0,
"query": {
"bool":{
"must": [{"match": {"ischeck": "false"}}],
}
}
}
"size": 0,
"query": {
"bool":{
"must": {"term" : { "ischeck" : "false" }}
}
}
}
返回的数据 value 就是我们需要的数据
{
"took" : 0,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 3476,
"relation" : "eq"
},
"max_score" : null,
"hits" : [ ]
}
}
2、字段过滤
过滤字段不存在的数据，filter + exists
使用 exists 进行过滤掉字段不存在的数据
"size": 0,
"query": {
"bool":{
"filter":{"exists":{"field":"subject" }},
"must": [{"range": {"createtime": {
"gte": 1654012800000,
"lte": 1655308799000}}
}]
}
}
3、聚合查询
1）分组 https://blog.csdn.net/cainiao1412/article/details/120876972
聚合分组查询，使用terms，按照某个字段中的值来分类，通过size的值来确定返回文档的数量，如果不指定值，默认返回10个
Es query 中，使用 term 进行精准查询，不会对字段进行分词，
使用terms，进行多个条件查询，类似 in
使用 script 进行多个字段 分组的实现，通过需要自己进行split处理
对uid进行分组
"aggs": {
"result": {
"terms": {
"field": "uid",
"size": 2147483647
}
}
}
对 uid+subject 进行分组 通过 size 指定大小
"aggs": {
"result": {
"terms": {
"script": { "inline": "doc['uid'].value +'-'+ doc['subject'].value"},
"size": 40
}
}
}
2）聚合查询先进行过滤，然后分组
size 表示query返回的数据
subject 存在的数据中 按照 uid-subject 分组数据
"size": 0,
"aggs": {
"filer-subject" : {
"filter": {
"bool" : {
"filter" : [
{"exists":{"field":"subject"}}
]
}
},
"aggs": {
"result" : {
"terms": {
"script": { "inline": "doc['uid'].value +'-'+ doc['subject'].value"},
"size": 40
}
}
}
}
}
``
# 返回的数据
```bash
"aggregations" : {
"filer-subject" : {
"doc_count" : 3557,
"result" : {
"doc_count_error_upper_bound" : 0,
"sum_other_doc_count" : 988,
"buckets" : [
{
"key" : "209372605317121-102",
"doc_count" : 794
},
{
"key" : "222580707950593-302",
"doc_count" : 447
},
{
"key" : "212246483697665-102",
"doc_count" : 374
},
{
"key" : "207843605348353-102",
"doc_count" : 328
}]
}}
对应的java代码
Script script = new Script(ScriptType.INLINE,Script.DEFAULT_SCRIPT_LANG , "doc['uid'].value+'-'+doc['subject'].value", new HashMap<>());
TermsAggregationBuilder aggregationBuilder = AggregationBuilders.terms("result").script(script).size(ESCommonConstant.ES_GROUP_QUERY_SIZE);
// search
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
searchSourceBuilder.aggregation(aggregationBuilder);
// query
BoolQueryBuilder boolQueryBuilder = QueryBuilders.boolQuery();
List<QueryBuilder> must = boolQueryBuilder.must();
if(Objects.nonNull(requestDWDProofreadRecordDTO.getStartTime()) && Objects.nonNull(requestDWDProofreadRecordDTO.getEndTime())){
must.add(QueryBuilders.rangeQuery(ProofreadDetailConstant.CREATETIME).from(requestDWDProofreadRecordDTO.getStartTime()).to(requestDWDProofreadRecordDTO.getEndTime()));
}
must.add(QueryBuilders.boolQuery().must((QueryBuilders.existsQuery("subject"))));
searchSourceBuilder.query(boolQueryBuilder);
searchSourceBuilder.size(0);
3）聚合多条件查询，并按指定的文档返回想要的数据文章来源：https://www.toymoban.com/news/detail-411885.html
"size": 0,
"aggs": {
# 该数据是 条件 ischeck 值为true，subject 存在，
# 分组 combinequestiontype分组返回总数量
"ischeck-count" : {
"filter": {
"bool" : {
"filter" : [
{"exists":{"field":"subject"}}
],
"must" : {"term" : {"ischeck" : "true"} }
}
},
"aggs": {
"result" : {
"terms": {
"field": "combinequestiontype",
"size": 30
}
}
}
},
# 该数据是 条件 proofreadresult存在，
# 分组 combinequestiontype分组返回总数
"proofreadresult-count" : {
"filter": {
"bool" : {
"filter" : [
{"exists":{"field":"proofreadresult"}}
]
}
},
"aggs": {
"result" : {
"terms": {
"field": "combinequestiontype",
"size": 30
}
}
}
},
# 该数据是 返回 isCheck 的数量
"ischeck_total": {
"terms": {
"field": "ischeck"
}
},
# 该数据是 返回 proofreadresult 字段存在 的数量
# 即就是 proofreadresult 不为空的数量
"proofreadresult_total": {
"filter": {
"bool" : {
"filter" : [
{"exists":{"field":"proofreadresult"}}
]
}
}
}
}
对应的java代码
// ischeck-count
FilterAggregationBuilder ischeckCount = AggregationBuilders.filter("ischeck-count", QueryBuilders.boolQuery()
.must(QueryBuilders.termQuery("ischeck", true))
.must(QueryBuilders.termQuery("uid", uid))
.filter(QueryBuilders.existsQuery("xxx")))
.subAggregation(AggregationBuilders.terms("result").field("xxx").size(30));
// proofreadresult-count
FilterAggregationBuilder proofreadCount = AggregationBuilders.filter("ischeck-count", QueryBuilders.boolQuery()
.must(QueryBuilders.termQuery("ischeck", true))
.must(QueryBuilders.termQuery("uid", uid))
.filter(QueryBuilders.existsQuery("xxx")));
searchSourceBuilder.aggregation(ischeckCount);
// 结果处理
List list = new ArrayList<>();
SearchResponse response = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);
Terms oneTerm = (Terms) response.getAggregations().asMap().get(“result”);
for (Terms.Bucket bucket : oneTerm.getBuckets()) {
ProofreadDetailDTO proofreadDetailDTO = new ProofreadDetailDTO();
// 此处自己split分隔处理
String[] strings = bucket.getKey().toString().split(“-”);
proofreadDetailDTO.setUid(Long.parseLong(strings[0]));
proofreadDetailDTO.setSubject(Integer.parseInt(strings[1]));
list.add(proofreadDetailDTO);
}文章来源地址https://www.toymoban.com/news/detail-411885.html
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