1.通过id且设置显示的字段查询
{ "_source" : {
"includes" : [
"id",
"title"
],
"excludes" : [ "content"]
},
"query": {
"term": {
"id": "282f85c59020c903e8adff91802815f0"
}
}
}
2.通过时间范围查询：//注意日期加引号
{
"query": {
"bool": {
"must": [
{
"range": {
"createtime": {
"format": "yyyy-MM-dd HH:mm:ss",
"from": "2017-12-14 16:25:26",
"to": "2017-12-14 17:25:26",
"include_lower": true,
"include_upper": false
}
}
}
]
}
}
}
或者
{
"query": {
"bool": {
"must": [
{
"range": {
"createtime": {
"gt": "2017-12-14 16:25:26",
"lte": "2017-12-14 17:25:26",
"include_lower": true,
"include_upper": false
}
}
}
]
}
}
}
3.通过数字区间范围查询
{
"query": {
"bool": {
"must": [
{
"range": {
"similarValue": {
"from": 0.1,
"to": 1,
"include_lower": true,
"include_upper": true
}
}
}
]
}
}
}
4.通过多条件查询，并且是“与”关系
{
"query": {
"bool": {
"must": [
{
"range": {
"similarValue": {
"from": 0.1,
"to": 1,
"include_lower": true,
"include_upper": true
}
}
},
{
"term": {
"dataSource": "财新网"
}
}
]
}
}
}
5.带分页的模糊查询
title字段：分词
{
"from": 10,
"size": 20,
"query": {
"match": {
"title": "中国杭州"
}
}
}
contentType:不分词，必须全词条匹配
{
"query": {
"match": {
"contentType": "企业新闻"
}
}
}
6.带操作符的模糊查询，该参数的默认值是"or"，变为"and"来要求所有的词条都需要被匹配，提高精确度。
{
"query": {
"match": {
"title": {
"query": "中大国际",
"operator": "and"
}
}
}
}
或通过百分比，来控制相关匹配度。
{
"query": {
"match": {
"title": {
"query": "中大国际",
"minimum_should_match": "75%"
}
}
}
}
7.match_phrase短语查询
{
"from": "10",
"size": "30",
"query": {
"match_phrase": {
"title": {
"query": "中国发展",
"slop": 1
}
}
}
}
另一种写法：
{
"query": {
"match": {
"title": {
"query": "中国发展",
"type": "phrase"
}
}
}
}
8.bool 联合查询
{
"query": {
"bool": {
"must": {
"match_phrase": {
"content": "宝马"
}
},
"must_not": {
"term": {
"contentType": "企业新闻"
}
}
}
}
}
9. 带分页带排序
{
"from": "0",
"size": "10",
"sort": [
{
"pubdate": "asc"
}
],
"query": {
"bool": {
"must": {
"match_phrase": {
"content": "宝马"
}
},
"must_not": {
"term": {
"contentType": "企业新闻"
}
}
}
}
}
10 range 范围查询
{
"query": {
"range": {
"pubdate": {
"gte": "2017-10-23"
}
}
}
}
11.多个bool关系的查询
{
"from": 10,
"size": 30,
"_source": {
"includes": [
"id",
"subLabelTypes",
"subEnterpriseName"
]
},
"query": {
"bool": {
"must": [
{
"term": {
"contentType": "企业风控"
}
},
{
"bool": {
"should": [
{
"match_phrase": {
"subLabelTypes": "延期付款付息"
}
},
{
"match_phrase": {
"subLabelTypes": "变更募资用途"
}
},
{
"match_phrase": {
"subLabelTypes": "延迟披露财报"
}
},
{
"match_phrase": {
"subLabelTypes": "兑付存在不确定性"
}
}
]
}
}
]
}
}
}
11.聚合操作，相当于mysql中的group by，求dataSource有哪些类型
{
"size": 0,
"aggs": {
"agg_data": {
"terms": {
"field": "dataSource",
"size":1000
}
}
}
}
12.求的最大值similarValue
{
"size": 0,
"aggs": {
"agg_sim": {
"sum": {
"field": "similarValue"
}
}
}
}
13.求dataSource的所有数据类型中similarValue的最小值是？
{
"size": 0,
"aggs": {
"agg_data": {
"terms": {
"field": "dataSource",
"size":1000
}
},
"agg_similarValue": {
"sum": {
"field": "similarValue"
}
}
}
}
14.求datasource中各个数据类型的最小值
{
"size": "0",
"aggregations": {
"agg_data": {
"terms": {
"field": "dataSource",
"size": 1000
},
"aggregations": {
"agg_similarValue": {
"sum": {
"field": "similarValue"
}
}
}
}
},
"ext": {}
}
15.contentType为企业风控的数据中，similarValue的平均值
{
"query": {
"term": {
"contentType": "企业风控"
}
},
"size": 0,
"aggs": {
"agg_age": {
"avg": {
"field": "similarValue"
}
}
}
}
16 查询某个企业中企业风控数据类型，在各个时间段入库数量
{
"query": {
"bool": {
"must": [
{
"term": {
"contentType": {
"value": "企业风控"
}
}
},
{
"match_phrase": {
"subEnterpriseName": {
"query": "乐视网信息技术(北京)股份有限公司"
}
}
}
]
}
},
"aggregations": {
"agg_date": {
"date_range": {
"field": "createtime",
"format": "yyyy-MM-dd HH:mm:ss",
"ranges": [
{
"to": "2017-12-31 23:59:59"
},
{
"from": "2018-01-01 01:00:00",
"to": "2018-01-09 00:00:00"
},
{
"from": "2018-01-10 00:00:00"
}
]
}
}
}
}
17.企业风控数据类型，各个相似值的数量
{
"query": {
"term": {
"contentType": "企业风控"
}
},
"size": "0",
"aggs": {
"agg_similarValue": {
"range": {
"field": "similarValue",
"ranges": [
{
"to": "0.6"
},
{
"from": 0.6,
"to": 0.9
},
{
"from": "1"
}
]
}
}
}
}
18.查询各个标签的数量 ，按统计量倒序排列
{
"size": 0,
"aggs": {
"agg_data": {
"terms": {
"field": "subLabelTypes.subLabelTypes_raw",
"size": 1000000,
"order": {
"_count": "desc"
}
}
}
}
}
19 查询某个企业在某个时间段的分组
{
"query": {
"bool": {
"must": [
{
"term": {
"contentType": "企业风控"
}
},
{
"match_phrase": {
"subEnterpriseName": "乐视网信息技术(北京)股份有限公司"
}
},
{
"range": {
"createtime": {
"gte": "2018-01-11 00:25:26",
"lte": "2018-01-12 17:25:26",
"include_lower": true,
"include_upper": true
}
}
}
]
}
},
"size": 0,
"aggs": {
"agg_data": {
"terms": {
"field": "subLabelTypes.subLabelTypes_raw",
"size": 1000,
"order": {
"_count": "desc"
}
}
}
}
}
20 以年月日，进行分组统计
以天：
{
"size": 0,
"aggs": {
"agg_age": {
"date_histogram": {
"field": "createtime",
"interval": "day",
"format": "yyyy-MM-dd",
"min_doc_count": 1,
"order": {
"_count": "desc"
}
}
}
}
}
以月：
{
"size": 0,
"aggs": {
"agg_age": {
"date_histogram": {
"field": "createtime",
"interval": "month",
"format": "yyyy-MM",
"min_doc_count": 1,
"order": {
"_count": "desc"
}
}
}
}
}
以年：
{
"size": 0,
"aggs": {
"agg_age": {
"date_histogram": {
"field": "createtime",
"interval": "year",
"format": "yyyy",
"min_doc_count": 1,
"order": {
"_count": "desc"
}
}
}
}
}
21.查询某个企业数据类型为“企业风控”的数据以天为单位统计每种标签类型的数据量。如果按时间排序将order中_count改为_key
//"min_doc_count":1; 值>=1的数据才显示
{
"query": {
"bool": {
"must": [
{
"term": {
"contentType": "企业风控"
}
},
{
"match_phrase": {
"subEnterpriseName": "乐视网信息技术(北京)股份有限公司"
}
}
,
{
"range": {
"createtime": {
"from": "2017-12",
"to": "2018-01",
"format": "yyyy-MM",
"include_lower": true,
"include_upper": true,
"boost": 1
}
}
}
]
}
},
"size": 0,
"aggs": {
"agg_date": {
"date_histogram": {
"field": "createtime",
"interval": "day",
"format": "yyyy-MM-dd",
"min_doc_count": 1,
"order": {
"_count": "desc"
}
},
"aggs": {
"agg_lable": {
"terms": {
"field": "subLabelTypes.subLabelTypes_raw",
"size": 1000,
"order": {
"_count": "desc"
}
}
}
}
}
}
}
22.以年
{
"query": {
"bool": {
"must": [
{
"term": {
"contentType": "企业风控"
}
},
{
"match_phrase": {
"subEnterpriseName": "乐视网信息技术(北京)股份有限公司"
}
}
]
}
},
"size": 0,
"aggs": {
"agg_date": {
"date_histogram": {
"field": "createtime",
"interval": "year",
"format": "yyyy",
"min_doc_count": 1,
"order": {
"_count": "desc"
}
},
"aggs": {
"agg_lable": {
"terms": {
"field": "subLabelTypes.subLabelTypes_raw",
"size": 1000,
"order": {
"_count": "desc"
}
}
}
}
}
}
}
23
{
"query": {
"bool": {
"must": [
{
"term": {
"contentType": "企业风控"
}
},
{
"match_phrase": {
"subEnterpriseName": "乐视网信息技术(北京)股份有限公司"
}
},
{
"range": {
"createtime": {
"from": "2017-11",
"to": "2018-02",
"format": "yyyy-MM",
"include_lower": true,
"include_upper": true,
"boost": 1
}
}
}
]
}
},
"size": 0,
"aggs": {
"agg_date": {
"date_histogram": {
"field": "createtime",
"interval": "month",
"format": "yyyy-MM",
"min_doc_count": 1,
"order": {
"_count": "desc"
}
},
"aggs": {
"agg_lable": {
"terms": {
"field": "subLabelTypes.subLabelTypes_raw",
"size": 1000,
"order": {
"_count": "desc"
}
}
}
}
}
}
}
DSL 各种查询例子:
http://blog.csdn.net/wthfeng/article/details/52953317
{
"size": 0,
"aggs": {
"agg_data": {
"terms": {
"field": "subLabelTypes.subLabelTypes_raw",
"size": 1000000,
"order": {
"_count": "desc"
}
}
}
}
}
不包含某个标签
{
"_source": {
"includes": [
"id",
"subLabelTypes"
]
},
"query": {
"bool": {
"must": [
{
"range": {
"createtime": {
"format": "yyyy-MM-dd HH:mm:ss",
"from": "2018-05-08 00:25:26",
"to": "2018-05-08 23:25:26",
"include_lower": true,
"include_upper": false
}
}
},
{
"term": {
"contentType": "企业风控"
}
}
],
"must_not": {
"match_phrase": {
"subLabelTypes": "企业风险"
}
}
}
}
}
