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我们知道在sql
中是可以实现 group by 字段a,字段b
,那么这种效果在elasticsearch
中该如何实现呢?此处我们记录在elasticsearch
中的3种方式来实现这个效果。
图片来源:https://www.elastic.co/guide/en/elasticsearch/reference/current/search-aggregations-bucket-terms-aggregation.html
从上图中,我们可以知道,可以通过3种方式来实现 多字段的聚合操作。
根据省(province
)和性别(sex
)来进行聚合,然后根据聚合后的每个桶的数据,在根据每个桶中的最大年龄(age
)来进行倒序排序。
PUT /index_person { "settings": { "number_of_shards": 1 }, "mappings": { "properties": { "id": { "type": "long" }, "name": { "type": "keyword" }, "province": { "type": "keyword" }, "sex": { "type": "keyword" }, "age": { "type": "integer" }, "address": { "type": "text", "analyzer": "ik_max_word", "fields": { "keyword": { "type": "keyword", "ignore_above": 256 } } } } } }
PUT /_bulk
{"create":{"_index":"index_person","_id":1}}
{"id":1,"name":"张三","sex":"男","age":20,"province":"湖北","address":"湖北省黄冈市罗田县匡河镇"}
{"create":{"_index":"index_person","_id":2}}
{"id":2,"name":"李四","sex":"男","age":19,"province":"江苏","address":"江苏省南京市"}
{"create":{"_index":"index_person","_id":3}}
{"id":3,"name":"王武","sex":"女","age":25,"province":"湖北","address":"湖北省武汉市江汉区"}
{"create":{"_index":"index_person","_id":4}}
{"id":4,"name":"赵六","sex":"女","age":30,"province":"北京","address":"北京市东城区"}
{"create":{"_index":"index_person","_id":5}}
{"id":5,"name":"钱七","sex":"女","age":16,"province":"北京","address":"北京市西城区"}
{"create":{"_index":"index_person","_id":6}}
{"id":6,"name":"王八","sex":"女","age":45,"province":"北京","address":"北京市朝阳区"}
GET /index_person/_search { "size": 0, "aggs": { "agg_province_sex": { "multi_terms": { "size": 10, "shard_size": 25, "order":{ "max_age": "desc" }, "terms": [ { "field": "province", "missing": "defaultProvince" }, { "field": "sex" } ] }, "aggs": { "max_age": { "max": { "field": "age" } } } } } }
@Test @DisplayName("多term聚合-根据省和性别聚合,然后根据最大年龄倒序") public void agg01() throws IOException { SearchRequest searchRequest = new SearchRequest.Builder() .size(0) .index("index_person") .aggregations("agg_province_sex", agg -> agg.multiTerms(multiTerms -> multiTerms.terms(term -> term.field("province")) .terms(term -> term.field("sex")) .order(new NamedValue<>("max_age", SortOrder.Desc)) ) .aggregations("max_age", ageAgg -> ageAgg.max(max -> max.field("age"))) ) .build(); System.out.println(searchRequest); SearchResponse<Object> response = client.search(searchRequest, Object.class); System.out.println(response); }
GET /index_person/_search { "size": 0, "runtime_mappings": { "runtime_province_sex": { "type": "keyword", "script": """ String province = doc['province'].value; String sex = doc['sex'].value; emit(province + '|' + sex); """ } }, "aggs": { "agg_province_sex": { "terms": { "field": "runtime_province_sex", "size": 10, "shard_size": 25, "order": { "max_age": "desc" } }, "aggs": { "max_age": { "max": { "field": "age" } } } } } }
@Test @DisplayName("多term聚合-根据省和性别聚合,然后根据最大年龄倒序") public void agg02() throws IOException { SearchRequest searchRequest = new SearchRequest.Builder() .size(0) .index("index_person") .runtimeMappings("runtime_province_sex", field -> { field.type(RuntimeFieldType.Keyword); field.script(script -> script.inline(new InlineScript.Builder() .lang(ScriptLanguage.Painless) .source("String province = doc['province'].value;\n" + " String sex = doc['sex'].value;\n" + " emit(province + '|' + sex);") .build())); return field; }) .aggregations("agg_province_sex", agg -> agg.terms(terms -> terms.field("runtime_province_sex") .size(10) .shardSize(25) .order(new NamedValue<>("max_age", SortOrder.Desc)) ) .aggregations("max_age", minAgg -> minAgg.max(max -> max.field("age"))) ) .build(); System.out.println(searchRequest); SearchResponse<Object> response = client.search(searchRequest, Object.class); System.out.println(response); }
我本地测试过,通过copyto没实现,此处故先不考虑
实现思路:
创建mapping时,多创建一个字段pipeline_province_sex
,该字段的值由创建数据时指定pipeline
来生产。
PUT /index_person { "settings": { "number_of_shards": 1 }, "mappings": { "properties": { "id": { "type": "long" }, "name": { "type": "keyword" }, "province": { "type": "keyword" }, "sex": { "type": "keyword" }, "age": { "type": "integer" }, "pipeline_province_sex":{ "type": "keyword" }, "address": { "type": "text", "analyzer": "ik_max_word", "fields": { "keyword": { "type": "keyword", "ignore_above": 256 } } } } } }
此处指定了一个字段pipeline_province_sex
,该字段的值会由pipeline
来处理。
PUT _ingest/pipeline/pipeline_index_person_provice_sex { "description": "将provice和sex的值拼接起来", "processors": [ { "set": { "field": "pipeline_province_sex", "value": ["{{province}}", "{{sex}}"] }, "join": { "field": "pipeline_province_sex", "separator": "|" } } ] }
PUT /_bulk?pipeline=pipeline_index_person_provice_sex
{"create":{"_index":"index_person","_id":1}}
{"id":1,"name":"张三","sex":"男","age":20,"province":"湖北","address":"湖北省黄冈市罗田县匡河镇"}
{"create":{"_index":"index_person","_id":2}}
{"id":2,"name":"李四","sex":"男","age":19,"province":"江苏","address":"江苏省南京市"}
{"create":{"_index":"index_person","_id":3}}
{"id":3,"name":"王武","sex":"女","age":25,"province":"湖北","address":"湖北省武汉市江汉区"}
{"create":{"_index":"index_person","_id":4}}
{"id":4,"name":"赵六","sex":"女","age":30,"province":"北京","address":"北京市东城区"}
{"create":{"_index":"index_person","_id":5}}
{"id":5,"name":"钱七","sex":"女","age":16,"province":"北京","address":"北京市西城区"}
{"create":{"_index":"index_person","_id":6}}
{"id":6,"name":"王八","sex":"女","age":45,"province":"北京","address":"北京市朝阳区"}
注意: 此处的插入需要指定上一步的pipeline
PUT /_bulk?pipeline=pipeline_index_person_provice_sex
GET /index_person/_search { "size": 0, "aggs": { "agg_province_sex": { "terms": { "field": "pipeline_province_sex", "size": 10, "shard_size": 25, "order": { "max_age": "desc" } }, "aggs": { "max_age": { "max": { "field": "age" } } } } } }
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