目錄
1、背景
我們知道當我們使用 terms
聚合時,當修改預設順序為_count asc
時,統計的結果是不準備的,而且官方也不推薦我們這樣做,而是推薦使用rare terms
聚合。rare terms
是一個稀少
的term聚合,可以一定程度的解決升序問題。
2、需求
統計province
欄位中包含上和湖
的term資料,並且最多隻能出現2次。獲取到聚合後的結果。
3、前置準備
3.1 準備mapping
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
}
}
}
}
}
}
3.2 準備資料
PUT /_bulk
{"create":{"_index":"index_person","_id":1}}
{"id":1,"name":"張三","sex":"男","age":20,"province":"湖北","address":"湖北省黃岡市羅田縣匡河鎮"}
{"create":{"_index":"index_person","_id":2}}
{"id":2,"name":"李四","sex":"男","age":19,"province":"江蘇","address":"江蘇省南京市"}
{"create":{"_index":"index_person","_id":3}}
{"id":3,"name":"王武","sex":"女","age":25,"province":"湖北","address":"湖北省武漢市江漢區"}
{"create":{"_index":"index_person","_id":4}}
{"id":4,"name":"趙六","sex":"女","age":30,"province":"北京","address":"北京市東城區"}
{"create":{"_index":"index_person","_id":5}}
{"id":5,"name":"錢七","sex":"女","age":16,"province":"北京","address":"北京市西城區"}
{"create":{"_index":"index_person","_id":6}}
{"id":6,"name":"王八","sex":"女","age":45,"province":"北京","address":"北京市朝陽區"}
{"create":{"_index":"index_person","_id":7}}
{"id":7,"name":"九哥","sex":"男","age":25,"province":"上海市","address":"上海市嘉定區"}
4、實現需求
4.1 dsl
GET /index_person/_search
{
"size": 0,
"aggs": {
"agg_province": {
"rare_terms": {
"field": "province",
"max_doc_count": 2,
"precision": 0.01,
"include": "(.*上.*|.*湖.*|.*江.*)",
"exclude": ["江蘇"],
"missing": "default省"
}
}
}
}
4.2 java程式碼
@Test
@DisplayName("稀少的term聚合,類似按照 _count asc 排序的terms聚合,但是terms聚合中按照_count asc的結果是不準的,需要使用 rare terms 聚合")
public void agg01() throws IOException {
SearchRequest searchRequest = new SearchRequest.Builder()
.size(0)
.index("index_person")
.aggregations("agg_province", agg ->
agg.rareTerms(rare ->
// 稀有詞 的欄位
rare.field("province")
// 該稀有詞最多可以出現在幾個文件中,最大值為100,如果要調整,需要修改search.max_buckets引數的值(嘗試修改這個值,不生效)
// 在該例子中,只要是出現的次數<=2的聚合都會返回
.maxDocCount(2L)
// 內部布穀鳥過濾器的精度,精度越小越準,但是相應的消耗記憶體也越多,最小值為 0.00001,預設值為 0.01
.precision(0.01)
// 應該包含在聚合的term, 當是單個欄位是,可以寫正規表示式
.include(include -> include.regexp("(.*上.*|.*湖.*|.*江.*)"))
// 排出在聚合中的term,當是集合時,需要寫準確的值
.exclude(exclude -> exclude.terms(Collections.singletonList("江蘇")))
// 當文件中缺失province欄位時,給預設值
.missing("default省")
)
)
.build();
System.out.println(searchRequest);
SearchResponse<Object> response = client.search(searchRequest, Object.class);
System.out.println(response);
}
一些注意事項都在註釋中。
4.3 執行結果
5、max_doc_count 和 search.max_buckets
6、注意事項
rare terms
統計返回的資料沒有大小
限制,而且受max_doc_count
引數的限制,比如:如果複合 max_doc_count 的分組有60個,那麼這60個分組會直接返回。max_doc_count
的值最大為100
,貌似不能修改。- 如果一臺節點聚合收集的結果過多,那麼很容易超過
search.max_buckets
的值,此時就需要修改這個值。
# 臨時修改
PUT /_cluster/settings
{"transient": {"search.max_buckets": 65536}}
# 永久修改
PUT /_cluster/settings
{"persistent": {"search.max_buckets": 65536}}