ElasticSearch進(jìn)階：一文全覽各種ES查詢(xún)?cè)贘ava中的實(shí)現(xiàn)
ElasticSearch進(jìn)階：一文全覽各種ES查詢(xún)?cè)贘ava中的實(shí)現(xiàn)
es基本語(yǔ)句詳解 查詢(xún)語(yǔ)句詳解
前言
- ElasticSearch第一篇：ElasticSearch基礎(chǔ)：從倒排索引說(shuō)起，快速認(rèn)知ES
完整項(xiàng)目已上傳至：ElasticSearch Demo 項(xiàng)目，該項(xiàng)目是關(guān)于springboot的集成項(xiàng)目，ElasticSearch部分請(qǐng)關(guān)注【elasticSearch-demo】模塊。覺(jué)得有幫助的隨手點(diǎn)個(gè)start！
這篇博文的主題是ES的查詢(xún)，因此我整理了盡可能齊全的ES查詢(xún)場(chǎng)景，形成下面的圖：
本文基于elasticsearch 7.13.2版本，es從7.0以后，發(fā)生了很大的更新。7.3以后，已經(jīng)不推薦使用TransportClient這個(gè)client，取而代之的是Java High Level REST Client RestHighLevelClient。
測(cè)試使用的數(shù)據(jù)示例
首先是，Mysql中的部分測(cè)試數(shù)據(jù)：
| id | name | age | sex | address | sect | skill | power | create_time | modify_time |
|---|---|---|---|---|---|---|---|---|---|
| 1 | 張無(wú)忌 | 18 | 男 | 光明頂 | 明教 | 九陽(yáng)神功 | 99 | 2021-05-14 16:50:33 | 2021-06-29 16:48:56 |
| 2 | 周芷若 | 17 | 女 | 峨眉山 | 峨嵋派 | 九陰真經(jīng) | 88 | 2021-05-14 11:37:07 | 2021-06-29 16:56:40 |
| 3 | 趙敏 | 14 | 女 | 大都 | 朝廷 | 無(wú) | 40 | 2021-05-14 11:37:07 | 2021-06-29 15:22:24 |
es 數(shù)據(jù)
POST test/_doc/1
{
"id": 1,
"name": "張無(wú)忌",
"age": 18,
"sex": "男",
"address": "光明頂",
"sect": "明教",
"skill": "九陽(yáng)神功",
"power": 99,
"create_time": "2021-05-14 16:50:33",
"modify_time": "2021-06-29 16:48:56"
}
POST test/_doc/2
{
"id": 2,
"name": "周芷若",
"age": 17,
"sex": "女",
"address": "峨眉山",
"sect": "峨嵋派",
"skill": "九陰真經(jīng)",
"power": 88,
"create_time": "2021-05-14 11:37:07",
"modify_time": "2021-06-29 16:56:40"
}
POST test/_doc/3
{
"id": 3,
"name": "趙敏",
"age": 14,
"sex": "女",
"address": "大都",
"sect": "朝廷",
"skill": "無(wú)",
"power": 40,
"create_time": "2021-05-14 11:37:07",
"modify_time": "2021-06-29 15:22:24"
}
Mysql中的一行數(shù)據(jù)在ES中以一個(gè)文檔形式存在：
{
"_index" : "person",
"_type" : "_doc",
"_id" : "4",
"_score" : 1.0,
"_source" : {
"address" : "峨眉山",
"modifyTime" : "2021-06-29 19:46:25",
"createTime" : "2021-05-14 11:37:07",
"sect" : "峨嵋派",
"sex" : "男",
"skill" : "降龍十八掌",
"name" : "宋青書(shū)",
"id" : 4,
"power" : 50,
"age" : 21
}
}
簡(jiǎn)單梳理了一下ES JavaAPI的相關(guān)體系，感興趣的可以自己研讀一下源碼。
接下來(lái)，我們用十幾個(gè)實(shí)例，迅速上手ES的查詢(xún)操作，每個(gè)示例將提供SQL語(yǔ)句、ES語(yǔ)句和Java代碼。
1 詞條查詢(xún)
所謂詞條查詢(xún)，也就是ES不會(huì)對(duì)查詢(xún)條件進(jìn)行分詞處理，只有當(dāng)詞條和查詢(xún)字符串完全匹配時(shí)，才會(huì)被查詢(xún)到。
1.1 等值查詢(xún)-term
等值查詢(xún)，即篩選出一個(gè)字段等于特定值的所有記錄。
SQL：
select * from person where name = '張無(wú)忌';
而使用ES查詢(xún)語(yǔ)句卻很不一樣（注意查詢(xún)字段帶上keyword）：
GET /person/_search
{
"query": {
"term": {
"name.keyword": {
"value": "張無(wú)忌",
"boost": 1.0
}
}
}
}
ElasticSearch 5.0以后，string類(lèi)型有重大變更，移除了string類(lèi)型，string字段被拆分成兩種新的數(shù)據(jù)類(lèi)型: text用于全文搜索的，而keyword用于關(guān)鍵詞搜索。
查詢(xún)結(jié)果：
{
"took" : 0,
"timed_out" : false,
"_shards" : { // 分片信息
"total" : 1, // 總計(jì)分片數(shù)
"successful" : 1, // 查詢(xún)成功的分片數(shù)
"skipped" : 0, // 跳過(guò)查詢(xún)的分片數(shù)
"failed" : 0 // 查詢(xún)失敗的分片數(shù)
},
"hits" : { // 命中結(jié)果
"total" : {
"value" : 1, // 數(shù)量
"relation" : "eq" // 關(guān)系：等于
},
"max_score" : 2.8526313, // 最高分?jǐn)?shù)
"hits" : [
{
"_index" : "person", // 索引
"_type" : "_doc", // 類(lèi)型
"_id" : "1",
"_score" : 2.8526313,
"_source" : {
"address" : "光明頂",
"modifyTime" : "2021-06-29 16:48:56",
"createTime" : "2021-05-14 16:50:33",
"sect" : "明教",
"sex" : "男",
"skill" : "九陽(yáng)神功",
"name" : "張無(wú)忌",
"id" : 1,
"power" : 99,
"age" : 18
}
}
]
}
}
Java中構(gòu)造ES請(qǐng)求的方式：（后續(xù)例子中只保留SearchSourceBuilder的構(gòu)建語(yǔ)句）
/**
* term精確查詢(xún)
*
* @throws IOException
*/
@Autowired
private RestHighLevelClient client;
@Test
public void queryTerm() throws IOException {
// 根據(jù)索引創(chuàng)建查詢(xún)請(qǐng)求
SearchRequest searchRequest = new SearchRequest("person");
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
// 構(gòu)建查詢(xún)語(yǔ)句
searchSourceBuilder.query(QueryBuilders.termQuery("name.keyword", "張無(wú)忌"));
System.out.println("searchSourceBuilder=====================" + searchSourceBuilder);
searchRequest.source(searchSourceBuilder);
SearchResponse response = client.search(searchRequest, RequestOptions.DEFAULT);
System.out.println(JSONObject.toJSON(response));
}
仔細(xì)觀(guān)察查詢(xún)結(jié)果，會(huì)發(fā)現(xiàn)ES查詢(xún)結(jié)果中會(huì)帶有_score這一項(xiàng)，ES會(huì)根據(jù)結(jié)果匹配程度進(jìn)行評(píng)分。打分是會(huì)耗費(fèi)性能的，如果確認(rèn)自己的查詢(xún)不需要評(píng)分，就設(shè)置查詢(xún)語(yǔ)句關(guān)閉評(píng)分：
GET /person/_search
{
"query": {
"constant_score": {
"filter": {
"term": {
"sect.keyword": {
"value": "張無(wú)忌",
"boost": 1.0
}
}
},
"boost": 1.0
}
}
}
Java構(gòu)建查詢(xún)語(yǔ)句：
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
// 這樣構(gòu)造的查詢(xún)條件，將不進(jìn)行score計(jì)算，從而提高查詢(xún)效率
searchSourceBuilder.query(QueryBuilders.constantScoreQuery(QueryBuilders.termQuery("sect.keyword", "明教")));
1.2 多值查詢(xún)-terms
多條件查詢(xún)類(lèi)似Mysql里的IN查詢(xún)，例如：
select * from persons where sect in('明教','武當(dāng)派');
ES查詢(xún)語(yǔ)句：
GET /person/_search
{
"query": {
"terms": {
"sect.keyword": [
"明教",
"武當(dāng)派"
],
"boost": 1.0
}
}
}
Java實(shí)現(xiàn)：
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
// 構(gòu)建查詢(xún)語(yǔ)句
searchSourceBuilder.query(QueryBuilders.termsQuery("sect.keyword", Arrays.asList("明教", "武當(dāng)派")));
}
1.3 范圍查詢(xún)-range
范圍查詢(xún)，即查詢(xún)某字段在特定區(qū)間的記錄。
SQL:
select * from pesons where age between 18 and 22;
ES查詢(xún)語(yǔ)句：
GET /person/_search
{
"query": {
"range": {
"age": {
"from": 10,
"to": 20,
"include_lower": true,
"include_upper": true,
"boost": 1.0
}
}
}
}
Java構(gòu)建查詢(xún)條件：
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
// 構(gòu)建查詢(xún)語(yǔ)句
searchSourceBuilder.query(QueryBuilders.rangeQuery("age").gte(10).lte(30));
}
1.4 前綴查詢(xún)-prefix
前綴查詢(xún)類(lèi)似于SQL中的模糊查詢(xún)。
SQL：
select * from persons where sect like '武當(dāng)%';
ES查詢(xún)語(yǔ)句：
{
"query": {
"prefix": {
"sect.keyword": {
"value": "武當(dāng)",
"boost": 1.0
}
}
}
}
Java構(gòu)建查詢(xún)條件：
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
// 構(gòu)建查詢(xún)語(yǔ)句
searchSourceBuilder.query(QueryBuilders.prefixQuery("sect.keyword","武當(dāng)"));
1.5 通配符查詢(xún)-wildcard
通配符查詢(xún)，與前綴查詢(xún)類(lèi)似，都屬于模糊查詢(xún)的范疇，但通配符顯然功能更強(qiáng)。
SQL：
select * from persons where name like '張%忌';
ES查詢(xún)語(yǔ)句：
{
"query": {
"wildcard": {
"sect.keyword": {
"wildcard": "張*忌",
"boost": 1.0
}
}
}
}
Java構(gòu)建查詢(xún)條件：
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
// 構(gòu)建查詢(xún)語(yǔ)句
searchSourceBuilder.query(QueryBuilders.wildcardQuery("sect.keyword","張*忌"));
2 復(fù)合查詢(xún)
前面的例子都是單個(gè)條件查詢(xún)，在實(shí)際應(yīng)用中，我們很有可能會(huì)過(guò)濾多個(gè)值或字段。先看一個(gè)簡(jiǎn)單的例子：
select * from persons where sex = '女' and sect = '明教';
這樣的多條件等值查詢(xún)，就要借用到組合過(guò)濾器了，其查詢(xún)語(yǔ)句是：
{
"query": {
"bool": {
"must": [
{
"term": {
"sex": {
"value": "女",
"boost": 1.0
}
}
},
{
"term": {
"sect.keywords": {
"value": "明教",
"boost": 1.0
}
}
}
],
"adjust_pure_negative": true,
"boost": 1.0
}
}
}
Java構(gòu)造查詢(xún)語(yǔ)句：
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
// 構(gòu)建查詢(xún)語(yǔ)句
searchSourceBuilder.query(QueryBuilders.boolQuery()
.must(QueryBuilders.termQuery("sex", "女"))
.must(QueryBuilders.termQuery("sect.keyword", "明教"))
);
2.1 布爾查詢(xún)
布爾過(guò)濾器（bool filter）屬于復(fù)合過(guò)濾器（compound filter）的一種 ，可以接受多個(gè)其他過(guò)濾器作為參數(shù)，并將這些過(guò)濾器結(jié)合成各式各樣的布爾（邏輯）組合。
bool 過(guò)濾器下可以有4種子條件，可以任選其中任意一個(gè)或多個(gè)。filter是比較特殊的，這里先不說(shuō)。
{
"bool" : {
"must" : [],
"should" : [],
"must_not" : [],
}
}
-
must：所有的語(yǔ)句都必須匹配，與 ‘=’ 等價(jià)。 -
must_not：所有的語(yǔ)句都不能匹配，與 ‘!=’ 或 not in 等價(jià)。 -
should：至少有n個(gè)語(yǔ)句要匹配，n由參數(shù)控制。
精度控制：
所有 must 語(yǔ)句必須匹配，所有 must_not 語(yǔ)句都必須不匹配，但有多少 should 語(yǔ)句應(yīng)該匹配呢？默認(rèn)情況下，沒(méi)有 should 語(yǔ)句是必須匹配的，只有一個(gè)例外：那就是當(dāng)沒(méi)有 must 語(yǔ)句的時(shí)候，至少有一個(gè) should 語(yǔ)句必須匹配。
我們可以通過(guò) minimum_should_match 參數(shù)控制需要匹配的 should 語(yǔ)句的數(shù)量，它既可以是一個(gè)絕對(duì)的數(shù)字，又可以是個(gè)百分比：
GET /person/_search
{
"query": {
"bool": {
"must": [
{
"term": {
"sex": {
"value": "女",
"boost": 1.0
}
}
}
],
"should": [
{
"term": {
"address.keyword": {
"value": "峨眉山",
"boost": 1.0
}
}
},
{
"term": {
"sect.keyword": {
"value": "明教",
"boost": 1.0
}
}
}
],
"adjust_pure_negative": true,
"minimum_should_match": "1",
"boost": 1.0
}
}
}
Java構(gòu)建查詢(xún)語(yǔ)句：
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
// 構(gòu)建查詢(xún)語(yǔ)句
searchSourceBuilder.query(QueryBuilders.boolQuery()
.must(QueryBuilders.termQuery("sex", "女"))
.should(QueryBuilders.termQuery("address.word", "峨眉山"))
.should(QueryBuilders.termQuery("sect.keyword", "明教"))
.minimumShouldMatch(1)
);
最后，看一個(gè)復(fù)雜些的例子，將bool的各子句聯(lián)合使用：
select
*
from
persons
where
sex = '女'
and
age between 30 and 40
and
sect != '明教'
and
(address = '峨眉山' OR skill = '暗器')
用 Elasticsearch 來(lái)表示上面的 SQL 例子：
GET /person/_search
{
"query": {
"bool": {
"must": [
{
"term": {
"sex": {
"value": "女",
"boost": 1.0
}
}
},
{
"range": {
"age": {
"from": 30,
"to": 40,
"include_lower": true,
"include_upper": true,
"boost": 1.0
}
}
}
],
"must_not": [
{
"term": {
"sect.keyword": {
"value": "明教",
"boost": 1.0
}
}
}
],
"should": [
{
"term": {
"address.keyword": {
"value": "峨眉山",
"boost": 1.0
}
}
},
{
"term": {
"skill.keyword": {
"value": "暗器",
"boost": 1.0
}
}
}
],
"adjust_pure_negative": true,
"minimum_should_match": "1",
"boost": 1.0
}
}
}
用Java構(gòu)建這個(gè)查詢(xún)條件：
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
// 構(gòu)建查詢(xún)語(yǔ)句
BoolQueryBuilder boolQueryBuilder = QueryBuilders.boolQuery()
.must(QueryBuilders.termQuery("sex", "女"))
.must(QueryBuilders.rangeQuery("age").gte(30).lte(40))
.mustNot(QueryBuilders.termQuery("sect.keyword", "明教"))
.should(QueryBuilders.termQuery("address.keyword", "峨眉山"))
.should(QueryBuilders.rangeQuery("power.keyword").gte(50).lte(80))
.minimumShouldMatch(1); // 設(shè)置should至少需要滿(mǎn)足幾個(gè)條件
// 將BoolQueryBuilder構(gòu)建到SearchSourceBuilder中
searchSourceBuilder.query(boolQueryBuilder);
2.2 Filter查詢(xún)
query和filter的區(qū)別：query查詢(xún)的時(shí)候，會(huì)先比較查詢(xún)條件，然后計(jì)算分值，最后返回文檔結(jié)果；而filter是先判斷是否滿(mǎn)足查詢(xún)條件，如果不滿(mǎn)足會(huì)緩存查詢(xún)結(jié)果（記錄該文檔不滿(mǎn)足結(jié)果），滿(mǎn)足的話(huà)，就直接緩存結(jié)果，filter不會(huì)對(duì)結(jié)果進(jìn)行評(píng)分，能夠提高查詢(xún)效率。
filter的使用方式比較多樣，下面用幾個(gè)例子演示一下。
方式一，單獨(dú)使用：
{
"query": {
"bool": {
"filter": [
{
"term": {
"sex": {
"value": "男",
"boost": 1.0
}
}
}
],
"adjust_pure_negative": true,
"boost": 1.0
}
}
}
單獨(dú)使用時(shí)，filter與must基本一樣，不同的是filter不計(jì)算評(píng)分，效率更高。
Java構(gòu)建查詢(xún)語(yǔ)句：
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
// 構(gòu)建查詢(xún)語(yǔ)句
searchSourceBuilder.query(QueryBuilders.boolQuery()
.filter(QueryBuilders.termQuery("sex", "男"))
);
方式二，和must、must_not同級(jí)，相當(dāng)于子查詢(xún)：
select * from (select * from persons where sect = '明教')) a where sex = '女';
ES查詢(xún)語(yǔ)句：
{
"query": {
"bool": {
"must": [
{
"term": {
"sect.keyword": {
"value": "明教",
"boost": 1.0
}
}
}
],
"filter": [
{
"term": {
"sex": {
"value": "女",
"boost": 1.0
}
}
}
],
"adjust_pure_negative": true,
"boost": 1.0
}
}
}
Java：
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
// 構(gòu)建查詢(xún)語(yǔ)句
searchSourceBuilder.query(QueryBuilders.boolQuery()
.must(QueryBuilders.termQuery("sect.keyword", "明教"))
.filter(QueryBuilders.termQuery("sex", "女"))
);
方式三，將must、must_not置于filter下，這種方式是最常用的：
{
"query": {
"bool": {
"filter": [
{
"bool": {
"must": [
{
"term": {
"sect.keyword": {
"value": "明教",
"boost": 1.0
}
}
},
{
"range": {
"age": {
"from": 20,
"to": 35,
"include_lower": true,
"include_upper": true,
"boost": 1.0
}
}
}
],
"must_not": [
{
"term": {
"sex.keyword": {
"value": "女",
"boost": 1.0
}
}
}
],
"adjust_pure_negative": true,
"boost": 1.0
}
}
],
"adjust_pure_negative": true,
"boost": 1.0
}
}
}
Java:
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
// 構(gòu)建查詢(xún)語(yǔ)句
searchSourceBuilder.query(QueryBuilders.boolQuery()
.filter(QueryBuilders.boolQuery()
.must(QueryBuilders.termQuery("sect.keyword", "明教"))
.must(QueryBuilders.rangeQuery("age").gte(20).lte(35))
.mustNot(QueryBuilders.termQuery("sex.keyword", "女")))
);
3 聚合查詢(xún)
接下來(lái)，我們將用一些案例演示ES聚合查詢(xún)。
3.1 最值、平均值、求和
案例：查詢(xún)最大年齡、最小年齡、平均年齡。
SQL：
select max(age) from persons;
ES：
GET /person/_search
{
"aggregations": {
"max_age": {
"max": {
"field": "age"
}
}
}
}
Java：
@Autowired
private RestHighLevelClient client;
@Test
public void maxQueryTest() throws IOException {
// 聚合查詢(xún)條件
AggregationBuilder aggBuilder = AggregationBuilders.max("max_age").field("age");
SearchRequest searchRequest = new SearchRequest("person");
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
// 將聚合查詢(xún)條件構(gòu)建到SearchSourceBuilder中
searchSourceBuilder.aggregation(aggBuilder);
System.out.println("searchSourceBuilder----->" + searchSourceBuilder);
searchRequest.source(searchSourceBuilder);
// 執(zhí)行查詢(xún)，獲取SearchResponse
SearchResponse response = client.search(searchRequest, RequestOptions.DEFAULT);
System.out.println(JSONObject.toJSON(response));
}
使用聚合查詢(xún)，結(jié)果中默認(rèn)只會(huì)返回10條文檔數(shù)據(jù)（當(dāng)然我們關(guān)心的是聚合的結(jié)果，而非文檔）。返回多少條數(shù)據(jù)可以自主控制：
GET /person/_search
{
"size": 20,
"aggregations": {
"max_age": {
"max": {
"field": "age"
}
}
}
}
而Java中只需增加下面一條語(yǔ)句即可：
searchSourceBuilder.size(20);
與max類(lèi)似，其他統(tǒng)計(jì)查詢(xún)也很簡(jiǎn)單：
AggregationBuilder minBuilder = AggregationBuilders.min("min_age").field("age");
AggregationBuilder avgBuilder = AggregationBuilders.avg("min_age").field("age");
AggregationBuilder sumBuilder = AggregationBuilders.sum("min_age").field("age");
AggregationBuilder countBuilder = AggregationBuilders.count("min_age").field("age");
3.2 去重查詢(xún)
案例：查詢(xún)一共有多少個(gè)門(mén)派。
SQL：
select count(distinct sect) from persons;
ES：
{
"aggregations": {
"sect_count": {
"cardinality": {
"field": "sect.keyword"
}
}
}
}
Java：
@Test
public void cardinalityQueryTest() throws IOException {
// 創(chuàng)建某個(gè)索引的request
SearchRequest searchRequest = new SearchRequest("person");
// 查詢(xún)條件
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
// 聚合查詢(xún)
AggregationBuilder aggBuilder = AggregationBuilders.cardinality("sect_count").field("sect.keyword");
searchSourceBuilder.size(0);
// 將聚合查詢(xún)構(gòu)建到查詢(xún)條件中
searchSourceBuilder.aggregation(aggBuilder);
System.out.println("searchSourceBuilder----->" + searchSourceBuilder);
searchRequest.source(searchSourceBuilder);
// 執(zhí)行查詢(xún)，獲取結(jié)果
SearchResponse response = client.search(searchRequest, RequestOptions.DEFAULT);
System.out.println(JSONObject.toJSON(response));
}
3.3 分組聚合
3.3.1 單條件分組
案例：查詢(xún)每個(gè)門(mén)派的人數(shù)
SQL：
select sect,count(id) from mytest.persons group by sect;
ES：
{
"size": 0,
"aggregations": {
"sect_count": {
"terms": {
"field": "sect.keyword",
"size": 10,
"min_doc_count": 1,
"shard_min_doc_count": 0,
"show_term_doc_count_error": false,
"order": [
{
"_count": "desc"
},
{
"_key": "asc"
}
]
}
}
}
}
Java：
SearchRequest searchRequest = new SearchRequest("person");
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
searchSourceBuilder.size(0);
// 按sect分組
AggregationBuilder aggBuilder = AggregationBuilders.terms("sect_count").field("sect.keyword");
searchSourceBuilder.aggregation(aggBuilder);
3.3.2 多條件分組
案例：查詢(xún)每個(gè)門(mén)派各有多少個(gè)男性和女性
SQL：
select sect,sex,count(id) from mytest.persons group by sect,sex;
ES：
{
"aggregations": {
"sect_count": {
"terms": {
"field": "sect.keyword",
"size": 10
},
"aggregations": {
"sex_count": {
"terms": {
"field": "sex.keyword",
"size": 10
}
}
}
}
}
}
3.4 過(guò)濾聚合
前面所有聚合的例子請(qǐng)求都省略了 query ，整個(gè)請(qǐng)求只不過(guò)是一個(gè)聚合。這意味著我們對(duì)全部數(shù)據(jù)進(jìn)行了聚合，但現(xiàn)實(shí)應(yīng)用中，我們常常對(duì)特定范圍的數(shù)據(jù)進(jìn)行聚合，例如下例。
案例：查詢(xún)明教中的最大年齡。 這涉及到聚合與條件查詢(xún)一起使用。
SQL：
select max(age) from mytest.persons where sect = '明教';
ES：
GET /person/_search
{
"query": {
"term": {
"sect.keyword": {
"value": "明教",
"boost": 1.0
}
}
},
"aggregations": {
"max_age": {
"max": {
"field": "age"
}
}
}
}
Java：
SearchRequest searchRequest = new SearchRequest("person");
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
// 聚合查詢(xún)條件
AggregationBuilder maxBuilder = AggregationBuilders.max("max_age").field("age");
// 等值查詢(xún)
searchSourceBuilder.query(QueryBuilders.termQuery("sect.keyword", "明教"));
searchSourceBuilder.aggregation(maxBuilder);
另外還有一些更復(fù)雜的查詢(xún)例子。
案例：查詢(xún)0-20，21-40，41-60，61以上的各有多少人。
SQL：
select
sum(case when age<=20 then 1 else 0 end) ageGroup1,
sum(case when age >20 and age <=40 then 1 else 0 end) ageGroup2,
sum(case when age >40 and age <=60 then 1 else 0 end) ageGroup3,
sum(case when age >60 and age <=200 then 1 else 0 end) ageGroup4
from
mytest.persons;
ES：
{
"size": 0,
"aggregations": {
"age_avg": {
"range": {
"field": "age",
"ranges": [
{
"from": 0.0,
"to": 20.0
},
{
"from": 21.0,
"to": 40.0
},
{
"from": 41.0,
"to": 60.0
},
{
"from": 61.0,
"to": 200.0
}
],
"keyed": false
}
}
}
}
Java：
查詢(xún)結(jié)果：文章來(lái)源：http://www.zghlxwxcb.cn/news/detail-787678.html
"aggregations" : {
"age_avg" : {
"buckets" : [
{
"key" : "0.0-20.0",
"from" : 0.0,
"to" : 20.0,
"doc_count" : 3
},
{
"key" : "21.0-40.0",
"from" : 21.0,
"to" : 40.0,
"doc_count" : 13
},
{
"key" : "41.0-60.0",
"from" : 41.0,
"to" : 60.0,
"doc_count" : 4
},
{
"key" : "61.0-200.0",
"from" : 61.0,
"to" : 200.0,
"doc_count" : 1
}
]
}
}
以上是ElasticSearch查詢(xún)的全部?jī)?nèi)容，豐富詳實(shí)，堪比操作手冊(cè)，強(qiáng)烈建議收藏！文章來(lái)源地址http://www.zghlxwxcb.cn/news/detail-787678.html
es 執(zhí)行語(yǔ)句記錄
# indices下所有數(shù)據(jù)
GET /person/_search
{
"query": {
"match_all": {}
}
}
# 等值查詢(xún)-term
GET /person/_search
{
"query": {
"term": {
"name.keyword": {
"value": "張無(wú)忌"
}
}
}
}
# 不進(jìn)行score計(jì)算，從而提高查詢(xún)效率
GET /person/_search
{
"query": {
"constant_score": {
"filter": {
"term": {
"name.keyword": "張無(wú)忌"
}
},
"boost": 1.2
}
}
}
# 多值查詢(xún)-terms
GET /person/_search
{
"query": {
"terms": {
"sect.keyword": [
"明教",
"武當(dāng)派"
]
}
}
}
# 范圍查詢(xún)-range
GET /person/_search
{
"query": {
"range": {
"age": {
"from": 10,
"to": 20
}
}
}
}
GET /person/_search
{
"query": {
"range": {
"age": {
"gte": 10,
"lte": 20
}
}
}
}
# 1.4 前綴查詢(xún)-prefix
GET /person/_search
{
"query": {
"prefix": {
"sect.keyword": {
"value": "武當(dāng)"
}
}
}
}
# 1.5 通配符查詢(xún)-wildcard
GET /person/_search
{
"query": {
"wildcard": {
"name.keyword": {
"value": "張*"
}
}
}
}
# 2 復(fù)合查詢(xún)
GET /person/_search
{
"query": {
"bool": {
"must": [
{
"term": {
"sex": {
"value": "女"
}
}
},
{
"term": {
"sect.keyword": {
"value": "朝廷"
}
}
}
]
}
}
}
到了這里，關(guān)于ElasticSearch進(jìn)階：一文全覽各種ES查詢(xún)?cè)贘ava中的實(shí)現(xiàn)的文章就介紹完了。如果您還想了解更多內(nèi)容，請(qǐng)?jiān)谟疑辖撬阉鱐OY模板網(wǎng)以前的文章或繼續(xù)瀏覽下面的相關(guān)文章，希望大家以后多多支持TOY模板網(wǎng)！
