當前位置：首頁 > 编程资源 > 编程问答 >内容正文

编程问答

ES笔记_转自尚硅谷_其中有JAVA操作_ES

發布時間：2023/12/18 编程问答 32 豆豆

生活随笔收集整理的這篇文章主要介紹了 ES笔记_转自尚硅谷_其中有JAVA操作_ES 小編覺得挺不錯的,現在分享給大家,幫大家做個參考.

1.1ES簡介

ES是使用java 語言并且基于lucence編寫的搜索引擎框架，他提供了分布式的全文搜索功能，提供了一個統一的基于restful風格的web 接口。

lucence:一個搜索引擎底層

分布式：突出ES的橫向擴展能力

全文檢索：將一段詞語進行分詞，并將分出的詞語統一的放在一個分詞庫中，再搜索時，根據關鍵字取分詞庫中檢索，找到匹配的內容（倒排索引）。

restful風格的web 接口：只要發送一個http請求，并且根據請求方式的不同，攜帶參數的不同，執行相應的功能。

應用廣泛：WIKI, github,Gold man

1.2ES的由來

回憶時光**許多年前，一個剛結婚的名叫 Shay Banon 的失業開發者，跟著他的妻子去了倫敦，他的妻子在那里學習廚師。在尋找一個賺錢的工作的時候，為了給他的妻子做一個食譜搜索引擎，他開始使用 Lucene 的一個早期版本。直接使用 Lucene 是很難的，因此 Shay 開始做一個抽象層，Java 開發者使用它可以很簡單的給他們的程序添加搜索功能。他發布了他的第一個開源項目 Compass。后來 Shay 獲得了一份工作，主要是高性能，分布式環境下的內存數據網格。這個對于高性能，實時，分布式搜索引擎的需求尤為突出，他決定重寫 Compass，把它變為一個獨立的服務并取名 Elasticsearch。第一個公開版本在2010年2月發布，從此以后，Elasticsearch 已經成為了 Github 上最活躍的項目之一，他擁有超過300名 contributors(目前736名 contributors )。一家公司已經開始圍繞 Elasticsearch 提供商業服務，并開發新的特性，但是，Elasticsearch 將永遠開源并對所有人可用。據說，Shay 的妻子還在等著她的食譜搜索引擎…

1.3ES和solr

1.solr 查詢死數據，速度比es快。但是數據如果是改變的，solr查詢速度會降低很多，ES的查詢速度沒有明顯的改變

2.solr搭建集群依賴ZK，ES本身就支持集群搭建

3.最開始solr 的社區很火爆，針對國內文檔少，ES出現后，國內社區火爆程度上升，，ES的文檔非常健全

4.ES對云計算和大數據支持很好

1.4倒排索引

[外鏈圖片轉存失敗,源站可能有防盜鏈機制,建議將圖片保存下來直接上傳(img-OxXmUsxu-1615965888734)(ES筆記.assets/image-20200727144457339.png)]

1.將存放的數據以一定的方式進行分詞，并將分詞的內容存放到一個單獨的分詞庫中。

2.當用戶取查詢數據時，會將用戶的查詢關鍵字進行分詞，然后去分詞庫中匹配內容，最終得到數據的id標識

3.根據id標識去存放數據的位置拉去指定數據

2 安裝

2.1 elasticsearch 安裝

http://hub.daocloud.io/ docker 鏡像工廠地址

version: "3.1" services:elasticsearch: image: daocloud.io/library/elasticsearch:6.5.4restart: alwayscontainer_name: elasticsearchports: - 9200:9200- 9300:9300kibana:image: daocloud.io/library/kibana:6.5.4restart: alwayscontainer_name: kibanaports: - 9200:9200environment:- elasticsearch_url=ip:9200depends_on:- elasticseatch

或者本地下載

2.2

https://github.com/medcl/elasticsearch-analysis-ik/archive/v6.8.10.zip

官方給的安裝的辦法 ./bin/elasticsearch-plugin install https://github.com/medcl/elasticsearch-analysis-ik/releases/download/v6.3.0/elasticsearch-analysis-ik-6.3.0.zip

本地自己安裝

https://github.com/medcl/elasticsearch-analysis-ik/archive/v6.8.10.zip 下載好后，執行 mvn clean package 打包（注意pom文件中的es的版本，如果和自己的es的版本不一致，手動改下） elasticsearch-analysis-ik-6.8.10\target\releases 中壓縮包的內容copy到 elasticsearch-6.8.10\plugins\ik 下

kibana 主要用到 Dev Tools 和 Management

POST _analyze {"analyzer": "ik_max_word","text":"我是中國人" }

3 es的基本操作

3.1 es的結構

3.1.1索引indx，分片，備份

ES服務中會創建多個索引每個縮影默認被分成5個分片每個分片存在至少一個備份分片備份分片不會幫助檢索數據（當ES檢索壓力特別大的時候才，備份分片才會幫助檢索數據）備份的分片必須放在不同的服務器中

[外鏈圖片轉存失敗,源站可能有防盜鏈機制,建議將圖片保存下來直接上傳(img-C9tTucAp-1615965888737)(ES筆記.assets/image-20200727174836230.png)]

3.1.2 類型type

一個索引下可以創建多個類型 PS:版本不同,類型的創建也不同

[外鏈圖片轉存失敗,源站可能有防盜鏈機制,建議將圖片保存下來直接上傳(img-nStFLdAZ-1615965888739)(ES筆記.assets/image-20200727175427524.png)]

3.1.3 文檔document

一個類型下可以有多個文檔，這個文檔就相當于mysql表中的多行數據

[外鏈圖片轉存失敗,源站可能有防盜鏈機制,建議將圖片保存下來直接上傳(img-YEqmIWE0-1615965888743)(ES筆記.assets/image-20200727175655572.png)]

3.1.4 屬性field

一個文檔中可以包含多個屬性，類似于mysql 表中的一行數據有多個列

[外鏈圖片轉存失敗,源站可能有防盜鏈機制,建議將圖片保存下來直接上傳(img-IfmXfxdY-1615965888746)(ES筆記.assets/image-20200727180642583.png)]

3.2操作ES的restful語法

GET請求：http://ip:port/index :查詢索引信息http://ip:port/index/type/doc_id :查詢指定的文檔信息 POST請求：http://ip:port/index/type/_search: 查詢文檔，可以在請求體中添加json字符串來代表查詢條件http://ip:port/index/type/doc_id/_update: 修改文檔，在請求體中添加json字符串來代表修改的信息 PUT請求：http://ip:port/index : 創建一個索引，需要在請求體中指定索引的信息http://ip:port/index/type/_mappings:代表創建索引時，指定索引文檔存儲屬性的信息 DELETE 請求：http://ip:port/index：刪除跑路http://ip:port/index/type/doc_id: 刪除指定的文檔

3.3 索引的操作

3.3.1 創建一個索引

#創建一個索引 #number_of_shards 分片 #number_of_replicas 備份 PUT /person {"settings": {"number_of_shards": 5, "number_of_replicas": 1} }

3.3.2 查看一個索引

1.management2. #查看索引信息 GET /person

3.3.3 刪除索引

1.management2. #刪除索引 DELETE /person

3.4 ES中Field可以指定的類型

https://www.elastic.co/guide/en/elasticsearch/reference/6.8/mapping-types.html 官方文檔

字符串類型:text: 一般用于全文檢索，將當前field 進行分詞keyword:當前field 不會進行分詞數值類型：long:Intger:short:byte:double:float:half_float: 精度比float 小一半scaled_float:根據一個long 和scaled 來表達一個浮點型 long-345, -scaled 100 ->3.45 時間類型：date類型,根據時間類型指定具體的格式PUT my_index{"mappings": {"_doc": {"properties": {"date": {"type": "date","format": "yyyy-MM-dd HH:mm:ss||yyyy-MM-dd||epoch_millis"}}}}} 布爾類型：boolean 類型，表達true 和false 二進制類型：binary類型暫時支持Base64編碼的字符串范圍類型：integer_range：float_range：long_range：賦值時，無需指定具體的內容，只需存儲一個范圍即可，gte,lte,gt,lt,double_range：date_range：ip_range：PUT range_index{"settings": {"number_of_shards": 2},"mappings": {"_doc": {"properties": {"expected_attendees": {"type": "integer_range"},"time_frame": {"type": "date_range", "format": "yyyy-MM-dd HH:mm:ss||yyyy-MM-dd||epoch_millis"}}}}}PUT range_index/_doc/1?refresh{"expected_attendees" : { "gte" : 10,"lte" : 20},"time_frame" : { "gte" : "2015-10-31 12:00:00", "lte" : "2015-11-01"}} 經緯度類型：geo_point:用來存儲經緯度 IP類型：ip:可以存儲IPV4 和IPV6 其他的數據類型，參考官網

3.5 創建索引并指定數據結構

#創建索引，指定數據類型 PUT /book {"settings": {#分片數"number_of_shards": 5,#備份數"number_of_replicas": 1},#指定數據類型"mappings": {#類型 Type"novel":{#文檔存儲的field"properties":{#field屬性名"name":{#類型"type":"text",#指定分詞器"analyzer":"ik_max_word",#指定當前的field可以被作為查詢的條件"index":true,#是否需要額外存儲"store":false},"author":{"type":"keyword"},"count":{"type":"long"},"on-sale":{"type":"date",#指定時間類型的格式化方式"format": "yyyy-MM-dd HH:mm:ss||yyyy-MM-dd||epoch_millis"},"descr":{"type":"text","analyzer":"ik_max_word"}}}} }

3.6 文檔操作

文檔在ES服務中的唯一標識， _indx ,_type,_id 三個內容為組合，鎖定一個文檔，操作時添加還時修改操作，

3.6.1 新建文檔

自動生成id #添加文檔，自動生成id POST /book/novel {"name":"盤龍","author":"我吃西紅柿","count":100000,"on-sale":"2001-01-01","descr":"大小的血睛鬃毛獅，力大無窮的紫睛金毛猿，毀天滅地的九頭蛇皇，攜帶著毀滅雷電的恐怖雷龍……這里無奇不有，這是一個廣博的魔幻世界。強者可以站在黑色巨龍的頭頂遨游天際，恐怖的魔法可以焚燒江河，可以毀滅城池，可以夷平山岳……" }#添加文檔,手動指定id PUT /book/novel/1 {"name":"紅樓夢","author":"曹雪芹","count":10000000,"on-sale":"2501-01-01","descr":"中國古代章回體長篇小說，中國古典四大名著之一，一般認為是清代作家曹雪芹所著。小說以賈、史、王、薛四大家族的興衰為背景，以富貴公子賈寶玉為視角，以賈寶玉與林黛玉、薛寶釵的愛情婚姻悲劇為主線，描繪了一批舉止見識出于須眉之上的閨閣佳人的人生百態，展現了真正的人性美和悲劇美" }

3.6.2 修改文檔

1.覆蓋式修改

#添加文檔,手動指定id PUT /book/novel/1 {"name":"紅樓夢","author":"曹雪芹","count":1000444,"on-sale":"2501-01-01","descr":"中國古代章回體長篇小說，中國古典四大名著之一，一般認為是清代作家曹雪芹所著。小說以賈、史、王、薛四大家族的興衰為背景，以富貴公子賈寶玉為視角，以賈寶玉與林黛玉、薛寶釵的愛情婚姻悲劇為主線，描繪了一批舉止見識出于須眉之上的閨閣佳人的人生百態，展現了真正的人性美和悲劇美" }

2.使用doc修改方式

#修改文檔，使用doc 方式 POST /book/novel/1/_update {"doc":{#指定需要修改的field和對應的值"count":566666} }

3.6.3 刪除文檔

#根據id刪除文檔 DELETE /book/novel/3mEnk3MBaSKoGN4T2olw

4.java 操作ElasticSearch

4.1 java 連接ES

創建maven工程導入依賴 <dependency><groupId>org.elasticsearch</groupId><artifactId>elasticsearch</artifactId><version>6.8.10</version></dependency> <dependency><groupId>org.elasticsearch.client</groupId><artifactId>elasticsearch-rest-high-level-client</artifactId><version>6.8.10</version></dependency> <dependency><groupId>junit</groupId><artifactId>junit</artifactId><version>4.12</version></dependency> <dependency><groupId>org.projectlombok</groupId><artifactId>lombok</artifactId><version>1.16.22</version></dependency>

創建client鏈接

package com.utils;import org.apache.http.HttpHost; import org.elasticsearch.client.RestClient; import org.elasticsearch.client.RestClientBuilder; import org.elasticsearch.client.RestHighLevelClient;public class EsClient {public static RestHighLevelClient getClient(){// 創建 HttpHostHttpHost httpHost = new HttpHost("127.0.0.1",9200);// 創建 RestClientBuilderRestClientBuilder builder = RestClient.builder(httpHost);// 創建 RestHighLevelClientRestHighLevelClient client = new RestHighLevelClient(builder);return client;} }

4.2創建索引

package com.test;import com.utils.EsClient; import org.elasticsearch.action.admin.indices.create.CreateIndexRequest; import org.elasticsearch.action.admin.indices.create.CreateIndexResponse; import org.elasticsearch.client.RequestOptions; import org.elasticsearch.client.RestHighLevelClient; import org.elasticsearch.common.settings.Settings; import org.elasticsearch.common.xcontent.XContentBuilder; import org.elasticsearch.common.xcontent.json.JsonXContent; import org.junit.Test;public class Demo2 {RestHighLevelClient client = EsClient.getClient();String index = "person";String type="man";@Testpublic void createIndx() throws Exception{// 1.準備關于索引的settingSettings.Builder settings = Settings.builder().put("number_of_shards", 2).put("number_of_replicas", 1);// 2.準備關于索引的mappingXContentBuilder mappings = JsonXContent.contentBuilder().startObject().startObject("properties").startObject("name").field("type", "text").endObject().startObject("age").field("type", "integer").endObject().startObject("birthday").field("type", "date").field("format", "yyyy-MM-dd").endObject().endObject().endObject();// 3.將settings和mappings 封裝到到一個Request對象中CreateIndexRequest request = new CreateIndexRequest(index).settings(settings).mapping(type,mappings);// 4.使用client 去連接ESCreateIndexResponse response = client.indices().create(request, RequestOptions.DEFAULT);System.out.println("response:"+response.toString());} }

4.3 檢查索引是否存在，刪除索引

4.3.1 檢查索引存在

4.3.2 刪除索引

package com.test;import com.utils.EsClient; import org.elasticsearch.action.admin.indices.create.CreateIndexRequest; import org.elasticsearch.action.admin.indices.create.CreateIndexResponse; import org.elasticsearch.action.admin.indices.delete.DeleteIndexRequest; import org.elasticsearch.action.support.master.AcknowledgedResponse; import org.elasticsearch.client.RequestOptions; import org.elasticsearch.client.RestHighLevelClient; import org.elasticsearch.client.indices.GetIndexRequest; import org.elasticsearch.common.settings.Settings; import org.elasticsearch.common.xcontent.XContentBuilder; import org.elasticsearch.common.xcontent.json.JsonXContent; import org.junit.Test;import java.io.IOException;public class Demo2 {RestHighLevelClient client = EsClient.getClient();String index = "person";String type="man";@Testpublic void testDelete() throws IOException {// 1.獲取requestDeleteIndexRequest request = new DeleteIndexRequest(index);// 2.使用client 操作requestAcknowledgedResponse delete = client.indices().delete(request, RequestOptions.DEFAULT);// 3.輸出結果System.out.println(delete.isAcknowledged());} }

4.4 Java操作文檔

4.4.1 添加文檔操作

public class Demo3 {ObjectMapper mapper = new ObjectMapper();RestHighLevelClient client = EsClient.getClient();String index = "person";String type="man";@Testpublic void createDocTest() throws IOException {// 1.準備一個json數據Person person = new Person(1,"張三",33,new Date());String json = mapper.writeValueAsString(person);// 2.創建一個request對象(手動指定的方式創建)IndexRequest request = new IndexRequest(index,type,person.getId().toString());request.source(json, XContentType.JSON);// 3.使用client 操作request對象生成docIndexResponse response = client.index(request, RequestOptions.DEFAULT);// 4.輸出返回結果System.out.println(response.getResult().toString());} }

4.4.2 修改文檔

public class Demo3 {ObjectMapper mapper = new ObjectMapper();RestHighLevelClient client = EsClient.getClient();String index = "person";String type="man";@Testpublic void updateDocTest() throws Exception{// 1.創建要跟新的MapMap<String,Object> doc = new HashMap<>();doc.put("name","張三三");// 2.創建request, 將doc 封裝進去UpdateRequest request = new UpdateRequest(index,type,"1");request.doc(doc);// 3. client 去操作 requestUpdateResponse response = client.update(request, RequestOptions.DEFAULT);// 4.輸出更新結果System.out.println(response.getResult());} }

4.4.3 刪除文檔

public class Demo3 {ObjectMapper mapper = new ObjectMapper();RestHighLevelClient client = EsClient.getClient();String index = "person";String type="man";@Testpublic void deleteDocTest() throws Exception{// 1.封裝刪除對象DeleteRequest request = new DeleteRequest(index,type,"1");// 2 client 操作 request對象DeleteResponse response = client.delete(request, RequestOptions.DEFAULT);// 3.輸出結果System.out.println(response.getResult().toString());} }

4.5 java批量操作文檔

批量操作新增

@Testpublic void bulkCreateDoc() throws Exception{// 1.準備多個json 對象Person p1 = new Person(1,"張三",23,new Date());Person p2 = new Person(2,"里斯",24,new Date());Person p3 = new Person(3,"王武",24,new Date());String json1 = mapper.writeValueAsString(p1);String json2 = mapper.writeValueAsString(p2);String json3 = mapper.writeValueAsString(p3);// 2.創建requestBulkRequest bulkRequest = new BulkRequest();bulkRequest.add(new IndexRequest(index,type,p1.getId().toString()).source(json1,XContentType.JSON)).add(new IndexRequest(index,type,p2.getId().toString()).source(json2,XContentType.JSON)).add(new IndexRequest(index,type,p3.getId().toString()).source(json3,XContentType.JSON));// 3.client 執行BulkResponse responses = client.bulk(bulkRequest, RequestOptions.DEFAULT);// 4.輸出結果System.out.println(responses.getItems().toString());}

批量刪除

public void bulkDelete() throws Exception{// 1.創建Request 對象BulkRequest bulkRequest = new BulkRequest();bulkRequest.add(new DeleteRequest(index,type,"1"));bulkRequest.add(new DeleteRequest(index,type,"2"));bulkRequest.add(new DeleteRequest(index,type,"3"));// 2.執行BulkResponse re = client.bulk(bulkRequest, RequestOptions.DEFAULT);// 3.輸出結果System.out.println(re.toString());}

5.ES 練習

索引：sms-logs-index 類型：sms-logs-type

[外鏈圖片轉存失敗,源站可能有防盜鏈機制,建議將圖片保存下來直接上傳(img-9c9TkWf4-1615965888749)(ES筆記.assets/image-20200728173057412.png)]

public class Demo4 {ObjectMapper mapper = new ObjectMapper();RestHighLevelClient client = EsClient.getClient();String index = "sms-logs-index";String type="sms-logs-type";@Testpublic void createIndex() throws Exception{// 1.準備關于索引的settingSettings.Builder settings = Settings.builder().put("number_of_shards", 3).put("number_of_replicas", 1);// 2.準備關于索引的mappingXContentBuilder mappings = JsonXContent.contentBuilder().startObject().startObject("properties").startObject("corpName").field("type", "keyword").endObject().startObject("createDate").field("type", "date").field("format", "yyyy-MM-dd").endObject().startObject("fee").field("type", "long").endObject().startObject("ipAddr").field("type", "ip").endObject().startObject("longCode").field("type", "keyword").endObject().startObject("mobile").field("type", "keyword").endObject().startObject("operatorId").field("type", "integer").endObject().startObject("province").field("type", "keyword").endObject().startObject("replyTotal").field("type", "integer").endObject().startObject("sendDate").field("type", "date").field("format", "yyyy-MM-dd").endObject().startObject("smsContent").field("type", "text").field("analyzer", "ik_max_word").endObject().startObject("state").field("type", "integer").endObject().endObject().endObject();// 3.將settings和mappings 封裝到到一個Request對象中CreateIndexRequest request = new CreateIndexRequest(index).settings(settings).mapping(type,mappings);// 4.使用client 去連接ESCreateIndexResponse response = client.indices().create(request, RequestOptions.DEFAULT);System.out.println("response:"+response.toString());}@Testpublic void bulkCreateDoc() throws Exception{// 1.準備多個json 對象String longcode = "1008687";String mobile ="138340658";List<String> companies = new ArrayList<>();companies.add("騰訊課堂");companies.add("阿里旺旺");companies.add("海爾電器");companies.add("海爾智家公司");companies.add("格力汽車");companies.add("蘇寧易購");List<String> provinces = new ArrayList<>();provinces.add("北京");provinces.add("重慶");provinces.add("上海");provinces.add("晉城");BulkRequest bulkRequest = new BulkRequest();for (int i = 1; i <16 ; i++) {Thread.sleep(1000);SmsLogs s1 = new SmsLogs();s1.setId(i);s1.setCreateDate(new Date());s1.setSendDate(new Date());s1.setLongCode(longcode+i);s1.setMobile(mobile+2*i);s1.setCorpName(companies.get(i%5));s1.setSmsContent(SmsLogs.doc.substring((i-1)*100,i*100));s1.setState(i%2);s1.setOperatorId(i%3);s1.setProvince(provinces.get(i%4));s1.setIpAddr("127.0.0."+i);s1.setReplyTotal(i*3);s1.setFee(i*6+"");String json1 = mapper.writeValueAsString(s1);bulkRequest.add(new IndexRequest(index,type,s1.getId().toString()).source(json1, XContentType.JSON));System.out.println("數據"+i+s1.toString());}// 3.client 執行BulkResponse responses = client.bulk(bulkRequest, RequestOptions.DEFAULT);// 4.輸出結果System.out.println(responses.getItems().toString());} }

6.ElasticSearch的各種查詢

6.1 term 和terms 查詢

6.1.1 term 查詢

term 查詢是代表完全匹配，搜索之前不會對你搜索的關鍵字進行分詞，直接拿關鍵字去文檔分詞庫中匹配內容 #term查詢 POST /sms-logs-index/sms-logs-type/_search {#limit ?"from": 0, #limit x,?"size":5,"query": {"term": {"province": {"value": "北京"}}} } public class TermSearch {ObjectMapper mapper = new ObjectMapper();RestHighLevelClient client = EsClient.getClient();String index = "sms-logs-index";String type="sms-logs-type";@Testpublic void termSearchTest() throws IOException {// 1.創建request對象SearchRequest request = new SearchRequest(index);request.types(type);// 2.創建查詢條件SearchSourceBuilder builder = new SearchSourceBuilder();builder.from(0);builder.size(5);builder.query(QueryBuilders.termQuery("province","北京"));request.source(builder);// 3.執行查詢SearchResponse response = client.search(request, RequestOptions.DEFAULT);// 4.輸出查詢結果for (SearchHit hit : response.getHits().getHits()) {Map<String, Object> sourceAsMap = hit.getSourceAsMap();System.out.println(sourceAsMap);}} }

6.1.2 查詢

terms 和 term 查詢的機制一樣，搜索之前不會對你搜索的關鍵字進行分詞，直接拿關鍵字去文檔分詞庫中匹配內容 terms:是針對一個字段包含多個值 term : where province =北京 terms: where province = 北京 or province =? (類似于mysql 中的 in) 也可針對 text, 只是在分詞庫中查詢的時候不會進行分詞 #terms 查詢 POST /sms-logs-index/sms-logs-type/_search {"query": {"terms": {"province": ["北京","晉城"]}} } public class TermSearch {ObjectMapper mapper = new ObjectMapper();RestHighLevelClient client = EsClient.getClient();String index = "sms-logs-index";String type="sms-logs-type";@Testpublic void termsSearchTest() throws IOException {// 1.創建request對象SearchRequest request = new SearchRequest(index);request.types(type);// 2.創建查詢條件SearchSourceBuilder builder = new SearchSourceBuilder();builder.query(QueryBuilders.termsQuery("province","北京","晉城"));request.source(builder);// 3.執行查詢SearchResponse response = client.search(request, RequestOptions.DEFAULT);// 輸出查詢結果for (SearchHit hit : response.getHits().getHits()) {System.out.println(hit.getSourceAsMap());}} }

6.2 match

match 查詢屬于高級查詢，會根據你查詢字段的類型不一樣，采用不同的查詢方式查詢的是日期或者數值，他會將你基于字符串的查詢內容轉換為日期或數值對待如果查詢的內容是一個不能被分詞的內容（keyword）,match 不會將你指定的關鍵字進行分詞如果查詢的內容是一個可以被分詞的內容（text）,match 查詢會將你指定的內容根據一定的方式進行分詞，去分詞庫中匹配指定的內容 match 查詢，實際底層就是多個term 查詢，將多個term查詢的結果給你封裝到一起

6.2.1 math_all

查詢全部內容，不指定查詢條件 #match_all 查詢 POST /sms-logs-index/sms-logs-type/_search {"query":{"match_all": {}} } public class MatchSearch {ObjectMapper mapper = new ObjectMapper();RestHighLevelClient client = EsClient.getClient();String index = "sms-logs-index";String type="sms-logs-type";@Testpublic void matchAllSearch() throws IOException {// 1.創建request對象SearchRequest request = new SearchRequest(index);request.types(type);// 2.創建查詢條件SearchSourceBuilder builder = new SearchSourceBuilder();builder.query(QueryBuilders.matchAllQuery());// ES 默認只查詢10條數據builder.size(20);request.source(builder);// 3.執行查詢SearchResponse response = client.search(request, RequestOptions.DEFAULT);// 4.輸出查詢結果for (SearchHit hit : response.getHits().getHits()) {System.out.println(hit.getSourceAsMap());}System.out.println(response.getHits().getHits().length);} }

6.2.2 match 查詢

指定一個field 作為查詢條件

#match 查詢 POST /sms-logs-index/sms-logs-type/_search {"query": {"match": {"smsContent": "偉大戰士"}} } public class MatchSearch {ObjectMapper mapper = new ObjectMapper();RestHighLevelClient client = EsClient.getClient();String index = "sms-logs-index";String type="sms-logs-type";@Testpublic void matchSearch() throws IOException {// 1.創建request對象SearchRequest request = new SearchRequest(index);request.types(type);// 2.創建查詢條件SearchSourceBuilder builder = new SearchSourceBuilder();//--------------------------------------------------------------builder.query(QueryBuilders.matchQuery("smsContent","偉大戰士"));//--------------------------------------------------------------builder.size(20);request.source(builder);// 3.執行查詢SearchResponse response = client.search(request, RequestOptions.DEFAULT);// 4.輸出查詢結果for (SearchHit hit : response.getHits().getHits()) {System.out.println(hit.getSourceAsMap());}System.out.println(response.getHits().getHits().length);}}

6.2.3 布爾match 查詢

基于一個field 匹配的內容，按照 and 或者or的方式連接 #布爾match查詢 POST /sms-logs-index/sms-logs-type/_search {"query": {"match": {"smsContent": {# 既包含戰士也包含團隊"query": "戰士團隊","operator": "and"}}} }#布爾match查詢 POST /sms-logs-index/sms-logs-type/_search {"query": {"match": {"smsContent": {# 既包含戰士或者團隊"query": "戰士團隊","operator": "or"}}} } @Testpublic void booleanMatchSearch() throws IOException {// 1.創建request對象SearchRequest request = new SearchRequest(index);request.types(type);// 2.創建查詢條件SearchSourceBuilder builder = new SearchSourceBuilder();//--------------------------------------------------------------builder.query(QueryBuilders.matchQuery("smsContent","戰士團隊").operator(Operator.AND));//--------------------------------------------------------------builder.size(20);request.source(builder);// 3.執行查詢SearchResponse response = client.search(request, RequestOptions.DEFAULT);// 4.輸出查詢結果for (SearchHit hit : response.getHits().getHits()) {System.out.println(hit.getSourceAsMap());}System.out.println(response.getHits().getHits().length);}

6.2.4 multi_match

match 針對一個field 做檢索，multi_math 針對多個field 進行檢索，多個field對應一個文本。 #multi_math 查詢 POST /sms-logs-index/sms-logs-type/_search {"query":{"multi_match": {"query": "北京","fields": ["province","smsContent"]}} } public void multiMatchSearch() throws IOException {// 1.創建request對象SearchRequest request = new SearchRequest(index);request.types(type);// 2.創建查詢條件SearchSourceBuilder builder = new SearchSourceBuilder();//--------------------------------------------------------------builder.query(QueryBuilders.multiMatchQuery("北京","province","smsContent"));//--------------------------------------------------------------builder.size(20);request.source(builder);// 3.執行查詢SearchResponse response = client.search(request, RequestOptions.DEFAULT);// 4.輸出查詢結果for (SearchHit hit : response.getHits().getHits()) {System.out.println(hit.getSourceAsMap());}System.out.println(response.getHits().getHits().length);}

6.3 其他查詢

6.3.1id 查詢

#id 查詢 GET /sms-logs-index/sms-logs-type/1 public class IdGetSearch {ObjectMapper mapper = new ObjectMapper();RestHighLevelClient client = EsClient.getClient();String index = "sms-logs-index";String type="sms-logs-type";@Testpublic void findById() throws IOException {// 創建GetRequest對象GetRequest request = new GetRequest(index,type,"1");// 執行查詢GetResponse response = client.get(request, RequestOptions.DEFAULT);// 輸出結果System.out.println(response.getSourceAsMap());} }

6.3.2 ids查詢

根據多個id 查詢,類似 mysql 中的 where in (id1,id2...) #ids 查詢 POST /sms-logs-index/sms-logs-type/_search {"query": {"ids": {"values": ["1","2","3"]}} } public void findByIds() throws IOException {// 創建request對象SearchRequest request = new SearchRequest(index);request.types(type);// 指定查詢條件SearchSourceBuilder builder = new SearchSourceBuilder();//--------------------------------------------------builder.query(QueryBuilders.idsQuery().addIds("1","2","3"));//------------------------------------------------------request.source(builder);// 執行SearchResponse response = client.search(request, RequestOptions.DEFAULT);// 輸出結果for (SearchHit hit : response.getHits().getHits()) {System.out.println(hit.getSourceAsMap());}}

6.3.3 prefix 查詢

前綴查詢，可以通過一個關鍵字去指定一個field 的前綴，從而查詢到指定文檔

#prefix 查詢 POST /sms-logs-index/sms-logs-type/_search {"query": {"prefix": {"corpName": {"value": "海"}}} } #match 查詢在這里是什么都查不到的和上邊的prefix 做比較 POST /sms-logs-index/sms-logs-type/_search {"query": {"match": {"corpName": "海"}} } public void findByPrefix() throws IOException {// 創建request對象SearchRequest request = new SearchRequest(index);request.types(type);// 指定查詢條件SearchSourceBuilder builder = new SearchSourceBuilder();//--------------------------------------------------builder.query(QueryBuilders.prefixQuery("corpName","阿"));//------------------------------------------------------request.source(builder);// 執行SearchResponse response = client.search(request, RequestOptions.DEFAULT);// 輸出結果for (SearchHit hit : response.getHits().getHits()) {System.out.println(hit.getSourceAsMap());}}

6.3.4 fuzzy 查詢

模糊查詢，我們可以輸入一個字符的大概，ES 可以根據輸入的大概去匹配內容。查詢結果不穩定 #fuzzy 查詢 POST /sms-logs-index/sms-logs-type/_search {"query": {"fuzzy": {"corpName": {"value": "騰訊客堂",#指定前邊幾個字符是不允許出現錯誤的"prefix_length": 2}}} } public void findByFuzzy() throws IOException {// 創建request對象SearchRequest request = new SearchRequest(index);request.types(type);// 指定查詢條件SearchSourceBuilder builder = new SearchSourceBuilder();//--------------------------------------------------builder.query(QueryBuilders.fuzzyQuery("corpName","騰訊客堂").prefixLength(2));//------------------------------------------------------request.source(builder);// 執行SearchResponse response = client.search(request, RequestOptions.DEFAULT);// 輸出結果for (SearchHit hit : response.getHits().getHits()) {System.out.println(hit.getSourceAsMap());}}

6.3.5 wildcard 查詢

通配查詢，同mysql中的like 是一樣的，可以在查詢時，在字符串中指定通配符*和占位符？ #wildcard 查詢 POST /sms-logs-index/sms-logs-type/_search {"query": {"wildcard": {"corpName": {"value": "海爾*"}}} }#wildcard 查詢 POST /sms-logs-index/sms-logs-type/_search {"query": {"wildcard": {"corpName": {"value": "海爾??"}}} } public void findByWildCard() throws IOException {// 創建request對象SearchRequest request = new SearchRequest(index);request.types(type);// 指定查詢條件SearchSourceBuilder builder = new SearchSourceBuilder();//--------------------------------------------------builder.query(QueryBuilders.wildcardQuery("corpName","海爾*"));//------------------------------------------------------request.source(builder);// 執行SearchResponse response = client.search(request, RequestOptions.DEFAULT);// 輸出結果for (SearchHit hit : response.getHits().getHits()) {System.out.println(hit.getSourceAsMap());}}

6.3.6 rang 查詢

范圍查詢，只針對數值類型，對一個field 進行大于或者小于的范圍指定

#rang 查詢 POST /sms-logs-index/sms-logs-type/_search {"query": {"range": {"fee": {"gte": 10,"lte": 20}}} } public void findByRang() throws IOException {// 創建request對象SearchRequest request = new SearchRequest(index);request.types(type);// 指定查詢條件SearchSourceBuilder builder = new SearchSourceBuilder();//--------------------------------------------------builder.query(QueryBuilders.rangeQuery("fee").gt(10).lte(30));//------------------------------------------------------request.source(builder);// 執行SearchResponse response = client.search(request, RequestOptions.DEFAULT);// 輸出結果for (SearchHit hit : response.getHits().getHits()) {System.out.println(hit.getSourceAsMap());}}

6.3.7 regexp 查詢

正則查詢，通過你編寫的正則表達式去匹配內容 Ps:prefix wildcard fuzzy 和regexp 查詢效率比較低 ,在要求效率比較高時，避免使用 #regexp 查詢 POST /sms-logs-index/sms-logs-type/_search {"query": {"regexp": {"mobile": "138[0-9]{8}"}} } public void findByRegexp() throws IOException {// 創建request對象SearchRequest request = new SearchRequest(index);request.types(type);// 指定查詢條件SearchSourceBuilder builder = new SearchSourceBuilder();//--------------------------------------------------builder.query(QueryBuilders.regexpQuery("mobile","138[0-9]{8}"));//------------------------------------------------------request.source(builder);// 執行SearchResponse response = client.search(request, RequestOptions.DEFAULT);// 輸出結果for (SearchHit hit : response.getHits().getHits()) {System.out.println(hit.getSourceAsMap());} }

6.4 深分頁 scrol l

ES 對from +size時又限制的，from +size 之和不能大于1W,超過后效率會十分低下原理：from+size ES查詢數據的方式，第一步將用戶指定的關鍵詞進行分詞，第二部將詞匯去分詞庫中進行檢索，得到多個文檔id,第三步去各個分片中拉去數據，耗時相對較長第四步根據score 將數據進行排序，耗時相對較長第五步根據from 和size 的值將部分數據舍棄，第六步，返回結果。scroll +size ES 查詢數據的方式第一步將用戶指定的關鍵詞進行分詞，第二部將詞匯去分詞庫中進行檢索，得到多個文檔id,第三步，將文檔的id放在一個上下文中第四步，根據指定的size去ES中檢索指定個數數據，拿完數據的文檔id,會從上下文中移除第五步，如果需要下一頁的數據，直接去ES的上下文中找后續內容。第六步，循環第四步和第五步scroll 不適合做實時查詢。 #scroll 查詢,返回第一頁數據，并將文檔id信息存放在ES上下文中，并指定生存時間 POST /sms-logs-index/sms-logs-type/_search?scroll=1m {"query": {"match_all": {}},"size": 2,"sort": [{"fee": {"order": "desc"}}] }#根據scroll 查詢下一頁數據 POST _search/scroll {"scroll_id":"DnF1ZXJ5VGhlbkZldGNoAwAAAAAAABbqFk04VlZ1cjlUU2t1eHpsQWNRY1YwWWcAAAAAAAAW7BZNOFZWdXI5VFNrdXh6bEFjUWNWMFlnAAAAAAAAFusWTThWVnVyOVRTa3V4emxBY1FjVjBZZw==","scroll":"1m" }#刪除scroll上下文中的數據 DELETE _search/scroll/DnF1ZXJ5VGhlbkZldGNoAwAAAAAAABchFk04VlZ1cjlUU2t1eHpsQWNRY1YwWWcAAAAAAAAXIBZNOFZWdXI5VFNrdXh6bEFjUWNWMFlnAAAAAAAAFx8WTThWVnVyOVRTa3V4emxBY1FjVjBZZw== public class ScrollSearch {ObjectMapper mapper = new ObjectMapper();RestHighLevelClient client = EsClient.getClient();String index = "sms-logs-index";String type="sms-logs-type";@Testpublic void scrollSearch() throws IOException {// 1.創建requestSearchRequest searchRequest = new SearchRequest(index);searchRequest.types(type);// 2.指定scroll信息,過期時間searchRequest.scroll(TimeValue.timeValueMinutes(1L));// 3.指定查詢條件SearchSourceBuilder builder = new SearchSourceBuilder();builder.size(4);builder.sort("fee", SortOrder.DESC);searchRequest.source(builder);// 4.獲取返回結果scrollId,獲取sourceSearchResponse response = client.search(searchRequest, RequestOptions.DEFAULT);String scrollId = response.getScrollId();System.out.println("-------------首頁數據---------------------");for (SearchHit hit : response.getHits().getHits()) {System.out.println(hit.getSourceAsMap());}while (true){// 5.創建scroll requestSearchScrollRequest scrollRequest = new SearchScrollRequest(scrollId);// 6.指定scroll 有效時間scrollRequest.scroll(TimeValue.timeValueMinutes(1L));// 7.執行查詢，返回查詢結果SearchResponse scroll = client.scroll(scrollRequest, RequestOptions.DEFAULT);// 8.判斷是否查詢到數據，查詢到輸出SearchHit[] searchHits = scroll.getHits().getHits();if(searchHits!=null && searchHits.length >0){System.out.println("-------------下一頁數據---------------------");for (SearchHit hit : searchHits) {System.out.println(hit.getSourceAsMap());}}else{// 9.沒有數據，結束System.out.println("-------------結束---------------------");break;}}// 10.創建 clearScrollRequestClearScrollRequest clearScrollRequest = new ClearScrollRequest();// 11.指定scrollIdclearScrollRequest.addScrollId(scrollId);//12.刪除scrollClearScrollResponse clearScrollResponse = client.clearScroll(clearScrollRequest, RequestOptions.DEFAULT);// 13.輸出結果System.out.println("刪除scroll:"+clearScrollResponse.isSucceeded());} }

6.5 delete-by-query

根據term,match 等查詢方式去刪除大量索引 PS:如果你要刪除的內容，時index下的大部分數據，推薦創建一個新的index,然后把保留的文檔內容，添加到全新的索引 #Delet-by-query 刪除 POST /sms-logs-index/sms-logs-type/_delete_by_query {"query": {"range": {"fee": {"lt": 20}}} } public void deleteByQuery() throws IOException {// 1.創建DeleteByQueryRequestDeleteByQueryRequest request = new DeleteByQueryRequest(index);request.types(type);// 2.指定條件request.setQuery(QueryBuilders.rangeQuery("fee").lt(20));// 3.執行BulkByScrollResponse response = client.deleteByQuery(request, RequestOptions.DEFAULT);// 4.輸出返回結果System.out.println(response.toString());}

6.6 復合查詢

復合過濾器，將你的多個查詢條件以一定的邏輯組合在一起，must:所有條件組合在一起，表示 and 的意思 must_not: 將must_not中的條件，全部都不匹配，表示not的意思 should:所有條件用should 組合在一起，表示or 的意思 #省是晉城或者北京 # 運營商不能是聯通 #smsContent 包含戰士和的 POST /sms-logs-index/sms-logs-type/_search {"query": {"bool": {"should": [{"term": {"province": {"value": "晉城"}}},{"term": {"province": {"value": "北京"}}}],"must_not": [{"term": {"operatorId": {"value": "2"}}}],"must": [{"match": {"smsContent": "戰士"}},{"match": {"smsContent": "的"}}]}} } public void boolSearch() throws IOException {// 1.創建 searchRequestSearchRequest request = new SearchRequest(index);request.types(type);// 2.指定查詢條件SearchSourceBuilder builder = new SearchSourceBuilder();BoolQueryBuilder boolQueryBuilder = new BoolQueryBuilder();// #省是晉城或者北京boolQueryBuilder.should(QueryBuilders.termQuery("province","北京"));boolQueryBuilder.should(QueryBuilders.termQuery("province","晉城"));//# 運營商不能是聯通boolQueryBuilder.mustNot(QueryBuilders.termQuery("operatorId",2));//#smsContent 包含戰士和的boolQueryBuilder.must(QueryBuilders.matchQuery("smsContent","戰士"));boolQueryBuilder.must(QueryBuilders.matchQuery("smsContent","的"));builder.query(boolQueryBuilder);request.source(builder);// 3.執行查詢SearchResponse response = client.search(request, RequestOptions.DEFAULT);// 4.輸出結果for (SearchHit hit : response.getHits().getHits()) {System.out.println(hit.getSourceAsMap());}}

6.6.2 boosting 查詢

boosting 查詢可以幫助我們去影響查詢后的scorepositive:只有匹配上positive 查詢的內容，才會被放到返回的結果集中negative: 如果匹配上了positive 也匹配上了negative, 就可以降低這樣的文檔score.negative_boost:指定系數,必須小于1 0.5 關于查詢時，分數時如何計算的：搜索的關鍵字再文檔中出現的頻次越高，分數越高指定的文檔內容越短，分數越高。我們再搜索時，指定的關鍵字也會被分詞，這個被分詞的內容，被分詞庫匹配的個數越多，分數就越高。 #boosting 查詢 POST /sms-logs-index/sms-logs-type/_search {"query": {"boosting": {"positive": {"match": {"smsContent": "戰士"}}, "negative": {"match": {"smsContent": "團隊"}},"negative_boost": 0.2}} } public void boostSearch() throws IOException {// 1.創建 searchRequestSearchRequest request = new SearchRequest(index);request.types(type);// 2.指定查詢條件SearchSourceBuilder builder = new SearchSourceBuilder();BoostingQueryBuilder boost = QueryBuilders.boostingQuery(QueryBuilders.matchQuery("smsContent", "戰士"),QueryBuilders.matchQuery("smsContent", "團隊")).negativeBoost(0.2f);builder.query(boost);request.source(builder);// 3.執行查詢SearchResponse response = client.search(request, RequestOptions.DEFAULT);// 4.輸出結果for (SearchHit hit : response.getHits().getHits()) {System.out.println(hit.getSourceAsMap());}}

6.7 filter 查詢

query 查詢：根據你的查詢條件，去計算文檔的匹配度得到一個分數，并根據分數排序，不會做緩存的。

filter 查詢：根據查詢條件去查詢文檔，不去計算分數，而且filter會對經常被過濾的數據進行緩存。

#filter 查詢 POST /sms-logs-index/sms-logs-type/_search {"query": {"bool": {"filter": [{"term": {"corpName": "海爾智家公司"}},{"range":{"fee":{"lte":50}}}]}} } public void filter() throws IOException {// 1.searchRequestSearchRequest searchRequest = new SearchRequest(index);searchRequest.types(type);// 2.指定查詢條件SearchSourceBuilder sourceBuilder = new SearchSourceBuilder();BoolQueryBuilder boolBuilder = QueryBuilders.boolQuery();boolBuilder.filter(QueryBuilders.termQuery("corpName","海爾智家公司"));boolBuilder.filter(QueryBuilders.rangeQuery("fee").gt(20));sourceBuilder.query(boolBuilder);searchRequest.source(sourceBuilder);// 3.執行SearchResponse response = client.search(searchRequest, RequestOptions.DEFAULT);// 4. 輸出結果for (SearchHit hit : response.getHits().getHits()) {System.out.println(hit.getSourceAsMap());System.out.println(hit.getId()+"的分數是："+hit.getScore());}}

6.8 高亮查詢

高亮查詢就是用戶輸入的關鍵字，以一定特殊樣式展示給用戶，讓用戶知道為什么這個結果被檢索出來高亮展示的數據，本身就是文檔中的一個field,單獨將field以highlight的形式返回給用戶 ES提供了一個highlight 屬性，他和query 同級別。frament_size: 指定高亮數據展示多少個字符回來pre_tags:指定前綴標簽<front color="red">post_tags:指定后綴標簽 #highlight 高亮查詢 POST /sms-logs-index/sms-logs-type/_search {"query": {"match": {"smsContent": "團隊"}},"highlight": {"fields": {"smsContent":{}},"pre_tags":"","post_tags":"","fragment_size":10} } public void highLightQuery() throws IOException {// 1.創建requestSearchRequest request = new SearchRequest(index);request.types(type);// 2.指定查詢條件，指定高亮SearchSourceBuilder builder = new SearchSourceBuilder();builder.query(QueryBuilders.matchQuery("smsContent","團隊"));HighlightBuilder highlightBuilder = new HighlightBuilder();highlightBuilder.field("smsContent",10).preTags("").postTags("");builder.highlighter(highlightBuilder);request.source(builder);// 3.執行SearchResponse response = client.search(request, RequestOptions.DEFAULT);//4. 輸出結果for (SearchHit hit : response.getHits().getHits()) {System.out.println(hit.getHighlightFields().get("smsContent"));}}

6.9 聚合查詢

ES的聚合查詢和mysql 的聚合查詢類似，ES的聚合查詢相比mysql 要強大得多。ES提供的統計數據的方式多種多樣。 #ES 聚合查詢的RSTFul 語法 POST /index/type/_search {"aggs":{"(名字)agg":{"agg_type":{"屬性"："值"}}} }

6.9.1 去重計數聚合查詢

去重計數，cardinality 先將返回的文檔中的一個指定的field進行去重，統計一共有多少條 # 去重計數查詢 province POST /sms-logs-index/sms-logs-type/_search {"aggs": {"provinceAgg": {"cardinality": {"field": "province"}}} } public void aggCardinalityC() throws IOException {// 1.創建requestSearchRequest request = new SearchRequest(index);request.types(type);// 2. 指定使用聚合查詢方式SearchSourceBuilder builder = new SearchSourceBuilder();builder.aggregation(AggregationBuilders.cardinality("provinceAgg").field("province"));request.source(builder);// 3.執行查詢SearchResponse response = client.search(request, RequestOptions.DEFAULT);// 4.輸出返回結果Cardinality agg = response.getAggregations().get("provinceAgg");System.out.println(agg.getValue());}

6.9.2 范圍統計

統計一定范圍內出現的文檔個數，比如，針對某一個field 的值再0~100,100~200,200~300 之間文檔出現的個數分別是多少范圍統計可以針對普通的數值，針對時間類型，針對ip類型都可以響應。數值 rang 時間 date_rang ip ip_rang #針對數值方式的范圍統計 from 帶等于效果，to 不帶等于效果 POST /sms-logs-index/sms-logs-type/_search {"aggs": {"agg": {"range": {"field": "fee","ranges": [{"to": 30},{"from": 30,"to": 60},{"from": 60}]}}} } #時間方式統計 POST /sms-logs-index/sms-logs-type/_search {"aggs": {"agg": {"date_range": {"field": "sendDate","format": "yyyy", "ranges": [{"to": "2000"},{"from": "2000"}]}}} } #ip 方式范圍統計 POST /sms-logs-index/sms-logs-type/_search {"aggs": {"agg": {"ip_range": {"field": "ipAddr","ranges": [{"to": "127.0.0.8"},{"from": "127.0.0.8"}]}}} } public void aggRang() throws IOException {// 1.創建requestSearchRequest request = new SearchRequest(index);request.types(type);// 2. 指定使用聚合查詢方式SearchSourceBuilder builder = new SearchSourceBuilder();builder.aggregation(AggregationBuilders.range("agg").field("fee").addUnboundedTo(30).addRange(30,60).addUnboundedFrom(60));request.source(builder);// 3.執行查詢SearchResponse response = client.search(request, RequestOptions.DEFAULT);// 4.輸出返回結果Range agg = response.getAggregations().get("agg");for (Range.Bucket bucket : agg.getBuckets()) {String key = bucket.getKeyAsString();Object from = bucket.getFrom();Object to = bucket.getTo();long docCount = bucket.getDocCount();System.out.println(String.format("key: %s ,from: %s ,to: %s ,docCount: %s",key,from,to,docCount));}}

6.9.3 統計聚合

他可以幫你查詢指定field 的最大值，最小值，平均值，平方和... 使用 extended_stats #統計聚合查詢 extended_stats POST /sms-logs-index/sms-logs-type/_search {"aggs": {"agg": {"extended_stats": {"field": "fee"}}} } // java實現 public void aggExtendedStats() throws IOException {// 1.創建requestSearchRequest request = new SearchRequest(index);request.types(type);// 2. 指定使用聚合查詢方式SearchSourceBuilder builder = new SearchSourceBuilder();builder.aggregation(AggregationBuilders.extendedStats("agg").field("fee"));request.source(builder);// 3.執行查詢SearchResponse response = client.search(request, RequestOptions.DEFAULT);// 4.輸出返回結果ExtendedStats extendedStats = response.getAggregations().get("agg");System.out.println("最大值："+extendedStats.getMaxAsString()+",最小值："+extendedStats.getMinAsString());}

6.9.4 其他聚合查詢查看官方文檔

https://www.elastic.co/guide/en/elasticsearch/reference/6.8/search-aggregations-metrics-weight-avg-aggregation.html

6.10 地圖經緯度搜索

#創建一個經緯度索引,指定一個 name ,一個location PUT /map {"settings": {"number_of_shards": 5,"number_of_replicas": 1},"mappings": {"map":{"properties":{"name":{"type":"text"},"location":{"type":"geo_point"}}}} }#添加測試數據 PUT /map/map/1 {"name":"天安門","location":{"lon": 116.403694,"lat":39.914492} }PUT /map/map/2 {"name":"百望山","location":{"lon": 116.26284,"lat":40.036576} }PUT /map/map/3 {"name":"北京動物園","location":{"lon": 116.347352,"lat":39.947468} }

6.10.1 ES 的地圖檢索方式

geo_distance :直線距離檢索方式 geo_bounding_box: 以2個點確定一個矩形，獲取再矩形內的數據 geo_polygon:以多個點，確定一個多邊形，獲取多邊形的全部數據

6.10.2 基于RESTFul 實現地圖檢索

geo_distance

#geo_distance POST /map/map/_search {"query": {"geo_distance":{#確定一個點"location":{"lon":116.434739,"lat":39.909843},#確定半徑"distance":20000,#指定形狀為圓形"distance_type":"arc"}} } #geo_bounding_box POST /map/map/_search {"query":{"geo_bounding_box":{"location":{"top_left":{"lon":116.327805,"lat":39.95499},"bottom_right":{"lon": 116.363162,"lat":39.938395}}}} } #geo_polygon POST /map/map/_search {"query":{"geo_polygon":{"location":{# 指定多個點確定位置"points":[{"lon":116.220296,"lat":40.075013},{"lon":116.346777,"lat":40.044751},{"lon":116.236106,"lat":39.981533} ]}}} }

6.10.3 java 實現 geo_polygon

public class GeoDemo {RestHighLevelClient client = EsClient.getClient();String index = "map";String type="map";@Testpublic void GeoPolygon() throws IOException {// 1.創建searchRequestSearchRequest request = new SearchRequest(index);request.types(type);// 2.指定檢索方式SearchSourceBuilder builder = new SearchSourceBuilder();List<GeoPoint> points = new ArrayList<>();points.add(new GeoPoint(40.075013,116.220296));points.add(new GeoPoint(40.044751,116.346777));points.add(new GeoPoint(39.981533,116.236106));builder.query(QueryBuilders.geoPolygonQuery("location",points));request.source(builder);// 3.執行SearchResponse response = client.search(request, RequestOptions.DEFAULT);// 4.輸出結果for (SearchHit hit : response.getHits().getHits()) {System.out.println(hit.getSourceAsMap());}} }

總結

以上是生活随笔為你收集整理的ES笔记_转自尚硅谷_其中有JAVA操作_ES的全部內容，希望文章能夠幫你解決所遇到的問題。

如果覺得生活随笔網站內容還不錯，歡迎將生活随笔推薦給好友。

上一篇：金钏跳井，凸显贾府主子冷血，下人们离心离
下一篇：职场技巧：高效实用的四象限法则