Elasticsearch：RestClient+SearchSourceBuilder使用案例[转]

原文地址：https://blog.51cto.com/xpleaf/2294268

1 前言

RestClient是较低层的API，这里使用基于其封装的高层API，即RestHighLevelClient。

需要添加的依赖如下：

<dependency> <groupId>org.elasticsearch</groupId> <artifactId>elasticsearch</artifactId> <version>5.6.10</version> </dependency> <dependency> <groupId>org.elasticsearch.client</groupId> <artifactId>elasticsearch-rest-high-level-client</artifactId> <version>5.6.10</version> </dependency>

较低版本的es可能不支持RestHighLevelClient。
查看一下其maven中央仓库：https://mvnrepository.com/artifact/org.elasticsearch.client/elasticsearch-rest-high-level-client
可以看到，5.6以上的版本才有。

2 测试案例

测试代码如下：

package com.xpleaf.es.leaf; import org.apache.http.HttpHost; import org.elasticsearch.action.search.SearchRequest; import org.elasticsearch.action.search.SearchResponse; import org.elasticsearch.client.RestClient; import org.elasticsearch.client.RestHighLevelClient; import org.elasticsearch.common.unit.TimeValue; import org.elasticsearch.index.query.*; import org.elasticsearch.search.builder.SearchSourceBuilder; import org.elasticsearch.search.sort.SortOrder; import org.junit.After; import org.junit.Before; import org.junit.Test; /** * @author xpleaf * @GitHub https://github.com/xpleaf * @Blog https://blog.51cto.com/xpleaf * @date 2018/10/7 下午12:05 */ public class RestHighLevelClientTest { private HttpHost[] esHosts = new HttpHost[]{ new HttpHost("localhost", 9200) }; private RestClient restClient = null; private RestHighLevelClient client = null; private BoolQueryBuilder boolQueryBuilder = null; @Before public void init() throws Exception { // 1.创建RestClient对象 restClient = RestClient.builder(esHosts).build(); client = new RestHighLevelClient(restClient); // 2.创建BoolQueryBuilder对象 boolQueryBuilder = new BoolQueryBuilder(); // 3.设置boolQueryBuilder条件 MatchPhraseQueryBuilder matchPhraseQueryBuilder = QueryBuilders .matchPhraseQuery("key_word", "广东"); MatchPhraseQueryBuilder matchPhraseQueryBuilder2 = QueryBuilders .matchPhraseQuery("key_word", "湖人"); RangeQueryBuilder rangeQueryBuilder = QueryBuilders .rangeQuery("postdate") .from("2016-01-01 00:00:00"); // 子boolQueryBuilder条件条件，用来表示查询条件or的关系 BoolQueryBuilder childBoolQueryBuilder = new BoolQueryBuilder() .should(matchPhraseQueryBuilder) .should(matchPhraseQueryBuilder2); // 4.添加查询条件到boolQueryBuilder中 boolQueryBuilder .must(childBoolQueryBuilder) .must(rangeQueryBuilder); } // 测试SearchSourceBuilder的搜索 @Test public void test01() throws Exception { // 1.创建并设置SearchSourceBuilder对象 SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder(); // 查询条件--->生成DSL查询语句 searchSourceBuilder.query(boolQueryBuilder); // 第几页 searchSourceBuilder.from(0); // 每页多少条数据 searchSourceBuilder.size(100); // 获取的字段（列）和不需要获取的列 searchSourceBuilder.fetchSource(new String[]{"postdate", "key_word"}, new String[]{}); // 设置排序规则 searchSourceBuilder.sort("postdate", SortOrder.ASC); // 设置超时时间为2s searchSourceBuilder.timeout(new TimeValue(2000)); // 2.创建并设置SearchRequest对象 SearchRequest searchRequest = new SearchRequest(); // 设置request要搜索的索引和类型 searchRequest.indices("spnews").types("news"); // 设置SearchSourceBuilder查询属性 searchRequest.source(searchSourceBuilder); // 3.查询 SearchResponse searchResponse = client.search(searchRequest); System.out.println(searchResponse.toString()); } @After public void after() throws Exception { restClient.close(); } }

3 分析

3.1 Rest Json

上面测试案例的查询条件：

// 2.创建BoolQueryBuilder对象 boolQueryBuilder = new BoolQueryBuilder(); // 3.设置boolQueryBuilder条件 MatchPhraseQueryBuilder matchPhraseQueryBuilder = QueryBuilders .matchPhraseQuery("key_word", "广东"); MatchPhraseQueryBuilder matchPhraseQueryBuilder2 = QueryBuilders .matchPhraseQuery("key_word", "湖人"); RangeQueryBuilder rangeQueryBuilder = QueryBuilders .rangeQuery("postdate") .from("2016-01-01 00:00:00"); // 子boolQueryBuilder条件条件，用来表示查询条件or的关系 BoolQueryBuilder childBoolQueryBuilder = new BoolQueryBuilder() .should(matchPhraseQueryBuilder) .should(matchPhraseQueryBuilder2); // 4.添加查询条件到boolQueryBuilder中 boolQueryBuilder .must(childBoolQueryBuilder) .must(rangeQueryBuilder);

实际上会转化为如下的es查询语句（可以debug一下，使用searchSourceBuilder就是用来做这种转换）：

{
  "from" : 0, "size" : 100, "timeout" : "2000ms", "query" : { "bool" : { "must" : [ { "bool" : { "should" : [ { "match_phrase" : { "key_word" : { "query" : "广东", "slop" : 0, "boost" : 1.0 } } }, { "match_phrase" : { "key_word" : { "query" : "湖人", "slop" : 0, "boost" : 1.0 } } } ], "disable_coord" : false, "adjust_pure_negative" : true, "boost" : 1.0 } }, { "range" : { "postdate" : { "from" : "2016-01-01 00:00:00", "to" : null, "include_lower" : true, "include_upper" : true, "boost" : 1.0 } } } ], "disable_coord" : false, "adjust_pure_negative" : true, "boost" : 1.0 } }, "_source" : { "includes" : [ "postdate", "key_word" ], "excludes" : [ ] }, "sort" : [ { "postdate" : { "order" : "asc" } } ] }

3.2 match query VS match_phrase query

注意其差别：

• match query：会对查询语句进行分词，分词后查询语句中的任何一个词项被匹配，文档就会被搜索到。如果想查询匹配所有关键词的文档，可以用and操作符连接；
• match_phrase query：满足下面两个条件才会被搜索到
  • （1）分词后所有词项都要出现在该字段中
  • （2）字段中的词项顺序要一致