SpringMVC项目使用elastic search搜索

项目需要，引入了elastic search(后续简称es)，后面将介绍本地对es的安装，使用以及java连接es查询的整个过程。

1、es索引字段建立与修改，以curl新增一个索引字段示例

curl -X PUT 
  http://127.0.0.1:9200/idx_your_entity/_mapping/your_entity 
  -H 'Content-Type: application/json' 
  -H 'Postman-Token: 326dd921-4f7e-498b-866a-2de5173a908f' 
  -H 'cache-control: no-cache' 
  -d '{
    "properties": {
       "is_enable":{
            "type":"integer"
        }
    }
}

2、使用logstash向es里面增量推数据，需要有update_date字段

input {
    jdbc {
        jdbc_driver_library => "D:/logstash-6.7.1/lib/sqljdbc4.jar"
        jdbc_driver_class => "com.microsoft.sqlserver.jdbc.SQLServerDriver"
        jdbc_connection_string => "jdbc:sqlserver://database_link;DatabaseName=HIM_bak;"
        jdbc_user => "username"
        jdbc_password => "password"
        schedule => "* * * * *"
        jdbc_default_timezone => "Asia/Shanghai"
		use_column_value => false
		tracking_column => "update_date"
        statement => "select 
			[fields you need] 
			from table WHERE update_date > :sql_last_value"
    }
}
output {
    elasticsearch {
        index => "idx_workhelp"
        document_type => "workhelp"
        document_id => "%{helpno}"
        hosts => ["127.0.0.1:9200"]
    }
}

3、es查询jar包，pom配置

<dependency>
    <groupId>org.elasticsearch.client</groupId>
        <artifactId>transport</artifactId>
    <version>6.7.1</version>
</dependency>

4、es数据源，查询client配置

@Bean
public TransportClient client() throws Exception {
    // init client
    TransportAddress transportAddress = new TransportAddress(InetAddress.getByName(hostName), port);
    Settings settings = Settings.builder().put("cluster.name", nodeName).build();
    client = new PreBuiltTransportClient(settings);
    client.addTransportAddress(transportAddress);
    logger.info("use es and elastic search connect successful");
    return client;
}

5、es查询条件的构建:这里介绍两种查询条件的构建，must表示且，should表示或；同时用到了两种匹配方式：termQuery代表完全匹配，配合索引类型 keywords 使用，matchQuery代表模糊匹配，配合text使用。

 BoolQueryBuilder boolQueryBuilder = QueryBuilders.boolQuery();
 //示例 A=a and B like %b% and (C like %c% or D like %d%)
 boolQueryBuilder.filter(QueryBuilders.termQuery(fieldA, a));
 boolQueryBuilder.must(QueryBuilders.matchQuery(fieldB, b));
 boolQueryBuilder.must(
                    QueryBuilders.boolQuery()
                    .should(QueryBuilders.matchQuery(fieldC, c))
                    .should(QueryBuilders.matchQuery(fieldD, d)));

6、设置关键词高亮显示

highlightBuilder.preTags("<span class='highLight'>");
highlightBuilder.postTags("</span>");
highlightBuilder.field(field);

7、把条件带入并且执行查询,hits即查询结构，需要的数据类型SearchHits结构不复杂，这里不再赘叙。

SearchRequestBuilder searchRequestBuilder = client
    .prepareSearch(INDEX)
    .setSearchType(SearchType.DFS_QUERY_THEN_FETCH)
    .setQuery(boolQueryBuilder);
searchRequestBuilder.highlighter(problemDescHiBuilder);
// 分页
searchRequestBuilder.setFrom(startIndex);
searchRequestBuilder.setSize(pageSize);
// 排序
searchRequestBuilder
    .addSort(SortBuilders.fieldSort(CREATEDATE))
    .addSort(SortBuilders.fieldSort(READCOUNT)
    .order(SortOrder.DESC));
SearchResponse response = searchRequestBuilder.get();
SearchHits hits = searchRequestBuilder.get().getHits();

8、查询结果。查询结果即对SearchHits进行处理，转化为自己项目的视图对象，一般为 业务实体VO 的命名方式进行表达，传到控制层。

9、最后：写到这里，大家有问题可以联系我共同学习探讨~