elasticsearch 6.0java api的使用

elasticsearch 6.0 中java api的使用

1：使用java api创建elasticsearch客户端

package com.search.elasticsearch;

import org.elasticsearch.client.transport.TransportClient;
import org.elasticsearch.common.settings.Settings;
import org.elasticsearch.common.transport.TransportAddress;
import org.elasticsearch.transport.client.PreBuiltTransportClient;

import java.io.IOException;
import java.io.InputStream;
import java.net.InetAddress;
import java.util.Properties;

public class ElasticsearchConfig {
    private static TransportClient client;
    public TransportClient getElasticsearchClient() {
        try {
            Settings settings = Settings.builder()
                    .put("cluster.name", "my-esLearn")  //连接的集群名
                    .put("client.transport.ignore_cluster_name", true)  //如果集群名不对，也能连接
                    .build();
            //创建client
            client = new PreBuiltTransportClient(settings)
                    .addTransportAddress(new TransportAddress(InetAddress.getByName("127.0.0.1"), 9300));  //主机和端口号
            return client;
        } catch (Exception e) {
            e.printStackTrace();
        }
        return null;
    }
}

2：使用客户端创建索引，索引中 某些字段指定ik分词器等

package com.search.elasticsearch;

import org.elasticsearch.action.DocWriteResponse;
import org.elasticsearch.action.admin.indices.analyze.AnalyzeRequestBuilder;
import org.elasticsearch.action.admin.indices.mapping.put.PutMappingRequest;
import org.elasticsearch.action.bulk.BulkItemResponse;
import org.elasticsearch.action.bulk.BulkRequestBuilder;
import org.elasticsearch.action.bulk.BulkResponse;
import org.elasticsearch.action.get.GetResponse;
import org.elasticsearch.action.index.IndexRequest;
import org.elasticsearch.action.index.IndexResponse;
import org.elasticsearch.action.search.SearchResponse;
import org.elasticsearch.action.search.SearchType;
import org.elasticsearch.action.update.UpdateRequest;
import org.elasticsearch.action.update.UpdateResponse;
import org.elasticsearch.client.IndicesAdminClient;
import org.elasticsearch.client.Requests;
import org.elasticsearch.client.transport.TransportClient;
import org.elasticsearch.common.settings.Settings;
import org.elasticsearch.common.transport.TransportAddress;
import org.elasticsearch.common.xcontent.XContentBuilder;
import org.elasticsearch.common.xcontent.XContentFactory;
import org.elasticsearch.index.query.QueryBuilders;
import org.elasticsearch.transport.client.PreBuiltTransportClient;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.beans.factory.annotation.Value;

import java.io.IOException;
import java.io.InputStream;
import java.net.InetAddress;
import java.util.Date;
import java.util.List;
import java.util.Properties;
import java.util.ResourceBundle;
import java.util.concurrent.ExecutionException;

import static org.elasticsearch.common.xcontent.XContentFactory.jsonBuilder;

public class ElasticSearchUtil {

    private static TransportClient client;
    public ElasticSearchUtil() {
        this.client=new ElasticsearchConfig().getElasticsearchClient();  //使用上面创建好的客户端添加到类中。
    }

    //创建索引，并给索引某些字段指定iK分词，以后向该索引中查询时，就会用ik分词。
    public void createIndex() throws IOException {
        //创建映射
        XContentBuilder mapping = XContentFactory.jsonBuilder()
                .startObject()
                .startObject("properties")
                //      .startObject("m_id").field("type","keyword").endObject()
 　　                  //title:字段名，  type:文本类型       analyzer ：分词器类型 
                .startObject("title").field("type", "text").field("analyzer", "ik_smart").endObject()   //该字段添加的内容，查询时将会使用ik_smart分词
                .startObject("content").field("type", "text").field("analyzer", "ik_max_word").endObject()
                .endObject()
                .endObject();

        //index：索引名   type：类型名（可以自己定义）
        PutMappingRequest putmap = Requests.putMappingRequest("index").type("type").source(mapping);
        //创建索引
        client.admin().indices().prepareCreate("index").execute().actionGet();
        //为索引添加映射
        client.admin().indices().putMapping(putmap).actionGet();
    }
}

这个时候索引就创建好了，mapping不能掉

3:  向上一步创建的索引中添加内容，包括id,id不能重复

    public void createIndex1() throws IOException {
        IndexResponse response = client.prepareIndex("index", "type", "1") //索引，类型，id
                .setSource(jsonBuilder()
                        .startObject()
                        .field("title", "title")   //字段，值
                        .field("content", "content")
                        .endObject()
                ).get();
    }

使用postman查询该索引：

4：更新索引，更新刚才创建的索引，如果id相同将会覆盖掉刚才的内容

    public void updateByClient() throws IOException, ExecutionException, InterruptedException {
        //每次添加id应该不同，相当于数据表中的主键，相同 的话将会进行覆盖
        UpdateResponse response = client.update(new UpdateRequest("index", "type", "1")
                .doc(XContentFactory.jsonBuilder()
                        .startObject()
                        .field("title", "中华人民共和国国歌,国歌是最好听的歌")
                        .field("content","中华人民共和国国歌,国歌是最好听的歌")
                        .endObject()
                )).get();
    }

使用postman查看该索引的内容

5：对索引进行查询，因为分词不同，分词器将会对要查询的内容先分词，再在子段中查询。

查询 子段 content

查询结果：

对title子段进行查询：

查询结果：

6：向 索引中再添加一条数据

    public void createIndex2() throws IOException {
        IndexResponse response = client.prepareIndex("index", "type", "2")
                .setSource(jsonBuilder()
                        .startObject()
                        .field("title", "中华民族是伟大的民族")
                        .field("content", "中华民族是伟大的民族")
                        .endObject()
                ).get();
    }

对字段content进行查询：

结果：两条数据都能查到，因为对查询内容 “中华人民共和国国歌”   进行细粒度划分，含有“中华” 一词，两条数据中都包含“中华”。

对字段title 进行查询：

查询结果： 只有一条数据，因为对title  使用的是 粗粒度分词

7：search api的操作：

   public void search() {
        SearchResponse response1 = client.prepareSearch("index1", "index")  //指定多个索引
                .setTypes("type1", "type")  //指定类型
                .setSearchType(SearchType.QUERY_THEN_FETCH)
                .setQuery(QueryBuilders.matchQuery("title", "中华人民共和国国歌"))  // Query
//                .setPostFilter(QueryBuilders.rangeQuery("age").from(12).to(18))     // Filter
                .setFrom(0).setSize(60).setExplain(true)
                .get();
        long totalHits1= response1.getHits().totalHits;  //命中个数
        System.out.println(totalHits1);

        SearchResponse response2 = client.prepareSearch("index1", "index")  //指定多个索引
                .setTypes("type1", "type")  //指定类型
                .setSearchType(SearchType.QUERY_THEN_FETCH)
                .setQuery(QueryBuilders.matchQuery("content", "中华人民共和国国歌"))  // Query
//                .setPostFilter(QueryBuilders.rangeQuery("age").from(12).to(18))     // Filter
                .setFrom(0).setSize(60).setExplain(true)
                .get();
        long totalHits2 = response2.getHits().totalHits;  //命中个数
        System.out.println(totalHits2);
    }

8：Get Api操作：

    public void get() {
        GetResponse response = client.prepareGet("index", "type", "1").get();
        Map<String, Object> source = response.getSource();
        Set<String> strings = source.keySet();
        Iterator<String> iterator = strings.iterator();
        while (iterator.hasNext()) {
            System.out.println(source.get(iterator.next()));
        }
    }

9：bulk api  批量创建索引，并添加数据

    /**
     * 批量创建索引，并添加数据
     * @throws IOException
     */
    public void bulkApi() throws IOException {

        BulkRequestBuilder bulkRequest = client.prepareBulk();

// either use client#prepare, or use Requests# to directly build index/delete requests
        bulkRequest.add(client.prepareIndex("twitter", "tweet", "1")
                .setSource(jsonBuilder()
                        .startObject()
                        .field("user", "kimchy")
                        .field("postDate", new Date())
                        .field("message", "trying out Elasticsearch")
                        .endObject()
                )
        );

        bulkRequest.add(client.prepareIndex("twitter", "tweet", "2")
                .setSource(jsonBuilder()
                        .startObject()
                        .field("user", "kimchy")
                        .field("postDate", new Date())
                        .field("message", "another post")
                        .endObject()
                )
        );

        BulkResponse bulkResponse = bulkRequest.get();
        if (bulkResponse.hasFailures()) {
            // process failures by iterating through each bulk response item
        }
    }

10 将搜索得到的数据以json数据形式返回。

   /**
     * 商品搜索
     */
    @RequestMapping("/productSearch")
    @ResponseBody
    public JSONObject productSearch(String text) {
        SearchResponse response1 = client.prepareSearch("product", "index")  //指定多个索引
                .setTypes("product", "type")  //指定类型
                .setSearchType(SearchType.QUERY_THEN_FETCH)
                .setQuery(QueryBuilders.matchQuery("name", text))  // Query
                .setFrom(0).setSize(60).setExplain(true)
                .get();

        SearchHit[] searchHits = response1.getHits().getHits();//命中个数

            JSONObject jsonObject = new JSONObject();
        for (int i = 0; i < searchHits.length; i++) {

            String sourceAsString = searchHits[i].getSourceAsString();
            jsonObject.put(i+"",sourceAsString);

        }

        return jsonObject;
    }

es比较快的原因：https://www.jianshu.com/p/ed7e1ebb2fb7

java api 官方文档：https://www.elastic.co/guide/en/elasticsearch/client/java-api/6.0/java-docs-index.html