Java操作Elasticsearch（API）

一.創建maven工程

工程結構

pom添加如下依賴：

	<properties>
        <es-version>5.6.1</es-version>
    </properties>
    <dependencies>
        <dependency>
            <groupId>org.elasticsearch</groupId>
            <artifactId>elasticsearch</artifactId>
            <version>${es-version}</version>
        </dependency>
        <dependency>
            <groupId>org.elasticsearch.client</groupId>
            <artifactId>transport</artifactId>
            <version>${es-version}</version>
        </dependency>
        <dependency>
            <groupId>org.apache.logging.log4j</groupId>
            <artifactId>log4j-core</artifactId>
            <version>2.9.0</version>
        </dependency>
        <dependency>
            <groupId>junit</groupId>
            <artifactId>junit</artifactId>
            <version>4.12</version>
            <scope>compile</scope>
        </dependency>
        <dependency>
            <groupId>com.fasterxml.jackson.core</groupId>
            <artifactId>jackson-core</artifactId>
            <version>2.7.3</version>
        </dependency>
        <dependency>
            <groupId>com.fasterxml.jackson.core</groupId>
            <artifactId>jackson-databind</artifactId>
            <version>2.7.3</version>
        </dependency>
        <dependency>
            <groupId>org.codehaus.jackson</groupId>
            <artifactId>jackson-mapper-asl</artifactId>
            <version>1.9.13</version>
        </dependency>
    </dependencies>

Article.java

public class Article {

    private String atcId;
    private String title;
    private String content;

log4j2.xml

<?xml version="1.0" encoding="utf-8" ?>
<Configuration xmlns="http://logging.apache.org/log4j/2.0/config">
    <Appenders>
        <Console name="Console" target="SYSTEM_OUT">
            <PatternLayout pattern="%m%n"></PatternLayout>
        </Console>
    </Appenders>
    <Loggers>
        <Root level="INFO">
            <AppenderRef ref="Console"></AppenderRef>
        </Root>
    </Loggers>
</Configuration>

二.測試API

2.1創建索引，刪除索引

    @Test
    public void esTest() throws UnknownHostException {
        //獲取集羣信息
        Settings settings = Settings.builder().put("cluster.name","my-es-search").build();
        //獲取客戶端
        PreBuiltTransportClient preBuiltTransportClient = new PreBuiltTransportClient(settings);
        //連接指定客戶端主機
        preBuiltTransportClient.addTransportAddress(new InetSocketTransportAddress(InetAddress.getByName("192.168.1.117"), 9300));
        System.out.println("" + preBuiltTransportClient.toString());
        //創建索引
		preBuiltTransportClient.admin().indices().prepareCreate("blog").get();
        //刪除索引
//        preBuiltTransportClient.admin().indices().prepareDelete("blog").get();
        //最後關閉客戶端
        preBuiltTransportClient.close();
    }

2.1插入文檔

1）json格式插入文檔

@Test
    public void esTest() throws UnknownHostException {
        //獲取集羣信息
        Settings settings = Settings.builder().put("cluster.name","my-es-search").build();
        //獲取客戶端
        PreBuiltTransportClient preBuiltTransportClient = new PreBuiltTransportClient(settings);
        //連接指定客戶端主機
        preBuiltTransportClient.addTransportAddress(new InetSocketTransportAddress(InetAddress.getByName("192.168.1.117"), 9300));
        //插入JSON文檔，沒有index會創建
   		Article article = new Article();
        article.setAtcId("1");
        article.setTitle("第一文");
        article.setContent("瀏覽器查看http://sdafadf:9200/blog2");
        String articleJson = JsonUtils.objectToJson(article);
        //prepareIndex(index名，type名，documentId)
        IndexResponse indexResponse = preBuiltTransportClient.prepareIndex("blog", "article", "1")
                .setSource(articleJson, XContentType.JSON)
                .get();
 	    System.out.println("1" + indexResponse.getId());        //輸出 11
        System.out.println("2" + indexResponse.getIndex());     //輸出 2blog
        System.out.println("3" + indexResponse.getType());      //輸出 3article
        System.out.println("4" + indexResponse.getResult());    //輸出 4CREATED
        System.out.println("5" + indexResponse.getShardId());   //輸出 5[blog][1]
        System.out.println("6" + indexResponse.getShardInfo()); //輸出 6ShardInfo{total=1, successful=1, failures=[]}
        System.out.println("7" + indexResponse.getVersion());   //輸出 71
        System.out.println("8" + indexResponse.getLocation(""));//輸出 8/blog/article/1?routing=
        //最後關閉客戶端
        preBuiltTransportClient.close();
    }

2）以map形式插入文檔

@Test
    public void esTest() throws UnknownHostException {
        //獲取集羣信息
        Settings settings = Settings.builder().put("cluster.name","my-es-search").build();
        //獲取客戶端
        PreBuiltTransportClient preBuiltTransportClient = new PreBuiltTransportClient(settings);
        //連接指定客戶端主機
        preBuiltTransportClient.addTransportAddress(new InetSocketTransportAddress(InetAddress.getByName("192.168.1.117"), 9300));
         //map形式插入文檔
        Map<String,Object> map = new HashMap<>();
        map.put("atcId","2");
        map.put("title","第二文");
        map.put("content","ID：ffmkiejjmecolpfloofpjologoblkegm\n");
        IndexResponse indexResponse2 = preBuiltTransportClient.prepareIndex("blog", "article", "2")
                .setSource(map)
                .get();
        //最後關閉客戶端
        preBuiltTransportClient.close();
    }

3）以ES構建器方式插入

@Test
    public void esTest() throws UnknownHostException {
        //獲取集羣信息
        Settings settings = Settings.builder().put("cluster.name","my-es-search").build();
        //獲取客戶端
        PreBuiltTransportClient preBuiltTransportClient = new PreBuiltTransportClient(settings);
        //連接指定客戶端主機
        preBuiltTransportClient.addTransportAddress(new InetSocketTransportAddress(InetAddress.getByName("192.168.1.117"), 9300));
         //ES構建器形式插入文檔
        XContentBuilder xContentBuilder = XContentFactory.jsonBuilder().startObject()
                .field("atcId", "3")
                .field("title", "第3文")
                .field("content", "頁面空白 報錯信息 此時頁面一片空白 報錯原因 Babel 默認只轉換")
                .endObject();
        IndexResponse indexResponse3 = preBuiltTransportClient.prepareIndex("blog", "article", "3")
                .setSource(xContentBuilder)
                .get();
        //最後關閉客戶端
        preBuiltTransportClient.close();
    }

插入後效果：

2.2搜索文檔

1）獲取單條數據prepareGet（index名，type名，es唯一id）

    @Test
    public void esTest() throws IOException {
        //獲取集羣信息
        Settings settings = Settings.builder().put("cluster.name", "my-es-search").build();
        //獲取客戶端
        PreBuiltTransportClient preBuiltTransportClient = new PreBuiltTransportClient(settings);
        //連接指定客戶端主機
        preBuiltTransportClient.addTransportAddress(new InetSocketTransportAddress(InetAddress.getByName("192.168.1.117"), 9300)); 
        //獲取數據
        GetResponse getResponse = preBuiltTransportClient.prepareGet("blog", "article", "1").get();
        System.out.println("獲取的數據爲：" + getResponse.getSourceAsString());//獲取的數據爲：{"atcId":"1","title":"第一文","content":"瀏覽器查看http://hadoop102:9200/blog2"}
        //最後關閉客戶端
        preBuiltTransportClient.close();
    }

2）獲取多條數據

具體請看註釋：

    @Test
    public void esTest() throws IOException {
        //獲取集羣信息
        Settings settings = Settings.builder().put("cluster.name", "my-es-search").build();
        //獲取客戶端
        PreBuiltTransportClient preBuiltTransportClient = new PreBuiltTransportClient(settings);
        //連接指定客戶端主機
        preBuiltTransportClient.addTransportAddress(new InetSocketTransportAddress(InetAddress.getByName("192.168.1.117"), 9300));
        //連續多個add一起寫，適用於獲取不同index，不同type的數據
        MultiGetResponse multiGetItemResponses = preBuiltTransportClient.prepareMultiGet().add("blog", "article", "1").add("blog", "article", "2").get();
        for (MultiGetItemResponse itemResponses : multiGetItemResponses) {
            GetResponse getResponse = itemResponses.getResponse();
            //如果真的存在，則打印
            if (getResponse.isExists()) {
                System.out.println("獲取的數據爲：" + getResponse.getSourceAsString());//
            }
        }
        System.out.println("#########br###########");
        //add()中要的id是一個不定長參數，可以一次性獲取多個id的document
        //適用於獲取同一index，同一type的數據
        MultiGetResponse multiGetItemResponses1 = preBuiltTransportClient.prepareMultiGet().add("blog", "article", "1", "2").get();
        for (MultiGetItemResponse itemResponses : multiGetItemResponses1) {
            GetResponse getResponse = itemResponses.getResponse();
            //如果真的存在，則打印
            if (getResponse.isExists()) {
                System.out.println("獲取的數據爲：" + getResponse.getSourceAsString());//
            }
        }
        //最後關閉客戶端
        preBuiltTransportClient.close();
    }
    最終輸出爲：
    獲取的數據爲：{"atcId":"1","title":"第一文","content":"瀏覽器查看http://hadoop102:9200/blog2"}
	獲取的數據爲：{"atcId":"2","title":"第二文","content":"ID：ffmkiejjmecolpfloofpjologoblkegm\n"}
	#########br###########
	獲取的數據爲：{"atcId":"1","title":"第一文","content":"瀏覽器查看http://hadoop102:9200/blog2"}
	獲取的數據爲：{"atcId":"2","title":"第二文","content":"ID：ffmkiejjmecolpfloofpjologoblkegm\n"}

2.3更新文檔

更新文檔的方式和插入文檔的神似，都是那幾種方式，如：
1）prepareUpdate的方式

@Test
    public void esTest() throws IOException {
        //獲取集羣信息
        Settings settings = Settings.builder().put("cluster.name", "my-es-search").build();
        //獲取客戶端
        PreBuiltTransportClient preBuiltTransportClient = new PreBuiltTransportClient(settings);
        //連接指定客戶端主機
        preBuiltTransportClient.addTransportAddress(new InetSocketTransportAddress(InetAddress.getByName("192.168.1.117"), 9300));
           //更新文檔
        Map<String, Object> map = new HashMap<>();
        map.put("title", "第一文-update文檔");
        UpdateResponse updateResponse = preBuiltTransportClient.prepareUpdate("blog", "article", "1").setDoc(map).get();
        System.out.println("" + updateResponse);//UpdateResponse[index=blog,type=article,id=1,version=2,result=updated,shards=ShardInfo{total=2, successful=1, failures=[]}]
        //最後關閉客戶端
        preBuiltTransportClient.close();
    }

修改後的效果：

2）UpdateRequest的方式

		//##############此處獲取preBuiltTransportClient和上面代碼中的一樣哈，就不重複了，直接關鍵代碼##########
 		Map<String, Object> map = new HashMap<>();
        map.put("title", "第一文-第二次update文檔");
        //UpdateRequest(String index, String type, String id)
        preBuiltTransportClient.update(new UpdateRequest("blog", "article", "1")
                .doc(map) //此處doc裏可以放json字符串, map，XContentBuilder.jsonBuilder IndexRequest等
        ).actionGet();
        //##########關閉clien代碼###########

修改後的效果：

2.4 upsert文檔(更新插入)

這種方式是：存在修改，不存在則插入

		//##############此處獲取preBuiltTransportClient和上面代碼中的一樣哈，就不重複了，直接關鍵代碼##########
 		Map<String, Object> map = new HashMap<>();
        map.put("atcId", "8");
        map.put("title", "update的文檔");
        map.put("content", "This is update的文檔content");
        Map<String, Object> mapUpsert = new HashMap<>();
        mapUpsert.put("atcId", "8");
        mapUpsert.put("title", "upsert的文檔");
        mapUpsert.put("content", "This is upsert的文檔content");
        preBuiltTransportClient.update(new UpdateRequest("blog", "article", "8")
                //此處doc和upsert裏可以放json字符串, map，XContentBuilder.jsonBuilder IndexRequest等
                //如果不存在插入mapUpsert的數據，否則修改成map的數據,執行2次可看效果
                .doc(map).upsert(mapUpsert)
        ).actionGet();
        //##########關閉clien代碼###########

第一次執行後的效果：（因爲id=8不存在，所以插入mapUpsert的數據）

第二次執行後的效果：（因爲id=8已存在，所以修改爲map的數據）

2.5 刪除文檔

刪除就是根據id刪除對應文檔
比如：這裏刪除id=2的文檔

		//##############此處獲取preBuiltTransportClient和上面代碼中的一樣哈，就不重複了，直接關鍵代碼##########
        DeleteResponse deleteResponse = preBuiltTransportClient.prepareDelete("blog", "article", "2").get();
        //DeleteRequest的方式，差不多的操作方式
//        DeleteResponse deleteResponse1 = preBuiltTransportClient.delete(new DeleteRequest("blog", "article", "2")).actionGet();        
        System.out.println("刪除結果：" + deleteResponse);
        //刪除結果：DeleteResponse[index=blog,type=article,id=2,version=2,result=deleted,shards=ShardInfo{total=2, successful=1, failures=[]}]
        //##########關閉clien代碼###########

刪除後，發現id=2的數據沒有了：

三.高級查詢

3.1 QueryBuilders.matchAllQuery() 查詢所有

		//##############此處獲取preBuiltTransportClient和上面代碼中的一樣哈，就不重複了，直接關鍵代碼##########
        SearchResponse searchResponse = preBuiltTransportClient.prepareSearch("blog").setTypes("article")
                .setQuery(QueryBuilders.matchAllQuery()).get();
        SearchHits searchHits = searchResponse.getHits();
        System.out.println("查詢的總條數：" + searchHits.getTotalHits());//查詢的總條數：3
        for (SearchHit searchHit : searchHits) {
            System.out.println("" + searchHit.getSourceAsString());
        }
        //{"atcId":"8","title":"update的文檔","content":"This is update的文檔content"}
        //{"atcId":"1","title":"第一文-第二次update文檔","content":"瀏覽器查看http://hadoop102:9200/blog2"}
        //{"atcId":"3","title":"第3文","content":"頁面空白 報錯信息 此時頁面一片空白 報錯原因 Babel 默認只轉換"}
        //##########關閉clien代碼###########

3.2 QueryBuilders.queryStringQuery(keyword) 根據所有字段分詞查詢

現在的數據裏只有id=1和id=8兩條數據裏有update關鍵字，且在不同的字段中，根據所有字段分詞查詢：在這裏是指既掃描title，又掃描content字段。所以這2個字段中包含update關鍵字的都會被查詢出來。

		//##############此處獲取preBuiltTransportClient和上面代碼中的一樣哈，就不重複了，直接關鍵代碼##########
        String keyword = "update";
        SearchResponse searchResponse = preBuiltTransportClient.prepareSearch("blog").setTypes("article")
                .setQuery(QueryBuilders.queryStringQuery(keyword)).get();
        SearchHits searchHits = searchResponse.getHits();
        System.out.println("查詢的總條數：" + searchHits.getTotalHits());//查詢的總條數：3
        for (SearchHit searchHit : searchHits) {
            System.out.println("" + searchHit.getSourceAsString());
        }
        //查詢的總條數：2
        //{"atcId":"8","title":"update的文檔","content":"This is update的文檔content"}
        //{"atcId":"1","title":"第一文-第二次update文檔","content":"瀏覽器查看http://hadoop102:9200/blog2"}
        //##########關閉clien代碼###########

3.3 QueryBuilders.wildcardQuery(字段, 通配符關鍵字) 通配符查詢

   ------->可用的通配符有：
   * ：表示0個或多個字符
   ? ：表示單個字符

1)星號通配符

		//##############此處獲取preBuiltTransportClient和上面代碼中的一樣哈，就不重複了，直接關鍵代碼##########
        String keywordLike = "*第*";
        SearchResponse searchResponse = preBuiltTransportClient.prepareSearch("blog").setTypes("article")
                .setQuery(QueryBuilders.wildcardQuery("title",keywordLike)).get();
        SearchHits searchHits = searchResponse.getHits();
        System.out.println("查詢的總條數：" + searchHits.getTotalHits());//查詢的總條數：3
        for (SearchHit searchHit : searchHits) {
            System.out.println("" + searchHit.getSourceAsString());
        }
        //查詢的總條數：2
		//"atcId":"1","title":"第一文-第二次update文檔","content":"瀏覽器查看http://hadoop102:9200/blog2"}
		//"atcId":"3","title":"第3文","content":"頁面空白 報錯信息 此時頁面一片空白 報錯原因 Babel 默認只轉換"}

        //##########關閉clien代碼###########

2）問號通配符

		//##############此處獲取preBuiltTransportClient和上面代碼中的一樣哈，就不重複了，直接關鍵代碼##########
        String keywordLike = "第?";//?第
        SearchResponse searchResponse = preBuiltTransportClient.prepareSearch("blog").setTypes("article")
                .setQuery(QueryBuilders.wildcardQuery("title",keywordLike)).get();
        SearchHits searchHits = searchResponse.getHits();
        System.out.println("查詢的總條數：" + searchHits.getTotalHits());//查詢的總條數：3
        for (SearchHit searchHit : searchHits) {
            System.out.println("" + searchHit.getSourceAsString());
        }
        //查詢的總條數：0
        //這個是因爲默認的分詞器對中文的分詞效果很差，所以查詢不到數據，後面會介紹ik分詞器
        //##########關閉clien代碼###########

3.4 QueryBuilders.termQuery(字段, 詞條關鍵字) 詞條查詢

		//##############此處獲取preBuiltTransportClient和上面代碼中的一樣哈，就不重複了，直接關鍵代碼##########
        String term = "第";
        SearchResponse searchResponse = preBuiltTransportClient.prepareSearch("blog").setTypes("article")
                .setQuery(QueryBuilders.termQuery("title",term)).get();
        SearchHits searchHits = searchResponse.getHits();
        System.out.println("查詢的總條數：" + searchHits.getTotalHits());//查詢的總條數：3
        for (SearchHit searchHit : searchHits) {
            System.out.println("" + searchHit.getSourceAsString());
        }
        //查詢的總條數：2
		//"atcId":"1","title":"第一文-第二次update文檔","content":"瀏覽器查看http://hadoop102:9200/blog2"}
		//"atcId":"3","title":"第3文","content":"頁面空白 報錯信息 此時頁面一片空白 報錯原因 Babel 默認只轉換"}

        //##########關閉clien代碼###########

3.5 QueryBuilders.fuzzyQuery(字段, 關鍵字) 模糊查詢

這個區別於mysql的模糊查詢，mysql的模糊查詢和星號*通配符的方式類似的，es的模糊查詢是根據模糊程度查詢對應數據：
使用編輯距離的模糊查詢，計算量較大，但是對用戶拼寫錯的場景比較有用(如：模糊查詢4)
可以通過設置屬性來限定查詢的模糊程度：
1）指定最小相似度偏差： “min_similarity”:1
2) 模糊查詢將擴展到的默認最大數。默認值爲50：maxExpansions。

		//##############此處獲取preBuiltTransportClient和上面代碼中的一樣哈，就不重複了，直接關鍵代碼##########
        //模糊查詢1:Babel
        String fuzzy = "Babel";
        SearchResponse searchResponse = preBuiltTransportClient.prepareSearch("blog").setTypes("article")
                .setQuery(QueryBuilders.fuzzyQuery("content",fuzzy)).get();
        SearchHits searchHits = searchResponse.getHits();
        System.out.println("查詢的總條數：" + searchHits.getTotalHits());//查詢的總條數：3
        for (SearchHit searchHit : searchHits) {
            System.out.println("" + searchHit.getSourceAsString());
        }
        //查詢的總條數：1
		//"atcId":"3","title":"第3文","content":"頁面空白 報錯信息 此時頁面一片空白 報錯原因 Babel 默認只轉換"}
		
		//模糊查詢2:babel（大小寫的轉換，全大寫BABEL是查詢不到的）
        String fuzzy = "nabel";
        SearchResponse searchResponse = preBuiltTransportClient.prepareSearch("blog").setTypes("article")
                .setQuery(QueryBuilders.fuzzyQuery("content",fuzzy)).get();
        SearchHits searchHits = searchResponse.getHits();
        System.out.println("查詢的總條數：" + searchHits.getTotalHits());//查詢的總條數：3
        for (SearchHit searchHit : searchHits) {
            System.out.println("" + searchHit.getSourceAsString());
        }
        //查詢的總條數：1
		//"atcId":"3","title":"第3文","content":"頁面空白 報錯信息 此時頁面一片空白 報錯原因 Babel 默認只轉換"}
		
		//模糊查詢3:updat（去掉兩邊的其中1個字符）
        String fuzzy = "updat";
        SearchResponse searchResponse = preBuiltTransportClient.prepareSearch("blog").setTypes("article")
                .setQuery(QueryBuilders.fuzzyQuery("content",fuzzy)).get();
        SearchHits searchHits = searchResponse.getHits();
        System.out.println("查詢的總條數：" + searchHits.getTotalHits());//查詢的總條數：3
        for (SearchHit searchHit : searchHits) {
            System.out.println("" + searchHit.getSourceAsString());
        }
        //查詢的總條數：1
		//{"atcId":"8","title":"update的文檔","content":"This is update的文檔content"}

		//模糊查詢4:upfate（寫錯一個字符）
        String fuzzy = "upfate";
        SearchResponse searchResponse = preBuiltTransportClient.prepareSearch("blog").setTypes("article")
                .setQuery(QueryBuilders.fuzzyQuery("content",fuzzy)).get();
        SearchHits searchHits = searchResponse.getHits();
        System.out.println("查詢的總條數：" + searchHits.getTotalHits());//查詢的總條數：3
        for (SearchHit searchHit : searchHits) {
            System.out.println("" + searchHit.getSourceAsString());
        }
        //查詢的總條數：1
		//{"atcId":"8","title":"update的文檔","content":"This is update的文檔content"}

		//模糊查詢5:date（去掉2個字符）
        String fuzzy = "upfate";
        SearchResponse searchResponse = preBuiltTransportClient.prepareSearch("blog").setTypes("article")
                .setQuery(QueryBuilders.fuzzyQuery("content",fuzzy)).get();
        SearchHits searchHits = searchResponse.getHits();
        System.out.println("查詢的總條數：" + searchHits.getTotalHits());//查詢的總條數：3
        for (SearchHit searchHit : searchHits) {
            System.out.println("" + searchHit.getSourceAsString());
        }
        //查詢的總條數：0
        //##########關閉clien代碼###########

3.6 組合查詢

//---->: queryStringQuery會將關鍵字進行分詞，然後再對應列上進行查詢匹配,不指定對應列的，在所有列進行查詢
//---->: boolQuery：組合查詢，多條件一起查詢
//---->: must:必須條件 類似and
//---->: mustNot: 必須不條件
//---->: should: 可能含有，類似 or
//---->: filter:過濾，一般配合rangeQuery().from().to()使用

 String[] isShowArr = {0,1};
 BoolQueryBuilder boolQuery = QueryBuilders.boolQuery();
 //這裏是查詢：顯示狀態是0，1，且商品名稱包含“蘋果”的商品。
 boolQuery.must(QueryBuilders.termsQuery("isShow", isShowList)) //termsQuery傳集合，termQuery傳單個
          .must(QueryBuilders.queryStringQuery("蘋果").field("productName"));

3.7 其他查詢

//範圍查詢，類似mysql的between and：查詢生日在("1990-01-01")到("1999-12-31")的
QueryBuilder qb = QueryBuilders.rangeQuery("birthday").from("1990-01-01").to("1999-12-31");
//前綴查詢：查詢姓名字段以“張”開頭的
QueryBuilder qb = QueryBuilders.prefixQuery("name","張")；
//ids查詢：查詢指定ids的對應文檔
QueryBuilder qb = QueryBuilders.idsQuery().addIds("1","3");
//type查詢，查詢指定index下指定type的所有文檔
QueryBuilder qb = QueryBuilders.typeQuery("blog");

四.mapping

數據如何存放到索引對象上，需要有一個映射配置，包括：數據類型、是否存儲、是否分詞等
mapping是類似於數據庫中的表結構定義，主要作用如下：
定義index下的字段名
定義字段類型，比如數值型、浮點型、布爾型等
定義倒排索引相關的設置，比如是否索引、記錄position等
1)在插入文檔的時候，es會根據插入的數據自動生成mapping映射

2）自定義mapping
首先，創建一個空的index（blog2）

        preBuiltTransportClient.admin().indices().prepareCreate("blog2").get();

此時mapping是空的{}

然後，新增mapping

// 1設置mapping
        XContentBuilder builder = XContentFactory.jsonBuilder()
                .startObject()
                .startObject("article")
                .startObject("properties")
                .startObject("id")
                .field("type", "string")
                .field("store", "yes")
                .endObject()
                .startObject("title")
                .field("type", "string")
                .field("store", "no")
                .endObject()
                .startObject("content")
                .field("type", "string")
                .field("store", "yes")
                .endObject()
                .endObject()
                .endObject()
                .endObject();

        // 2 添加mapping
        PutMappingRequest mapping = Requests.putMappingRequest("blog2").type("article").source(builder);
        preBuiltTransportClient.admin().indices().putMapping(mapping).get();

刷新，重新查看索引信息如下：

發現：string會被自動轉換成text類型

【end】這個就是Java操作Elasticsearch的常用API啦，關於ik分詞器，下篇再見。