elasticSearch Java Api使用

1 创建 client 客户端

private final static String host = "127.0.0.1";//创建客户端public static Client getClient() {    try {        Client client = TransportClient.builder().build()                .addTransportAddress(new InetSocketTransportAddress(InetAddress.getByName(host), 9300));        return client;    } catch (Exception ex) {        System.out.println(ex);    }    return null;}

2.根据index，type查询数据 ，由于Elasticsearch是天生异步的，执行execute后会在等到查询结果之前就返回caller block，所以我们可以简单的使用actionGet()方法来阻塞程序直到查询结构返回。

public static void forGetResponse(String getIndex, String getType, String getId) {
    //GetResponse getResponse = getClient().prepareGet(getIndex, getType, getId).execute().actionGet();
    GetResponse getResponse = getClient().prepareGet(getIndex, getType, getId).get();    Map<String, Object> responMap = getResponse.getSourceAsMap();

    //转换成json的格式    System.out.println("getResponse返回结果为:" + Json2Str(responMap));}

3. 插入一条数据到ES，由于设置了主键,如果id存在就做更新的操作，不存在就插入类似mysql的upsert操作，另外在用spark对ES的写入的时候因为有native的接口 直接Data Frame进行写入，所以此upsert是可以设置的如：conf.set（"es.write.operation","upsert"）

Client cli = getClient();IndexResponse response = cli.prepareIndex("account", "stu", String.valueOf(students.getSid()))//参数说明： 索引，类型 ，_id)        .setSource(Json2Str(students))//setSource可以传以上map string  byte[] 几种方式        .get();boolean created = response.isCreated();

4.

这里自定义了某个Type的索引映射（Mapping），默认ES会自动处理数据类型的映射：针对整型映射为long，浮点数为double，字符串映射为string，时间为date，true或false为boolean。
注意：针对字符串，ES默认会做“analyzed”处理，即先做分词、去掉stop words等处理再index。如果你需要把一个字符串做为整体被索引到，需要把这个字段这样设置：field("index", "not_analyzed")。 例如：中华人民共和国

//搜索 select name from table where name=zhangsan and age >12 and age <18

SearchResponse searchResponse = cli.prepareSearch("account")//可以同时搜索多个索引prepareSearch("index","index2")        .setTypes("stu", "info")//可以同时搜索多个类型        .setSearchType(SearchType.DFS_QUERY_THEN_FETCH)        .setQuery(QueryBuilders.termQuery("sex", "male"))                 // Query        .setPostFilter(QueryBuilders.rangeQuery("age").from(10).to(20))     // Filter        .setFrom(0)        .setSize(10)        .setExplain(true)        .execute()        .actionGet();
封装方法：查询response返回的结果集
    public static void forSearchResponse(SearchResponse response) {        //SearchHit类代表了一个满足查询条件的document，获得SearchHit后可以通过便利来输出每一个hit的信息        for (SearchHit searchHit : response.getHits()) {            //获取高亮显示的数据，含有富文本/*            Map<String, HighlightField> highlightResult = searchHit.getHighlightFields();            HighlightField highlightField = highlightResult.get("name");            Text[] titleText = highlightField.fragments();            String higtName = "";            for (Text text : titleText) {                higtName += text;            }*/            Map<String, Object> source = searchHit.getSource();            if (!source.isEmpty()) {                Iterator<Map.Entry<String, Object>> it = source.entrySet().iterator();                while (it.hasNext()) {                    Map.Entry<String, Object> entry = it.next();                    System.out.println("hists结果为：" + entry.getKey() + "----" + entry.getValue());                }            }        }    }

5.简单的聚合操作

public static void forAggreationSearch() {    SearchRequestBuilder srb = getClient().prepareSearch("account");    srb.setTypes("stu");    TermsBuilder ageTermsBuilder = AggregationBuilders.terms("gradeAge").field("age");    TermsBuilder sexTermsBuilder = AggregationBuilders.terms("gradeSex").field("sex");    sexTermsBuilder.subAggregation(ageTermsBuilder);    srb.addAggregation(sexTermsBuilder);    SearchResponse response = srb.execute().actionGet();    Map<String, Aggregation> aggMap = response.getAggregations().asMap();    StringTerms sexTerms = (StringTerms) aggMap.get("gradeSex");    Iterator<Bucket> sexBuckets = sexTerms.getBuckets().iterator();    while (sexBuckets.hasNext()) {        Bucket sexBucket = sexBuckets.next();        System.out.println("性别:" + sexBucket.getKey() + " 人数为：" + sexBucket.getDocCount());        StringTerms ageTerms = (StringTerms) sexBucket.getAggregations().asMap().get("gradeAge");        Iterator<Bucket> ageBuckets = ageTerms.getBuckets().iterator();        while (ageBuckets.hasNext()) {            Bucket ageBucket = ageBuckets.next();            System.out.println("性别：" + sexBucket.getKey() + "  " + ageBucket.getKey() + "岁" + "，人数为：" + ageBucket.getDocCount());        }    }}