3、使用

在上一小节中实现了创建索引，这一小节来试一下数据的检索功能。
在代码中实现 搜索address中包含mill的所有人的年龄分布以及平均薪资 这个功能，如果是在 kibana 中，使用的是下面的DSL语句：

GET /bank/_search
{
  "query": { //查询
    "match": {
      "address": "mill"
    }
  },
  "aggs": { //聚合
    "ageAgg": { //年龄分布
      "terms": {
        "field": "age",
        "size": 10 //只取10中聚合的结果
      }
    },
    "balanceAvg":{//平均薪资
      "avg": {
        "field": "balance"
      }
    }
  }
}

结果如下图所示：

在这里插入图片描述

要在 SpringBoot 集成环境中该如何实现呢？下面来使用代码实现上面的功能。

1）、测试类 PafcmallSearchApplicationTests.java 中添加测试方法searchData()：

/**
 * 检索数据
 *
 * @throws IOException
 */
@Test
void searchData() throws IOException {
    // 1、创建检索请求
    SearchRequest searchRequest = new SearchRequest();
    // 指定索引
    searchRequest.indices("bank");
    // 指定DSL，检索条件
    SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
    // 1.1）、构造检索条件
    //        sourceBuilder.query(QueryBuilders.termQuery("user", "kimchy"));
    //        sourceBuilder.from(0);
    //        sourceBuilder.size(5);
    //        sourceBuilder.timeout(new TimeValue(60, TimeUnit.SECONDS));

    searchSourceBuilder.query(QueryBuilders.matchQuery("address","mill"));

    // 聚合数据
    // 1.2）、根据年龄分布聚合
    TermsAggregationBuilder ageAgg = AggregationBuilders.terms("ageAgg").field("age").size(10);
    searchSourceBuilder.aggregation(ageAgg);

    // 1.3）、计算平薪资
    AvgAggregationBuilder balanceAvg = AggregationBuilders.avg("balanceAvg").field("balance");
    searchSourceBuilder.aggregation(balanceAvg);

    System.out.println("检索条件："+searchSourceBuilder.toString());
    searchRequest.source(searchSourceBuilder);

    // 2、执行检索
    SearchResponse searchResponse = client.search(searchRequest, PafcmallElasticsearchConfig.COMMON_OPTIONS);

    // 3、分析结果 searchResponse
    System.out.println(searchResponse.toString());

    //3.1）、获取所有查到的数据
    SearchHits hits = searchResponse.getHits(); // 获取到最外围的 hits
    SearchHit[] searchHits = hits.getHits(); // 内围的 hits 数组
    for (SearchHit hit : searchHits) {
        /**
             * "_index":"bank",
             *        "_type":"account",
             *        "_id":"970",
             *        "_score":5.4032025,
             *        "_source":{
             */
        //            hit.getIndex();hit.getType()''
        String str = hit.getSourceAsString();
        Account account = JSON.parseObject(str, Account.class);

        System.out.println(account.toString());

    }
    //3.1）、获取这次检索到的分析数据
    Aggregations aggregations = searchResponse.getAggregations();
    // 可以遍历获取聚合数据
    //        for (Aggregation aggregation : aggregations.asList()) {
    //            System.out.println("当前聚合："+aggregation.getName());
    //            aggregation.getXxx
    //        }
    // 也可使使用下面的方式
    Terms ageAgg1 = aggregations.get("ageAgg");
    for (Terms.Bucket bucket : ageAgg1.getBuckets()) {
        String keyAsString = bucket.getKeyAsString();
        System.out.println("年龄："+keyAsString+" ==> 有 "+bucket.getDocCount()+" 个");
    }

    Avg balanceAvg1 = aggregations.get("balanceAvg");
    System.out.println("平均薪资："+balanceAvg);
}

2）、添加收集结果的测试类：

/**
 * 测试用账号类
 */
@ToString
@Data
static class Account {
    private int account_number;
    private int balance;
    private String firstname;
    private String lastname;
    private int age;
    private String gender;
    private String address;
    private String employer;
    private String email;
    private String city;
    private String state;
}

3）、执行测试方法，结果如下：