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一，使用Elasticsearch的Java RESTHighLevel Client完成复杂的查询请求

前面es进阶学习中，我们学习过复杂的DSL查询。

POST bank/_search
{"query": {"match": {"address": {"query": "Mill"}}},"aggregations": {"ageAgg": {"terms": {"field": "age","size": 10}},"ageAvg": {"avg": {"field": "age"}},"balanceAvg": {"avg": {"field": "balance"}}}
}

如何使用Java客户端执行复杂的查询呢？

使用Elasticsearch的Java REST High-Level Client执行一个复杂的带有聚合的搜索请求。

1. 创建检索请求 (SearchRequest)

• 创建 SearchRequest 对象:

  • SearchRequest searchRequest = new SearchRequest();

• 指定索引:

  • searchRequest.indices("bank");

2. 构造检索条件 (SearchSourceBuilder)

• 创建 SearchSourceBuilder 对象:

  • SearchSourceBuilder sourceBuilder = new SearchSourceBuilder();

• 设置查询条件:

  • sourceBuilder.query(QueryBuilders.matchQuery("address", "Mill"));

• 添加聚合:

  • 按年龄分组的聚合:

    • TermsAggregationBuilder ageAgg = AggregationBuilders.terms("ageAgg").field("age").size(10);
    • sourceBuilder.aggregation(ageAgg);

  • 计算平均年龄:

    • AvgAggregationBuilder ageAvg = AggregationBuilders.avg("ageAvg").field("age");
    • sourceBuilder.aggregation(ageAvg);

  • 计算平均薪资:

    • AvgAggregationBuilder balanceAvg = AggregationBuilders.avg("balanceAvg").field("balance");
    • sourceBuilder.aggregation(balanceAvg);

• 打印检索条件:

  • System.out.println("检索条件：" + sourceBuilder);

• 将检索条件添加到 SearchRequest 中:

  • searchRequest.source(sourceBuilder);

3. 执行检索 (SearchResponse)

• 执行搜索请求:

  • SearchResponse searchResponse = client.search(searchRequest, RequestOptions.DEFAULT);

• 打印检索结果:

  • System.out.println("检索结果：" + searchResponse);

4. 处理解析结果

• 获取搜索命中的文档:

  • SearchHits hits = searchResponse.getHits();
  • SearchHit[] searchHits = hits.getHits();

• 遍历并处理每个文档:

  • for (SearchHit searchHit : searchHits) {String sourceAsString = searchHit.getSourceAsString();Account account = JSON.parseObject(sourceAsString, Account.class);System.out.println(account);
    }
    

5. 获取聚合信息

• 获取聚合结果:

  • Aggregations aggregations = searchResponse.getAggregations();

• 处理年龄分布的聚合:

  • Terms ageAgg1 = aggregations.get("ageAgg");
    for (Terms.Bucket bucket : ageAgg1.getBuckets()) {String keyAsString = bucket.getKeyAsString();System.out.println("年龄：" + keyAsString + " ==> " + bucket.getDocCount());
    }
    

• 处理平均年龄的聚合:

  • Avg ageAvg1 = aggregations.get("ageAvg");
    System.out.println("平均年龄：" + ageAvg1.getValue());
    

• 处理平均薪资的聚合:

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

完整代码如下：

	/*** 复杂检索*/@Testpublic void searchData() throws IOException {//1. 创建检索请求SearchRequest searchRequest = new SearchRequest();//1.1）指定索引searchRequest.indices("bank");//1.2）构造检索条件SearchSourceBuilder sourceBuilder = new SearchSourceBuilder();sourceBuilder.query(QueryBuilders.matchQuery("address", "Mill"));//1.2.1)按照年龄分布进行聚合TermsAggregationBuilder ageAgg = AggregationBuilders.terms("ageAgg").field("age").size(10);sourceBuilder.aggregation(ageAgg);//1.2.2)计算平均年龄AvgAggregationBuilder ageAvg = AggregationBuilders.avg("ageAvg").field("age");sourceBuilder.aggregation(ageAvg);//1.2.3)计算平均薪资AvgAggregationBuilder balanceAvg = AggregationBuilders.avg("balanceAvg").field("balance");sourceBuilder.aggregation(balanceAvg);System.out.println("检索条件：" + sourceBuilder);searchRequest.source(sourceBuilder);//2. 执行检索SearchResponse searchResponse = client.search(searchRequest, RequestOptions.DEFAULT);System.out.println("检索结果：" + searchResponse);//3. 将检索结果封装为BeanSearchHits hits = searchResponse.getHits();SearchHit[] searchHits = hits.getHits();for (SearchHit searchHit : searchHits) {String sourceAsString = searchHit.getSourceAsString();Account account = JSON.parseObject(sourceAsString, Account.class);System.out.println(account);}//4. 获取聚合信息Aggregations aggregations = searchResponse.getAggregations();Terms ageAgg1 = aggregations.get("ageAgg");for (Terms.Bucket bucket : ageAgg1.getBuckets()) {String keyAsString = bucket.getKeyAsString();System.out.println("年龄：" + keyAsString + " ==> " + bucket.getDocCount());}Avg ageAvg1 = aggregations.get("ageAvg");System.out.println("平均年龄：" + ageAvg1.getValue());Avg balanceAvg1 = aggregations.get("balanceAvg");System.out.println("平均薪资：" + balanceAvg1.getValue());}

二，AI时代的效率提升

相对于DSL，使用Java客户端来完成复杂的请求，代码是比较复杂不好理解的。

DSL相对清晰、容易理解。

所以，我们可以先根据需求，写好DSL，然后用大模型工具比如通义千问、Kimi、ChatGPT等将DSL转换为Java代码，这样我们就无需逐行编写复杂难懂的Java代码了，只需要在测试过程中进行微调即可。