很多时候需要利用java api读取Elasticsearch. 目前官方首推的是RestHighLevelClient. 所以可以尝试使用这个客户端进行简单的语句生成和操作.

首先在Maven的pom中添加dependency

<dependency>
   <groupId>org.elasticsearch.client</groupId>
   <artifactId>elasticsearch-rest-high-level-client</artifactId>
   <version>7.10.1</version>
</dependency>

之后, 在java中可以直接写入一下代码. 创建client,指定2个端口,具体原因不知道.但是官方文档中有参考.

我才用的是 boolQueryBuilder,生成2个filter的效果. 做了范围查询和关键词匹配. filter不需要计算成绩,性能好点.

设置了fetchSource,这样只会include指定的field,减少返回数据.

rangeQuery可以用于数值和时间段查询

RestHighLevelClient client = new RestHighLevelClient(RestClient
        .builder(new HttpHost("localhost", 9200, "http"), new HttpHost("localhost", 9201, "http")));
    SearchRequest searchRequest = new SearchRequest("all_indices");
    SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
    searchSourceBuilder.fetchSource(new String[] {"date_search", "message"}, new String[] {});
    // searchSourceBuilder.from(0).size(1);
    BoolQueryBuilder boolQueryBuilder = QueryBuilders.boolQuery();
    boolQueryBuilder.filter(QueryBuilders.termQuery("tags", "exception_text"));
    boolQueryBuilder.filter(QueryBuilders.rangeQuery("date_search").gte("now-1d/d").lte("now/d"));

    searchSourceBuilder.query(boolQueryBuilder);
    searchRequest.source(searchSourceBuilder);
    try {
      SearchResponse rp = client.search(searchRequest, RequestOptions.DEFAULT);
      SearchHits hits = rp.getHits();

      hits.forEach(test -> {
       Map<String, Object> sourceAsMap = test.getSourceAsMap();
       String message = (String) sourceAsMap.get("message");
      });
      
      client.close();
      client = null;
    } catch (IOException e) {
      e.printStackTrace();
    }

最后生成的dsl类似:

{
    "query": {
        "bool": {
            "filter": [
                {
                    "term": {
                        "tags": {
                            "value": "exception_text", 
                            "boost": 1
                        }
                    }
                }, 
                {
                    "range": {
                        "date_search": {
                            "from": "now-1d/d", 
                            "to": "now/d", 
                            "include_lower": true, 
                            "include_upper": true, 
                            "boost": 1
                        }
                    }
                }
            ], 
            "adjust_pure_negative": true, 
            "boost": 1
        }
    }, 
    "_source": {
        "includes": [
            "date_search", 
            "message"
        ], 
        "excludes": [ ]
    }
}