它是一个组件,允许对 Elasticsearch 实时执行类似 sql 的查询。您可以将 Elasticsearch SQL 看作是一个翻译器,它同时理解 SQL 和 Elasticsearch,并且通过 Elasticsearch 功能,可以方便地实时读取和处理数据。
它具有本地集成 ?根据底层存储,对相关节点高效地执行每个查询。
没有外部部件 ?不需要额外的硬件、进程、运行时或库来查询Elasticsearch。
轻量级和高效率 ?它包含并公开了SQL,以便实时进行适当的全文本搜索。
PUT /schoollist/_bulk?refresh {"index":{"_id": "CBSE"}} {"name": "GleanDale", "Address": "JR. Court Lane", "start_date": "2011-06-02", "student_count": 561} {"index":{"_id": "ICSE"}} {"name": "Top-Notch", "Address": "Gachibowli Main Road", "start_date": "1989- 05-26", "student_count": 482} {"index":{"_id": "State Board"}} {"name": "Sunshine", "Address": "Main Street", "start_date": "1965-06-01", "student_count": 604}
运行上面的代码后,我们得到如下所示的响应:
{ "took" : 277, "errors" : false, "items" : [ { "index" : { "_index" : "schoollist", "_type" : "_doc", "_id" : "CBSE", "_version" : 1, "result" : "created", "forced_refresh" : true, "_shards" : { "total" : 2, "successful" : 1, "failed" : 0 }, "_seq_no" : 0, "_primary_term" : 1, "status" : 201 } }, { "index" : { "_index" : "schoollist", "_type" : "_doc", "_id" : "ICSE", "_version" : 1, "result" : "created", "forced_refresh" : true, "_shards" : { "total" : 2, "successful" : 1, "failed" : 0 }, "_seq_no" : 1, "_primary_term" : 1, "status" : 201 } }, { "index" : { "_index" : "schoollist", "_type" : "_doc", "_id" : "State Board", "_version" : 1, "result" : "created", "forced_refresh" : true, "_shards" : { "total" : 2, "successful" : 1, "failed" : 0 }, "_seq_no" : 2, "_primary_term" : 1, "status" : 201 } } ] }
以下示例显示了如何构建SQL查询-
POST /_sql?format=txt { "query": "SELECT * FROM schoollist WHERE start_date < '2000-01-01'" }
运行上面的代码后,我们得到如下所示的响应:
Address | name | start_date | student_count --------------------+---------------+------------------------+--------------- Gachibowli Main Road|Top-Notch |1989-05-26T00:00:00.000Z|482 Main Street |Sunshine |1965-06-01T00:00:00.000Z|604
Note ?通过更改上面的SQL查询,您可以获得不同的结果集。