Elasticsearch 简明教程

Elasticsearch - SQL Access

它是一个组件，允许在实时中针对 Elasticsearch 执行类似于 SQL 的查询。你可以将 Elasticsearch SQL 视为一个翻译器，它既了解 SQL 也了解 Elasticsearch，并且可以轻松地按比例利用 Elasticsearch 的功能，实时读取和处理数据。

It is a component that allows SQL-like queries to be executed in real-time against Elasticsearch. You can think of Elasticsearch SQL as a translator, one that understands both SQL and Elasticsearch and makes it easy to read and process data in real-time, at scale by leveraging Elasticsearch capabilities.

Advantages of Elasticsearch SQL

  1. It has native integration − Each and every query is efficiently executed against the relevant nodes according to the underlying storage.

  2. No external parts − No need for additional hardware, processes, runtimes or libraries to query Elasticsearch.

  3. Lightweight and efficient − it embraces and exposes SQL to allow proper full-text search, in real-time.

Example

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}

在运行以上代码时，我们得到响应，如下所示：-

On running the above code, we get the response as shown below −

{
   "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
         }
      }
   ]
}

SQL Query

以下示例显示了构造 SQL 查询的方式 −

The following example shows how we frame the SQL query −

POST /_sql?format=txt
{
   "query": "SELECT * FROM schoollist WHERE start_date < '2000-01-01'"
}

在运行以上代码时，我们得到响应，如下所示：-

On running the above code, we get the response as shown below −

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 − 通过更改上述 SQL 查询，你可以获得不同的结果集。

Note − By changing the SQL query above, you can get different result sets.