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。
Elasticsearch SQL的优点
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。
实例
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
}
}
]
}SQL查询
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|604Note −通过更改上面的SQL查询，您可以获得不同的结果集。