从补丁 198 开始，Amazon Redshift 将不再支持创建新的 Python UDF。现有的 Python UDF 将继续正常运行至 2026 年 6 月 30 日。有关更多信息，请参阅[博客文章](https://aws.amazon.com/blogs/big-data/amazon-redshift-python-user-defined-functions-will-reach-end-of-support-after-june-30-2026/)。
# 调用 Data API
您可以调用数据 API 或 AWS CLI 以在集群或无服务器工作组上运行 SQL 语句。运行 SQL 语句的主要操作是《Amazon Redshift Data API Reference》**中的 [https://docs.aws.amazon.com/redshift-data/latest/APIReference/API_ExecuteStatement.html](https://docs.aws.amazon.com/redshift-data/latest/APIReference/API_ExecuteStatement.html) 和 [https://docs.aws.amazon.com/redshift-data/latest/APIReference/API_BatchExecuteStatement.html](https://docs.aws.amazon.com/redshift-data/latest/APIReference/API_BatchExecuteStatement.html)。数据 API 支持 AWS 开发工具包所支持的编程语言。有关它们的更多信息，请参阅[用于在 AWS 上构建的工具](https://aws.amazon.com/tools/)。
要查看调用 Data API 的代码示例，请参阅 *GitHub* 中的 [Redshift 数据 API入门](https://github.com/aws-samples/getting-started-with-amazon-redshift-data-api#getting-started-with-redshift-data-api)。此存储库包含使用 AWS Lambda，从 Amazon EC2、AWS Glue Data Catalog 和 Amazon SageMaker Runtime 访问 Amazon Redshift 数据的示例。示例编程语言包括 Python、Go、Java 和 Javascript。
您可以使用 AWS CLI 调用 Data API。
以下示例使用 AWS CLI 调用数据 API。要运行示例，请编辑参数值以匹配您的环境。在许多示例中，会提供 `cluster-identifier` 以针对集群运行。在针对无服务器工作组运行时，需改为提供 `workgroup-name`。这些示例演示了一些数据 API 操作。有关更多信息，请参阅 *AWS CLI 命令参考*。
以下示例中的命令已被拆分和格式化以便于阅读。并非所有示例都显示了所有参数和响应。有关完整请求语法、请求参数、响应语法和响应元素的 API 定义，请参阅 [Amazon Redshift Data API Reference](https://docs.aws.amazon.com/redshift-data/latest/APIReference/)。
# 将 SQL 语句传递到 Amazon Redshift 数据仓库
本页中的示例讲述了将 SQL 语句传递到数据仓库的不同方法
## 运行 SQL 语句
要运行 SQL 语句，请使用 `aws redshift-data execute-statement` AWS CLI 命令。
以下 AWS CLI 命令针对集群运行一个 SQL 语句，并返回一个标识符来获取结果。此示例使用 AWS Secrets Manager 身份验证方法。
```
aws redshift-data execute-statement
--secret-arn arn:aws:secretsmanager:us-west-2:123456789012:secret:myuser-secret-hKgPWn
--cluster-identifier mycluster-test
--sql "select * from stl_query limit 1"
--database dev
```
以下为响应示例。
```
{
"ClusterIdentifier": "mycluster-test",
"CreatedAt": 1598323175.823,
"Database": "dev",
"Id": "c016234e-5c6c-4bc5-bb16-2c5b8ff61814",
"SecretArn": "arn:aws:secretsmanager:us-west-2:123456789012:secret:myuser-secret-hKgPWn"
}
```
以下 AWS CLI 命令针对集群运行一个 SQL 语句，并返回一个标识符来获取结果。此示例使用临时凭证身份验证方法。
```
aws redshift-data execute-statement
--db-user myuser
--cluster-identifier mycluster-test
--database dev
--sql "select * from stl_query limit 1"
```
以下为响应示例。
```
{
"ClusterIdentifier": "mycluster-test",
"CreatedAt": 1598306924.632,
"Database": "dev",
"DbUser": "myuser",
"Id": "d9b6c0c9-0747-4bf4-b142-e8883122f766"
}
```
以下 AWS CLI 命令针对无服务器工作组运行一个 SQL 语句，并返回一个标识符来获取结果。此示例使用临时凭证身份验证方法。
```
aws redshift-data execute-statement
--database dev
--workgroup-name myworkgroup
--sql "select 1;"
```
以下为响应示例。
```
{
"CreatedAt": "2022-02-11T06:25:28.748000+00:00",
"Database": "dev",
"DbUser": "IAMR:RoleName",
"Id": "89dd91f5-2d43-43d3-8461-f33aa093c41e",
"WorkgroupName": "myworkgroup"
}
```
以下 AWS CLI 命令针对集群运行一个 SQL 语句，并返回一个标识符来获取结果。此示例使用 AWS Secrets Manager 身份验证方法和幂等性令牌。
```
aws redshift-data execute-statement
--secret-arn arn:aws:secretsmanager:us-west-2:123456789012:secret:myuser-secret-hKgPWn
--cluster-identifier mycluster-test
--sql "select * from stl_query limit 1"
--database dev
--client-token b855dced-259b-444c-bc7b-d3e8e33f94g1
```
以下为响应示例。
```
{
"ClusterIdentifier": "mycluster-test",
"CreatedAt": 1598323175.823,
"Database": "dev",
"Id": "c016234e-5c6c-4bc5-bb16-2c5b8ff61814",
"SecretArn": "arn:aws:secretsmanager:us-west-2:123456789012:secret:myuser-secret-hKgPWn"
}
```
## 运行带有参数的 SQL 语句
要运行 SQL 语句，请使用 `aws redshift-data execute-statement` AWS CLI 命令。
以下 AWS CLI 命令针对集群运行一个 SQL 语句，并返回一个标识符来获取结果。此示例使用 AWS Secrets Manager 身份验证方法。SQL 文本具有命名参数 `distance`。在这种情况下，在谓词中使用的距离是 `5`。在 SELECT 语句中，列名的命名参数只能在谓词中使用。SQL 语句的命名参数值在 `parameters` 选项中指定。
```
aws redshift-data execute-statement
--secret-arn arn:aws:secretsmanager:us-west-2:123456789012:secret:myuser-secret-hKgPWn
--cluster-identifier mycluster-test
--sql "SELECT ratecode FROM demo_table WHERE trip_distance > :distance"
--parameters "[{\"name\": \"distance\", \"value\": \"5\"}]"
--database dev
```
以下为响应示例。
```
{
"ClusterIdentifier": "mycluster-test",
"CreatedAt": 1598323175.823,
"Database": "dev",
"Id": "c016234e-5c6c-4bc5-bb16-2c5b8ff61814",
"SecretArn": "arn:aws:secretsmanager:us-west-2:123456789012:secret:myuser-secret-hKgPWn"
}
```
以下示例使用示例数据库中的 `EVENT` 表。有关更多信息，请参阅《Amazon Redshift 数据库开发人员指南》**中的 [EVENT 表](https://docs.aws.amazon.com/redshift/latest/dg/r_eventtable.html)。
如果您的数据库中没有 `EVENT` 表，则可以使用数据 API 创建一个，如下所示：
```
aws redshift-data execute-statement
--database dev
--cluster-id mycluster-test
--db-user awsuser
--sql "create table event( eventid integer not null distkey,
venueid smallint not null,
catid smallint not null,
dateid smallint not null sortkey,
eventname varchar(200),
starttime timestamp)"
```
以下命令将一个行插入 `EVENT` 表。
```
aws redshift-data execute-statement
--database dev
--cluster-id mycluster-test
--db-user awsuser
--sql "insert into event values(:eventid, :venueid::smallint, :catid, :dateid, :eventname, :starttime)"
--parameters "[{\"name\": \"eventid\", \"value\": \"1\"}, {\"name\": \"venueid\", \"value\": \"1\"},
{\"name\": \"catid\", \"value\": \"1\"},
{\"name\": \"dateid\", \"value\": \"1\"},
{\"name\": \"eventname\", \"value\": \"event 1\"},
{\"name\": \"starttime\", \"value\": \"2022-02-22\"}]"
```
以下命令将另一个行插入 `EVENT` 表。该示例演示以下内容：
+ 名为 `id` 参数在 SQL 文本中使用了四次。
+ 插入参数 `starttime` 时自动应用隐式类型转换。
+ `venueid` 列是转换为 SMALLINT 数据类型的类型。
+ 表示 DATE 数据类型的字符串将隐式转换为 TIMESTAMP 数据类型。
+ 注释可以在 SQL 文本中使用。
```
aws redshift-data execute-statement
--database dev
--cluster-id mycluster-test
--db-user awsuser
--sql "insert into event values(:id, :id::smallint, :id, :id, :eventname, :starttime) /*this is comment, and it won't apply parameterization for :id, :eventname or :starttime here*/"
--parameters "[{\"name\": \"eventname\", \"value\": \"event 2\"},
{\"name\": \"starttime\", \"value\": \"2022-02-22\"},
{\"name\": \"id\", \"value\": \"2\"}]"
```
下面显示了两个插入的行：
```
eventid | venueid | catid | dateid | eventname | starttime
---------+---------+-------+--------+-----------+---------------------
1 | 1 | 1 | 1 | event 1 | 2022-02-22 00:00:00
2 | 2 | 2 | 2 | event 2 | 2022-02-22 00:00:00
```
以下命令使用 WHERE 子句中的命名参数来检索 `eventid` 为 `1` 的行。
```
aws redshift-data execute-statement
--database dev
--cluster-id mycluster-test
--db-user awsuser
--sql "select * from event where eventid=:id"
--parameters "[{\"name\": \"id\", \"value\": \"1\"}]"
```
运行以下命令以获取上一个 SQL 语句的 SQL 结果：
```
aws redshift-data get-statement-result --id 7529ad05-b905-4d71-9ec6-8b333836eb5a
```
提供以下结果：
```
{
"Records": [
[
{
"longValue": 1
},
{
"longValue": 1
},
{
"longValue": 1
},
{
"longValue": 1
},
{
"stringValue": "event 1"
},
{
"stringValue": "2022-02-22 00:00:00.0"
}
]
],
"ColumnMetadata": [
{
"isCaseSensitive": false,
"isCurrency": false,
"isSigned": true,
"label": "eventid",
"length": 0,
"name": "eventid",
"nullable": 0,
"precision": 10,
"scale": 0,
"schemaName": "public",
"tableName": "event",
"typeName": "int4"
},
{
"isCaseSensitive": false,
"isCurrency": false,
"isSigned": true,
"label": "venueid",
"length": 0,
"name": "venueid",
"nullable": 0,
"precision": 5,
"scale": 0,
"schemaName": "public",
"tableName": "event",
"typeName": "int2"
},
{
"isCaseSensitive": false,
"isCurrency": false,
"isSigned": true,
"label": "catid",
"length": 0,
"name": "catid",
"nullable": 0,
"precision": 5,
"scale": 0,
"schemaName": "public",
"tableName": "event",
"typeName": "int2"
},
{
"isCaseSensitive": false,
"isCurrency": false,
"isSigned": true,
"label": "dateid",
"length": 0,
"name": "dateid",
"nullable": 0,
"precision": 5,
"scale": 0,
"schemaName": "public",
"tableName": "event",
"typeName": "int2"
},
{
"isCaseSensitive": true,
"isCurrency": false,
"isSigned": false,
"label": "eventname",
"length": 0,
"name": "eventname",
"nullable": 1,
"precision": 200,
"scale": 0,
"schemaName": "public",
"tableName": "event",
"typeName": "varchar"
},
{
"isCaseSensitive": false,
"isCurrency": false,
"isSigned": false,
"label": "starttime",
"length": 0,
"name": "starttime",
"nullable": 1,
"precision": 29,
"scale": 6,
"schemaName": "public",
"tableName": "event",
"typeName": "timestamp"
}
],
"TotalNumRows": 1
}
```
## 运行多条 SQL 语句
要使用一个命令运行多个 SQL 语句，请使用 `aws redshift-data batch-execute-statement` AWS CLI 命令。
以下 AWS CLI 命令针对集群运行三个 SQL 语句，并返回一个标识符来获取结果。此示例使用临时凭证身份验证方法。
```
aws redshift-data batch-execute-statement
--db-user myuser
--cluster-identifier mycluster-test
--database dev
--sqls "set timezone to BST" "select * from mytable" "select * from another_table"
```
以下为响应示例。
```
{
"ClusterIdentifier": "mycluster-test",
"CreatedAt": 1598306924.632,
"Database": "dev",
"DbUser": "myuser",
"Id": "d9b6c0c9-0747-4bf4-b142-e8883122f766"
}
```
# 列出有关 SQL 语句的元数据
要列出有关 SQL 语句的元数据，请使用 `aws redshift-data list-statements` AWS CLI 命令。运行此命令的授权基于调用者的 IAM 权限。
以下 AWS CLI 命令列出了运行的 SQL 语句。
```
aws redshift-data list-statements
--status ALL
```
以下为响应示例。
```
{
"Statements": [
{
"CreatedAt": 1598306924.632,
"Id": "d9b6c0c9-0747-4bf4-b142-e8883122f766",
"QueryString": "select * from stl_query limit 1",
"Status": "FINISHED",
"UpdatedAt": 1598306926.667
},
{
"CreatedAt": 1598311717.437,
"Id": "e0ebd578-58b3-46cc-8e52-8163fd7e01aa",
"QueryString": "select * from stl_query limit 1",
"Status": "FAILED",
"UpdatedAt": 1598311719.008
},
{
"CreatedAt": 1598313683.65,
"Id": "c361d4f7-8c53-4343-8c45-6b2b1166330c",
"QueryString": "select * from stl_query limit 1",
"Status": "ABORTED",
"UpdatedAt": 1598313685.495
},
{
"CreatedAt": 1598306653.333,
"Id": "a512b7bd-98c7-45d5-985b-a715f3cfde7f",
"QueryString": "select 1",
"Status": "FINISHED",
"UpdatedAt": 1598306653.992
}
]
}
```
# 描述有关 SQL 语句的元数据
要获取 SQL 语句的元数据描述，请使用 `aws redshift-data describe-statement` AWS CLI 命令。运行此命令的授权基于调用者的 IAM 权限。
以下 AWS CLI 命令描述 SQL 语句。
```
aws redshift-data describe-statement
--id d9b6c0c9-0747-4bf4-b142-e8883122f766
```
以下为响应示例。
```
{
"ClusterIdentifier": "mycluster-test",
"CreatedAt": 1598306924.632,
"Duration": 1095981511,
"Id": "d9b6c0c9-0747-4bf4-b142-e8883122f766",
"QueryString": "select * from stl_query limit 1",
"RedshiftPid": 20859,
"RedshiftQueryId": 48879,
"ResultRows": 1,
"ResultSize": 4489,
"Status": "FINISHED",
"UpdatedAt": 1598306926.667
}
```
以下是使用多个 SQL 语句运行 `batch-execute-statement` 命令后的 `describe-statement` 响应示例。
```
{
"ClusterIdentifier": "mayo",
"CreatedAt": 1623979777.126,
"Duration": 6591877,
"HasResultSet": true,
"Id": "b2906c76-fa6e-4cdf-8c5f-4de1ff9b7652",
"RedshiftPid": 31459,
"RedshiftQueryId": 0,
"ResultRows": 2,
"ResultSize": 22,
"Status": "FINISHED",
"SubStatements": [
{
"CreatedAt": 1623979777.274,
"Duration": 3396637,
"HasResultSet": true,
"Id": "b2906c76-fa6e-4cdf-8c5f-4de1ff9b7652:1",
"QueryString": "select 1;",
"RedshiftQueryId": -1,
"ResultRows": 1,
"ResultSize": 11,
"Status": "FINISHED",
"UpdatedAt": 1623979777.903
},
{
"CreatedAt": 1623979777.274,
"Duration": 3195240,
"HasResultSet": true,
"Id": "b2906c76-fa6e-4cdf-8c5f-4de1ff9b7652:2",
"QueryString": "select 2;",
"RedshiftQueryId": -1,
"ResultRows": 1,
"ResultSize": 11,
"Status": "FINISHED",
"UpdatedAt": 1623979778.076
}
],
"UpdatedAt": 1623979778.183
}
```
# 获取 SQL 语句的结果
要从运行的 SQL 语句中获取结果，请使用 `redshift-data get-statement-result` 或 `redshift-data get-statement-result-v2` AWS CLI 命令。来自 `get-statement-result` 的结果采用 JSON 格式。来自 `get-statement-result-v2` 的结果采用 CSV 格式。您可以提供响应 `execute-statement` 或者 `batch-execute-statement` 而收到的 `Id`。可以在 `describe-statement` 的结果中检索 `batch-execute-statement` 运行的 SQL 语句的 `Id` 值，并以冒号和 `b2906c76-fa6e-4cdf-8c5f-4de1ff9b7652:2` 等序号为该值添加后缀。如果使用 `batch-execute-statement` 运行多个 SQL 语句，则每个 SQL 语句都有一个 `Id` 值，如 `describe-statement` 中所示。运行此命令的授权基于调用者的 IAM 权限。
以下语句返回 `execute-statement` 运行的 SQL 语句的结果，该语句让 `ResultFormat` 默认为 `JSON`。要检索结果，请调用 `get-statement-result` 操作。
```
aws redshift-data get-statement-result
--id d9b6c0c9-0747-4bf4-b142-e8883122f766
```
以下语句返回 `batch-execute-statement` 运行的第二个 SQL 语句的结果。
```
aws redshift-data get-statement-result
--id b2906c76-fa6e-4cdf-8c5f-4de1ff9b7652:2
```
以下是调用 `get-statement-result` 的响应示例，其中在响应的 `Records` 键中以 JSON 格式返回 SQL 结果。
```
{
"ColumnMetadata": [
{
"isCaseSensitive": false,
"isCurrency": false,
"isSigned": true,
"label": "userid",
"length": 0,
"name": "userid",
"nullable": 0,
"precision": 10,
"scale": 0,
"schemaName": "",
"tableName": "stll_query",
"typeName": "int4"
},
{
"isCaseSensitive": false,
"isCurrency": false,
"isSigned": true,
"label": "query",
"length": 0,
"name": "query",
"nullable": 0,
"precision": 10,
"scale": 0,
"schemaName": "",
"tableName": "stll_query",
"typeName": "int4"
},
{
"isCaseSensitive": true,
"isCurrency": false,
"isSigned": false,
"label": "label",
"length": 0,
"name": "label",
"nullable": 0,
"precision": 320,
"scale": 0,
"schemaName": "",
"tableName": "stll_query",
"typeName": "bpchar"
},
{
"isCaseSensitive": false,
"isCurrency": false,
"isSigned": true,
"label": "xid",
"length": 0,
"name": "xid",
"nullable": 0,
"precision": 19,
"scale": 0,
"schemaName": "",
"tableName": "stll_query",
"typeName": "int8"
},
{
"isCaseSensitive": false,
"isCurrency": false,
"isSigned": true,
"label": "pid",
"length": 0,
"name": "pid",
"nullable": 0,
"precision": 10,
"scale": 0,
"schemaName": "",
"tableName": "stll_query",
"typeName": "int4"
},
{
"isCaseSensitive": true,
"isCurrency": false,
"isSigned": false,
"label": "database",
"length": 0,
"name": "database",
"nullable": 0,
"precision": 32,
"scale": 0,
"schemaName": "",
"tableName": "stll_query",
"typeName": "bpchar"
},
{
"isCaseSensitive": true,
"isCurrency": false,
"isSigned": false,
"label": "querytxt",
"length": 0,
"name": "querytxt",
"nullable": 0,
"precision": 4000,
"scale": 0,
"schemaName": "",
"tableName": "stll_query",
"typeName": "bpchar"
},
{
"isCaseSensitive": false,
"isCurrency": false,
"isSigned": false,
"label": "starttime",
"length": 0,
"name": "starttime",
"nullable": 0,
"precision": 29,
"scale": 6,
"schemaName": "",
"tableName": "stll_query",
"typeName": "timestamp"
},
{
"isCaseSensitive": false,
"isCurrency": false,
"isSigned": false,
"label": "endtime",
"length": 0,
"name": "endtime",
"nullable": 0,
"precision": 29,
"scale": 6,
"schemaName": "",
"tableName": "stll_query",
"type": 93,
"typeName": "timestamp"
},
{
"isCaseSensitive": false,
"isCurrency": false,
"isSigned": true,
"label": "aborted",
"length": 0,
"name": "aborted",
"nullable": 0,
"precision": 10,
"scale": 0,
"schemaName": "",
"tableName": "stll_query",
"typeName": "int4"
},
{
"isCaseSensitive": false,
"isCurrency": false,
"isSigned": true,
"label": "insert_pristine",
"length": 0,
"name": "insert_pristine",
"nullable": 0,
"precision": 10,
"scale": 0,
"schemaName": "",
"tableName": "stll_query",
"typeName": "int4"
},
{
"isCaseSensitive": false,
"isCurrency": false,
"isSigned": true,
"label": "concurrency_scaling_status",
"length": 0,
"name": "concurrency_scaling_status",
"nullable": 0,
"precision": 10,
"scale": 0,
"schemaName": "",
"tableName": "stll_query",
"typeName": "int4"
}
],
"Records": [
[
{
"longValue": 1
},
{
"longValue": 3
},
{
"stringValue": "health"
},
{
"longValue": 1023
},
{
"longValue": 15279
},
{
"stringValue": "dev"
},
{
"stringValue": "select system_status from stv_gui_status;"
},
{
"stringValue": "2020-08-21 17:33:51.88712"
},
{
"stringValue": "2020-08-21 17:33:52.974306"
},
{
"longValue": 0
},
{
"longValue": 0
},
{
"longValue": 6
}
]
],
"TotalNumRows": 1
}
```
以下示例显示了 `execute-statement` 运行的一条 SQL 语句，该语句以 JSON 格式返回结果。表 `testingtable` 有三个整数列（col1、col2、col3），还有三行的值分别为（1、2、3）、（4、5、6）和（7、8、9）。
```
aws redshift-data execute-statement
--database dev
--sql "SELECT col1, col2, col3 FROM testingtable"
--cluster-id mycluster-test
--result-format JSON
```
```
{
"ClusterIdentifier": "mycluster-test",
"CreatedAt": "2024-04-02T16:45:25.144000+00:00",
"Database": "dev",
"DbUser": "IAMR:Administrator",
"Id": "d468d942-6df9-4f85-8ae3-bac01a61aec3"
}
```
以下是调用 `get-statement-result` 的响应示例，其中在响应的 `Records` 键中以 JSON 格式返回 SQL 结果。
```
aws redshift-data get-statement-result
--id d468d942-6df9-4f85-8ae3-bac01a61aec3
```
```
{
"Records": [
[
{
"longValue": 1
},
{
"longValue": 2
},
{
"longValue": 3
}
],
[
{
"longValue": 4
},
{
"longValue": 5
},
{
"longValue": 6
}
],
[
{
"longValue": 7
},
{
"longValue": 8
},
{
"longValue": 9
}
]
],
"ColumnMetadata": [
{
"isCaseSensitive": false,
"isCurrency": false,
"isSigned": true,
"label": "col1",
"name": "col1",
"nullable": 1,
"precision": 10,
"scale": 0,
"schemaName": "public",
"tableName": "testingtable",
"typeName": "int4",
"length": 0
},
{
"isCaseSensitive": false,
"isCurrency": false,
"isSigned": true,
"label": "col2",
"name": "col2",
"nullable": 1,
"precision": 10,
"scale": 0,
"schemaName": "public",
"tableName": "testingtable",
"typeName": "int4",
"length": 0
},
{
"isCaseSensitive": false,
"isCurrency": false,
"isSigned": true,
"label": "col3",
"name": "col3",
"nullable": 1,
"precision": 10,
"scale": 0,
"schemaName": "public",
"tableName": "testingtable",
"typeName": "int4",
"length": 0
}
],
"TotalNumRows": 3
}
```
以下示例显示了 `execute-statement` 运行的一条 SQL 语句，该语句以 CSV 格式返回结果。表 `testingtable` 有三个整数列（col1、col2、col3），还有三行的值分别为（1、2、3）、（4、5、6）和（7、8、9）。
```
aws redshift-data execute-statement
--database dev
--sql "SELECT col1, col2, col3 FROM testingtable"
--cluster-id mycluster-test
--result-format CSV
```
```
{
"ClusterIdentifier": "mycluster-test",
"CreatedAt": "2024-04-02T16:45:25.144000+00:00",
"Database": "dev",
"DbUser": "IAMR:Administrator",
"Id": "d468d942-6df9-4f85-8ae3-bac01a61aec3"
}
```
以下是调用 `get-statement-result-v2` 的响应示例，其中在响应的 `Records` 键中以 CSV 格式返回 SQL 结果。行由回车符和换行符（\$1r\$1n）分隔。`Records` 中返回的第一行是列标题。以 CSV 格式返回的结果以 1 MB 为单位返回，其中每个分块可以存储任意数量的行，最大为 1MB。
```
aws redshift-data get-statement-result-v2
--id d468d942-6df9-4f85-8ae3-bac01a61aec3
```
```
{
"Records": [
{
"CSVRecords": "col1,col2,col3\r\n1,2,3\r\n4,5,6\r\n7,8,9\r\n"
}
],
"ColumnMetadata": [
{
"isCaseSensitive": false,
"isCurrency": false,
"isSigned": true,
"label": "col1",
"name": "col1",
"nullable": 1,
"precision": 10,
"scale": 0,
"schemaName": "public",
"tableName": "testingtable",
"typeName": "int4",
"length": 0
},
{
"isCaseSensitive": false,
"isCurrency": false,
"isSigned": true,
"label": "col2",
"name": "col2",
"nullable": 1,
"precision": 10,
"scale": 0,
"schemaName": "public",
"tableName": "testingtable",
"typeName": "int4",
"length": 0
},
{
"isCaseSensitive": false,
"isCurrency": false,
"isSigned": true,
"label": "col3",
"name": "col3",
"nullable": 1,
"precision": 10,
"scale": 0,
"schemaName": "public",
"tableName": "testingtable",
"typeName": "int4",
"length": 0
}
],
"TotalNumRows": 3,
"ResultFormat": "csv"
}
```
# 描述表
要获取描述表的元数据，请使用 `aws redshift-data describe-table` AWS CLI 命令。
以下 AWS CLI 命令针对集群运行一个 SQL 语句，并返回描述表的元数据。此示例使用 AWS Secrets Manager 身份验证方法。
```
aws redshift-data describe-table
--cluster-identifier mycluster-test
--database dev
--schema information_schema
--table sql_features
--secret-arn arn:aws:secretsmanager:us-west-2:123456789012:secret:myuser-secret-hKgPWn
```
以下为响应示例。
```
{
"ColumnList": [
{
"isCaseSensitive": false,
"isCurrency": false,
"isSigned": false,
"length": 2147483647,
"name": "feature_id",
"nullable": 1,
"precision": 2147483647,
"scale": 0,
"schemaName": "information_schema",
"tableName": "sql_features",
"typeName": "character_data"
},
{
"isCaseSensitive": false,
"isCurrency": false,
"isSigned": false,
"length": 2147483647,
"name": "feature_name",
"nullable": 1,
"precision": 2147483647,
"scale": 0,
"schemaName": "information_schema",
"tableName": "sql_features",
"typeName": "character_data"
}
]
}
```
以下 AWS CLI 命令针对集群运行一个 SQL 语句来描述表。此示例使用临时凭证身份验证方法。
```
aws redshift-data describe-table
--db-user myuser
--cluster-identifier mycluster-test
--database dev
--schema information_schema
--table sql_features
```
以下为响应示例。
```
{
"ColumnList": [
{
"isCaseSensitive": false,
"isCurrency": false,
"isSigned": false,
"length": 2147483647,
"name": "feature_id",
"nullable": 1,
"precision": 2147483647,
"scale": 0,
"schemaName": "information_schema",
"tableName": "sql_features",
"typeName": "character_data"
},
{
"isCaseSensitive": false,
"isCurrency": false,
"isSigned": false,
"length": 2147483647,
"name": "feature_name",
"nullable": 1,
"precision": 2147483647,
"scale": 0,
"schemaName": "information_schema",
"tableName": "sql_features",
"typeName": "character_data"
},
{
"isCaseSensitive": false,
"isCurrency": false,
"isSigned": false,
"length": 2147483647,
"name": "sub_feature_id",
"nullable": 1,
"precision": 2147483647,
"scale": 0,
"schemaName": "information_schema",
"tableName": "sql_features",
"typeName": "character_data"
},
{
"isCaseSensitive": false,
"isCurrency": false,
"isSigned": false,
"length": 2147483647,
"name": "sub_feature_name",
"nullable": 1,
"precision": 2147483647,
"scale": 0,
"schemaName": "information_schema",
"tableName": "sql_features",
"typeName": "character_data"
},
{
"isCaseSensitive": false,
"isCurrency": false,
"isSigned": false,
"length": 2147483647,
"name": "is_supported",
"nullable": 1,
"precision": 2147483647,
"scale": 0,
"schemaName": "information_schema",
"tableName": "sql_features",
"typeName": "character_data"
},
{
"isCaseSensitive": false,
"isCurrency": false,
"isSigned": false,
"length": 2147483647,
"name": "is_verified_by",
"nullable": 1,
"precision": 2147483647,
"scale": 0,
"schemaName": "information_schema",
"tableName": "sql_features",
"typeName": "character_data"
},
{
"isCaseSensitive": false,
"isCurrency": false,
"isSigned": false,
"length": 2147483647,
"name": "comments",
"nullable": 1,
"precision": 2147483647,
"scale": 0,
"schemaName": "information_schema",
"tableName": "sql_features",
"typeName": "character_data"
}
]
}
```
# 列出集群中的数据库
要列出集群中的数据库，请使用 `aws redshift-data list-databases` AWS CLI 命令。
以下 AWS CLI 命令针对集群运行一个 SQL 语句来列出数据库。此示例使用 AWS Secrets Manager 身份验证方法。
```
aws redshift-data list-databases
--secret-arn arn:aws:secretsmanager:us-west-2:123456789012:secret:myuser-secret-hKgPWn
--cluster-identifier mycluster-test
--database dev
```
以下为响应示例。
```
{
"Databases": [
"dev"
]
}
```
以下 AWS CLI 命令针对集群运行一个 SQL 语句来列出数据库。此示例使用临时凭证身份验证方法。
```
aws redshift-data list-databases
--db-user myuser
--cluster-identifier mycluster-test
--database dev
```
以下为响应示例。
```
{
"Databases": [
"dev"
]
}
```
# 列出数据库中的架构
要列出数据库中的 schema，请使用 `aws redshift-data list-schemas` AWS CLI 命令。
以下 AWS CLI 命令针对集群运行一个 SQL 语句来列出数据库中的架构。此示例使用 AWS Secrets Manager 身份验证方法。
```
aws redshift-data list-schemas
--secret-arn arn:aws:secretsmanager:us-west-2:123456789012:secret:myuser-secret-hKgPWn
--cluster-identifier mycluster-test
--database dev
```
以下为响应示例。
```
{
"Schemas": [
"information_schema",
"pg_catalog",
"pg_internal",
"public"
]
}
```
以下 AWS CLI 命令针对集群运行一个 SQL 语句来列出数据库中的架构。此示例使用临时凭证身份验证方法。
```
aws redshift-data list-schemas
--db-user mysuser
--cluster-identifier mycluster-test
--database dev
```
以下为响应示例。
```
{
"Schemas": [
"information_schema",
"pg_catalog",
"pg_internal",
"public"
]
}
```
# 列出数据库中的表
要列出数据库中的表，请使用 `aws redshift-data list-tables` AWS CLI 命令。
以下 AWS CLI 命令针对集群运行一个 SQL 语句来列出数据库中的表。此示例使用 AWS Secrets Manager 身份验证方法。
```
aws redshift-data list-tables
--secret-arn arn:aws:secretsmanager:us-west-2:123456789012:secret:myuser-secret-hKgPWn
--cluster-identifier mycluster-test
--database dev
--schema information_schema
```
以下为响应示例。
```
{
"Tables": [
{
"name": "sql_features",
"schema": "information_schema",
"type": "SYSTEM TABLE"
},
{
"name": "sql_implementation_info",
"schema": "information_schema",
"type": "SYSTEM TABLE"
}
}
```
以下 AWS CLI 命令针对集群运行一个 SQL 语句来列出数据库中的表。此示例使用临时凭证身份验证方法。
```
aws redshift-data list-tables
--db-user myuser
--cluster-identifier mycluster-test
--database dev
--schema information_schema
```
以下为响应示例。
```
{
"Tables": [
{
"name": "sql_features",
"schema": "information_schema",
"type": "SYSTEM TABLE"
},
{
"name": "sql_implementation_info",
"schema": "information_schema",
"type": "SYSTEM TABLE"
}
]
}
```