Passing SQL statements to an Amazon Redshift data warehouse
The examples in this page cover different ways to pass a SQL statement to your data warehouse
Run a SQL statement
To run a SQL statement, use the aws redshift-data execute-statement
Amazon CLI command.
The following Amazon CLI command runs a SQL statement against a cluster and returns an identifier to fetch the results. This example uses the Amazon Secrets Manager authentication method.
aws redshift-data execute-statement --secret arn:aws:secretsmanager:us-west-2:123456789012:secret:myuser-secret-hKgPWn --cluster-identifier mycluster-test --sql "select * from stl_query limit 1" --database dev
The following is an example of the response.
{ "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" }
The following Amazon CLI command runs a SQL statement against a cluster and returns an identifier to fetch the results. This example uses the temporary credentials authentication method.
aws redshift-data execute-statement --db-user myuser --cluster-identifier mycluster-test --database dev --sql "select * from stl_query limit 1"
The following is an example of the response.
{ "ClusterIdentifier": "mycluster-test", "CreatedAt": 1598306924.632, "Database": "dev", "DbUser": "myuser", "Id": "d9b6c0c9-0747-4bf4-b142-e8883122f766" }
The following Amazon CLI command runs a SQL statement against a serverless workgroup and returns an identifier to fetch the results. This example uses the temporary credentials authentication method.
aws redshift-data execute-statement --database dev --workgroup-name myworkgroup --sql "select 1;"
The following is an example of the response.
{ "CreatedAt": "2022-02-11T06:25:28.748000+00:00", "Database": "dev", "DbUser": "IAMR:RoleName", "Id": "89dd91f5-2d43-43d3-8461-f33aa093c41e", "WorkgroupName": "myworkgroup" }
The following Amazon CLI command runs a SQL statement against a cluster and returns an identifier to fetch the results. This example uses the Amazon Secrets Manager authentication method and an idempotency token.
aws redshift-data execute-statement --secret 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
The following is an example of the response.
{ "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" }
Run a SQL statement with parameters
To run a SQL statement, use the aws redshift-data execute-statement
Amazon CLI command.
The
following Amazon CLI command runs a SQL statement against a cluster and returns an
identifier to fetch the results. This example uses the Amazon Secrets Manager authentication
method. The SQL text has named parameter distance. In this case, the
distance used in the predicate is 5. In a SELECT statement, named
parameters for column names can only be used in the predicate. Values for named
parameters for the SQL statement are specified in the parameters
option.
aws redshift-data execute-statement --secret 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
The following is an example of the response.
{ "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" }
The following example uses the EVENT table from the sample database.
For more information, see EVENT table in the
Amazon Redshift Database Developer Guide.
If you don't already have the EVENT table in your database, you can
create one using the Data API as follows:
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)"
The following command inserts one row into the EVENT table.
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\"}]"
The following command inserts a second row into the EVENT table. This
example demonstrates the following:
-
The parameter named
idis used four times in the SQL text. -
Implicit type conversion is applied automatically when inserting parameter
starttime. -
The
venueidcolumn is type cast to SMALLINT data type. -
Character strings that represent the DATE data type are implicitly converted into the TIMESTAMP data type.
-
Comments can be used within SQL text.
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\"}]"
The following shows the two inserted rows:
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
The following command uses a named parameter in a WHERE clause to retrieve the row
where eventid is 1.
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\"}]"
Run the following command to get the SQL results of the previous SQL statement:
aws redshift-data get-statement-result --id 7529ad05-b905-4d71-9ec6-8b333836eb5a
Provides the following results:
{ "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 }
Run multiple SQL statements
To run multiple SQL statements with one command, use the aws redshift-data
batch-execute-statement Amazon CLI command.
The following Amazon CLI command runs three SQL statements against a cluster and returns an identifier to fetch the results. This example uses the temporary credentials authentication method.
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"
The following is an example of the response.
{ "ClusterIdentifier": "mycluster-test", "CreatedAt": 1598306924.632, "Database": "dev", "DbUser": "myuser", "Id": "d9b6c0c9-0747-4bf4-b142-e8883122f766" }