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Add credentials

  1. Create a new pipeline or open an existing pipeline.
  2. Expand the left side of your screen to view the file browser.
  3. Scroll down and click on a file named io_config.yaml.
  4. Enter the following keys and values under the key named default (you can have multiple profiles, add it under whichever is relevant to you)
When connecting to Redshift Serverless, you can use workgroup-name.account-number.aws-region.redshift-serverless.amazonaws.com as the REDSHIFT_HOST value.

Using SQL block

  1. Create a new pipeline or open an existing pipeline.
  2. Add a data loader, transformer, or data exporter block.
  3. Select SQL.
  4. Under the Data provider dropdown, select Redshift.
  5. Under the Profile dropdown, select default (or the profile you added credentials underneath).
  6. Next to the Save to schema label, enter the schema name you want this block to save data to.
  7. Under the Write policy dropdown, select Replace or Append (please see SQL blocks guide for more information on write policies).
  8. Enter in this test query: SELECT 1.
  9. Run the block.

Using Python block

  1. Create a new pipeline or open an existing pipeline.
  2. Add a data loader, transformer, or data exporter block (the code snippet below is for a data loader).
  3. Select Generic (no template).
  4. Enter this code snippet (note: change the config_profile from default if you have a different profile):
  1. Run the block.

  1. Custom types.
To overwrite a column type when running a python export block, simply specify the column name and type in the overwrite_types dict in data exporter config Here is an example code snippet:

Method arguments