Amazon Redshift
  • 04 Jul 2024
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Amazon Redshift

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Article summary

Amazon Redshift is one of many delivery destinations that Bobsled supports. When delivering data from cloud object storage, Bobsled will turn the selected folders into tables in Redshift. To facilitate data sharing, Bobsled leverages Amazon Redshift native data sharing. Each Amazon Account granted access to the Bobsled share are granted access to all tables shared in the Bobsled Share.


Bobsled-managed Amazon Redshift

To learn how to Configure a Amazon Redshift destination in Bobsled, please visit Bobsled-managed Amazon Redshift setup guide.

Authorization

Bobsled requires a consumer's Amazon Account ID in order to grant access to the share.


Bobsled supports various advanced settings to further control how tables are delivered in Amazon Redshift.

Sort Key

Bobsled supports the setting of sort key ↗ of a table in Redshift, resulting in optimized tables for expected query patterns.

  • To set up clustering, access the advanced settings icon on the right side of the table configuration screen.

  • Each table can have one cluster key configuration.

  • The order of the selected keys during setup is important, and Bobsled will respect that order.

Clustering can also be set using the tableSettings property on a share using the API ↗

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If you are interested in using clustering to deliver optimized tables to your consumers but need assistance with the setup, please reach out to your account team.

Datatype override

Bobsled offers the capability to override a column's data type in your source schema with a different data type in the destination table.

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If you wish to leverage data type overriding, please reach out to your account team.

Schema migration support

When new columns are added to tables or files, Bobsled efficiently handles schema migrations by adding new columns to existing tables without disrupting deliveries.

  • When new columns are introduced, they're seamlessly integrated, and any missing data in these columns is defaulted to null values.

    • This approach ensures that data loading continues smoothly, even with schema changes, preventing load failures and maintaining data integrity.

  • Our schema migration strategy is designed for flexibility and reliability during data structure evolution.

  • When columns aren't present in new files, the values for missing columns is set to null.


Consuming a data transfer

Once you’ve configured your destination in a share, granted access to a consumer, and transferred data, learn how to consume a data transfer in Amazon Redshift.


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