Скачать или смотреть How to Efficiently Update Your Redshift Spectrum External Table Column Type

Learn how to easily update the column type in your `Redshift Spectrum` external table without losing data by creating a new table.
---
This video is based on the question https://stackoverflow.com/q/62899873/ asked by the user 'Vaibhav Rai' ( https://stackoverflow.com/u/6473246/ ) and on the answer https://stackoverflow.com/a/62929567/ provided by the user 'botchniaque' ( https://stackoverflow.com/u/1680826/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

Visit these links for original content and any more details, such as alternate solutions, latest updates/developments on topic, comments, revision history etc. For example, the original title of the Question was: Redshift spectrum - Updating external spectrum table column type

Also, Content (except music) licensed under CC BY-SA https://meta.stackexchange.com/help/l...
The original Question post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license, and the original Answer post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license.

If anything seems off to you, please feel free to write me at vlogize [AT] gmail [DOT] com.
---
Updating External Spectrum Table Column Type in Redshift

When working with Amazon Redshift and utilizing Redshift Spectrum to create external tables, you may encounter scenarios where you need to alter column types. This can be a common task, especially as the needs of your data evolve. In this guide, we will explore a specific use case where you need to update a column's data type in an external spectrum table.

The Challenge

You might find yourself in a situation like the following:

You have an external table, test_table_1, with four columns.

One column, user_app, is defined using a custom data type.

Due to evolving requirements, there is a need to modify this column to include additional nested structures.

For example, here’s how your current table column is structured:

[[See Video to Reveal this Text or Code Snippet]]

You now want to update it to:

[[See Video to Reveal this Text or Code Snippet]]

The Solution

The straightforward solution in this case is to drop the existing table and create it anew with the updated column type. Since this is an external table, you won’t risk losing any data stored in the underlying data sources.

Steps to Update the Table

Drop the Existing Table

Use the following command to drop the current external table.

[[See Video to Reveal this Text or Code Snippet]]

Create a New Table

Redefine the table with the updated column structure.

[[See Video to Reveal this Text or Code Snippet]]

Key Considerations

Data Preservation: Since it’s an external table, dropping it won’t affect the actual data stored in your data lake or external storage.

Downtime: Be mindful that the table will be unavailable during the drop-and-create operations.

Dependencies: Review any dependent queries or applications that might be affected by dropping the table.

Conclusion

Updating the column type of an external table in Redshift Spectrum is an essential skill for maintaining the flexibility of your data model. By following the steps outlined in this post, you can ensure that your user_app column is modified while preserving the integrity of your data source.

Embrace the power of simplicity—sometimes, dropping and recreating a table is the most efficient solution!

If you have more questions about using Redshift Spectrum or other Amazon Web Services, feel free to ask in the comments below!