docs: Document schema preservation behavior on SaveMode.Overwrite (#1456) #1457
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Summary of ChangesHello @sahilkumarsingh, I'm Gemini Code Assist1! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed! This pull request enhances the documentation for the Spark-BigQuery connector by providing crucial information regarding the schema preservation behavior when using Highlights
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Code Review
This pull request adds important documentation about the schema preservation behavior when using SaveMode.Overwrite. The new section clearly explains that the existing schema is retained, which can be a source of confusion for users upgrading from older versions. The provided workarounds for intentional schema changes are helpful. My review includes a minor suggestion to ensure the version numbers mentioned are accurate, aligning with the information in the PR description.
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
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cc: @davidrabinowitz |
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cc: @yalimu-g |
| `INTEGER` to `DOUBLE`), the write will fail with a type mismatch error. To change the schema, either: | ||
| - Drop the table before overwriting | ||
| - Use BigQuery DDL to alter the table schema first | ||
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For some of the schema difference the following options can work with overwrite:
Programmatic Relaxation: Set .option("allowFieldRelaxation", "true") for nullability changes and .option("allowFieldAddition", "true") for new columns.
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Yes, we can add this detail. Shall I add it?
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Done, please check.
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/gcbrun |
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/gcbrun |
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looks like a CI infrastructure test issue |
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/gcbrun |
2 participants
Description
This PR addresses the issue #1456
Documents the schema preservation behaviour when using
SaveMode.Overwrite, which was updated somewhere between 0.22.2 and 0.41.0 versions.Changes
Why
Users upgrading from versions prior to 0.41.0 encounter unexpected failures when overwriting tables with different column types. This documentation helps users understand the expected behaviour and provides workarounds.