kosiew opened a new pull request, #14769:
URL: https://github.com/apache/datafusion/pull/14769
## Which issue does this PR close?
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- Closes #14765.
## Rationale for this change
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Why are you proposing this change? If this is already explained clearly in
the issue then this section is not needed.
Explaining clearly why changes are proposed helps reviewers understand your
changes and offer better suggestions for fixes.
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The fill_null operation is a common requirement in data processing
frameworks like PySpark, where users need to replace null values across
multiple columns efficiently. Adding a fill_null function to DataFusion and
datafusion-python provides a convenient way to perform this operation without
requiring complex expressions such as coalesce or manual conditional statements.
This change improves usability and aligns DataFusion's feature set more
closely with other popular data processing frameworks.
## What changes are included in this PR?
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There is no need to duplicate the description in the issue here but it is
sometimes worth providing a summary of the individual changes in this PR.
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Introduced a new fill_null function in DataFrame that replaces null values
in selected columns or all columns if none are specified.
Ensured type safety by only allowing replacements that can be cast to the
respective column's type.
Implemented a fallback mechanism where columns remain unchanged if the
provided value cannot be cast to their type.
Added helper function find_columns to validate column existence.
Included comprehensive test cases for fill_null, verifying behavior for both
single-column and all-column replacements.
## Are these changes tested?
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Yes, the following test cases have been added:
test_fill_null: Verifies the ability to replace null values in specific
columns with the provided values.
test_fill_null_all_columns: Ensures the function works correctly when no
column list is provided, replacing nulls in all columns where casting is
possible.
Tests confirm that invalid casts do not modify the original column values.
## Are there any user-facing changes?
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If there are user-facing changes then we may require documentation to be
updated before approving the PR.
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Yes, this PR introduces a new fill_null method for DataFrames, allowing
users to efficiently replace null values in their datasets. This enhances
usability and streamlines null handling within DataFusion.
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There are no breaking changes to existing APIs.
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