release/2.0.9-spark-3.5 #598
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* Replace 'withColumns' with 'select' (#582) 'withColumns' was introduced in Spark 3.3, so it won't work for Deequ's <3.3 builds. * Replace rdd with dataframe functions in Histogram analyzer (#586) Co-authored-by: Shriya Vanvari <svanvari@amazon.com> * Updated version in pom.xml to 2.0.8-spark-3.5 (#578) Co-authored-by: Yannis Mentekidis <mentekid@amazon.com> --------- Co-authored-by: Josh <5685731+marcantony@users.noreply.github.com> Co-authored-by: Shriya Vanvari <vanvari.shriya@gmail.com> Co-authored-by: Shriya Vanvari <svanvari@amazon.com> Co-authored-by: Yannis Mentekidis <mentekid@users.noreply.github.com> Co-authored-by: Yannis Mentekidis <mentekid@amazon.com>
* Fix row level bug when composing outcome - When a check fails due to a precondition failure, the row level results are not evaluated correctly. - For example, let's say a check has a completeness constraint which passes, and a minimum constraint which fails due to a precondition failure. - The row level results will be the results for just the completeness constraint. There will be no results generated for the minimum constraint, and therefore the row level results will be incorrect. - We fix this by adding a default outcome for when the row level result column is not provided by the analyzer. * Added similar logic to RowLevelConstraint as well Skipped RowLevelGroupedConstraint because only UniqueValueRatio/Uniqueness use it, and they don't use preconditions.
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Description of changes:
Update release version name in pom.xml to
2.0.9-spark-3.5By submitting this pull request, I confirm that my contribution is made under the terms of the Apache 2.0 license.