[SPARK-51418][SQL] Fix DataSource PARTITON TABLE w/ Hive type incompatible partition columns#50182
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yaooqinn wants to merge 5 commits intoapache:masterfrom
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[SPARK-51418][SQL] Fix DataSource PARTITON TABLE w/ Hive type incompatible partition columns#50182yaooqinn wants to merge 5 commits intoapache:masterfrom
yaooqinn wants to merge 5 commits intoapache:masterfrom
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…tible partition columns
dongjoon-hyun
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+1, LGTM (Pending CIs). Thank you, @yaooqinn .
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Thank you @dongjoon-hyun The CI has already passed https://github.com/yaooqinn/spark/actions/runs/13718779026, but w/o being properly updated here. Let's wait for the GA for the latest sync. |
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…tible partition columns ### What changes were proposed in this pull request? ``` 25/03/06 08:25:17 WARN HiveExternalCatalog: Hive incompatible types found: timestamp_ntz. Persisting data source table `spark_catalog`.`default`.`c` into Hive metastore in Spark SQL specific format, which is NOT compatible with Hive. org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: InvalidObjectException(message:Invalid partition column type: timestamp_ntz) ``` The partition columns are duplicated and stored both in the HMS column meta and the table properties. If they contain incompatible data types, the HMS Meta API will fail the process. We can rely on the table properties to read/write ### Why are the changes needed? bugfix, otherwise, newly added spark data types are not able to be used as partition columns ### Does this PR introduce _any_ user-facing change? Yes, More type cases are supported for partitioned datasouce tables stored in HMS ### How was this patch tested? new tests ### Was this patch authored or co-authored using generative AI tooling? no Closes #50182 from yaooqinn/SPARK-51418. Authored-by: Kent Yao <yao@apache.org> Signed-off-by: Kent Yao <yao@apache.org> (cherry picked from commit f11bc75) Signed-off-by: Kent Yao <yao@apache.org>
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Merged to master and 4.0, thank you again @dongjoon-hyun |
zifeif2
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Nov 14, 2025
…tible partition columns ### What changes were proposed in this pull request? ``` 25/03/06 08:25:17 WARN HiveExternalCatalog: Hive incompatible types found: timestamp_ntz. Persisting data source table `spark_catalog`.`default`.`c` into Hive metastore in Spark SQL specific format, which is NOT compatible with Hive. org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: InvalidObjectException(message:Invalid partition column type: timestamp_ntz) ``` The partition columns are duplicated and stored both in the HMS column meta and the table properties. If they contain incompatible data types, the HMS Meta API will fail the process. We can rely on the table properties to read/write ### Why are the changes needed? bugfix, otherwise, newly added spark data types are not able to be used as partition columns ### Does this PR introduce _any_ user-facing change? Yes, More type cases are supported for partitioned datasouce tables stored in HMS ### How was this patch tested? new tests ### Was this patch authored or co-authored using generative AI tooling? no Closes apache#50182 from yaooqinn/SPARK-51418. Authored-by: Kent Yao <yao@apache.org> Signed-off-by: Kent Yao <yao@apache.org> (cherry picked from commit d55a8ba) Signed-off-by: Kent Yao <yao@apache.org>
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What changes were proposed in this pull request?
The partition columns are duplicated and stored both in the HMS column meta and the table properties. If they contain incompatible data types, the HMS Meta API will fail the process.
We can rely on the table properties to read/write
Why are the changes needed?
bugfix, otherwise, newly added spark data types are not able to be used as partition columns
Does this PR introduce any user-facing change?
Yes, More type cases are supported for partitioned datasouce tables stored in HMS
How was this patch tested?
new tests
Was this patch authored or co-authored using generative AI tooling?
no