[SPARK-53450] Nulls are filled unexpectedly after converting hive table scan to logical relation #52193
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…to logical relation
peter-toth
approved these changes
Sep 2, 2025
| if (shouldInfer) { | ||
| val tableName = relation.tableMeta.identifier.unquotedString |
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We can drop relation. here for code consistency.
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Nice catch! Thank you, @peter-toth
yaooqinn
commented
Sep 2, 2025
sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveMetastoreCatalog.scala
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Merged to master, thank you @peter-toth |
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What changes were proposed in this pull request?
This PR introduces a configuration
spark.sql.hive.convertMetastoreAsNullableto set nullable to true for all fields while converting Hive parquet/orc tables to datasources to fix a data-correctness issue.Why are the changes needed?
Hive tables are generally schema-on-read, and those Spark-executed Hive DDLs are not always Hive compatible.
We have an online case that produces incorrect values while
convertMetastoreParquet=true, for a null record, it sometimes returns 5, others 0, and no other values are witnessed yet.I've tried 4 ways to read the table and data
It turns out that the incorrect table schema led to wrong results.
So, in this PR, I added a new configuration to fall back on how Hive handles nullability blindly.
Does this PR introduce any user-facing change?
No
How was this patch tested?
Unfortunately, I've not yet figured out a reproducible unit test to cover this. So, I packed and tested online with our prod data
Before this PR
After this PR
Was this patch authored or co-authored using generative AI tooling?
no