Type Widening in ALTER TABLE CHANGE COLUMN #2645
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| val isEnabled = DeltaConfigs.ENABLE_TYPE_WIDENING.fromMetaData(metadata) | ||
| if (isEnabled && !isSupported(protocol)) { | ||
| throw new IllegalStateException( | ||
| s"Table property '${DeltaConfigs.ENABLE_TYPE_WIDENING.key}' is " + |
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I guess this should be using the error framework?
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This should never happen unless there's a bug in the implementation, so I wouldn't give it an error class. We typically wouldn't want to document that error as a user-facing error
spark/src/test/scala/org/apache/spark/sql/delta/DeltaTypeWideningSuite.scala
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spark/src/test/scala/org/apache/spark/sql/delta/DeltaTypeWideningSuite.scala
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spark/src/test/scala/org/apache/spark/sql/delta/DeltaTypeWideningSuite.scala
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spark/src/test/scala/org/apache/spark/sql/delta/DeltaTypeWideningSuite.scala
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spark/src/test/scala/org/apache/spark/sql/delta/DeltaTypeWideningSuite.scala
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spark/src/test/scala/org/apache/spark/sql/delta/DeltaTypeWideningSuite.scala
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spark/src/test/scala/org/apache/spark/sql/delta/DeltaTypeWideningSuite.scala
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spark/src/test/scala/org/apache/spark/sql/delta/DeltaTypeWideningSuite.scala
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| test("row group skipping Short -> Int") { | ||
| withSQLConf( | ||
| SQLConf.FILES_MAX_PARTITION_BYTES.key -> 1024.toString) { |
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How do we verify that this actually leads to row group skipping? FWIW it looks like this should lead to regular min/max data skipping on the Delta log. The max partition bytes only affects how we read chunks, i.e., it'll split a parquet file of >1024 bytes over multiple tasks (1024 bytes each), but if the file is still a single row group, then only one of the tasks will actually read it (the task that gets the "middle" byte of the row group), and the other files will simply ignore the row group. And with the current way of writing, each file will have only one row group, so the row group skipping will be equal to the Delta-level file skipping, so it should never skip, really.
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This test doesn't make a lot of sense here anymore, I added it back when I found the overflow issue in parquet row group skipping and kept it around but it's redundant with the test I added when I fixed the issue in Spark:
https://github.com/databricks/runtime/blob/a9d6a9d6191264ced1f0658ff6675b0f30e8e77f/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetQuerySuite.scala#L1216
I'm removing it, I don't think it's worth the effort to get it to accurately cover an issue that the Spark test already covers a lot better
| @@ -625,6 +626,18 @@ object ManagedCommitTableFeature | |||
| } | |||
| } | |||
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| object TypeWideningTableFeature extends ReaderWriterFeature(name = "typeWidening-dev") | |||
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since we are using -dev right now and its not ready for users using it. is it behind the isTesting flag?
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Which Delta project/connector is this regarding?
Description
This change introduces the
typeWideningdelta table feature, allowing to widen the type of existing columns and fields in a delta table using theALTER TABLE CHANGE COLUMN TYPEorALTER TABLE REPLACE COLUMNScommands.The table feature is introduced as
typeWidening-devduring implementation and is available in testing only.For now, only byte -> short -> int are supported. Other changes will require support in the Spark parquet reader that will be introduced in Spark 4.0
Type widening feature request: #2622
Type Widening protocol RFC: #2624
How was this patch tested?
A new test suite
DeltaTypeWideningSuiteis created, containing:DeltaTypeWideningAlterTableTests: Covers applying supported and unsupported type changes on partitioned columns, non-partitioned columns and nested fieldsDeltaTypeWideningTableFeatureTests: Covers adding thetypeWideningtable featureDoes this PR introduce any user-facing changes?
The table feature is available in testing only, there's no user-facing changes as of now.
The type widening table feature will introduce the following changes:
typeWideningvia a table property:Note: both ALTER TABLE commands reuse the existing syntax for setting a table property and applying a type change, no new SQL syntax is being introduced by this feature.