[SPARK-45827][SQL] Move data type checks to CreatableRelationProvider #45409
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
cloud-fan
reviewed
Mar 7, 2024
Comment on lines
185
to
187
| def supportsDataType( | ||
| dt: DataType | ||
| ): Boolean = { |
There was a problem hiding this comment.
Suggested change
| def supportsDataType( | |
| dt: DataType | |
| ): Boolean = { | |
| def supportsDataType(dt: DataType): Boolean = { |
cloud-fan
reviewed
Mar 7, 2024
Comment on lines
190
to
191
| case MapType(k, v, _) => | ||
| supportsDataType(k) && supportsDataType(v) |
There was a problem hiding this comment.
Suggested change
| case MapType(k, v, _) => | |
| supportsDataType(k) && supportsDataType(v) | |
| case MapType(k, v, _) => supportsDataType(k) && supportsDataType(v) |
cloud-fan
reviewed
Mar 7, 2024
| case udt: UserDefinedType[_] => supportsDataType(udt.sqlType) | ||
| case _: AnsiIntervalType | CalendarIntervalType | VariantType => false | ||
| case BinaryType | BooleanType | ByteType | CalendarIntervalType | CharType(_) | DateType | | ||
| DayTimeIntervalType(_, _) | _ : DecimalType | DoubleType | FloatType | |
There was a problem hiding this comment.
It's confusing to have the interval types in both the true and false case matches. Shall we stick with the allowlist approach and only list the supported types?
There was a problem hiding this comment.
Oh, that was an accident. I'll remove from this list. I can have it only list supported types.
cloud-fan
reviewed
Mar 7, 2024
| val e = intercept[AnalysisException] { | ||
| dataSource.planForWriting(SaveMode.ErrorIfExists, df.logicalPlan) | ||
| } | ||
| assert(e.getMessage.contains("UNSUPPORTED_DATA_TYPE_FOR_DATASOURCE")) |
There was a problem hiding this comment.
let's use checkError for it.
|
@cloud-fan Thanks for the review! I've updated with your feedback. |
cloud-fan
reviewed
Mar 7, 2024
| * Check if the relation supports the given data type. | ||
| * | ||
| * @param dt Data type to check | ||
| * @return True if the data type is supported |
cloud-fan
approved these changes
Mar 7, 2024
yaooqinn
changed the title
|
thanks, merging to master! |
dongjoon-hyun
pushed a commit
that referenced
this pull request
Mar 11, 2024
### What changes were proposed in this pull request? #45409 created a default allow-list of types for data sources. The intent was to only prevent creation of the two types that had already been prevented elsewhere in code, but the match expression matched `StringType`, which is an object representing the default collation, instead of the `StringType` class, which represents any collation. This PR fixes the issue. ### Why are the changes needed? Without it, the previous PR would be a breaking change for data sources that write StringType with a non-default collation. ### Does this PR introduce _any_ user-facing change? It reverts the previous unintentional user-facing change. ### How was this patch tested? Unit test. ### Was this patch authored or co-authored using generative AI tooling? No. Closes #45463 from cashmand/SPARK-45827-followup. Authored-by: cashmand <david.cashman@databricks.com> Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
jpcorreia99
pushed a commit
to jpcorreia99/spark
that referenced
this pull request
Mar 12, 2024
### What changes were proposed in this pull request? In DataSource.scala, there are checks to prevent writing Variant and Interval types to a `CreatableRelationalProvider`. This PR unifies the checks in a method on `CreatableRelationalProvider` so that data sources can override in order to specify a different set of supported data types. ### Why are the changes needed? Allows data sources to specify what types they support, while providing a sensible default for most data sources. ### Does this PR introduce _any_ user-facing change? The error message for Variant and Interval are now shared, and are a bit more generic. The intent is to otherwise not have any user-facing change. ### How was this patch tested? Unit tests added. ### Was this patch authored or co-authored using generative AI tooling? No. Closes apache#45409 from cashmand/SPARK-45827-CreatableRelationProvider. Authored-by: cashmand <david.cashman@databricks.com> Signed-off-by: Wenchen Fan <wenchen@databricks.com>
jpcorreia99
pushed a commit
to jpcorreia99/spark
that referenced
this pull request
Mar 12, 2024
### What changes were proposed in this pull request? apache#45409 created a default allow-list of types for data sources. The intent was to only prevent creation of the two types that had already been prevented elsewhere in code, but the match expression matched `StringType`, which is an object representing the default collation, instead of the `StringType` class, which represents any collation. This PR fixes the issue. ### Why are the changes needed? Without it, the previous PR would be a breaking change for data sources that write StringType with a non-default collation. ### Does this PR introduce _any_ user-facing change? It reverts the previous unintentional user-facing change. ### How was this patch tested? Unit test. ### Was this patch authored or co-authored using generative AI tooling? No. Closes apache#45463 from cashmand/SPARK-45827-followup. Authored-by: cashmand <david.cashman@databricks.com> Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
sweisdb
pushed a commit
to sweisdb/spark
that referenced
this pull request
Apr 1, 2024
### What changes were proposed in this pull request? apache#45409 created a default allow-list of types for data sources. The intent was to only prevent creation of the two types that had already been prevented elsewhere in code, but the match expression matched `StringType`, which is an object representing the default collation, instead of the `StringType` class, which represents any collation. This PR fixes the issue. ### Why are the changes needed? Without it, the previous PR would be a breaking change for data sources that write StringType with a non-default collation. ### Does this PR introduce _any_ user-facing change? It reverts the previous unintentional user-facing change. ### How was this patch tested? Unit test. ### Was this patch authored or co-authored using generative AI tooling? No. Closes apache#45463 from cashmand/SPARK-45827-followup. Authored-by: cashmand <david.cashman@databricks.com> Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
What changes were proposed in this pull request?
In DataSource.scala, there are checks to prevent writing Variant and Interval types to a
CreatableRelationalProvider. This PR unifies the checks in a method onCreatableRelationalProviderso that data sources can override in order to specify a different set of supported data types.Why are the changes needed?
Allows data sources to specify what types they support, while providing a sensible default for most data sources.
Does this PR introduce any user-facing change?
The error message for Variant and Interval are now shared, and are a bit more generic. The intent is to otherwise not have any user-facing change.
How was this patch tested?
Unit tests added.
Was this patch authored or co-authored using generative AI tooling?
No.