[SPARK-52601][SQL] Support primitive types in TransformingEncoder#51313
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eejbyfeldt wants to merge 1 commit intoapache:masterfrom
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[SPARK-52601][SQL] Support primitive types in TransformingEncoder#51313eejbyfeldt wants to merge 1 commit intoapache:masterfrom
eejbyfeldt wants to merge 1 commit intoapache:masterfrom
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@hvanhovell You reviewed #50023 where |
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Merged to master! |
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@eejbyfeldt thanks for doing this! Can you create a backport for Spark 4.0? |
eejbyfeldt
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Sep 16, 2025
Support defining TransformingEncoder that has a primitive type as the input type. To support defining TransformingEncoder that has a primitive type as the input type. This came up for me when using a Scala 3 opaque type around a Long as a timestamp but wating have the encoder encode it as a timestamp. Ideally Spark would have some way of encoding a micro second timestamp without going through a java.sql.Timestamp or java.time.Instant. But this at least makes it possible to achive something similar (but less efficient) by defining a TransformingEncoder that takes a Long and returns a java.sql.Timestamp. Yes, it allows TransformingEncoder to be used in more cases. New and existing unit tests. No Closes apache#51313 from eejbyfeldt/SPARK-52601. Authored-by: Emil Ejbyfeldt <emil.ejbyfeldt@choreograph.com> Signed-off-by: Herman van Hovell <herman@databricks.com>
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Created the backport here #52354 |
dongjoon-hyun
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Sep 16, 2025
Backport of #51313 to 4.0 branch. ### What changes were proposed in this pull request? Support defining TransformingEncoder that has a primitive type as the input type. ### Why are the changes needed? This came up for me when using a Scala 3 opaque type around a Long as a timestamp but wating have the encoder encode it as a timestamp. Ideally Spark would have some way of encoding a micro second timestamp without going through a java.sql.Timestamp or java.time.Instant. But this at least makes it possible to achive something similar (but less efficient) by defining a TransformingEncoder that takes a Long and returns a java.sql.Timestamp. ### Does this PR introduce _any_ user-facing change? Yes, it allows TransformingEncoder to be used in more cases. ### How was this patch tested? New and existing unit tests. ### Was this patch authored or co-authored using generative AI tooling? No. Closes #52354 from eejbyfeldt/SPARK-52601-4.0. Authored-by: Emil Ejbyfeldt <emil.ejbyfeldt@choreograph.com> Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
zifeif2
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Nov 14, 2025
Backport of apache#51313 to 4.0 branch. ### What changes were proposed in this pull request? Support defining TransformingEncoder that has a primitive type as the input type. ### Why are the changes needed? This came up for me when using a Scala 3 opaque type around a Long as a timestamp but wating have the encoder encode it as a timestamp. Ideally Spark would have some way of encoding a micro second timestamp without going through a java.sql.Timestamp or java.time.Instant. But this at least makes it possible to achive something similar (but less efficient) by defining a TransformingEncoder that takes a Long and returns a java.sql.Timestamp. ### Does this PR introduce _any_ user-facing change? Yes, it allows TransformingEncoder to be used in more cases. ### How was this patch tested? New and existing unit tests. ### Was this patch authored or co-authored using generative AI tooling? No. Closes apache#52354 from eejbyfeldt/SPARK-52601-4.0. Authored-by: Emil Ejbyfeldt <emil.ejbyfeldt@choreograph.com> Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
huangxiaopingRD
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Nov 25, 2025
### What changes were proposed in this pull request? Support defining TransformingEncoder that has a primitive type as the input type. ### Why are the changes needed? To support defining TransformingEncoder that has a primitive type as the input type. This came up for me when using a Scala 3 opaque type around a Long as a timestamp but wating have the encoder encode it as a timestamp. Ideally Spark would have some way of encoding a micro second timestamp without going through a java.sql.Timestamp or java.time.Instant. But this at least makes it possible to achive something similar (but less efficient) by defining a TransformingEncoder that takes a Long and returns a java.sql.Timestamp. ### Does this PR introduce _any_ user-facing change? Yes, it allows TransformingEncoder to be used in more cases. ### How was this patch tested? New and existing unit tests. ### Was this patch authored or co-authored using generative AI tooling? No Closes apache#51313 from eejbyfeldt/SPARK-52601. Authored-by: Emil Ejbyfeldt <emil.ejbyfeldt@choreograph.com> Signed-off-by: Herman van Hovell <herman@databricks.com>
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What changes were proposed in this pull request?
Support defining TransformingEncoder that has a primitive type as the input type.
Why are the changes needed?
To support defining TransformingEncoder that has a primitive type as the input type.
This came up for me when using a Scala 3 opaque type around a Long as a timestamp but wating have the encoder encode it as a timestamp. Ideally Spark would have some way of encoding a micro second timestamp without going through a java.sql.Timestamp or java.time.Instant. But this at least makes it possible to achive something similar (but less efficient) by defining a TransformingEncoder that takes a Long and returns a java.sql.Timestamp.
Does this PR introduce any user-facing change?
Yes, it allows TransformingEncoder to be used in more cases.
How was this patch tested?
New and existing unit tests.
Was this patch authored or co-authored using generative AI tooling?
No