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[SPARK-4113] [SQL] [PySpark] type conversionfor python udf #2973
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Test build #22341 has started for PR 2973 at commit
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Test FAILed. |
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Test build #485 has started for PR 2973 at commit
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Test PASSed. |
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Nit/existing: I'd avoid creating attributes which is actually pretty expensive due to an AtomicLong and use the public API for schema. I think instead of these two lines you can just do the following here and above.
val fieldTypes = schema.fields.map(_.dataType)|
Thanks for the quick fix! A few minor comments. |
Conflicts: sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala
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Test build #22377 has started for PR 2973 at commit
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Test build #22378 has started for PR 2973 at commit
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Test build #489 has started for PR 2973 at commit
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Test build #22379 has started for PR 2973 at commit
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Test build #22377 has finished for PR 2973 at commit
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Test PASSed. |
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Test build #22378 has finished for PR 2973 at commit
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Test PASSed. |
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Test build #22379 has finished for PR 2973 at commit
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Test PASSed. |
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Test build #489 has finished for PR 2973 at commit
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Thanks! Merged to master. |
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FYI this is actually: SPARK-4113 |
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thanks, update the link |
Call Python UDF on ArrayType/MapType/PrimitiveType, the returnType can also be ArrayType/MapType/PrimitiveType.
For StructType, it will act as tuple (without attributes). If returnType is StructType, it also should be tuple.