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https://issues.apache.org/jira/browse/SPARK-18108?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Richard Moorhead updated SPARK-18108:
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Attachment: stacktrace.out
> Partition discovery fails with explicitly written long partitions
> -----------------------------------------------------------------
>
> Key: SPARK-18108
> URL: https://issues.apache.org/jira/browse/SPARK-18108
> Project: Spark
> Issue Type: Question
> Components: Spark Core
> Affects Versions: 2.0.1
> Reporter: Richard Moorhead
> Priority: Minor
> Attachments: stacktrace.out
>
>
> We have parquet data written from Spark1.6 that, when read from 2.0.1,
> produces errors.
> {code}
> case class A(a: Long, b: Int)
> val as = Seq(A(1,2))
> //partition explicitly written
> spark.createDataFrame(as).write.parquet("/data/a=1/")
> spark.read.parquet("/data/").collect
> {code}
> The above code fails; stack trace attached.
> If an integer used, explicit partition discovery succeeds.
> {code}
> case class A(a: Int, b: Int)
> val as = Seq(A(1,2))
> //partition explicitly written
> spark.createDataFrame(as).write.parquet("/data/a=1/")
> spark.read.parquet("/data/").collect
> {code}
> The action succeeds. Additionally, if 'partitionBy' is used instead of
> explicit writes, partition discovery succeeds.
> Question: Is the first example a reasonable use case?
> [PartitioningUtils|https://github.com/apache/spark/blob/branch-2.0/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/PartitioningUtils.scala#L319]
> seems to default to Integer types unless the partition value exceeds the
> integer type's length.
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