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Posted to issues@spark.apache.org by "Hyukjin Kwon (Jira)" <ji...@apache.org> on 2022/08/29 01:57:00 UTC
[jira] [Resolved] (SPARK-40212) SparkSQL castPartValue does not properly handle byte & short
[ https://issues.apache.org/jira/browse/SPARK-40212?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Hyukjin Kwon resolved SPARK-40212.
----------------------------------
Fix Version/s: 3.4.0
Resolution: Fixed
Issue resolved by pull request 37659
[https://github.com/apache/spark/pull/37659]
> SparkSQL castPartValue does not properly handle byte & short
> ------------------------------------------------------------
>
> Key: SPARK-40212
> URL: https://issues.apache.org/jira/browse/SPARK-40212
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 3.3.0
> Reporter: Brennan Stein
> Assignee: Brennan Stein
> Priority: Major
> Fix For: 3.4.0
>
>
> Reading in a parquet file partitioned on disk by a `Byte`-type column fails with the following exception:
>
> {code:java}
> [info] Cause: java.lang.ClassCastException: java.lang.Integer cannot be cast to java.lang.Byte
> [info] at scala.runtime.BoxesRunTime.unboxToByte(BoxesRunTime.java:95)
> [info] at org.apache.spark.sql.catalyst.expressions.BaseGenericInternalRow.getByte(rows.scala:39)
> [info] at org.apache.spark.sql.catalyst.expressions.BaseGenericInternalRow.getByte$(rows.scala:39)
> [info] at org.apache.spark.sql.catalyst.expressions.GenericInternalRow.getByte(rows.scala:195)
> [info] at org.apache.spark.sql.catalyst.expressions.JoinedRow.getByte(JoinedRow.scala:86)
> [info] at org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificUnsafeProjection.writeFields_0_6$(Unknown Source)
> [info] at org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificUnsafeProjection.apply(Unknown Source)
> [info] at org.apache.spark.sql.execution.datasources.parquet.ParquetFileFormat.$anonfun$buildReaderWithPartitionValues$8(ParquetFileFormat.scala:385)
> [info] at org.apache.spark.sql.execution.datasources.RecordReaderIterator$$anon$1.next(RecordReaderIterator.scala:62)
> [info] at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.next(FileScanRDD.scala:189)
> [info] at scala.collection.Iterator$$anon$10.next(Iterator.scala:461)
> [info] at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
> [info] at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
> [info] at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:760)
> [info] at org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:364)
> [info] at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:890)
> [info] at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:890)
> [info] at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
> [info] at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:365)
> [info] at org.apache.spark.rdd.RDD.iterator(RDD.scala:329)
> [info] at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
> [info] at org.apache.spark.scheduler.Task.run(Task.scala:136)
> [info] at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:548)
> [info] at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1504)
> [info] at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:551)
> [info] at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
> [info] at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
> [info] at java.lang.Thread.run(Thread.java:748) {code}
> I believe the issue to stem from [PartitioningUtils::castPartValueToDesiredType|https://github.com/apache/spark/blob/master/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/PartitioningUtils.scala#L533] returning an Integer for ByteType and ShortType (which then fails to unbox to the expected type):
>
> {code:java}
> case ByteType | ShortType | IntegerType => Integer.parseInt(value) {code}
>
> The issue appears to have been introduced in [this commit|https://github.com/apache/spark/commit/fc29c91f27d866502f5b6cc4261d4943b5cccc7e] so likely affects Spark 3.2 as well, though I've only tested on 3.3.0.
>
>
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