[jira] [Commented] (SPARK-40212) SparkSQL castPartValue does not properly handle byte & short

2022-08-25 Thread Brennan Stein (Jira)


[ 
https://issues.apache.org/jira/browse/SPARK-40212?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17584884#comment-17584884
 ] 

Brennan Stein commented on SPARK-40212:
---

Is a PR with unit test adequate reproduction? :) Realized it was actually a 
very simple fix

[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
>Priority: Major
>
> 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/fc29c91f27d866502f5b6cc4261d4943b57e]
>  so likely affects Spark 3.2 as well, though I've only tested on 3.3.0.
>  
>  



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[jira] [Created] (SPARK-40212) SparkSQL castPartValue does not properly handle byte & short

2022-08-24 Thread Brennan Stein (Jira)
Brennan Stein created SPARK-40212:
-

 Summary: 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


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/fc29c91f27d866502f5b6cc4261d4943b57e]
 so likely affects Spark 3.2 as well, though I've only tested on 3.3.0.

 

 



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