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[BUG] When+sequence could trigger "Illegal sequence boundaries" error #5023

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viadea opened this issue Mar 23, 2022 · 2 comments · Fixed by #5042
Closed

[BUG] When+sequence could trigger "Illegal sequence boundaries" error #5023

viadea opened this issue Mar 23, 2022 · 2 comments · Fixed by #5042
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@andygrove
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bug Something isn't working P0 Must have for release
Milestone
Mar 21 - Apr 1

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@viadea
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viadea commented Mar 23, 2022 •
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Below is a minimum repro in pyspark:

Env:
22.02GA jars
or
22.04Snapshot jars(20220322)

Reproduced on Databricks 9.1ML GPU and also local workstation.

Repro

data = [
 ("James,,Smith",["Java","Scala","C++"],["Spark","Java"],"OH","CA"),
 ("Michael,Rose,",["Spark"],["Spark","Java"],"NY","NJ"),
 ("Robert,,Williams",["CSharp","VB"],[],"UT","NV")
]

from pyspark.sql.types import StringType, ArrayType,StructType,StructField
schema = StructType([ 
    StructField("name",StringType(),True), 
    StructField("languagesAtSchool",ArrayType(StringType()),True), 
    StructField("languagesAtWork",ArrayType(StringType()),True), 
    StructField("currentState", StringType(), True), 
    StructField("previousState", StringType(), True)
  ])

df = spark.createDataFrame(data=data,schema=schema)
df.write.format("parquet").mode("overwrite").save("/tmp/testparquet")
df2 = spark.read.parquet("/tmp/testparquet")
df2.show()

spark.conf.set("spark.rapids.sql.enabled",True)
df2.withColumn("new_column", when (  (size(col("languagesAtWork")) > 0 ) , sequence(lit(1), size(col("languagesAtWork")),lit(1))) ).show()

Error:

java.lang.IllegalArgumentException: requirement failed: Illegal sequence boundaries: step > 0 but start > stop

Full stacktrace:

Caused by: java.lang.IllegalArgumentException: requirement failed: Illegal sequence boundaries: step > 0 but start > stop
	at scala.Predef$.require(Predef.scala:281)
	at org.apache.spark.sql.rapids.GpuSequenceUtil$.$anonfun$checkSequenceInputs$5(collectionOperations.scala:558)
	at org.apache.spark.sql.rapids.GpuSequenceUtil$.$anonfun$checkSequenceInputs$5$adapted(collectionOperations.scala:557)
	at com.nvidia.spark.rapids.Arm.withResource(Arm.scala:28)
	at com.nvidia.spark.rapids.Arm.withResource$(Arm.scala:26)
	at org.apache.spark.sql.rapids.GpuSequenceUtil$.withResource(collectionOperations.scala:533)
	at org.apache.spark.sql.rapids.GpuSequenceUtil$.$anonfun$checkSequenceInputs$2(collectionOperations.scala:557)
	at org.apache.spark.sql.rapids.GpuSequenceUtil$.$anonfun$checkSequenceInputs$2$adapted(collectionOperations.scala:549)
	at com.nvidia.spark.rapids.Arm.withResource(Arm.scala:28)
	at com.nvidia.spark.rapids.Arm.withResource$(Arm.scala:26)
	at org.apache.spark.sql.rapids.GpuSequenceUtil$.withResource(collectionOperations.scala:533)
	at org.apache.spark.sql.rapids.GpuSequenceUtil$.$anonfun$checkSequenceInputs$1(collectionOperations.scala:549)
	at org.apache.spark.sql.rapids.GpuSequenceUtil$.$anonfun$checkSequenceInputs$1$adapted(collectionOperations.scala:541)
	at com.nvidia.spark.rapids.Arm.withResource(Arm.scala:28)
	at com.nvidia.spark.rapids.Arm.withResource$(Arm.scala:26)
	at org.apache.spark.sql.rapids.GpuSequenceUtil$.withResource(collectionOperations.scala:533)
	at org.apache.spark.sql.rapids.GpuSequenceUtil$.checkSequenceInputs(collectionOperations.scala:541)
	at org.apache.spark.sql.rapids.GpuSequenceUtil$.computeSequenceSizes(collectionOperations.scala:599)
	at org.apache.spark.sql.rapids.GpuSequence.$anonfun$columnarEval$7(collectionOperations.scala:681)
	at com.nvidia.spark.rapids.Arm.closeOnExcept(Arm.scala:87)
	at com.nvidia.spark.rapids.Arm.closeOnExcept$(Arm.scala:85)
	at org.apache.spark.sql.rapids.GpuSequence.closeOnExcept(collectionOperations.scala:653)
	at org.apache.spark.sql.rapids.GpuSequence.$anonfun$columnarEval$4(collectionOperations.scala:680)
	at com.nvidia.spark.rapids.Arm.withResource(Arm.scala:28)
	at com.nvidia.spark.rapids.Arm.withResource$(Arm.scala:26)
	at org.apache.spark.sql.rapids.GpuSequence.withResource(collectionOperations.scala:653)
	at org.apache.spark.sql.rapids.GpuSequence.$anonfun$columnarEval$3(collectionOperations.scala:676)
	at com.nvidia.spark.rapids.Arm.withResource(Arm.scala:37)
	at com.nvidia.spark.rapids.Arm.withResource$(Arm.scala:35)
	at org.apache.spark.sql.rapids.GpuSequence.withResource(collectionOperations.scala:653)
	at org.apache.spark.sql.rapids.GpuSequence.$anonfun$columnarEval$1(collectionOperations.scala:672)
	at com.nvidia.spark.rapids.Arm.withResource(Arm.scala:28)
	at com.nvidia.spark.rapids.Arm.withResource$(Arm.scala:26)
	at org.apache.spark.sql.rapids.GpuSequence.withResource(collectionOperations.scala:653)
	at org.apache.spark.sql.rapids.GpuSequence.columnarEval(collectionOperations.scala:671)
	at com.nvidia.spark.rapids.RapidsPluginImplicits$ReallyAGpuExpression.columnarEval(implicits.scala:34)
	at com.nvidia.spark.rapids.GpuConditionalExpression.$anonfun$computeIfElse$2(conditionalExpressions.scala:159)
	at com.nvidia.spark.rapids.Arm.withResource(Arm.scala:28)
	at com.nvidia.spark.rapids.Arm.withResource$(Arm.scala:26)
	at com.nvidia.spark.rapids.GpuCaseWhen.withResource(conditionalExpressions.scala:309)
	at com.nvidia.spark.rapids.GpuConditionalExpression.$anonfun$computeIfElse$1(conditionalExpressions.scala:158)
	at com.nvidia.spark.rapids.Arm.withResourceIfAllowed(Arm.scala:73)
	at com.nvidia.spark.rapids.Arm.withResourceIfAllowed$(Arm.scala:71)
	at com.nvidia.spark.rapids.GpuCaseWhen.withResourceIfAllowed(conditionalExpressions.scala:309)
	at com.nvidia.spark.rapids.GpuConditionalExpression.computeIfElse(conditionalExpressions.scala:157)
	at com.nvidia.spark.rapids.GpuConditionalExpression.computeIfElse$(conditionalExpressions.scala:152)
	at com.nvidia.spark.rapids.GpuCaseWhen.computeIfElse(conditionalExpressions.scala:309)
	at com.nvidia.spark.rapids.GpuCaseWhen.$anonfun$columnarEval$6(conditionalExpressions.scala:362)
	at scala.collection.IndexedSeqOptimized.foldRight(IndexedSeqOptimized.scala:65)
	at scala.collection.IndexedSeqOptimized.foldRight$(IndexedSeqOptimized.scala:72)
	at scala.collection.mutable.ArrayBuffer.foldRight(ArrayBuffer.scala:49)
	at com.nvidia.spark.rapids.GpuCaseWhen.columnarEval(conditionalExpressions.scala:360)
	at com.nvidia.spark.rapids.RapidsPluginImplicits$ReallyAGpuExpression.columnarEval(implicits.scala:34)
	at com.nvidia.spark.rapids.GpuExpressionsUtils$.columnarEvalToColumn(GpuExpressions.scala:93)
	at com.nvidia.spark.rapids.GpuUnaryExpression.columnarEval(GpuExpressions.scala:202)
	at com.nvidia.spark.rapids.RapidsPluginImplicits$ReallyAGpuExpression.columnarEval(implicits.scala:34)
	at com.nvidia.spark.rapids.GpuAlias.columnarEval(namedExpressions.scala:109)
	at com.nvidia.spark.rapids.RapidsPluginImplicits$ReallyAGpuExpression.columnarEval(implicits.scala:34)
	at com.nvidia.spark.rapids.GpuExpressionsUtils$.columnarEvalToColumn(GpuExpressions.scala:93)
	at com.nvidia.spark.rapids.GpuProjectExec$.projectSingle(basicPhysicalOperators.scala:102)
	at com.nvidia.spark.rapids.GpuProjectExec$.$anonfun$project$1(basicPhysicalOperators.scala:109)
	at com.nvidia.spark.rapids.RapidsPluginImplicits$MapsSafely.$anonfun$safeMap$1(implicits.scala:162)
	at com.nvidia.spark.rapids.RapidsPluginImplicits$MapsSafely.$anonfun$safeMap$1$adapted(implicits.scala:159)
	at scala.collection.immutable.List.foreach(List.scala:392)
	at com.nvidia.spark.rapids.RapidsPluginImplicits$MapsSafely.safeMap(implicits.scala:159)
	at com.nvidia.spark.rapids.RapidsPluginImplicits$AutoCloseableProducingSeq.safeMap(implicits.scala:194)
	at com.nvidia.spark.rapids.GpuProjectExec$.project(basicPhysicalOperators.scala:109)
	at com.nvidia.spark.rapids.GpuProjectExec$.projectAndClose(basicPhysicalOperators.scala:73)
	at com.nvidia.spark.rapids.GpuProjectExec.$anonfun$doExecuteColumnar$1(basicPhysicalOperators.scala:149)
	at scala.collection.Iterator$$anon$10.next(Iterator.scala:459)
	at com.nvidia.spark.rapids.GpuBaseLimitExec$$anon$1.next(limit.scala:71)
	at com.nvidia.spark.rapids.GpuBaseLimitExec$$anon$1.next(limit.scala:65)
	at org.apache.spark.sql.rapids.execution.GpuShuffleExchangeExecBase$$anon$1.partNextBatch(GpuShuffleExchangeExecBase.scala:288)
	at org.apache.spark.sql.rapids.execution.GpuShuffleExchangeExecBase$$anon$1.hasNext(GpuShuffleExchangeExecBase.scala:304)
	at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:132)
	at org.apache.spark.shuffle.ShuffleWriteProcessor.write(ShuffleWriteProcessor.scala:59)
	at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99)
	at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:52)
	at org.apache.spark.scheduler.Task.run(Task.scala:131)
	at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:497)
	at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439)
	at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:500)
	at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
	at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
	... 1 more

CPU Spark works fine.

Basically the column "languagesAtWork" has some empty array value, seems even if "when clause" is FALSE, we are evaluating the expression(which contains sequence).
@viadea viadea added bug Something isn't working ? - Needs Triage Need team to review and classify labels Mar 23, 2022
@viadea
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viadea commented Mar 23, 2022

The input dataframe is :

+----------------+------------------+---------------+------------+-------------+
|            name| languagesAtSchool|languagesAtWork|currentState|previousState|
+----------------+------------------+---------------+------------+-------------+
|    James,,Smith|[Java, Scala, C++]|  [Spark, Java]|          OH|           CA|
|   Michael,Rose,|           [Spark]|  [Spark, Java]|          NY|           NJ|
|Robert,,Williams|      [CSharp, VB]|             []|          UT|           NV|
+----------------+------------------+---------------+------------+-------------+

And the expected output is:

+----------------+------------------+---------------+------------+-------------+----------+
|            name| languagesAtSchool|languagesAtWork|currentState|previousState|new_column|
+----------------+------------------+---------------+------------+-------------+----------+
|    James,,Smith|[Java, Scala, C++]|  [Spark, Java]|          OH|           CA|    [1, 2]|
|   Michael,Rose,|           [Spark]|  [Spark, Java]|          NY|           NJ|    [1, 2]|
|Robert,,Williams|      [CSharp, VB]|             []|          UT|           NV|      null|
+----------------+------------------+---------------+------------+-------------+----------+

@viadea
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viadea commented Mar 23, 2022

Is it related to #3849 regarding case/when evaluation?

@sameerz sameerz added P0 Must have for release and removed ? - Needs Triage Need team to review and classify labels Mar 23, 2022
@sameerz sameerz added this to the Mar 21 - Apr 1 milestone Mar 23, 2022
This was referenced Mar 24, 2022
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Implement hasSideEffects for GpuSequence andygrove/spark-rapids
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@andygrove @sameerz @viadea