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[BUG] qa_nightly_select_test failure in test_select #2217

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jlowe opened this issue Apr 21, 2021 · 1 comment · Fixed by #2218
Closed

[BUG] qa_nightly_select_test failure in test_select #2217

jlowe opened this issue Apr 21, 2021 · 1 comment · Fixed by #2218
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@jlowe
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@jlowe
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jlowe commented Apr 21, 2021

The nightly dev job failed in qa_nightly_select_test with this error log, looks like a missing match case

07:37:00  =================================== FAILURES ===================================
07:37:00  _______________ test_select[REGEXP_REPLACE(strF, 'Yu', 'Eric')] ________________
07:37:00  
07:37:00  sql_query_line = ("SELECT REGEXP_REPLACE(strF, 'Yu', 'Eric') FROM test_table", "REGEXP_REPLACE(strF, 'Yu', 'Eric')")
07:37:00  pytestconfig = <_pytest.config.Config object at 0x7f97c65924f0>
07:37:00  
07:37:00      @approximate_float
07:37:00      @incompat
07:37:00      @qarun
07:37:00      @pytest.mark.parametrize('sql_query_line', SELECT_SQL, ids=idfn)
07:37:00      def test_select(sql_query_line, pytestconfig):
07:37:00          sql_query = sql_query_line[0]
07:37:00          if sql_query:
07:37:00              print(sql_query)
07:37:00              with_cpu_session(num_stringDf)
07:37:00  >           assert_gpu_and_cpu_are_equal_collect(lambda spark: spark.sql(sql_query), conf=_qa_conf)
07:37:00  
07:37:00  src/main/python/qa_nightly_select_test.py:167: 
07:37:00  _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
07:37:00  src/main/python/asserts.py:360: in assert_gpu_and_cpu_are_equal_collect
07:37:00      _assert_gpu_and_cpu_are_equal(func, 'COLLECT', conf=conf, is_cpu_first=is_cpu_first)
07:37:00  src/main/python/asserts.py:341: in _assert_gpu_and_cpu_are_equal
07:37:00      run_on_gpu()
07:37:00  src/main/python/asserts.py:334: in run_on_gpu
07:37:00      from_gpu = with_gpu_session(bring_back,
07:37:00  src/main/python/spark_session.py:95: in with_gpu_session
07:37:00      return with_spark_session(func, conf=copy)
07:37:00  src/main/python/spark_session.py:68: in with_spark_session
07:37:00      ret = func(_spark)
07:37:00  src/main/python/asserts.py:179: in <lambda>
07:37:00      bring_back = lambda spark: limit_func(spark).collect()
07:37:00  /home/jenkins/agent/workspace/rapids_integration-dev-github-311/jars/spark-3.1.1-bin-hadoop3.2/python/lib/pyspark.zip/pyspark/sql/dataframe.py:677: in collect
07:37:00      sock_info = self._jdf.collectToPython()
07:37:00  /home/jenkins/agent/workspace/rapids_integration-dev-github-311/jars/spark-3.1.1-bin-hadoop3.2/python/lib/py4j-0.10.9-src.zip/py4j/java_gateway.py:1304: in __call__
07:37:00      return_value = get_return_value(
07:37:00  /home/jenkins/agent/workspace/rapids_integration-dev-github-311/jars/spark-3.1.1-bin-hadoop3.2/python/lib/pyspark.zip/pyspark/sql/utils.py:111: in deco
07:37:00      return f(*a, **kw)
07:37:00  _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
07:37:00  
07:37:00  answer = 'xro675276'
07:37:00  gateway_client = <py4j.java_gateway.GatewayClient object at 0x7f97c5baa790>
07:37:00  target_id = 'o675275', name = 'collectToPython'
07:37:00  
07:37:00      def get_return_value(answer, gateway_client, target_id=None, name=None):
07:37:00          """Converts an answer received from the Java gateway into a Python object.
07:37:00      
07:37:00          For example, string representation of integers are converted to Python
07:37:00          integer, string representation of objects are converted to JavaObject
07:37:00          instances, etc.
07:37:00      
07:37:00          :param answer: the string returned by the Java gateway
07:37:00          :param gateway_client: the gateway client used to communicate with the Java
07:37:00              Gateway. Only necessary if the answer is a reference (e.g., object,
07:37:00              list, map)
07:37:00          :param target_id: the name of the object from which the answer comes from
07:37:00              (e.g., *object1* in `object1.hello()`). Optional.
07:37:00          :param name: the name of the member from which the answer comes from
07:37:00              (e.g., *hello* in `object1.hello()`). Optional.
07:37:00          """
07:37:00          if is_error(answer)[0]:
07:37:00              if len(answer) > 1:
07:37:00                  type = answer[1]
07:37:00                  value = OUTPUT_CONVERTER[type](answer[2:], gateway_client)
07:37:00                  if answer[1] == REFERENCE_TYPE:
07:37:00  >                   raise Py4JJavaError(
07:37:00                          "An error occurred while calling {0}{1}{2}.\n".
07:37:00                          format(target_id, ".", name), value)
07:37:00  E                   py4j.protocol.Py4JJavaError: An error occurred while calling o675275.collectToPython.
07:37:00  E                   : scala.MatchError: List(strF#496130, Yu, Eric, 1) (of class scala.collection.immutable.$colon$colon)
07:37:00  E                   	at com.nvidia.spark.rapids.shims.spark311.Spark311Shims$$anon$4.convertToGpu(Spark311Shims.scala:194)
07:37:00  E                   	at com.nvidia.spark.rapids.shims.spark311.Spark311Shims$$anon$4.convertToGpu(Spark311Shims.scala:180)
07:37:00  E                   	at com.nvidia.spark.rapids.UnaryExprMeta.convertToGpu(RapidsMeta.scala:805)
07:37:00  E                   	at com.nvidia.spark.rapids.UnaryExprMeta.convertToGpu(RapidsMeta.scala:797)
07:37:00  E                   	at com.nvidia.spark.rapids.GpuOverrides$$anon$152.$anonfun$convertToGpu$19(GpuOverrides.scala:2686)
07:37:00  E                   	at scala.collection.immutable.Stream.map(Stream.scala:418)
07:37:00  E                   	at com.nvidia.spark.rapids.GpuOverrides$$anon$152.convertToGpu(GpuOverrides.scala:2686)
07:37:00  E                   	at com.nvidia.spark.rapids.GpuOverrides$$anon$152.convertToGpu(GpuOverrides.scala:2683)
07:37:00  E                   	at com.nvidia.spark.rapids.SparkPlanMeta.convertIfNeeded(RapidsMeta.scala:642)
07:37:00  E                   	at com.nvidia.spark.rapids.GpuOverrides.applyOverrides(GpuOverrides.scala:3050)
07:37:00  E                   	at com.nvidia.spark.rapids.GpuOverrides.apply(GpuOverrides.scala:3012)
07:37:00  E                   	at com.nvidia.spark.rapids.GpuOverrides.apply(GpuOverrides.scala:2998)
07:37:00  E                   	at org.apache.spark.sql.execution.ApplyColumnarRulesAndInsertTransitions.$anonfun$apply$1(Columnar.scala:532)
07:37:00  E                   	at org.apache.spark.sql.execution.ApplyColumnarRulesAndInsertTransitions.$anonfun$apply$1$adapted(Columnar.scala:531)
07:37:00  E                   	at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
07:37:00  E                   	at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)
07:37:00  E                   	at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)
07:37:00  E                   	at org.apache.spark.sql.execution.ApplyColumnarRulesAndInsertTransitions.apply(Columnar.scala:531)
07:37:00  E                   	at org.apache.spark.sql.execution.ApplyColumnarRulesAndInsertTransitions.apply(Columnar.scala:495)
07:37:00  E                   	at org.apache.spark.sql.execution.QueryExecution$.$anonfun$prepareForExecution$1(QueryExecution.scala:372)
07:37:00  E                   	at scala.collection.LinearSeqOptimized.foldLeft(LinearSeqOptimized.scala:126)
07:37:00  E                   	at scala.collection.LinearSeqOptimized.foldLeft$(LinearSeqOptimized.scala:122)
07:37:00  E                   	at scala.collection.immutable.List.foldLeft(List.scala:89)
07:37:00  E                   	at org.apache.spark.sql.execution.QueryExecution$.prepareForExecution(QueryExecution.scala:371)
07:37:00  E                   	at org.apache.spark.sql.execution.QueryExecution.$anonfun$executedPlan$1(QueryExecution.scala:117)
07:37:00  E                   	at org.apache.spark.sql.catalyst.QueryPlanningTracker.measurePhase(QueryPlanningTracker.scala:111)
07:37:00  E                   	at org.apache.spark.sql.execution.QueryExecution.$anonfun$executePhase$1(QueryExecution.scala:143)
07:37:00  E                   	at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:772)
07:37:00  E                   	at org.apache.spark.sql.execution.QueryExecution.executePhase(QueryExecution.scala:143)
07:37:00  E                   	at org.apache.spark.sql.execution.QueryExecution.executedPlan$lzycompute(QueryExecution.scala:117)
07:37:00  E                   	at org.apache.spark.sql.execution.QueryExecution.executedPlan(QueryExecution.scala:110)
07:37:00  E                   	at org.apache.spark.sql.execution.QueryExecution.$anonfun$simpleString$2(QueryExecution.scala:161)
07:37:00  E                   	at org.apache.spark.sql.execution.ExplainUtils$.processPlan(ExplainUtils.scala:115)
07:37:00  E                   	at org.apache.spark.sql.execution.QueryExecution.simpleString(QueryExecution.scala:161)
07:37:00  E                   	at org.apache.spark.sql.execution.QueryExecution.org$apache$spark$sql$execution$QueryExecution$$explainString(QueryExecution.scala:206)
07:37:00  E                   	at org.apache.spark.sql.execution.QueryExecution.explainString(QueryExecution.scala:175)
07:37:00  E                   	at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$5(SQLExecution.scala:98)
07:37:00  E                   	at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:163)
07:37:00  E                   	at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:90)
07:37:00  E                   	at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:772)
07:37:00  E                   	at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:64)
07:37:00  E                   	at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3685)
07:37:00  E                   	at org.apache.spark.sql.Dataset.collectToPython(Dataset.scala:3516)
07:37:00  E                   	at sun.reflect.GeneratedMethodAccessor73.invoke(Unknown Source)
07:37:00  E                   	at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
07:37:00  E                   	at java.lang.reflect.Method.invoke(Method.java:498)
07:37:00  E                   	at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
07:37:00  E                   	at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
07:37:00  E                   	at py4j.Gateway.invoke(Gateway.java:282)
07:37:00  E                   	at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
07:37:00  E                   	at py4j.commands.CallCommand.execute(CallCommand.java:79)
07:37:00  E                   	at py4j.GatewayConnection.run(GatewayConnection.java:238)
07:37:00  E                   	at java.lang.Thread.run(Thread.java:748)
07:37:00  
07:37:00  /home/jenkins/agent/workspace/rapids_integration-dev-github-311/jars/spark-3.1.1-bin-hadoop3.2/python/lib/py4j-0.10.9-src.zip/py4j/protocol.py:326: Py4JJavaError
07:37:00  ----------------------------- Captured stdout call -----------------------------
07:37:00  SELECT REGEXP_REPLACE(strF, 'Yu', 'Eric') FROM test_table
07:37:00  ### CREATE DATAFRAME 1  ####
07:37:00  1990-01-01
07:37:00  ### CPU RUN ###
07:37:00  ### GPU RUN ###
07:37:00  _______________________________ test_re_replace ________________________________
07:37:00  
07:37:00      def test_re_replace():
07:37:00          gen = mk_str_gen('.{0,5}TEST[\ud720 A]{0,5}')
07:37:00  >       assert_gpu_and_cpu_are_equal_collect(
07:37:00                  lambda spark: unary_op_df(spark, gen).selectExpr(
07:37:00                      'REGEXP_REPLACE(a, "TEST", "PROD")',
07:37:00                      'REGEXP_REPLACE(a, "TEST", "")',
07:37:00                      'REGEXP_REPLACE(a, "TEST", "%^[]\ud720")',
07:37:00                      'REGEXP_REPLACE(a, "TEST", NULL)'))
07:37:00  
07:37:00  src/main/python/string_test.py:190: 
07:37:00  _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
07:37:00  src/main/python/asserts.py:360: in assert_gpu_and_cpu_are_equal_collect
07:37:00      _assert_gpu_and_cpu_are_equal(func, 'COLLECT', conf=conf, is_cpu_first=is_cpu_first)
07:37:00  src/main/python/asserts.py:341: in _assert_gpu_and_cpu_are_equal
07:37:00      run_on_gpu()
07:37:00  src/main/python/asserts.py:334: in run_on_gpu
07:37:00      from_gpu = with_gpu_session(bring_back,
07:37:00  src/main/python/spark_session.py:95: in with_gpu_session
07:37:00      return with_spark_session(func, conf=copy)
07:37:00  src/main/python/spark_session.py:68: in with_spark_session
07:37:00      ret = func(_spark)
07:37:00  src/main/python/asserts.py:179: in <lambda>
07:37:00      bring_back = lambda spark: limit_func(spark).collect()
07:37:00  /home/jenkins/agent/workspace/rapids_integration-dev-github-311/jars/spark-3.1.1-bin-hadoop3.2/python/lib/pyspark.zip/pyspark/sql/dataframe.py:677: in collect
07:37:00      sock_info = self._jdf.collectToPython()
07:37:00  /home/jenkins/agent/workspace/rapids_integration-dev-github-311/jars/spark-3.1.1-bin-hadoop3.2/python/lib/py4j-0.10.9-src.zip/py4j/java_gateway.py:1304: in __call__
07:37:00      return_value = get_return_value(
07:37:00  /home/jenkins/agent/workspace/rapids_integration-dev-github-311/jars/spark-3.1.1-bin-hadoop3.2/python/lib/pyspark.zip/pyspark/sql/utils.py:111: in deco
07:37:00      return f(*a, **kw)
07:37:00  _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
07:37:00  
07:37:00  answer = 'xro841966'
07:37:00  gateway_client = <py4j.java_gateway.GatewayClient object at 0x7f97c5baa790>
07:37:00  target_id = 'o841965', name = 'collectToPython'
07:37:00  
07:37:00      def get_return_value(answer, gateway_client, target_id=None, name=None):
07:37:00          """Converts an answer received from the Java gateway into a Python object.
07:37:00      
07:37:00          For example, string representation of integers are converted to Python
07:37:00          integer, string representation of objects are converted to JavaObject
07:37:00          instances, etc.
07:37:00      
07:37:00          :param answer: the string returned by the Java gateway
07:37:00          :param gateway_client: the gateway client used to communicate with the Java
07:37:00              Gateway. Only necessary if the answer is a reference (e.g., object,
07:37:00              list, map)
07:37:00          :param target_id: the name of the object from which the answer comes from
07:37:00              (e.g., *object1* in `object1.hello()`). Optional.
07:37:00          :param name: the name of the member from which the answer comes from
07:37:00              (e.g., *hello* in `object1.hello()`). Optional.
07:37:00          """
07:37:00          if is_error(answer)[0]:
07:37:00              if len(answer) > 1:
07:37:00                  type = answer[1]
07:37:00                  value = OUTPUT_CONVERTER[type](answer[2:], gateway_client)
07:37:00                  if answer[1] == REFERENCE_TYPE:
07:37:00  >                   raise Py4JJavaError(
07:37:00                          "An error occurred while calling {0}{1}{2}.\n".
07:37:00                          format(target_id, ".", name), value)
07:37:00  E                   py4j.protocol.Py4JJavaError: An error occurred while calling o841965.collectToPython.
07:37:00  E                   : scala.MatchError: List(a#533521, TEST, PROD, 1) (of class scala.collection.immutable.$colon$colon)
07:37:00  E                   	at com.nvidia.spark.rapids.shims.spark311.Spark311Shims$$anon$4.convertToGpu(Spark311Shims.scala:194)
07:37:00  E                   	at com.nvidia.spark.rapids.shims.spark311.Spark311Shims$$anon$4.convertToGpu(Spark311Shims.scala:180)
07:37:00  E                   	at com.nvidia.spark.rapids.UnaryExprMeta.convertToGpu(RapidsMeta.scala:805)
07:37:00  E                   	at com.nvidia.spark.rapids.UnaryExprMeta.convertToGpu(RapidsMeta.scala:797)
07:37:00  E                   	at com.nvidia.spark.rapids.GpuOverrides$$anon$152.$anonfun$convertToGpu$19(GpuOverrides.scala:2686)
07:37:00  E                   	at scala.collection.immutable.Stream.map(Stream.scala:418)
07:37:00  E                   	at com.nvidia.spark.rapids.GpuOverrides$$anon$152.convertToGpu(GpuOverrides.scala:2686)
07:37:00  E                   	at com.nvidia.spark.rapids.GpuOverrides$$anon$152.convertToGpu(GpuOverrides.scala:2683)
07:37:00  E                   	at com.nvidia.spark.rapids.SparkPlanMeta.convertIfNeeded(RapidsMeta.scala:642)
07:37:00  E                   	at com.nvidia.spark.rapids.GpuOverrides.applyOverrides(GpuOverrides.scala:3050)
07:37:00  E                   	at com.nvidia.spark.rapids.GpuOverrides.apply(GpuOverrides.scala:3012)
07:37:00  E                   	at com.nvidia.spark.rapids.GpuOverrides.apply(GpuOverrides.scala:2998)
07:37:00  E                   	at org.apache.spark.sql.execution.ApplyColumnarRulesAndInsertTransitions.$anonfun$apply$1(Columnar.scala:532)
07:37:00  E                   	at org.apache.spark.sql.execution.ApplyColumnarRulesAndInsertTransitions.$anonfun$apply$1$adapted(Columnar.scala:531)
07:37:00  E                   	at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
07:37:00  E                   	at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)
07:37:00  E                   	at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)
07:37:00  E                   	at org.apache.spark.sql.execution.ApplyColumnarRulesAndInsertTransitions.apply(Columnar.scala:531)
07:37:00  E                   	at org.apache.spark.sql.execution.ApplyColumnarRulesAndInsertTransitions.apply(Columnar.scala:495)
07:37:00  E                   	at org.apache.spark.sql.execution.QueryExecution$.$anonfun$prepareForExecution$1(QueryExecution.scala:372)
07:37:00  E                   	at scala.collection.LinearSeqOptimized.foldLeft(LinearSeqOptimized.scala:126)
07:37:00  E                   	at scala.collection.LinearSeqOptimized.foldLeft$(LinearSeqOptimized.scala:122)
07:37:00  E                   	at scala.collection.immutable.List.foldLeft(List.scala:89)
07:37:00  E                   	at org.apache.spark.sql.execution.QueryExecution$.prepareForExecution(QueryExecution.scala:371)
07:37:00  E                   	at org.apache.spark.sql.execution.QueryExecution.$anonfun$executedPlan$1(QueryExecution.scala:117)
07:37:00  E                   	at org.apache.spark.sql.catalyst.QueryPlanningTracker.measurePhase(QueryPlanningTracker.scala:111)
07:37:00  E                   	at org.apache.spark.sql.execution.QueryExecution.$anonfun$executePhase$1(QueryExecution.scala:143)
07:37:00  E                   	at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:772)
07:37:00  E                   	at org.apache.spark.sql.execution.QueryExecution.executePhase(QueryExecution.scala:143)
07:37:00  E                   	at org.apache.spark.sql.execution.QueryExecution.executedPlan$lzycompute(QueryExecution.scala:117)
07:37:00  E                   	at org.apache.spark.sql.execution.QueryExecution.executedPlan(QueryExecution.scala:110)
07:37:00  E                   	at org.apache.spark.sql.execution.QueryExecution.$anonfun$simpleString$2(QueryExecution.scala:161)
07:37:00  E                   	at org.apache.spark.sql.execution.ExplainUtils$.processPlan(ExplainUtils.scala:115)
07:37:00  E                   	at org.apache.spark.sql.execution.QueryExecution.simpleString(QueryExecution.scala:161)
07:37:00  E                   	at org.apache.spark.sql.execution.QueryExecution.org$apache$spark$sql$execution$QueryExecution$$explainString(QueryExecution.scala:206)
07:37:00  E                   	at org.apache.spark.sql.execution.QueryExecution.explainString(QueryExecution.scala:175)
07:37:00  E                   	at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$5(SQLExecution.scala:98)
07:37:00  E                   	at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:163)
07:37:00  E                   	at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:90)
07:37:00  E                   	at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:772)
07:37:00  E                   	at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:64)
07:37:00  E                   	at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3685)
07:37:00  E                   	at org.apache.spark.sql.Dataset.collectToPython(Dataset.scala:3516)
07:37:00  E                   	at sun.reflect.GeneratedMethodAccessor73.invoke(Unknown Source)
07:37:00  E                   	at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
07:37:00  E                   	at java.lang.reflect.Method.invoke(Method.java:498)
07:37:00  E                   	at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
07:37:00  E                   	at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
07:37:00  E                   	at py4j.Gateway.invoke(Gateway.java:282)
07:37:00  E                   	at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
07:37:00  E                   	at py4j.commands.CallCommand.execute(CallCommand.java:79)
07:37:00  E                   	at py4j.GatewayConnection.run(GatewayConnection.java:238)
07:37:00  E                   	at java.lang.Thread.run(Thread.java:748)
07:37:00  
07:37:00  /home/jenkins/agent/workspace/rapids_integration-dev-github-311/jars/spark-3.1.1-bin-hadoop3.2/python/lib/py4j-0.10.9-src.zip/py4j/protocol.py:326: Py4JJavaError
07:37:00  ----------------------------- Captured stdout call -----------------------------
07:37:00  ### CPU RUN ###
07:37:00  ### GPU RUN ###
@jlowe jlowe added bug Something isn't working ? - Needs Triage Need team to review and classify labels Apr 21, 2021
@jlowe jlowe self-assigned this Apr 21, 2021
@jlowe jlowe removed the ? - Needs Triage Need team to review and classify label Apr 21, 2021
@jlowe jlowe mentioned this issue Apr 21, 2021
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jlowe commented Apr 21, 2021

This was triggered by #2192. RegExpReplace has four child expressions in Spark 3.1+, so unpacking 4 children into a 3-sequence crashes.

This was referenced Apr 22, 2021
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Fix incorrect RegExpReplace children handling on Spark 3.1+ jlowe/spark-rapids
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