[BUG] udf-examples-native case failed core dump

[pxLi]

Describe the bug
first seen in examples-udf-examples-native run:179
https://github.com/NVIDIA/spark-rapids-examples/tree/branch-24.12/examples/UDF-Examples/RAPIDS-accelerated-UDFs

17:42:00  24/12/09 09:42:00 INFO RapidsPluginUtils: RAPIDS Accelerator build: Map(url -> https://github.com/NVIDIA/spark-rapids.git, branch -> HEAD, 
revision -> fb2f72df881582855393135d6e574111716ec7bb, version -> 24.12.0-SNAPSHOT, date -> 2024-12-08T10:18:05Z, cudf_version -> 24.12.0-SNAPSHOT, user -> root)
17:42:00  24/12/09 09:42:00 INFO RapidsPluginUtils: RAPIDS Accelerator JNI build: Map(url -> https://github.com/NVIDIA/spark-rapids-jni.git, branch -> HEAD, gpu_architectures -> 70;75;80;86;90, 
revision -> 7842da04bd6486f2389c441f0e1aa094c5eef469, version -> 24.12.0-SNAPSHOT, date -> 2024-12-08T05:18:03Z, user -> root)
17:42:00  24/12/09 09:42:00 INFO RapidsPluginUtils: cudf build: Map(url -> https://github.com/rapidsai/cudf.git, branch -> HEAD, gpu_architectures -> 70;75;80;86;90, 
revision -> 439321edb43082fb75f195b6be2049c925279089, version -> 24.12.0-SNAPSHOT, date -> 2024-12-08T05:17:59Z, user -> root)
17:42:00  24/12/09 09:42:00 INFO RapidsPluginUtils: RAPIDS Accelerator Private Map(url -> https://gitlab-master.nvidia.com/nvspark/spark-rapids-private.git, branch -> HEAD, 
revision -> 2f08e20170b66621d1f14ee0fb351ef5630ea811, version -> 24.12.0-SNAPSHOT, date -> 2024-12-08T03:33:41Z, user -> root)
...
...
...
17:42:11  ============================= test session starts ==============================
17:42:11  platform linux -- Python 3.10.16, pytest-7.4.4, pluggy-1.5.0 -- /opt/conda/bin/python3
17:42:11  cachedir: .pytest_cache
17:42:11  rootdir: /home/jenkins/agent/workspace/jenkins-examples-udf-examples-native-179/examples/UDF-Examples/RAPIDS-accelerated-UDFs
17:42:11  configfile: pytest.ini
17:42:11  plugins: order-1.3.0, xdist-3.6.1
17:42:11  collecting ... collected 8 items
17:42:11  
17:42:16  src/main/python/rapids_udf_test.py::test_hive_simple_udf 24/12/09 09:42:16 WARN GpuOverrides: 
17:42:16    ! <RDDScanExec> cannot run on GPU because GPU does not currently support the operator class org.apache.spark.sql.execution.RDDScanExec
17:42:16      @Expression <AttributeReference> i#7 could run on GPU
17:42:16      @Expression <AttributeReference> s#8 could run on GPU
17:42:16  
17:42:17  PASSED          [ 12%]
17:42:17  src/main/python/rapids_udf_test.py::test_hive_generic_udf 24/12/09 09:42:17 WARN GpuOverrides: 
17:42:17    ! <RDDScanExec> cannot run on GPU because GPU does not currently support the operator class org.apache.spark.sql.execution.RDDScanExec
17:42:17      @Expression <AttributeReference> s#18 could run on GPU
17:42:17  
17:42:18  24/12/09 09:42:17 WARN GpuOverrides: 
17:42:18    ! <RDDScanExec> cannot run on GPU because GPU does not currently support the operator class org.apache.spark.sql.execution.RDDScanExec
17:42:18      @Expression <AttributeReference> dec#26 could run on GPU
17:42:18  
17:42:18  PASSED         [ 25%]
17:42:18  src/main/python/rapids_udf_test.py::test_hive_simple_udf_native 24/12/09 09:42:18 WARN GpuOverrides: 
17:42:18    ! <RDDScanExec> cannot run on GPU because GPU does not currently support the operator class org.apache.spark.sql.execution.RDDScanExec
17:42:18      @Expression <AttributeReference> s#34 could run on GPU
17:42:18  
17:42:18  #
17:42:18  # A fatal error has been detected by the Java Runtime Environment:
17:42:18  #
17:42:18  #  SIGSEGV (0xb) at pc=0x00007f02da529598, pid=177, tid=0x00007f02c9bff700
17:42:18  #
17:42:18  # JRE version: OpenJDK Runtime Environment (8.0_432) (build 1.8.0_432-8u432-ga~us1-0ubuntu2~20.04-ga)
17:42:18  # Java VM: OpenJDK 64-Bit Server VM (25.432-bga mixed mode linux-amd64 compressed oops)
17:42:18  # Problematic frame:
17:42:18  # C  [libcuda.so.1+0x186598]

core dump: (complete file hs_err_pid177.log)

---------------  T H R E A D  ---------------

Current thread (0x00007f0244029000):  JavaThread "Executor task launch worker for task 0.0 in stage 7.0 (TID 7)" daemon [_thread_in_native, id=361, stack(0x00007f02c9aff000,0x00007f02c9c00000)]

siginfo: si_signo: 11 (SIGSEGV), si_code: 2 (SEGV_ACCERR), si_addr: 0x00007f01a73a3f10

Registers:
RAX=0x00007f01a73a3f40, RBX=0x0000000000000001, RCX=0x00007f02ca600100, RDX=0x0000000000000100
RSP=0x00007f02c9bfa8d8, RBP=0x00007f02c9bfa8e0, RSI=0x00007f02ca600040, RDI=0x00007f01a73a3f00
R8 =0x0000000000000100, R9 =0x0000000000000000, R10=0x0000000000000004, R11=0x0000000000000008
R12=0x0000000000000100, R13=0x00007f02ca600000, R14=0x00007f01a73a3f00, R15=0x0000000000000001
RIP=0x00007f02da529598, EFLAGS=0x0000000000010202, CSGSFS=0x002b000000000033, ERR=0x0000000000000007
  TRAPNO=0x000000000000000e

Top of Stack: (sp=0x00007f02c9bfa8d8)
0x00007f02c9bfa8d8:   0000000000000001 00007f02c9bfa970
0x00007f02c9bfa8e8:   00007f02da61ab5a 00007f02c9bfa940
0x00007f02c9bfa8f8:   00007f02c9bfb3a8 0000000000000100
0x00007f02c9bfa908:   0000000000000100 00007f01a73a3f00
0x00007f02c9bfa918:   00007f02ca600000 00007f02c9bfaee0
0x00007f02c9bfa928:   0000000000000000 0000000000000100
0x00007f02c9bfa938:   0000000000000100 00007f02c9bfa9a0
0x00007f02c9bfa948:   00007f0130d3a280 00007f02c9bfb3a8
0x00007f02c9bfa958:   0000000000000000 00007f02c9bfaee0
0x00007f02c9bfa968:   00007f02c9bfaee0 00007f02c9bfa9a0
0x00007f02c9bfa978:   00007f02da76483b 0000000000000000
0x00007f02c9bfa988:   00007f0130d3a280 00007f02c9bfb3a8
0x00007f02c9bfa998:   0000000000000002 00007f02c9bfb2c0
0x00007f02c9bfa9a8:   00007f02da765101 0000000000000001
0x00007f02c9bfa9b8:   00007f02c9bfaee0 0000000200000000
0x00007f02c9bfa9c8:   00007f02c9bfaa50 0000000000000001
0x00007f02c9bfa9d8:   0000000000000000 00007f0259059fc0
0x00007f02c9bfa9e8:   00007f02c9bfb3a8 00007f0130d3a4d8
0x00007f02c9bfa9f8:   0000000000000000 0000000000000001
0x00007f02c9bfaa08:   00007f02c9bfab20 0000000000000001
0x00007f02c9bfaa18:   0000000000000001 0000000000000001
0x00007f02c9bfaa28:   0000000000000100 0000000000000100
0x00007f02c9bfaa38:   00007f0259057b00 00007f0259057b00
0x00007f02c9bfaa48:   0000000000000000 0000000000000001
0x00007f02c9bfaa58:   0000000000000000 0000000000000000
0x00007f02c9bfaa68:   0000000000000000 00007f0259059160
0x00007f02c9bfaa78:   0000000000000000 0000000000000100
0x00007f02c9bfaa88:   0000000000000001 0000000000000000
0x00007f02c9bfaa98:   0000000000000000 0000000000000000
0x00007f02c9bfaaa8:   0000000000000000 0000000000000000
0x00007f02c9bfaab8:   0000000000000000 0000000000000000
0x00007f02c9bfaac8:   0000000000000000 0000000000000000 

Instructions: (pc=0x00007f02da529598)
0x00007f02da529578:   f8 48 8d 0c 16 0f 1f 00 0f 28 56 10 0f 28 4e 20
0x00007f02da529588:   48 83 c6 40 48 83 c0 40 0f 28 46 f0 0f 28 66 c0
0x00007f02da529598:   0f 2b 50 d0 0f 2b 60 c0 0f 2b 48 e0 0f 2b 40 f0
0x00007f02da5295a8:   48 39 ce 75 d3 48 01 fa 41 83 e0 3f 49 83 f8 0f 

Register to memory mapping:

RAX=0x00007f01a73a3f40: <offset 0x2a57af40> in /tmp/cudf760737925635621984.so at 0x00007f017ce29000
RBX=0x0000000000000001 is an unknown value
RCX=0x00007f02ca600100 is an unknown value
RDX=0x0000000000000100 is an unknown value
RSP=0x00007f02c9bfa8d8 is pointing into the stack for thread: 0x00007f0244029000
RBP=0x00007f02c9bfa8e0 is pointing into the stack for thread: 0x00007f0244029000
RSI=0x00007f02ca600040 is an unknown value
RDI=0x00007f01a73a3f00: <offset 0x2a57af00> in /tmp/cudf760737925635621984.so at 0x00007f017ce29000
R8 =0x0000000000000100 is an unknown value
R9 =0x0000000000000000 is an unknown value
R10=0x0000000000000004 is an unknown value
R11=0x0000000000000008 is an unknown value
R12=0x0000000000000100 is an unknown value
R13=0x00007f02ca600000 is an unknown value
R14=0x00007f01a73a3f00: <offset 0x2a57af00> in /tmp/cudf760737925635621984.so at 0x00007f017ce29000
R15=0x0000000000000001 is an unknown value


Stack: [0x00007f02c9aff000,0x00007f02c9c00000],  sp=0x00007f02c9bfa8d8,  free space=1006k
Native frames: (J=compiled Java code, j=interpreted, Vv=VM code, C=native code)
C  [libcuda.so.1+0x186598]
C  [libcuda.so.1+0x277b5a]
C  [libcuda.so.1+0x3c183b]
C  [libcuda.so.1+0x3c2101]
C  [libcuda.so.1+0x4faf9b]
C  [libcuda.so.1+0x13b116]
C  [libcuda.so.1+0x13b529]
C  [libcuda.so.1+0x13bdc7]
C  [libcuda.so.1+0x2dbca1]
C  [cudf760737925635621984.so+0x39eafc1]

Java frames: (J=compiled Java code, j=interpreted, Vv=VM code)
j  com.nvidia.spark.rapids.udf.hive.StringWordCount.countWords(J)J+0
j  com.nvidia.spark.rapids.udf.hive.StringWordCount.evaluateColumnar(I[Lai/rapids/cudf/ColumnVector;)Lai/rapids/cudf/ColumnVector;+141
j  com.nvidia.spark.rapids.GpuUserDefinedFunction.$anonfun$columnarEval$4(Lcom/nvidia/spark/rapids/GpuUserDefinedFunction;Lorg/apache/spark/sql/vectorized/ColumnarBatch;[Lai/rapids/cudf/ColumnVector;Lai/rapids/cudf/NvtxRange;)Lcom/nvidia/spark/rapids/GpuColumnVector;+11
j  com.nvidia.spark.rapids.GpuUserDefinedFunction$$Lambda$3508.apply(Ljava/lang/Object;)Ljava/lang/Object;+16
j  com.nvidia.spark.rapids.Arm$.withResource(Ljava/lang/AutoCloseable;Lscala/Function1;)Ljava/lang/Object;+2
j  com.nvidia.spark.rapids.GpuUserDefinedFunction.$anonfun$columnarEval$2(Lcom/nvidia/spark/rapids/GpuUserDefinedFunction;Lorg/apache/spark/sql/vectorized/ColumnarBatch;Lscala/collection/Seq;)Lcom/nvidia/spark/rapids/GpuColumnVector;+64
j  com.nvidia.spark.rapids.GpuUserDefinedFunction$$Lambda$3506.apply(Ljava/lang/Object;)Ljava/lang/Object;+12
j  com.nvidia.spark.rapids.Arm$.withResource(Lscala/collection/Seq;Lscala/Function1;)Ljava/lang/Object;+2
j  com.nvidia.spark.rapids.GpuUserDefinedFunction.columnarEval(Lorg/apache/spark/sql/vectorized/ColumnarBatch;)Lcom/nvidia/spark/rapids/GpuColumnVector;+34
j  com.nvidia.spark.rapids.GpuUserDefinedFunction.columnarEval$(Lcom/nvidia/spark/rapids/GpuUserDefinedFunction;Lorg/apache/spark/sql/vectorized/ColumnarBatch;)Lcom/nvidia/spark/rapids/GpuColumnVector;+2
j  org.apache.spark.sql.hive.rapids.GpuHiveSimpleUDF.columnarEval(Lorg/apache/spark/sql/vectorized/ColumnarBatch;)Lcom/nvidia/spark/rapids/GpuColumnVector;+2
j  com.nvidia.spark.rapids.RapidsPluginImplicits$ReallyAGpuExpression.columnarEval(Lorg/apache/spark/sql/vectorized/ColumnarBatch;)Lcom/nvidia/spark/rapids/GpuColumnVector;+8
j  com.nvidia.spark.rapids.GpuAlias.columnarEval(Lorg/apache/spark/sql/vectorized/ColumnarBatch;)Lcom/nvidia/spark/rapids/GpuColumnVector;+11
j  com.nvidia.spark.rapids.RapidsPluginImplicits$ReallyAGpuExpression.columnarEval(Lorg/apache/spark/sql/vectorized/ColumnarBatch;)Lcom/nvidia/spark/rapids/GpuColumnVector;+8
j  com.nvidia.spark.rapids.GpuProjectExec$.$anonfun$project$1(Lorg/apache/spark/sql/vectorized/ColumnarBatch;Lorg/apache/spark/sql/catalyst/expressions/Expression;)Lcom/nvidia/spark/rapids/GpuColumnVector;+8
j  com.nvidia.spark.rapids.GpuProjectExec$$$Lambda$3503.apply(Ljava/lang/Object;)Ljava/lang/Object;+8
j  com.nvidia.spark.rapids.RapidsPluginImplicits$MapsSafely.$anonfun$safeMap$1(Lscala/collection/mutable/Builder;Lscala/Function1;Ljava/lang/Object;)V+6
j  com.nvidia.spark.rapids.RapidsPluginImplicits$MapsSafely.$anonfun$safeMap$1$adapted(Lscala/collection/mutable/Builder;Lscala/Function1;Ljava/lang/Object;)Ljava/lang/Object;+3
j  com.nvidia.spark.rapids.RapidsPluginImplicits$MapsSafely$$Lambda$3504.apply(Ljava/lang/Object;)Ljava/lang/Object;+9
J 9093 C2 scala.collection.immutable.List.foreach(Lscala/Function1;)V (32 bytes) @ 0x00007f030276a274 [0x00007f030276a1c0+0xb4]
j  com.nvidia.spark.rapids.RapidsPluginImplicits$MapsSafely.safeMap(Lscala/collection/SeqLike;Lscala/Function1;Lscala/collection/generic/CanBuildFrom;)Ljava/lang/Object;+16
j  com.nvidia.spark.rapids.RapidsPluginImplicits$AutoCloseableProducingSeq.safeMap(Lscala/Function1;)Lscala/collection/Seq;+12
j  com.nvidia.spark.rapids.GpuProjectExec$.project(Lorg/apache/spark/sql/vectorized/ColumnarBatch;Lscala/collection/Seq;)Lorg/apache/spark/sql/vectorized/ColumnarBatch;+44
j  com.nvidia.spark.rapids.GpuTieredProject.$anonfun$project$2(Lorg/apache/spark/sql/vectorized/ColumnarBatch;Lscala/collection/Seq;Lai/rapids/cudf/NvtxRange;)Lorg/apache/spark/sql/vectorized/ColumnarBatch;+5
j  com.nvidia.spark.rapids.GpuTieredProject$$Lambda$3499.apply(Ljava/lang/Object;)Ljava/lang/Object;+12
j  com.nvidia.spark.rapids.Arm$.withResource(Ljava/lang/AutoCloseable;Lscala/Function1;)Ljava/lang/Object;+2
j  com.nvidia.spark.rapids.GpuTieredProject.recurse$2(Lscala/collection/Seq;Lorg/apache/spark/sql/vectorized/ColumnarBatch;Z)Lorg/apache/spark/sql/vectorized/ColumnarBatch;+79
j  com.nvidia.spark.rapids.GpuTieredProject.project(Lorg/apache/spark/sql/vectorized/ColumnarBatch;)Lorg/apache/spark/sql/vectorized/ColumnarBatch;+7
j  com.nvidia.spark.rapids.GpuTieredProject.$anonfun$projectWithRetrySingleBatchInternal$5(Lcom/nvidia/spark/rapids/GpuTieredProject;Lorg/apache/spark/sql/vectorized/ColumnarBatch;)Lorg/apache/spark/sql/vectorized/ColumnarBatch;+2
j  com.nvidia.spark.rapids.GpuTieredProject$$Lambda$3498.apply()Ljava/lang/Object;+8
j  com.nvidia.spark.rapids.RmmRapidsRetryIterator$.withRestoreOnRetry(Lscala/collection/Seq;Lscala/Function0;)Ljava/lang/Object;+1
j  com.nvidia.spark.rapids.GpuTieredProject.$anonfun$projectWithRetrySingleBatchInternal$4(Lcom/nvidia/spark/rapids/GpuTieredProject;Lorg/apache/spark/sql/vectorized/ColumnarBatch;)Lorg/apache/spark/sql/vectorized/ColumnarBatch;+14
j  com.nvidia.spark.rapids.GpuTieredProject$$Lambda$3497.apply(Ljava/lang/Object;)Ljava/lang/Object;+8
j  com.nvidia.spark.rapids.Arm$.withResource(Ljava/lang/AutoCloseable;Lscala/Function1;)Ljava/lang/Object;+2
j  com.nvidia.spark.rapids.GpuTieredProject.$anonfun$projectWithRetrySingleBatchInternal$3(Lcom/nvidia/spark/rapids/GpuTieredProject;Lcom/nvidia/spark/rapids/SpillableColumnarBatch;)Lorg/apache/spark/sql/vectorized/ColumnarBatch;+15
j  com.nvidia.spark.rapids.GpuTieredProject$$Lambda$3493.apply()Ljava/lang/Object;+8
j  com.nvidia.spark.rapids.RmmRapidsRetryIterator$NoInputSpliterator.next()Ljava/lang/Object;+7
j  com.nvidia.spark.rapids.RmmRapidsRetryIterator$RmmRapidsRetryIterator.next()Ljava/lang/Object;+116
j  com.nvidia.spark.rapids.RmmRapidsRetryIterator$RmmRapidsRetryAutoCloseableIterator.next()Ljava/lang/Object;+18
j  com.nvidia.spark.rapids.RmmRapidsRetryIterator$.drainSingleWithVerification(Lscala/collection/Iterator;)Ljava/lang/Object;+18
j  com.nvidia.spark.rapids.RmmRapidsRetryIterator$.withRetryNoSplit(Lscala/Function0;)Ljava/lang/Object;+18
j  com.nvidia.spark.rapids.GpuTieredProject.$anonfun$projectWithRetrySingleBatchInternal$1(Lcom/nvidia/spark/rapids/GpuTieredProject;Lcom/nvidia/spark/rapids/SpillableColumnarBatch;Lscala/Option;)Lorg/apache/spark/sql/vectorized/ColumnarBatch;+24
j  com.nvidia.spark.rapids.GpuTieredProject$$Lambda$3488.apply(Ljava/lang/Object;)Ljava/lang/Object;+12
j  com.nvidia.spark.rapids.Arm$.withResource(Lscala/Option;Lscala/Function1;)Ljava/lang/Object;+2
j  com.nvidia.spark.rapids.GpuTieredProject.projectWithRetrySingleBatchInternal(Lcom/nvidia/spark/rapids/SpillableColumnarBatch;Z)Lorg/apache/spark/sql/vectorized/ColumnarBatch;+37
j  com.nvidia.spark.rapids.GpuTieredProject.projectAndCloseWithRetrySingleBatch(Lcom/nvidia/spark/rapids/SpillableColumnarBatch;)Lorg/apache/spark/sql/vectorized/ColumnarBatch;+3
j  com.nvidia.spark.rapids.GpuProjectExec.$anonfun$internalDoExecuteColumnar$2(Lorg/apache/spark/sql/vectorized/ColumnarBatch;Lcom/nvidia/spark/rapids/GpuTieredProject;Lcom/nvidia/spark/rapids/NvtxWithMetrics;)Lorg/apache/spark/sql/vectorized/ColumnarBatch;+16
j  com.nvidia.spark.rapids.GpuProjectExec$$Lambda$3470.apply(Ljava/lang/Object;)Ljava/lang/Object;+12
j  com.nvidia.spark.rapids.Arm$.withResource(Ljava/lang/AutoCloseable;Lscala/Function1;)Ljava/lang/Object;+2
j  com.nvidia.spark.rapids.GpuProjectExec.$anonfun$internalDoExecuteColumnar$1(Lcom/nvidia/spark/rapids/GpuMetric;Lcom/nvidia/spark/rapids/GpuTieredProject;Lcom/nvidia/spark/rapids/GpuMetric;Lcom/nvidia/spark/rapids/GpuMetric;Lorg/apache/spark/sql/vectorized/ColumnarBatch;)Lorg/apache/spark/sql/vectorized/ColumnarBatch;+41
j  com.nvidia.spark.rapids.GpuProjectExec$$Lambda$3432.apply(Ljava/lang/Object;)Ljava/lang/Object;+20
J 7502 C2 scala.collection.Iterator$$anon$10.next()Ljava/lang/Object; (19 bytes) @ 0x00007f03024010c0 [0x00007f0302401060+0x60]
j  com.nvidia.spark.rapids.ColumnarToRowIterator.$anonfun$fetchNextBatch$3(Lcom/nvidia/spark/rapids/ColumnarToRowIterator;Ljava/lang/Object;Lcom/nvidia/spark/rapids/NvtxWithMetrics;)Lscala/None$;+24
j  com.nvidia.spark.rapids.ColumnarToRowIterator$$Lambda$3438.apply(Ljava/lang/Object;)Ljava/lang/Object;+12
j  com.nvidia.spark.rapids.Arm$.withResource(Ljava/lang/AutoCloseable;Lscala/Function1;)Ljava/lang/Object;+2
j  com.nvidia.spark.rapids.ColumnarToRowIterator.fetchNextBatch()Lscala/Option;+51
j  com.nvidia.spark.rapids.ColumnarToRowIterator.loadNextBatch()V+10
J 10272 C2 com.nvidia.spark.rapids.ColumnarToRowIterator.hasNext()Z (62 bytes) @ 0x00007f0302a22ccc [0x00007f0302a22c60+0x6c]
J 7506 C2 scala.collection.Iterator$$anon$10.hasNext()Z (10 bytes) @ 0x00007f0302388664 [0x00007f0302388620+0x44]
j  org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(ZILscala/collection/Iterator;)Lscala/collection/Iterator;+199
j  org.apache.spark.sql.execution.SparkPlan$$Lambda$2626.apply(Ljava/lang/Object;)Ljava/lang/Object;+12
j  org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(Lscala/Function1;Lorg/apache/spark/TaskContext;ILscala/collection/Iterator;)Lscala/collection/Iterator;+2
j  org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(Lscala/Function1;Lorg/apache/spark/TaskContext;Ljava/lang/Object;Lscala/collection/Iterator;)Lscala/collection/Iterator;+7
j  org.apache.spark.rdd.RDD$$Lambda$2627.apply(Ljava/lang/Object;Ljava/lang/Object;Ljava/lang/Object;)Ljava/lang/Object;+13
j  org.apache.spark.rdd.MapPartitionsRDD.compute(Lorg/apache/spark/Partition;Lorg/apache/spark/TaskContext;)Lscala/collection/Iterator;+27
j  org.apache.spark.rdd.RDD.computeOrReadCheckpoint(Lorg/apache/spark/Partition;Lorg/apache/spark/TaskContext;)Lscala/collection/Iterator;+26
j  org.apache.spark.rdd.RDD.iterator(Lorg/apache/spark/Partition;Lorg/apache/spark/TaskContext;)Lscala/collection/Iterator;+42
j  org.apache.spark.scheduler.ResultTask.runTask(Lorg/apache/spark/TaskContext;)Ljava/lang/Object;+203
j  org.apache.spark.scheduler.Task.run(JILorg/apache/spark/metrics/MetricsSystem;Lscala/collection/immutable/Map;Lscala/Option;)Ljava/lang/Object;+226
j  org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Lorg/apache/spark/executor/Executor$TaskRunner;Lscala/runtime/BooleanRef;)Ljava/lang/Object;+36
j  org.apache.spark.executor.Executor$TaskRunner$$Lambda$2582.apply()Ljava/lang/Object;+8
j  org.apache.spark.util.Utils$.tryWithSafeFinally(Lscala/Function0;Lscala/Function0;)Ljava/lang/Object;+4
j  org.apache.spark.executor.Executor$TaskRunner.run()V+443
j  java.util.concurrent.ThreadPoolExecutor.runWorker(Ljava/util/concurrent/ThreadPoolExecutor$Worker;)V+95
j  java.util.concurrent.ThreadPoolExecutor$Worker.run()V+5
j  java.lang.Thread.run()V+11
v  ~StubRoutines::call_stub

Steps/Code to reproduce bug
build and test case at: https://github.com/NVIDIA/spark-rapids-examples/blob/branch-24.12/examples/UDF-Examples/RAPIDS-accelerated-UDFs/README.md#building-and-run-the-tests-without-native-code-examples
https://github.com/NVIDIA/spark-rapids-examples/blob/branch-24.12/examples/UDF-Examples/RAPIDS-accelerated-UDFs/src/main/python/rapids_udf_test.py

Expected behavior
A clear and concise description of what you expected to happen.

Environment details (please complete the following information)

• Environment location: [Standalone, YARN, Kubernetes, Cloud(specify cloud provider)]
• Spark configuration settings related to the issue

Additional context
Add any other context about the problem here.

[pxLi]

As it failed with 24.12,
open the ticket to spark-rapids instead of the example repo to determine the impact first

cc @sameerz

[jihoonson]

Thanks @pxLi for filing the issue. Looking into it.