将 Python UDF 应用于 Spark 数据帧时出现 java.lang.IllegalArgumentException

Posted 2023-04-13

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【中文标题】将 Python UDF 应用于 Spark 数据帧时出现 java.lang.IllegalArgumentException【英文标题】：java.lang.IllegalArgumentException when applying a Python UDF to a Spark dataframe 【发布时间】：2019-11-15 14:16:13 【问题描述】：

我正在本地机器上使用 Pyspark 2.3.1 测试 pandas_udf (https://spark.apache.org/docs/2.3.1/api/python/pyspark.sql.html#pyspark.sql.functions.pandas_udf) 文档中提供的示例代码：

from pyspark.sql import SparkSession
from pyspark.sql.functions import pandas_udf, PandasUDFType
df = spark.createDataFrame(
    [(1, 1.0), (1, 2.0), (2, 3.0), (2, 5.0), (2, 10.0)],
    ("id", "v"))  
@pandas_udf("id long, v double", PandasUDFType.GROUPED_MAP)  
def normalize(pdf):
    v = pdf.v
    return pdf.assign(v=(v - v.mean()) / v.std())
df.groupby("id").apply(normalize).show()

但是当我这样做时，我提出了一个java.lang.IllegalArgumentException（完整的堆栈跟踪显示在这篇文章下方）。

知道我做错了什么吗？

完整的堆栈跟踪：

[Stage 23:======================================================>(99 + 1) / 100]2019-11-15 15:13:26 ERROR Executor:91 - Exception in task 44.0 in stage 23.0 (TID 410)
java.lang.IllegalArgumentException
    at java.nio.ByteBuffer.allocate(ByteBuffer.java:334)
    at org.apache.arrow.vector.ipc.message.MessageChannelReader.readNextMessage(MessageChannelReader.java:64)
    at org.apache.arrow.vector.ipc.message.MessageSerializer.deserializeSchema(MessageSerializer.java:104)
    at org.apache.arrow.vector.ipc.ArrowStreamReader.readSchema(ArrowStreamReader.java:128)
    at org.apache.arrow.vector.ipc.ArrowReader.initialize(ArrowReader.java:181)
    at org.apache.arrow.vector.ipc.ArrowReader.ensureInitialized(ArrowReader.java:172)
    at org.apache.arrow.vector.ipc.ArrowReader.getVectorSchemaRoot(ArrowReader.java:65)
    at org.apache.spark.sql.execution.python.ArrowPythonRunner$$anon$1.read(ArrowPythonRunner.scala:161)
    at org.apache.spark.sql.execution.python.ArrowPythonRunner$$anon$1.read(ArrowPythonRunner.scala:121)
    at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:252)
    at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
    at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:439)
    at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
    at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage3.processNext(Unknown Source)
    at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
    at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$10$$anon$1.hasNext(WholeStageCodegenExec.scala:614)
    at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:253)
    at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:247)
    at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:830)
    at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:830)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
    at org.apache.spark.scheduler.Task.run(Task.scala:109)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
    at java.lang.Thread.run(Thread.java:748)
2019-11-15 15:13:26 WARN  TaskSetManager:66 - Lost task 44.0 in stage 23.0 (TID 410, localhost, executor driver): java.lang.IllegalArgumentException
    at java.nio.ByteBuffer.allocate(ByteBuffer.java:334)
    at org.apache.arrow.vector.ipc.message.MessageChannelReader.readNextMessage(MessageChannelReader.java:64)
    at org.apache.arrow.vector.ipc.message.MessageSerializer.deserializeSchema(MessageSerializer.java:104)
    at org.apache.arrow.vector.ipc.ArrowStreamReader.readSchema(ArrowStreamReader.java:128)
    at org.apache.arrow.vector.ipc.ArrowReader.initialize(ArrowReader.java:181)
    at org.apache.arrow.vector.ipc.ArrowReader.ensureInitialized(ArrowReader.java:172)
    at org.apache.arrow.vector.ipc.ArrowReader.getVectorSchemaRoot(ArrowReader.java:65)
    at org.apache.spark.sql.execution.python.ArrowPythonRunner$$anon$1.read(ArrowPythonRunner.scala:161)
    at org.apache.spark.sql.execution.python.ArrowPythonRunner$$anon$1.read(ArrowPythonRunner.scala:121)
    at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:252)
    at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
    at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:439)
    at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
    at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage3.processNext(Unknown Source)
    at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
    at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$10$$anon$1.hasNext(WholeStageCodegenExec.scala:614)
    at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:253)
    at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:247)
    at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:830)
    at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:830)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
    at org.apache.spark.scheduler.Task.run(Task.scala:109)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
    at java.lang.Thread.run(Thread.java:748)

2019-11-15 15:13:26 ERROR TaskSetManager:70 - Task 44 in stage 23.0 failed 1 times; aborting job
---------------------------------------------------------------------------
Py4JJavaError                             Traceback (most recent call last)
<ipython-input-24-a7591207fb94> in <module>
----> 1 df.groupby("id").apply(normalize).show()

~/.virtualenvs/godfather/lib/python3.7/site-packages/pyspark/sql/dataframe.py in show(self, n, truncate, vertical)
    348         """
    349         if isinstance(truncate, bool) and truncate:
--> 350             print(self._jdf.showString(n, 20, vertical))
    351         else:
    352             print(self._jdf.showString(n, int(truncate), vertical))

~/.virtualenvs/godfather/lib/python3.7/site-packages/py4j/java_gateway.py in __call__(self, *args)
   1255         answer = self.gateway_client.send_command(command)
   1256         return_value = get_return_value(
-> 1257             answer, self.gateway_client, self.target_id, self.name)
   1258
   1259         for temp_arg in temp_args:

~/.virtualenvs/godfather/lib/python3.7/site-packages/pyspark/sql/utils.py in deco(*a, **kw)
     61     def deco(*a, **kw):
     62         try:
---> 63             return f(*a, **kw)
     64         except py4j.protocol.Py4JJavaError as e:
     65             s = e.java_exception.toString()

~/.virtualenvs/godfather/lib/python3.7/site-packages/py4j/protocol.py in get_return_value(answer, gateway_client, target_id, name)
    326                 raise Py4JJavaError(
    327                     "An error occurred while calling 012.\n".
--> 328                     format(target_id, ".", name), value)
    329             else:
    330                 raise Py4JError(

Py4JJavaError: An error occurred while calling o243.showString.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 44 in stage 23.0 failed 1 times, most recent failure: Lost task 44.0 in stage 23.0 (TID 410, localhost, executor driver): java.lang.IllegalArgumentException
    at java.nio.ByteBuffer.allocate(ByteBuffer.java:334)
    at org.apache.arrow.vector.ipc.message.MessageChannelReader.readNextMessage(MessageChannelReader.java:64)
    at org.apache.arrow.vector.ipc.message.MessageSerializer.deserializeSchema(MessageSerializer.java:104)
    at org.apache.arrow.vector.ipc.ArrowStreamReader.readSchema(ArrowStreamReader.java:128)
    at org.apache.arrow.vector.ipc.ArrowReader.initialize(ArrowReader.java:181)
    at org.apache.arrow.vector.ipc.ArrowReader.ensureInitialized(ArrowReader.java:172)
    at org.apache.arrow.vector.ipc.ArrowReader.getVectorSchemaRoot(ArrowReader.java:65)
    at org.apache.spark.sql.execution.python.ArrowPythonRunner$$anon$1.read(ArrowPythonRunner.scala:161)
    at org.apache.spark.sql.execution.python.ArrowPythonRunner$$anon$1.read(ArrowPythonRunner.scala:121)
    at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:252)
    at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
    at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:439)
    at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
    at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage3.processNext(Unknown Source)
    at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
    at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$10$$anon$1.hasNext(WholeStageCodegenExec.scala:614)
    at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:253)
    at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:247)
    at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:830)
    at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:830)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
    at org.apache.spark.scheduler.Task.run(Task.scala:109)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
    at java.lang.Thread.run(Thread.java:748)

Driver stacktrace:
    at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1602)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1590)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1589)
    at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
    at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
    at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1589)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:831)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:831)
    at scala.Option.foreach(Option.scala:257)
    at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:831)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1823)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1772)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1761)
    at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
    at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:642)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:2034)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:2055)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:2074)
    at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:363)
    at org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:38)
    at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$collectFromPlan(Dataset.scala:3273)
    at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2484)
    at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2484)
    at org.apache.spark.sql.Dataset$$anonfun$52.apply(Dataset.scala:3254)
    at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:77)
    at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3253)
    at org.apache.spark.sql.Dataset.head(Dataset.scala:2484)
    at org.apache.spark.sql.Dataset.take(Dataset.scala:2698)
    at org.apache.spark.sql.Dataset.showString(Dataset.scala:254)
    at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
    at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.lang.reflect.Method.invoke(Method.java:498)
    at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
    at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
    at py4j.Gateway.invoke(Gateway.java:282)
    at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
    at py4j.commands.CallCommand.execute(CallCommand.java:79)
    at py4j.GatewayConnection.run(GatewayConnection.java:238)
    at java.lang.Thread.run(Thread.java:748)
Caused by: java.lang.IllegalArgumentException
    at java.nio.ByteBuffer.allocate(ByteBuffer.java:334)
    at org.apache.arrow.vector.ipc.message.MessageChannelReader.readNextMessage(MessageChannelReader.java:64)
    at org.apache.arrow.vector.ipc.message.MessageSerializer.deserializeSchema(MessageSerializer.java:104)
    at org.apache.arrow.vector.ipc.ArrowStreamReader.readSchema(ArrowStreamReader.java:128)
    at org.apache.arrow.vector.ipc.ArrowReader.initialize(ArrowReader.java:181)
    at org.apache.arrow.vector.ipc.ArrowReader.ensureInitialized(ArrowReader.java:172)
    at org.apache.arrow.vector.ipc.ArrowReader.getVectorSchemaRoot(ArrowReader.java:65)
    at org.apache.spark.sql.execution.python.ArrowPythonRunner$$anon$1.read(ArrowPythonRunner.scala:161)
    at org.apache.spark.sql.execution.python.ArrowPythonRunner$$anon$1.read(ArrowPythonRunner.scala:121)
    at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:252)
    at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
    at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:439)
    at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
    at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage3.processNext(Unknown Source)
    at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
    at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$10$$anon$1.hasNext(WholeStageCodegenExec.scala:614)
    at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:253)
    at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:247)
    at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:830)
    at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:830)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
    at org.apache.spark.scheduler.Task.run(Task.scala:109)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
    ... 1 more

【问题讨论】：

【参考方案1】：

根据https://issues.apache.org/jira/browse/SPARK-29367，您需要：

设置环境变量

ARROW_PRE_0_15_IPC_FORMAT=1

或使用早于0.15 的pyarrow 版本，例如0.14.1

【讨论】：

我使用 scala arrow 1.0.1 和 pyarrow 1.0.1 使用相同的数据偶尔仍然会出现此错误【参考方案2】：

我的解决方案与 this one 密切相关，但我必须在 UDF 中设置环境变量，以便在执行程序上正确定义它：

@pandas_udf("id long, v double", PandasUDFType.GROUPED_MAP)  
def normalize(pdf):
    import os
    os.environ['ARROW_PRE_0_15_IPC_FORMAT']='1'

    v = pdf.v
    return pdf.assign(v=(v - v.mean()) / v.std())

【讨论】：

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