Pyspark &引用；索引处的值为空"；使用udf时出错_Pyspark_Apache Spark Sql

Pyspark &引用；索引处的值为空"；使用udf时出错

pyspark

Pyspark &引用；索引处的值为空"；使用udf时出错,pyspark,apache-spark-sql,Pyspark,Apache Spark Sql,对于pyspark中的数据帧，如果使用F.lit（1）（或任何其他值）初始化列，则会将其分配给pandas_udf中的某些值（在本例中使用shift（），但可能发生在任何其他函数），这会导致“索引处的值为null”错误有人能提供一些线索来解释为什么会发生这种情况吗？这是pyspark中的一个bug吗请参阅下面的代码和错误 spark = SparkSession.builder.appName('test').getOrCreate() df = spark.createDataFrame(

对于pyspark中的数据帧，如果使用F.lit（1）（或任何其他值）初始化列，则会将其分配给pandas_udf中的某些值（在本例中使用shift（），但可能发生在任何其他函数），这会导致“索引处的值为null”错误

有人能提供一些线索来解释为什么会发生这种情况吗？这是pyspark中的一个bug吗

请参阅下面的代码和错误

spark = SparkSession.builder.appName('test').getOrCreate()
df = spark.createDataFrame([Row(id=1, name='a', c=3),
Row(id=2, name='b', c=6),
Row(id=3, name='a', c=2),
Row(id=4, name='b', c=9),
Row(id=5, name='c', c=7)])

df = df.withColumn('f', F.lit(1))


@pandas_udf(df.schema, PandasUDFType.GROUPED_MAP)
def shift_test(pdf):
    pdf['f'] = pdf['c'].shift(1)
    return pdf

df = df.groupby(['name']).apply(shift_test)
df.show()

如果我将列

设置为

请参见下面的输出

+---+---+----+---+
|  c| id|name|  f|
+---+---+----+---+
|  3|  1|   a|  1|
|  6|  2|   b|  1|
|  2|  3|   a|  1|
|  9|  4|   b|  1|
|  7|  5|   c|  1|
+---+---+----+---+


---------------------------------------------------------------------------
Py4JJavaError                             Traceback (most recent call last)
<ipython-input-46-5b4a8c6e0258> in <module>
     18 
     19 df = df.groupby(['name']).apply(shift_test)
---> 20 df.show()

Py4JJavaError: An error occurred while calling o3378.showString.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 97 in stage 426.0 failed 4 times, most recent failure: Lost task 97.3 in stage 426.0 (TID 6258, optoldevny1, executor 0): java.lang.IllegalStateException: Value at index is null
    at org.apache.arrow.vector.IntVector.get(IntVector.java:101)
    at org.apache.spark.sql.vectorized.ArrowColumnVector$IntAccessor.getInt(ArrowColumnVector.java:299)
    at org.apache.spark.sql.vectorized.ArrowColumnVector.getInt(ArrowColumnVector.java:84)
    at org.apache.spark.sql.execution.vectorized.MutableColumnarRow.getInt(MutableColumnarRow.java:117)
    at org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificUnsafeProjection.apply(Unknown Source)
    at org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificUnsafeProjection.apply(Unknown Source)
    at scala.collection.Iterator$$anon$11.next(Iterator.scala:410)
    at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage3.processNext(Unknown Source)
    at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
    at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$13$$anon$1.hasNext(WholeStageCodegenExec.scala:636)
    at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:255)
    at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:247)
    at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:858)
    at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:858)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:346)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:310)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:346)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:310)
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
    at org.apache.spark.scheduler.Task.run(Task.scala:123)
    at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:408)
    at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:414)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
    at java.util.concurrent.ThreadPoolExecutor$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$$failJobAndIndependentStages(DAGScheduler.scala:1891)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1879)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1878)
    at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
    at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
    at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1878)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:927)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:927)
    at scala.Option.foreach(Option.scala:257)
    at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:927)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2112)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2061)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2050)
    at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
    at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:738)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:2061)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:2082)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:2101)
    at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:365)
    at org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:38)
    at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$collectFromPlan(Dataset.scala:3389)
    at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2550)
    at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2550)
    at org.apache.spark.sql.Dataset$$anonfun$52.apply(Dataset.scala:3370)
    at org.apache.spark.sql.execution.SQLExecution$$anonfun$withNewExecutionId$1.apply(SQLExecution.scala:80)
    at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:127)
    at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:75)
    at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3369)
    at org.apache.spark.sql.Dataset.head(Dataset.scala:2550)
    at org.apache.spark.sql.Dataset.take(Dataset.scala:2764)
    at org.apache.spark.sql.Dataset.getRows(Dataset.scala:254)
    at org.apache.spark.sql.Dataset.showString(Dataset.scala:291)
    at sun.reflect.GeneratedMethodAccessor67.invoke(Unknown Source)
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.lang.reflect.Method.invoke(Method.java:498)
    at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
    at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
    at py4j.Gateway.invoke(Gateway.java:282)
    at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
    at py4j.commands.CallCommand.execute(CallCommand.java:79)
    at py4j.GatewayConnection.run(GatewayConnection.java:238)
    at java.lang.Thread.run(Thread.java:748)
Caused by: java.lang.IllegalStateException: Value at index is null
    at org.apache.arrow.vector.IntVector.get(IntVector.java:101)
    at org.apache.spark.sql.vectorized.ArrowColumnVector$IntAccessor.getInt(ArrowColumnVector.java:299)
    at org.apache.spark.sql.vectorized.ArrowColumnVector.getInt(ArrowColumnVector.java:84)
    at org.apache.spark.sql.execution.vectorized.MutableColumnarRow.getInt(MutableColumnarRow.java:117)
    at org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificUnsafeProjection.apply(Unknown Source)
    at org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificUnsafeProjection.apply(Unknown Source)
    at scala.collection.Iterator$$anon$11.next(Iterator.scala:410)
    at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage3.processNext(Unknown Source)
    at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
    at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$13$$anon$1.hasNext(WholeStageCodegenExec.scala:636)
    at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:255)
    at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:247)
    at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:858)
    at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:858)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:346)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:310)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:346)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:310)
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
    at org.apache.spark.scheduler.Task.run(Task.scala:123)
    at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:408)
    at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:414)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
    ... 1 more

+---+---+----+---+
|c | id | name | f|
+---+---+----+---+
|3 | 1 | a | 1|
|6 | 2 | b | 1|
|2 | 3 | a | 1|
|9 | 4 | b | 1|
|7 | 5 | c | 1|
+---+---+----+---+
---------------------------------------------------------------------------
Py4JJavaError回溯（最近一次调用）
在里面
18
19 df=df.groupby（['name']）。应用（shift_测试）
--->20 df.show（）
Py4JJavaError:调用o3378.showString时出错。
：org.apache.spark.sparkeexception:作业因阶段失败而中止：阶段426.0中的Task 97失败4次，最近的失败：阶段426.0中的Task 97.3丢失（TID 6258，optoldevny1，executor 0）：java.lang.IllegalStateException:索引处的值为null
位于org.apache.arrow.vector.IntVector.get（IntVector.java:101）
位于org.apache.spark.sql.vectoried.ArrowColumnVector$IntAccessor.getInt（ArrowColumnVector.java:299）
位于org.apache.spark.sql.vectoried.ArrowColumnVector.getInt（ArrowColumnVector.java:84）
位于org.apache.spark.sql.execution.vectoried.MutableColumnarRow.getInt（MutableColumnarRow.java:117）
位于org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificUnsafeProjection.apply（未知源）
位于org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificUnsafeProjection.apply（未知源）
位于scala.collection.Iterator$$anon$11.next（Iterator.scala:410）
位于org.apache.spark.sql.catalyst.expressions.GeneratedClass$GenerateEditorForCodeGenStage3.processNext（未知源）
位于org.apache.spark.sql.execution.BufferedRowIterator.hasNext（BufferedRowIterator.java:43）
位于org.apache.spark.sql.execution.whisttagecodegenexec$$anonfun$13$$anon$1.hasNext（whisttagecodegenexec.scala:636）
位于org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply（SparkPlan.scala:255）
位于org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply（SparkPlan.scala:247）
位于org.apache.spark.rdd.rdd$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply（rdd.scala:858）
位于org.apache.spark.rdd.rdd$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply（rdd.scala:858）
位于org.apache.spark.rdd.MapPartitionsRDD.compute（MapPartitionsRDD.scala:52）
在org.apache.spark.rdd.rdd.computeOrReadCheckpoint（rdd.scala:346）上
位于org.apache.spark.rdd.rdd.iterator（rdd.scala:310）
位于org.apache.spark.rdd.MapPartitionsRDD.compute（MapPartitionsRDD.scala:52）
在org.apache.spark.rdd.rdd.computeOrReadCheckpoint（rdd.scala:346）上
位于org.apache.spark.rdd.rdd.iterator（rdd.scala:310）
位于org.apache.spark.scheduler.ResultTask.runTask（ResultTask.scala:90）
位于org.apache.spark.scheduler.Task.run（Task.scala:123）
位于org.apache.spark.executor.executor$TaskRunner$$anonfun$10.apply（executor.scala:408）
位于org.apache.spark.util.Utils$.tryWithSafeFinally（Utils.scala:1360）
位于org.apache.spark.executor.executor$TaskRunner.run（executor.scala:414）
位于java.util.concurrent.ThreadPoolExecutor.runWorker（ThreadPoolExecutor.java:1149）
位于java.util.concurrent.ThreadPoolExecutor$Worker.run（ThreadPoolExecutor.java:624）
运行（Thread.java:748）
驱动程序堆栈跟踪：
位于org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages（DAGScheduler.scala:1891）
位于org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply（DAGScheduler.scala:1879）
位于org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply（DAGScheduler.scala:1878）
位于scala.collection.mutable.resizeblearray$class.foreach（resizeblearray.scala:59）
位于scala.collection.mutable.ArrayBuffer.foreach（ArrayBuffer.scala:48）
位于org.apache.spark.scheduler.DAGScheduler.abortStage（DAGScheduler.scala:1878）
位于org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply（DAGScheduler.scala:927）
位于org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply（DAGScheduler.scala:927）
位于scala.Option.foreach（Option.scala:257）
位于org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed（DAGScheduler.scala:927）
位于org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive（DAGScheduler.scala:2112）
位于org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive（DAGScheduler.scala:2061）
位于org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive（DAGScheduler.scala:2050）
位于org.apache.spark.util.EventLoop$$anon$1.run（EventLoop.scala:49）
位于org.apache.spark.scheduler.DAGScheduler.runJob（DAGScheduler.scala:738）
位于org.apache.spark.SparkContext.runJob（SparkContext.scala:2061）
位于org.apache.spark.SparkContext.runJob（SparkContext.scala:2082）
位于org.apache.spark.SparkContext.runJob（SparkContext.scala:2101）
位于org.apache.spark.sql.execution.SparkPlan.executeTake（SparkPlan.scala:365）
位于org.apache.spark.sql.execution.CollectLimitExec.executeCollect（limit.scala:38）
位于org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$collectFromPlan（Dataset.scala:3389）
位于org.apache.spark.sql.Dataset$$anonfun$head$1.apply（Dataset.scala:2550）
位于org.apache.spark.sql.Dataset$$anonfun$head$1.apply（Dataset.scala:2550）
位于org.apache.spark.sql.Dataset$$anonfun$52.apply（Dataset.scala:3370）
位于org.apache.spark.sql.execution.SQLExecution$$anonfun$和newexecutionid$1.apply（SQLExecution.scala:80）
在org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated（SQLExecution.scala:127）
@pandas_udf(df.schema, PandasUDFType.GROUPED_MAP)
def shift_test(pdf):
    pdf['f'] = pdf['c'].shift(1)
    pdf['f'].fillna(value=-1, inplace=True) #replace missing values with -1
    return pdf

+---+---+----+---+
|  c| id|name|  f|
+---+---+----+---+
|  7|  5|   c| -1|
|  6|  2|   b| -1|
|  9|  4|   b|  6|
|  2|  3|   a| -1|
|  3|  1|   a|  2|
+---+---+----+---+


# Schema of output DataFrame
new_schema = StructType([
    StructField("c", IntegerType(), False), 
    StructField("id", IntegerType(), False), 
    StructField("name", StringType(), False), 
    StructField("f", IntegerType(), True)
  ])

@pandas_udf(new_schema, PandasUDFType.GROUPED_MAP)
def shift_test(pdf):
    pdf['f'] = pdf['c'].shift(1)
    return pdf