I prepare a simple example (python) as follows to illustrate what I found:
- The code works well by calling a persist beforehand under all Spark
versions
- Without calling persist, the code works well under Spark 2.2.0 but doesn't
work under Spark 2.1.1 and Spark 2.1.2
- It really looks like a bug in Spark. Does anyone know which solved Spark
issues are related?
========================== CODE ==========================
from __future__ import absolute_import, division, print_function
import pyspark.sql.types as T
import pyspark.sql.functions as F
# 2.1.1, 2.1.2 doesn't work
# 2.2.0 works
print(spark.version)
df = spark.createDataFrame(
[{'name': 'a', 'scores': ['1', '2']}, {'name': 'b', 'scores': None}],
T.StructType(
[T.StructField('name', T.StringType(), True),
T.StructField('scores', T.ArrayType(T.StringType()), True)]
)
)
print(df.collect())
df.printSchema()
def loop_array(l):
for e in l:
pass
return "pass"
# should work with persist
# tmp = df.filter(F.col('scores').isNotNull()).withColumn(
# 'new_col',
# F.udf(loop_array)('scores')
# ).persist()
# won't work
tmp = df.filter(F.col('scores').isNotNull()).withColumn(
'new_col',
F.udf(loop_array)('scores')
)
print(tmp.collect())
tmp.filter(F.col('new_col').isNotNull()).count()
======================== CODE END ========================
====================== ERROR MESSAGE ======================
---------------------------------------------------------------------------
Py4JJavaError Traceback (most recent call last)
<ipython-input-9-572fb022ddab> in <module>()
----> 1 tmp.filter(F.col('new_col').isNotNull()).count()
/databricks/spark/python/pyspark/sql/dataframe.py in count(self)
378 2
379 """
--> 380 return int(self._jdf.count())
381
382 @ignore_unicode_prefix
/databricks/spark/python/lib/py4j-0.10.4-src.zip/py4j/java_gateway.py in
__call__(self, *args)
1131 answer = self.gateway_client.send_command(command)
1132 return_value = get_return_value(
-> 1133 answer, self.gateway_client, self.target_id, self.name)
1134
1135 for temp_arg in temp_args:
/databricks/spark/python/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()
/databricks/spark/python/lib/py4j-0.10.4-src.zip/py4j/protocol.py in
get_return_value(answer, gateway_client, target_id, name)
317 raise Py4JJavaError(
318 "An error occurred while calling {0}{1}{2}.\n".
--> 319 format(target_id, ".", name), value)
320 else:
321 raise Py4JError(
Py4JJavaError: An error occurred while calling o235.count.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 3
in stage 2.0 failed 4 times, most recent failure: Lost task 3.3 in stage 2.0
(TID 14, 10.179.231.249, executor 0):
org.apache.spark.api.python.PythonException: Traceback (most recent call
last):
File "/databricks/spark/python/pyspark/worker.py", line 171, in main
process()
File "/databricks/spark/python/pyspark/worker.py", line 166, in process
serializer.dump_stream(func(split_index, iterator), outfile)
File "/databricks/spark/python/pyspark/worker.py", line 103, in <lambda>
func = lambda _, it: map(mapper, it)
File "<string>", line 1, in <lambda>
File "/databricks/spark/python/pyspark/worker.py", line 70, in <lambda>
return lambda *a: f(*a)
File "<ipython-input-6-bb6d09a4128f>", line 2, in loop_array
TypeError: 'NoneType' object is not iterable
at
org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRDD.scala:193)
at
org.apache.spark.api.python.PythonRunner$$anon$1.<init>(PythonRDD.scala:234)
at org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:152)
at
org.apache.spark.sql.execution.python.BatchEvalPythonExec$$anonfun$doExecute$1.apply(BatchEvalPythonExec.scala:144)
at
org.apache.spark.sql.execution.python.BatchEvalPythonExec$$anonfun$doExecute$1.apply(BatchEvalPythonExec.scala:87)
at
org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:797)
at
org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:797)
at
org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at
org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at
org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at
org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:96)
at
org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53)
at org.apache.spark.scheduler.Task.run(Task.scala:99)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:322)
at
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Driver stacktrace:
at
org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1442)
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1430)
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1429)
at
scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at
org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1429)
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:803)
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:803)
at scala.Option.foreach(Option.scala:257)
at
org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:803)
at
org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1657)
at
org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1612)
at
org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1601)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
at
org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:628)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1937)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1950)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1963)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1977)
at org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:936)
at
org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at
org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:362)
at org.apache.spark.rdd.RDD.collect(RDD.scala:935)
at
org.apache.spark.sql.execution.SparkPlan.executeCollect(SparkPlan.scala:275)
at
org.apache.spark.sql.Dataset$$anonfun$count$1.apply(Dataset.scala:2409)
at
org.apache.spark.sql.Dataset$$anonfun$count$1.apply(Dataset.scala:2408)
at org.apache.spark.sql.Dataset$$anonfun$60.apply(Dataset.scala:2791)
at
org.apache.spark.sql.execution.SQLExecution$$anonfun$withNewExecutionId$1.apply(SQLExecution.scala:87)
at
org.apache.spark.sql.execution.SQLExecution$.withFileAccessAudit(SQLExecution.scala:53)
at
org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:70)
at org.apache.spark.sql.Dataset.withAction(Dataset.scala:2790)
at org.apache.spark.sql.Dataset.count(Dataset.scala:2408)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at
sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at
sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:280)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:214)
at java.lang.Thread.run(Thread.java:745)
Caused by: org.apache.spark.api.python.PythonException: Traceback (most
recent call last):
File "/databricks/spark/python/pyspark/worker.py", line 171, in main
process()
File "/databricks/spark/python/pyspark/worker.py", line 166, in process
serializer.dump_stream(func(split_index, iterator), outfile)
File "/databricks/spark/python/pyspark/worker.py", line 103, in <lambda>
func = lambda _, it: map(mapper, it)
File "<string>", line 1, in <lambda>
File "/databricks/spark/python/pyspark/worker.py", line 70, in <lambda>
return lambda *a: f(*a)
File "<ipython-input-6-bb6d09a4128f>", line 2, in loop_array
TypeError: 'NoneType' object is not iterable
at
org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRDD.scala:193)
at
org.apache.spark.api.python.PythonRunner$$anon$1.<init>(PythonRDD.scala:234)
at org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:152)
at
org.apache.spark.sql.execution.python.BatchEvalPythonExec$$anonfun$doExecute$1.apply(BatchEvalPythonExec.scala:144)
at
org.apache.spark.sql.execution.python.BatchEvalPythonExec$$anonfun$doExecute$1.apply(BatchEvalPythonExec.scala:87)
at
org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:797)
at
org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:797)
at
org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at
org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at
org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at
org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:96)
at
org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53)
at org.apache.spark.scheduler.Task.run(Task.scala:99)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:322)
at
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
... 1 more
==================== ERROR MESSAGE END ====================
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