I'm trying to optimize a neural network coded with Tensorflow by setting different seeds and parallelize each training stage with PySpark. This was inspired by mixing RL and Genetic Algorithms. My problem is that when I run the code, when doing .collect() it crashes and I can't figure it out why. I also ran the code without using the mainSpark function in order to check if the error was in other place and it worked fine. What I'm doing wrong and how can I fix it?
I'm using tensorflow 2.6 and pyspark 3.0.1
The code is as follows:
def mainSpark(data,seed,main_folder,train=True):
with tf.Graph().as_default() as g:
environment = Enviroment(data = data)
agent = Agent(seed,environment.state_dim,environment.action_space,main_folder)
reward,_ = playSpark(environment,agent,train)
g.finalize()
return reward,environment
def playSpark(env,agent,train=True):
state = env.reset(train)
done = False
episode_reward = 0
reward = 0
while not done:
action = agent.act(state)
state,reward,done,info = env.step(action)
episode_reward+=reward
return episode_reward,env
if __name__ == '__main__':
MAIN_FOLDER = 'rl_train_results/rl_normal_environment_v1'
spark = ps.sql.SparkSession.builder.master('local[*]').appName('sparkRunGeneticOpt').getOrCreate()
sc = spark.sparkContext
for generation in range(N_GENS):
individuals = [np.random.randint(2,size=10) for _ in range(10)]
generation_scores = sc.parallelize(individuals).map(
lambda s: (s,mainSpark(_price,s,MAIN_FOLDER))
)
generation_scores = generation_scores.collect()
print(generation_scores)
The model that is inside the agent is like this:
class Agent():
def __init__(self,seed,space_dim):
self.space_dim = space_dim
self.seed = seed
int_seed = int(seed,2)
self.set_seed(int_seed)
def create_model(self):
model = tf.keras.models.Sequential([
tf.keras.layers.Input(shape=(self.space_dim,),name='inputs'),
tf.keras.layers.Dense(50,activation='relu',name='d1'),
tf.keras.layers.Dense(20,activation='relu',name='d2'),
tf.keras.layers.Dense(3,activation='softmax',name='output')
])
return model
def set_seed(self,seed=None):
if seed is None:
tf.random.set_seed(int(self.seed,2))
else:
if isinstance(seed,str):
seed = int(seed,2)
tf.random.set_seed(seed)
And the error log is this:
21/11/05 01:08:47 ERROR Executor: Exception in task 0.0 in stage 0.0 (TID 0)
org.apache.spark.SparkException: Python worker exited unexpectedly (crashed)
at org.apache.spark.api.python.BasePythonRunner$ReaderIterator$$anonfun$1.applyOrElse(PythonRunner.scala:536)
at org.apache.spark.api.python.BasePythonRunner$ReaderIterator$$anonfun$1.applyOrElse(PythonRunner.scala:525)
at scala.runtime.AbstractPartialFunction.apply(AbstractPartialFunction.scala:38)
at org.apache.spark.api.python.PythonRunner$$anon$3.read(PythonRunner.scala:643)
at org.apache.spark.api.python.PythonRunner$$anon$3.read(PythonRunner.scala:621)
at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:456)
at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
at scala.collection.Iterator.foreach(Iterator.scala:941)
at scala.collection.Iterator.foreach$(Iterator.scala:941)
at org.apache.spark.InterruptibleIterator.foreach(InterruptibleIterator.scala:28)
at scala.collection.generic.Growable.$plus$plus$eq(Growable.scala:62)
at scala.collection.generic.Growable.$plus$plus$eq$(Growable.scala:53)
at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:105)
at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:49)
at scala.collection.TraversableOnce.to(TraversableOnce.scala:315)
at scala.collection.TraversableOnce.to$(TraversableOnce.scala:313)
at org.apache.spark.InterruptibleIterator.to(InterruptibleIterator.scala:28)
at scala.collection.TraversableOnce.toBuffer(TraversableOnce.scala:307)
at scala.collection.TraversableOnce.toBuffer$(TraversableOnce.scala:307)
at org.apache.spark.InterruptibleIterator.toBuffer(InterruptibleIterator.scala:28)
at scala.collection.TraversableOnce.toArray(TraversableOnce.scala:294)
at scala.collection.TraversableOnce.toArray$(TraversableOnce.scala:288)
at org.apache.spark.InterruptibleIterator.toArray(InterruptibleIterator.scala:28)
at org.apache.spark.rdd.RDD.$anonfun$collect$2(RDD.scala:1004)
at org.apache.spark.SparkContext.$anonfun$runJob$5(SparkContext.scala:2139)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:127)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:446)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1377)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:449)
at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1128)
at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:628)
at java.base/java.lang.Thread.run(Thread.java:834)
Caused by: java.io.EOFException
at java.base/java.io.DataInputStream.readInt(DataInputStream.java:397)
at org.apache.spark.api.python.PythonRunner$$anon$3.read(PythonRunner.scala:628)
... 29 more
21/11/05 01:08:48 WARN TaskSetManager: Lost task 0.0 in stage 0.0 (TID 0, Asus, executor driver): org.apache.spark.SparkException: Python worker exite
d unexpectedly (crashed)
at org.apache.spark.api.python.BasePythonRunner$ReaderIterator$$anonfun$1.applyOrElse(PythonRunner.scala:536)
at org.apache.spark.api.python.BasePythonRunner$ReaderIterator$$anonfun$1.applyOrElse(PythonRunner.scala:525)
at scala.runtime.AbstractPartialFunction.apply(AbstractPartialFunction.scala:38)
at org.apache.spark.api.python.PythonRunner$$anon$3.read(PythonRunner.scala:643)
at org.apache.spark.api.python.PythonRunner$$anon$3.read(PythonRunner.scala:621)
at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:456)
at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
at scala.collection.Iterator.foreach(Iterator.scala:941)
at scala.collection.Iterator.foreach$(Iterator.scala:941)
at org.apache.spark.InterruptibleIterator.foreach(InterruptibleIterator.scala:28)
at scala.collection.generic.Growable.$plus$plus$eq(Growable.scala:62)
at scala.collection.generic.Growable.$plus$plus$eq$(Growable.scala:53)
at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:105)
at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:49)
at scala.collection.TraversableOnce.to(TraversableOnce.scala:315)
at scala.collection.TraversableOnce.to$(TraversableOnce.scala:313)
at org.apache.spark.InterruptibleIterator.to(InterruptibleIterator.scala:28)
at scala.collection.TraversableOnce.toBuffer(TraversableOnce.scala:307)
at scala.collection.TraversableOnce.toBuffer$(TraversableOnce.scala:307)
at org.apache.spark.InterruptibleIterator.toBuffer(InterruptibleIterator.scala:28)
at scala.collection.TraversableOnce.toArray(TraversableOnce.scala:294)
at scala.collection.TraversableOnce.toArray$(TraversableOnce.scala:288)
at org.apache.spark.InterruptibleIterator.toArray(InterruptibleIterator.scala:28)
at org.apache.spark.rdd.RDD.$anonfun$collect$2(RDD.scala:1004)
at org.apache.spark.SparkContext.$anonfun$runJob$5(SparkContext.scala:2139)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:127)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:446)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1377)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:449)
at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1128)
at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:628)
at java.base/java.lang.Thread.run(Thread.java:834)
Caused by: java.io.EOFException
at java.base/java.io.DataInputStream.readInt(DataInputStream.java:397)
at org.apache.spark.api.python.PythonRunner$$anon$3.read(PythonRunner.scala:628)
... 29 more
21/11/05 01:08:48 ERROR TaskSetManager: Task 0 in stage 0.0 failed 1 times; aborting job
Traceback (most recent call last):
21/11/05 01:08:48 WARN TaskSetManager: Lost task 1.0 in stage 0.0 (TID 1, Asus, executor driver): TaskKilled (Stage cancelled)
File ".\mainSpark.py", line 125, in <module>
generation_scores = generation_scores.collect()
File "D:\Anaconda3\lib\site-packages\pyspark\rdd.py", line 889, in collect
sock_info = self.ctx._jvm.PythonRDD.collectAndServe(self._jrdd.rdd())
File "D:\Anaconda3\lib\site-packages\py4j\java_gateway.py", line 1304, in __call__
return_value = get_return_value(
File "D:\Anaconda3\lib\site-packages\pyspark\sql\utils.py", line 128, in deco
return f(*a, **kw)
File "D:\Anaconda3\lib\site-packages\py4j\protocol.py", line 326, in get_return_value
raise Py4JJavaError(
py4j.protocol.Py4JJavaError: An error occurred while calling z:org.apache.spark.api.python.PythonRDD.collectAndServe.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 0.0 failed 1 times, most recent failure: Lost task 0.0 in stage 0
.0 (TID 0, Asus, executor driver): org.apache.spark.SparkException: Python worker exited unexpectedly (crashed)
at org.apache.spark.api.python.BasePythonRunner$ReaderIterator$$anonfun$1.applyOrElse(PythonRunner.scala:536)
at org.apache.spark.api.python.BasePythonRunner$ReaderIterator$$anonfun$1.applyOrElse(PythonRunner.scala:525)
at scala.runtime.AbstractPartialFunction.apply(AbstractPartialFunction.scala:38)
at org.apache.spark.api.python.PythonRunner$$anon$3.read(PythonRunner.scala:643)
at org.apache.spark.api.python.PythonRunner$$anon$3.read(PythonRunner.scala:621)
at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:456)
at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
at scala.collection.Iterator.foreach(Iterator.scala:941)
at scala.collection.Iterator.foreach$(Iterator.scala:941)
at org.apache.spark.InterruptibleIterator.foreach(InterruptibleIterator.scala:28)
at scala.collection.generic.Growable.$plus$plus$eq(Growable.scala:62)
at scala.collection.generic.Growable.$plus$plus$eq$(Growable.scala:53)
at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:105)
at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:49)
at scala.collection.TraversableOnce.to(TraversableOnce.scala:315)
at scala.collection.TraversableOnce.to$(TraversableOnce.scala:313)
at org.apache.spark.InterruptibleIterator.to(InterruptibleIterator.scala:28)
at scala.collection.TraversableOnce.toBuffer(TraversableOnce.scala:307)
at scala.collection.TraversableOnce.toBuffer$(TraversableOnce.scala:307)
at org.apache.spark.InterruptibleIterator.toBuffer(InterruptibleIterator.scala:28)
at scala.collection.TraversableOnce.toArray(TraversableOnce.scala:294)
at scala.collection.TraversableOnce.toArray$(TraversableOnce.scala:288)
at org.apache.spark.InterruptibleIterator.toArray(InterruptibleIterator.scala:28)
at org.apache.spark.rdd.RDD.$anonfun$collect$2(RDD.scala:1004)
at org.apache.spark.SparkContext.$anonfun$runJob$5(SparkContext.scala:2139)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:127)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:446)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1377)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:449)
at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1128)
at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:628)
at java.base/java.lang.Thread.run(Thread.java:834)
Caused by: java.io.EOFException
at java.base/java.io.DataInputStream.readInt(DataInputStream.java:397)
at org.apache.spark.api.python.PythonRunner$$anon$3.read(PythonRunner.scala:628)
... 29 more
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2059)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2008)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2007)
at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2007)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:973)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:973)
at scala.Option.foreach(Option.scala:407)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:973)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2239)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2188)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2177)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:775)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2099)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2120)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2139)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2164)
at org.apache.spark.rdd.RDD.$anonfun$collect$1(RDD.scala:1004)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:388)
at org.apache.spark.rdd.RDD.collect(RDD.scala:1003)
at org.apache.spark.api.python.PythonRDD$.collectAndServe(PythonRDD.scala:168)
at org.apache.spark.api.python.PythonRDD.collectAndServe(PythonRDD.scala)
at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at java.base/jdk.internal.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.base/java.lang.reflect.Method.invoke(Method.java:566)
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.base/java.lang.Thread.run(Thread.java:834)
Caused by: org.apache.spark.SparkException: Python worker exited unexpectedly (crashed)
at org.apache.spark.api.python.BasePythonRunner$ReaderIterator$$anonfun$1.applyOrElse(PythonRunner.scala:536)
at org.apache.spark.api.python.BasePythonRunner$ReaderIterator$$anonfun$1.applyOrElse(PythonRunner.scala:525)
at scala.runtime.AbstractPartialFunction.apply(AbstractPartialFunction.scala:38)
at org.apache.spark.api.python.PythonRunner$$anon$3.read(PythonRunner.scala:643)
at org.apache.spark.api.python.PythonRunner$$anon$3.read(PythonRunner.scala:621)
at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:456)
at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
at scala.collection.Iterator.foreach(Iterator.scala:941)
at scala.collection.Iterator.foreach$(Iterator.scala:941)
at org.apache.spark.InterruptibleIterator.foreach(InterruptibleIterator.scala:28)
at scala.collection.generic.Growable.$plus$plus$eq(Growable.scala:62)
at scala.collection.generic.Growable.$plus$plus$eq$(Growable.scala:53)
at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:105)
at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:49)
at scala.collection.TraversableOnce.to(TraversableOnce.scala:315)
at scala.collection.TraversableOnce.to$(TraversableOnce.scala:313)
at org.apache.spark.InterruptibleIterator.to(InterruptibleIterator.scala:28)
at scala.collection.TraversableOnce.toBuffer(TraversableOnce.scala:307)
at scala.collection.TraversableOnce.toBuffer$(TraversableOnce.scala:307)
at org.apache.spark.InterruptibleIterator.toBuffer(InterruptibleIterator.scala:28)
at scala.collection.TraversableOnce.toArray(TraversableOnce.scala:294)
at scala.collection.TraversableOnce.toArray$(TraversableOnce.scala:288)
at org.apache.spark.InterruptibleIterator.toArray(InterruptibleIterator.scala:28)
at org.apache.spark.rdd.RDD.$anonfun$collect$2(RDD.scala:1004)
at org.apache.spark.SparkContext.$anonfun$runJob$5(SparkContext.scala:2139)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:127)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:446)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1377)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:449)
at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1128)
at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:628)
... 1 more
Caused by: java.io.EOFException
at java.base/java.io.DataInputStream.readInt(DataInputStream.java:397)
at org.apache.spark.api.python.PythonRunner$$anon$3.read(PythonRunner.scala:628)
... 29 more
Related
I have 12 smaller parquet files which I successfully read them and combine them. I'm trying to save the combined dataframe in one parquet file in S3 but It shows me an error
from pyspark.sql import SparkSession
spark = SparkSession.builder.appName('combine_files').getOrCreate()
the files are in this dir
df=spark.read.parquet("s3://aws-emr-resources-359367213591-us-east-1/taxi_data_2020/*").coalesce(1)
df.count()
24649092
when I try to write (save the dataframe in parquet format in s3 folder)
df.write.parquet("s3://aws-emr-resources-359367213591-us-east-1/merged_data_2020/single")
it shows me this error, how i can solve it
An error was encountered:
An error occurred while calling o268.parquet.
: org.apache.spark.SparkException: Job aborted.
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:202)
at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand.run(InsertIntoHadoopFsRelationCommand.scala:174)
at org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult$lzycompute(commands.scala:104)
at org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult(commands.scala:102)
at org.apache.spark.sql.execution.command.DataWritingCommandExec.doExecute(commands.scala:122)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:178)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:174)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:202)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:199)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:174)
at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:114)
at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:112)
at org.apache.spark.sql.DataFrameWriter$$anonfun$runCommand$1.apply(DataFrameWriter.scala:696)
at org.apache.spark.sql.DataFrameWriter$$anonfun$runCommand$1.apply(DataFrameWriter.scala:696)
at org.apache.spark.sql.execution.SQLExecution$.org$apache$spark$sql$execution$SQLExecution$$executeQuery$1(SQLExecution.scala:83)
at org.apache.spark.sql.execution.SQLExecution$$anonfun$withNewExecutionId$1$$anonfun$apply$1.apply(SQLExecution.scala:94)
at org.apache.spark.sql.execution.QueryExecutionMetrics$.withMetrics(QueryExecutionMetrics.scala:141)
at org.apache.spark.sql.execution.SQLExecution$.org$apache$spark$sql$execution$SQLExecution$$withMetrics(SQLExecution.scala:178)
at org.apache.spark.sql.execution.SQLExecution$$anonfun$withNewExecutionId$1.apply(SQLExecution.scala:93)
at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:200)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:92)
at org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:696)
at org.apache.spark.sql.DataFrameWriter.saveToV1Source(DataFrameWriter.scala:305)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:291)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:249)
at org.apache.spark.sql.DataFrameWriter.parquet(DataFrameWriter.scala:586)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:282)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:238)
at java.lang.Thread.run(Thread.java:750)
Caused by: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 7.0 failed 4 times, most recent failure: Lost task 0.3 in stage 7.0 (TID 13, ip-172-31-75-44.ec2.internal, executor 6): org.apache.spark.SparkException: Task failed while writing rows.
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask(FileFormatWriter.scala:261)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1.apply(FileFormatWriter.scala:174)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1.apply(FileFormatWriter.scala:173)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:123)
at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:411)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1405)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:417)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:750)
Caused by: java.lang.UnsupportedOperationException: org.apache.parquet.column.values.dictionary.PlainValuesDictionary$PlainDoubleDictionary
at org.apache.parquet.column.Dictionary.decodeToInt(Dictionary.java:45)
at org.apache.spark.sql.execution.datasources.parquet.ParquetDictionary.decodeToInt(ParquetDictionary.java:31)
at org.apache.spark.sql.execution.vectorized.OnHeapColumnVector.getInt(OnHeapColumnVector.java:298)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$13$$anon$1.hasNext(WholeStageCodegenExec.scala:585)
at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:439)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask$3.apply(FileFormatWriter.scala:248)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask$3.apply(FileFormatWriter.scala:246)
at org.apache.spark.util.Utils$.tryWithSafeFinallyAndFailureCallbacks(Utils.scala:1439)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask(FileFormatWriter.scala:252)
... 10 more
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:2171)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:2159)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:2158)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2158)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:1011)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:1011)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1011)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2419)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2368)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2357)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:822)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2111)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:171)
... 37 more
Caused by: org.apache.spark.SparkException: Task failed while writing rows.
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask(FileFormatWriter.scala:261)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1.apply(FileFormatWriter.scala:174)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1.apply(FileFormatWriter.scala:173)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:123)
at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:411)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1405)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:417)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
... 1 more
Caused by: java.lang.UnsupportedOperationException: org.apache.parquet.column.values.dictionary.PlainValuesDictionary$PlainDoubleDictionary
at org.apache.parquet.column.Dictionary.decodeToInt(Dictionary.java:45)
at org.apache.spark.sql.execution.datasources.parquet.ParquetDictionary.decodeToInt(ParquetDictionary.java:31)
at org.apache.spark.sql.execution.vectorized.OnHeapColumnVector.getInt(OnHeapColumnVector.java:298)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$13$$anon$1.hasNext(WholeStageCodegenExec.scala:585)
at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:439)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask$3.apply(FileFormatWriter.scala:248)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask$3.apply(FileFormatWriter.scala:246)
at org.apache.spark.util.Utils$.tryWithSafeFinallyAndFailureCallbacks(Utils.scala:1439)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask(FileFormatWriter.scala:252)
... 10 more
Traceback (most recent call last):
File "/usr/lib/spark/python/lib/pyspark.zip/pyspark/sql/readwriter.py", line 847, in parquet
self._jwrite.parquet(path)
File "/usr/lib/spark/python/lib/py4j-0.10.7-src.zip/py4j/java_gateway.py", line 1257, in call
answer, self.gateway_client, self.target_id, self.name)
File "/usr/lib/spark/python/lib/pyspark.zip/pyspark/sql/utils.py", line 63, in deco
return f(*a, **kw)
File "/usr/lib/spark/python/lib/py4j-0.10.7-src.zip/py4j/protocol.py", line 328, in get_return_value
format(target_id, ".", name), value)
py4j.protocol.Py4JJavaError: An error occurred while calling o268.parquet.
: org.apache.spark.SparkException: Job aborted.
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:202)
at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand.run(InsertIntoHadoopFsRelationCommand.scala:174)
at org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult$lzycompute(commands.scala:104)
at org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult(commands.scala:102)
at org.apache.spark.sql.execution.command.DataWritingCommandExec.doExecute(commands.scala:122)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:178)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:174)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:202)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:199)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:174)
at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:114)
at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:112)
at org.apache.spark.sql.DataFrameWriter$$anonfun$runCommand$1.apply(DataFrameWriter.scala:696)
at org.apache.spark.sql.DataFrameWriter$$anonfun$runCommand$1.apply(DataFrameWriter.scala:696)
at org.apache.spark.sql.execution.SQLExecution$.org$apache$spark$sql$execution$SQLExecution$$executeQuery$1(SQLExecution.scala:83)
at org.apache.spark.sql.execution.SQLExecution$$anonfun$withNewExecutionId$1$$anonfun$apply$1.apply(SQLExecution.scala:94)
at org.apache.spark.sql.execution.QueryExecutionMetrics$.withMetrics(QueryExecutionMetrics.scala:141)
at org.apache.spark.sql.execution.SQLExecution$.org$apache$spark$sql$execution$SQLExecution$$withMetrics(SQLExecution.scala:178)
at org.apache.spark.sql.execution.SQLExecution$$anonfun$withNewExecutionId$1.apply(SQLExecution.scala:93)
at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:200)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:92)
at org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:696)
at org.apache.spark.sql.DataFrameWriter.saveToV1Source(DataFrameWriter.scala:305)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:291)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:249)
at org.apache.spark.sql.DataFrameWriter.parquet(DataFrameWriter.scala:586)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:282)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:238)
at java.lang.Thread.run(Thread.java:750)
Caused by: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 7.0 failed 4 times, most recent failure: Lost task 0.3 in stage 7.0 (TID 13, ip-172-31-75-44.ec2.internal, executor 6): org.apache.spark.SparkException: Task failed while writing rows.
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask(FileFormatWriter.scala:261)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1.apply(FileFormatWriter.scala:174)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1.apply(FileFormatWriter.scala:173)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:123)
at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:411)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1405)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:417)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:750)
Caused by: java.lang.UnsupportedOperationException: org.apache.parquet.column.values.dictionary.PlainValuesDictionary$PlainDoubleDictionary
at org.apache.parquet.column.Dictionary.decodeToInt(Dictionary.java:45)
at org.apache.spark.sql.execution.datasources.parquet.ParquetDictionary.decodeToInt(ParquetDictionary.java:31)
at org.apache.spark.sql.execution.vectorized.OnHeapColumnVector.getInt(OnHeapColumnVector.java:298)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$13$$anon$1.hasNext(WholeStageCodegenExec.scala:585)
at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:439)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask$3.apply(FileFormatWriter.scala:248)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask$3.apply(FileFormatWriter.scala:246)
at org.apache.spark.util.Utils$.tryWithSafeFinallyAndFailureCallbacks(Utils.scala:1439)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask(FileFormatWriter.scala:252)
... 10 more
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:2171)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:2159)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:2158)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2158)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:1011)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:1011)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1011)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2419)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2368)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2357)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:822)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2111)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:171)
... 37 more
Caused by: org.apache.spark.SparkException: Task failed while writing rows.
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask(FileFormatWriter.scala:261)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1.apply(FileFormatWriter.scala:174)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1.apply(FileFormatWriter.scala:173)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:123)
at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:411)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1405)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:417)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
... 1 more
Caused by: java.lang.UnsupportedOperationException: org.apache.parquet.column.values.dictionary.PlainValuesDictionary$PlainDoubleDictionary
at org.apache.parquet.column.Dictionary.decodeToInt(Dictionary.java:45)
at org.apache.spark.sql.execution.datasources.parquet.ParquetDictionary.decodeToInt(ParquetDictionary.java:31)
at org.apache.spark.sql.execution.vectorized.OnHeapColumnVector.getInt(OnHeapColumnVector.java:298)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$13$$anon$1.hasNext(WholeStageCodegenExec.scala:585)
at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:439)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask$3.apply(FileFormatWriter.scala:248)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask$3.apply(FileFormatWriter.scala:246)
at org.apache.spark.util.Utils$.tryWithSafeFinallyAndFailureCallbacks(Utils.scala:1439)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask(FileFormatWriter.scala:252)
... 10 more
df.write.parquet("s3a://aws-emr-resources-359367213591-us-east-1/merged_data_2020/single")
This is a Production code running fine until last week. Then, this parquet write error showed up and never getting resolved.
While writing to AWS S3 in parquet format, I tried several dataframe.repartitions(300) - 300, 500, 2400, 6000. But no luck. The code by itself runs fine, but some times gives count error if I add a count() on a dataframe. (intermittently).
So I removed all the count()s in the code to run the code without errors. Now, It fails while writing to the AWS s3 location.
The code is running on Databricks notebook - Databricks Runtime Version
8.3 (includes Apache Spark 3.1.1, Scala 2.12). The code is written in pyspark(python 3.8). The code runs on AWS r5.8xlarge instances.
I am stuck with this, any help is very much appreciated.
Py4JJavaError Traceback (most recent call last)
<command-2026517708936858> in <module>
3
4 #save data_agg for next step
----> 5 dataframe.repartition(6000).write.parquet(s3://path_to_write, mode='overwrite')
/databricks/spark/python/pyspark/sql/readwriter.py in parquet(self, path, mode, partitionBy, compression)
1275 self.partitionBy(partitionBy)
1276 self._set_opts(compression=compression)
-> 1277 self._jwrite.parquet(path)
1278
1279 def text(self, path, compression=None, lineSep=None):
/databricks/spark/python/lib/py4j-0.10.9-src.zip/py4j/java_gateway.py in __call__(self, *args)
1302
1303 answer = self.gateway_client.send_command(command)
-> 1304 return_value = get_return_value(
1305 answer, self.gateway_client, self.target_id, self.name)
1306
/databricks/spark/python/pyspark/sql/utils.py in deco(*a, **kw)
115 def deco(*a, **kw):
116 try:
--> 117 return f(*a, **kw)
118 except py4j.protocol.Py4JJavaError as e:
119 converted = convert_exception(e.java_exception)
/databricks/spark/python/lib/py4j-0.10.9-src.zip/py4j/protocol.py in get_return_value(answer, gateway_client, target_id, name)
324 value = OUTPUT_CONVERTER[type](answer[2:], gateway_client)
325 if answer[1] == REFERENCE_TYPE:
--> 326 raise Py4JJavaError(
327 "An error occurred while calling {0}{1}{2}.\n".
328 format(target_id, ".", name), value)
Py4JJavaError: An error occurred while calling o1773.parquet.
: org.apache.spark.SparkException: Job aborted.
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:289)
at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand.run(InsertIntoHadoopFsRelationCommand.scala:203)
at org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult$lzycompute(commands.scala:121)
at org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult(commands.scala:119)
at org.apache.spark.sql.execution.command.DataWritingCommandExec.doExecute(commands.scala:144)
at org.apache.spark.sql.execution.SparkPlan.$anonfun$execute$1(SparkPlan.scala:196)
at org.apache.spark.sql.execution.SparkPlan.$anonfun$executeQuery$1(SparkPlan.scala:240)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:165)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:236)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:192)
at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:167)
at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:166)
at org.apache.spark.sql.DataFrameWriter.$anonfun$runCommand$1(DataFrameWriter.scala:1079)
at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withCustomExecutionEnv$5(SQLExecution.scala:126)
at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:267)
at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withCustomExecutionEnv$1(SQLExecution.scala:104)
at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:852)
at org.apache.spark.sql.execution.SQLExecution$.withCustomExecutionEnv(SQLExecution.scala:77)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:217)
at org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:1079)
at org.apache.spark.sql.DataFrameWriter.saveToV1Source(DataFrameWriter.scala:468)
at org.apache.spark.sql.DataFrameWriter.saveInternal(DataFrameWriter.scala:438)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:303)
at org.apache.spark.sql.DataFrameWriter.parquet(DataFrameWriter.scala:964)
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:380)
at py4j.Gateway.invoke(Gateway.java:295)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:251)
at java.lang.Thread.run(Thread.java:748)
Caused by: org.apache.spark.SparkException: Multiple failures in stage materialization.
at org.apache.spark.sql.execution.adaptive.AdaptiveSparkPlanExec.cleanUpAndThrowException(AdaptiveSparkPlanExec.scala:838)
at org.apache.spark.sql.execution.adaptive.AdaptiveSparkPlanExec.$anonfun$getFinalPhysicalPlan$1(AdaptiveSparkPlanExec.scala:321)
at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:852)
at org.apache.spark.sql.execution.adaptive.AdaptiveSparkPlanExec.getFinalPhysicalPlan(AdaptiveSparkPlanExec.scala:276)
at org.apache.spark.sql.execution.adaptive.AdaptiveSparkPlanExec.doExecute(AdaptiveSparkPlanExec.scala:378)
at org.apache.spark.sql.execution.SparkPlan.$anonfun$execute$1(SparkPlan.scala:196)
at org.apache.spark.sql.execution.SparkPlan.$anonfun$executeQuery$1(SparkPlan.scala:240)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:165)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:236)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:192)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:233)
... 34 more
Suppressed: org.apache.spark.SparkException: Job aborted due to stage failure: ShuffleMapStage 46 (parquet at NativeMethodAccessorImpl.java:0) has failed the maximum allowable number of times: 4. Most recent failure reason: org.apache.spark.shuffle.FetchFailedException: Connecting to /100.64.19.5:4048 failed in the last 4750 ms, fail this connection directly
at org.apache.spark.storage.ShuffleBlockFetcherIterator.throwFetchFailedException(ShuffleBlockFetcherIterator.scala:771)
at org.apache.spark.storage.ShuffleBlockFetcherIterator.$anonfun$next$1(ShuffleBlockFetcherIterator.scala:686)
at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110)
at org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:577)
at org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:70)
at org.apache.spark.util.CompletionIterator.next(CompletionIterator.scala:29) at scala.collection.Iterator$$anon$11.nextCur(Iterator.scala:484)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:490)
at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:458)
at org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:31)
at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:458)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage14.agg_doAggregateWithKeys_0$(Unknown Source)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage14.sort_addToSorter_0$(Unknown Source)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage14.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:757)
at org.apache.spark.sql.execution.RowIteratorFromScala.advanceNext(RowIterator.scala:83)
at org.apache.spark.sql.execution.joins.SortMergeFullOuterJoinScanner.advancedLeft(SortMergeJoinExec.scala:1088)
at org.apache.spark.sql.execution.joins.SortMergeFullOuterJoinScanner.<init>(SortMergeJoinExec.scala:1078)
at org.apache.spark.sql.execution.joins.SortMergeJoinExec.$anonfun$doExecute$1(SortMergeJoinExec.scala:222)
at org.apache.spark.rdd.ZippedPartitionsRDD2.compute(ZippedPartitionsRDD.scala:125)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:380) at org.apache.spark.rdd.RDD.iterator(RDD.scala:344)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:60)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:380)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:344)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:60)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:380)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:344)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:60)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:380)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:344)
at org.apache.spark.shuffle.ShuffleWriteProcessor.write(ShuffleWriteProcessor.scala:59)
at org.apache.spark.scheduler.ShuffleMapTask.$anonfun$runTask$3(ShuffleMapTask.scala:81)
at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110)
at org.apache.spark.scheduler.ShuffleMapTask.$anonfun$runTask$1(ShuffleMapTask.scala:81)
at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
at org.apache.spark.scheduler.Task.doRunTask(Task.scala:150)
at org.apache.spark.scheduler.Task.$anonfun$run$1(Task.scala:119)
at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110)
at org.apache.spark.scheduler.Task.run(Task.scala:91)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$13(Executor.scala:812)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1643)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$4(Executor.scala:815)
at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:671)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Caused by: java.io.IOException: Connecting to /100.64.19.5:4048 failed in the last 4750 ms, fail this connection directly
at org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:214)
at org.apache.spark.network.shuffle.ExternalBlockStoreClient.lambda$fetchBlocks$0(ExternalBlockStoreClient.java:101)
at org.apache.spark.network.shuffle.RetryingBlockFetcher.fetchAllOutstanding(RetryingBlockFetcher.java:153)
at org.apache.spark.network.shuffle.RetryingBlockFetcher.lambda$initiateRetry$0(RetryingBlockFetcher.java:181)
at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511) at java.util.concurrent.FutureTask.run(FutureTask.java:266)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at io.netty.util.concurrent.FastThreadLocalRunnable.run(FastThreadLocalRunnable.java:30)
... 1 more
at org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2765)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2712)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2706)
at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2706)
at org.apache.spark.scheduler.DAGScheduler.handleTaskCompletion(DAGScheduler.scala:2263)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2970)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2914)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2902)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
Suppressed: [CIRCULAR REFERENCE: org.apache.spark.SparkException: Job aborted due to stage failure: ShuffleMapStage 46 (parquet at NativeMethodAccessorImpl.java:0) has failed the maximum allowable number of times: 4. Most recent failure reason: org.apache.spark.shuffle.FetchFailedException: Connecting to /100.64.19.5:4048 failed in the last 4750 ms, fail this connection directly at org.apache.spark.storage.ShuffleBlockFetcherIterator.throwFetchFailedException(ShuffleBlockFetcherIterator.scala:771) at org.apache.spark.storage.ShuffleBlockFetcherIterator.$anonfun$next$1(ShuffleBlockFetcherIterator.scala:686) at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110) at org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:577) at org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:70) at org.apache.spark.util.CompletionIterator.next(CompletionIterator.scala:29) at scala.collection.Iterator$$anon$11.nextCur(Iterator.scala:484) at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:490) at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:458) at org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:31) at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37) at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:458) at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage14.agg_doAggregateWithKeys_0$(Unknown Source) at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage14.sort_addToSorter_0$(Unknown Source) at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage14.processNext(Unknown Source) at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:757) at org.apache.spark.sql.execution.RowIteratorFromScala.advanceNext(RowIterator.scala:83) at org.apache.spark.sql.execution.joins.SortMergeFullOuterJoinScanner.advancedLeft(SortMergeJoinExec.scala:1088) at org.apache.spark.sql.execution.joins.SortMergeFullOuterJoinScanner.<init>(SortMergeJoinExec.scala:1078) at org.apache.spark.sql.execution.joins.SortMergeJoinExec.$anonfun$doExecute$1(SortMergeJoinExec.scala:222) at org.apache.spark.rdd.ZippedPartitionsRDD2.compute(ZippedPartitionsRDD.scala:125) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:380) at org.apache.spark.rdd.RDD.iterator(RDD.scala:344) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:60) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:380) at org.apache.spark.rdd.RDD.iterator(RDD.scala:344) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:60) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:380) at org.apache.spark.rdd.RDD.iterator(RDD.scala:344) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:60) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:380) at org.apache.spark.rdd.RDD.iterator(RDD.scala:344) at org.apache.spark.shuffle.ShuffleWriteProcessor.write(ShuffleWriteProcessor.scala:59) at org.apache.spark.scheduler.ShuffleMapTask.$anonfun$runTask$3(ShuffleMapTask.scala:81) at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110) at org.apache.spark.scheduler.ShuffleMapTask.$anonfun$runTask$1(ShuffleMapTask.scala:81) at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110) at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53) at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41) at org.apache.spark.scheduler.Task.doRunTask(Task.scala:150) at org.apache.spark.scheduler.Task.$anonfun$run$1(Task.scala:119) at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110) at org.apache.spark.scheduler.Task.run(Task.scala:91) at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$13(Executor.scala:812) at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1643) at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$4(Executor.scala:815) at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23) at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:671) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) at java.lang.Thread.run(Thread.java:748) Caused by: java.io.IOException: Connecting to /100.64.19.5:4048 failed in the last 4750 ms, fail this connection directly at org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:214) at org.apache.spark.network.shuffle.ExternalBlockStoreClient.lambda$fetchBlocks$0(ExternalBlockStoreClient.java:101) at org.apache.spark.network.shuffle.RetryingBlockFetcher.fetchAllOutstanding(RetryingBlockFetcher.java:153) at org.apache.spark.network.shuffle.RetryingBlockFetcher.lambda$initiateRetry$0(RetryingBlockFetcher.java:181) at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511) at java.util.concurrent.FutureTask.run(FutureTask.java:266) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) at io.netty.util.concurrent.FastThreadLocalRunnable.run(FastThreadLocalRunnable.java:30) ... 1 more ]
I am getting the following error due to stage materialization.
Connect timed out. Verify the connection properties. Make sure that an
instance of SQL Server is running on the host and accepting TCP/IP
connections at the port. Make sure that TCP connections to the port are not
blocked by a firewall.
Stage materialization may happen due to connection issues at intermediate stages where a connection required to be established may have broken.
In case it helps: Are you using .checkpoint or .local_checkpoint? I was facing a similar issue (stage materialization) and found it helpful:
If this problem persists, you may consider using rdd.checkpoint() instead, which is slower than local checkpointing but more fault-tolerant.
I'm trying to export a table I crawled from a postgres(rds) database into glue. There's one field with a decimal(10, 2) type. Now I have several problems.
Exporting the table from glue(using spark 2.4, 3.1 python 3) into s3 with the following code:
datasource = glueContext.create_dynamic_frame.from_catalog(
database='source_database',
table_name='table',
)
glueContext.write_dynamic_frame.from_options(
frame=datasource,
connection_type="s3",
connection_options={"path": "s3//..."},
format='parquet',
)
Results in the error:
py4j.protocol.Py4JJavaError: An error occurred while calling o89.pyWriteDynamicFrame.
: org.apache.spark.SparkException: Job aborted.
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:231)
at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand.run(InsertIntoHadoopFsRelationCommand.scala:195)
at org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult$lzycompute(commands.scala:108)
at org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult(commands.scala:106)
at org.apache.spark.sql.execution.command.DataWritingCommandExec.doExecute(commands.scala:131)
at org.apache.spark.sql.execution.SparkPlan.$anonfun$execute$1(SparkPlan.scala:185)
at org.apache.spark.sql.execution.SparkPlan.$anonfun$executeQuery$1(SparkPlan.scala:223)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:220)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:181)
at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:134)
at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:133)
at org.apache.spark.sql.DataFrameWriter.$anonfun$runCommand$1(DataFrameWriter.scala:989)
at org.apache.spark.sql.catalyst.QueryPlanningTracker$.withTracker(QueryPlanningTracker.scala:107)
at org.apache.spark.sql.execution.SQLExecution$.withTracker(SQLExecution.scala:232)
at org.apache.spark.sql.execution.SQLExecution$.executeQuery$1(SQLExecution.scala:110)
at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$6(SQLExecution.scala:135)
at org.apache.spark.sql.catalyst.QueryPlanningTracker$.withTracker(QueryPlanningTracker.scala:107)
at org.apache.spark.sql.execution.SQLExecution$.withTracker(SQLExecution.scala:232)
at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$5(SQLExecution.scala:135)
at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:253)
at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:134)
at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:772)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:68)
at org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:989)
at org.apache.spark.sql.DataFrameWriter.saveToV1Source(DataFrameWriter.scala:438)
at org.apache.spark.sql.DataFrameWriter.saveInternal(DataFrameWriter.scala:415)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:301)
at com.amazonaws.services.glue.SparkSQLDataSink.$anonfun$writeDynamicFrame$3(DataSink.scala:595)
at com.amazonaws.services.glue.SparkSQLDataSink.$anonfun$writeDynamicFrame$3$adapted(DataSink.scala:582)
at com.amazonaws.services.glue.util.FileSchemeWrapper.$anonfun$executeWithQualifiedScheme$1(FileSchemeWrapper.scala:77)
at com.amazonaws.services.glue.util.FileSchemeWrapper.executeWith(FileSchemeWrapper.scala:70)
at com.amazonaws.services.glue.util.FileSchemeWrapper.executeWithQualifiedScheme(FileSchemeWrapper.scala:77)
at com.amazonaws.services.glue.SparkSQLDataSink.writeDynamicFrame(DataSink.scala:582)
at com.amazonaws.services.glue.DataSink.pyWriteDynamicFrame(DataSink.scala:64)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:282)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:238)
at java.lang.Thread.run(Thread.java:748)
Caused by: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 0.0 failed 4 times, most recent failure: Lost task 0.3 in stage 0.0 (TID 3) (172.31.12.229 executor 1): org.postgresql.util.PSQLException: Bad value for type BigDecimal : NaN
at org.postgresql.jdbc.PgResultSet.toBigDecimal(PgResultSet.java:3059)
at org.postgresql.jdbc.PgResultSet.toBigDecimal(PgResultSet.java:3068)
at org.postgresql.jdbc.PgResultSet.getNumeric(PgResultSet.java:2486)
at org.postgresql.jdbc.PgResultSet.getBigDecimal(PgResultSet.java:2438)
at org.postgresql.jdbc.PgResultSet.getBigDecimal(PgResultSet.java:406)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$makeGetter$3(JdbcUtils.scala:403)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$makeGetter$3$adapted(JdbcUtils.scala:401)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anon$1.getNext(JdbcUtils.scala:352)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anon$1.getNext(JdbcUtils.scala:334)
at org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:73)
at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
at org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:31)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:755)
at org.apache.spark.sql.execution.UnsafeExternalRowSorter.sort(UnsafeExternalRowSorter.java:225)
at org.apache.spark.sql.execution.exchange.ShuffleExchangeExec$.$anonfun$prepareShuffleDependency$10(ShuffleExchangeExec.scala:379)
at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:898)
at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:898)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:337)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:337)
at org.apache.spark.shuffle.ShuffleWriteProcessor.write(ShuffleWriteProcessor.scala:59)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:52)
at org.apache.spark.scheduler.Task.run(Task.scala:131)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:497)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:500)
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.failJobAndIndependentStages(DAGScheduler.scala:2465)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2414)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2413)
at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2413)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:1124)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:1124)
at scala.Option.foreach(Option.scala:407)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1124)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2679)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2621)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2610)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:914)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2238)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:200)
... 45 more
Caused by: org.postgresql.util.PSQLException: Bad value for type BigDecimal : NaN
at org.postgresql.jdbc.PgResultSet.toBigDecimal(PgResultSet.java:3059)
at org.postgresql.jdbc.PgResultSet.toBigDecimal(PgResultSet.java:3068)
at org.postgresql.jdbc.PgResultSet.getNumeric(PgResultSet.java:2486)
at org.postgresql.jdbc.PgResultSet.getBigDecimal(PgResultSet.java:2438)
at org.postgresql.jdbc.PgResultSet.getBigDecimal(PgResultSet.java:406)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$makeGetter$3(JdbcUtils.scala:403)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$makeGetter$3$adapted(JdbcUtils.scala:401)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anon$1.getNext(JdbcUtils.scala:352)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anon$1.getNext(JdbcUtils.scala:334)
at org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:73)
at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
at org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:31)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:755)
at org.apache.spark.sql.execution.UnsafeExternalRowSorter.sort(UnsafeExternalRowSorter.java:225)
at org.apache.spark.sql.execution.exchange.ShuffleExchangeExec$.$anonfun$prepareShuffleDependency$10(ShuffleExchangeExec.scala:379)
at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:898)
at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:898)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:337)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:337)
at org.apache.spark.shuffle.ShuffleWriteProcessor.write(ShuffleWriteProcessor.scala:59)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:52)
at org.apache.spark.scheduler.Task.run(Task.scala:131)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:497)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:500)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
... 1 more
2021-09-13 09:52:47,872 ERROR [main] glue.ProcessLauncher "/opt/amazon/lib/python3.6/site-packages/awsglue/context.py", line 277, in write_dynamic_frame_from_options format, format_options, transformation_ctx) File "/opt/amazon/lib/python3.6/site-packages/awsglue/context.py", line 300, in write_from_options return sink.write(frame_or_dfc) File "/opt/amazon/lib/python3.6/site-packages/awsglue/data_sink.py", line 35, in write return self.writeFrame(dynamic_frame_or_dfc, info) File "/opt/amazon/lib/python3.6/site-packages/awsglue/data_sink.py", line 31, in writeFrame return DynamicFrame(self._jsink.pyWriteDynamicFrame(dynamic_frame._jdf, callsite(), info), dynamic_frame.glue_ctx, dynamic_frame.name + "_errors") File "/opt/amazon/spark/python/lib/py4j-0.10.9-src.zip/py4j/java_gateway.py", line 1305, in __call__ answer, self.gateway_client, self.target_id, self.name) File "/opt/amazon/spark/python/lib/pyspark.zip/pyspark/sql/utils.py", line 111, in deco return f(*a, **kw) File "/opt/amazon/spark/python/lib/py4j-0.10.9-src.zip/py4j/protocol.py", line 328, in get_return_value format(target_id, ".", name), value) py4j.protocol.Py4JJavaError: An error occurred while calling o89.pyWriteDynamicFrame. : org.apache.spark.SparkException: Job aborted. at org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:231) at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand.run(InsertIntoHadoopFsRelationCommand.scala:195) at org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult$lzycompute(commands.scala:108) at org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult(commands.scala:106) at org.apache.spark.sql.execution.command.DataWritingCommandExec.doExecute(commands.scala:131) at org.apache.spark.sql.execution.SparkPlan.$anonfun$execute$1(SparkPlan.scala:185) at org.apache.spark.sql.execution.SparkPlan.$anonfun$executeQuery$1(SparkPlan.scala:223) at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151) at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:220) at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:181) at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:134) at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:133) at org.apache.spark.sql.DataFrameWriter.$anonfun$runCommand$1(DataFrameWriter.scala:989) at org.apache.spark.sql.catalyst.QueryPlanningTracker$.withTracker(QueryPlanningTracker.scala:107) at org.apache.spark.sql.execution.SQLExecution$.withTracker(SQLExecution.scala:232) at org.apache.spark.sql.execution.SQLExecution$.executeQuery$1(SQLExecution.scala:110) at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$6(SQLExecution.scala:135) at org.apache.spark.sql.catalyst.QueryPlanningTracker$.withTracker(QueryPlanningTracker.scala:107) at org.apache.spark.sql.execution.SQLExecution$.withTracker(SQLExecution.scala:232) at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$5(SQLExecution.scala:135) at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:253) at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:134) at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:772) at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:68) at org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:989) at org.apache.spark.sql.DataFrameWriter.saveToV1Source(DataFrameWriter.scala:438) at org.apache.spark.sql.DataFrameWriter.saveInternal(DataFrameWriter.scala:415) at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:301) at com.amazonaws.services.glue.SparkSQLDataSink.$anonfun$writeDynamicFrame$3(DataSink.scala:595) at com.amazonaws.services.glue.SparkSQLDataSink.$anonfun$writeDynamicFrame$3$adapted(DataSink.scala:582) at com.amazonaws.services.glue.util.FileSchemeWrapper.$anonfun$executeWithQualifiedScheme$1(FileSchemeWrapper.scala:77) at com.amazonaws.services.glue.util.FileSchemeWrapper.executeWith(FileSchemeWrapper.scala:70) at com.amazonaws.services.glue.util.FileSchemeWrapper.executeWithQualifiedScheme(FileSchemeWrapper.scala:77) at com.amazonaws.services.glue.SparkSQLDataSink.writeDynamicFrame(DataSink.scala:582) at com.amazonaws.services.glue.DataSink.pyWriteDynamicFrame(DataSink.scala:64) 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: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 0.0 failed 4 times, most recent failure: Lost task 0.3 in stage 0.0 (TID 3) (172.31.12.229 executor 1): org.postgresql.util.PSQLException: Bad value for type BigDecimal : NaN at org.postgresql.jdbc.PgResultSet.toBigDecimal(PgResultSet.java:3059) at org.postgresql.jdbc.PgResultSet.toBigDecimal(PgResultSet.java:3068) at org.postgresql.jdbc.PgResultSet.getNumeric(PgResultSet.java:2486) at org.postgresql.jdbc.PgResultSet.getBigDecimal(PgResultSet.java:2438) at org.postgresql.jdbc.PgResultSet.getBigDecimal(PgResultSet.java:406) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$makeGetter$3(JdbcUtils.scala:403) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$makeGetter$3$adapted(JdbcUtils.scala:401) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anon$1.getNext(JdbcUtils.scala:352) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anon$1.getNext(JdbcUtils.scala:334) at org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:73) at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37) at org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:31) at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source) at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:755) at org.apache.spark.sql.execution.UnsafeExternalRowSorter.sort(UnsafeExternalRowSorter.java:225) at org.apache.spark.sql.execution.exchange.ShuffleExchangeExec$.$anonfun$prepareShuffleDependency$10(ShuffleExchangeExec.scala:379) at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:898) at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:898) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373) at org.apache.spark.rdd.RDD.iterator(RDD.scala:337) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373) at org.apache.spark.rdd.RDD.iterator(RDD.scala:337) at org.apache.spark.shuffle.ShuffleWriteProcessor.write(ShuffleWriteProcessor.scala:59) at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99) at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:52) at org.apache.spark.scheduler.Task.run(Task.scala:131) at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:497) at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:500) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) at java.lang.Thread.run(Thread.java:748) Driver stacktrace: at org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2465) at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2414) at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2413) at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62) at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55) at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49) at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2413) at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:1124) at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:1124) at scala.Option.foreach(Option.scala:407) at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1124) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2679) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2621) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2610) at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49) at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:914) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2238) at org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:200) ... 45 more Caused by: org.postgresql.util.PSQLException: Bad value for type BigDecimal : NaN at org.postgresql.jdbc.PgResultSet.toBigDecimal(PgResultSet.java:3059) at org.postgresql.jdbc.PgResultSet.toBigDecimal(PgResultSet.java:3068) at org.postgresql.jdbc.PgResultSet.getNumeric(PgResultSet.java:2486) at org.postgresql.jdbc.PgResultSet.getBigDecimal(PgResultSet.java:2438) at org.postgresql.jdbc.PgResultSet.getBigDecimal(PgResultSet.java:406) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$makeGetter$3(JdbcUtils.scala:403) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$makeGetter$3$adapted(JdbcUtils.scala:401) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anon$1.getNext(JdbcUtils.scala:352) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anon$1.getNext(JdbcUtils.scala:334) at org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:73) at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37) at org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:31) at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source) at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:755) at org.apache.spark.sql.execution.UnsafeExternalRowSorter.sort(UnsafeExternalRowSorter.java:225) at org.apache.spark.sql.execution.exchange.ShuffleExchangeExec$.$anonfun$prepareShuffleDependency$10(ShuffleExchangeExec.scala:379) at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:898) at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:898) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373) at org.apache.spark.rdd.RDD.iterator(RDD.scala:337) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373) at org.apache.spark.rdd.RDD.iterator(RDD.scala:337) at org.apache.spark.shuffle.ShuffleWriteProcessor.write(ShuffleWriteProcessor.scala:59) at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99) at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:52) at org.apache.spark.scheduler.Task.run(Task.scala:131) at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:497) at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:500) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) ... 1 more
I also changed the datatype of the field with this decimal type(within the glue catalog) to a double within the catalog to a double but glue(spark) seems to pick the original schema of the table.
There's a similar post to this mine but I don't have direct access to call the .getDouble() method since I'm not interfacing with the java/scala code within glue.
How can I resolve this?
If any of the column have 'NaN' value in table, then it will show 'AWS Glue Bad value for type BigDecimal : NaN' error while trying to create frame.
I am new in Spark, and I have some problems to register informations in a file.
The problem is the following:
I have declared the avglens RDD with the following command:
var avglens = sc.textFile("C:/Program Files/spark-3.1.1-bin-hadoop2.7/README.md")
.flatMap(line => line.split(' '))
.map(word => (word(0), word.length))
.groupByKey()
.map(pair => (pair._1, pair._2.sum/pair._2.size.toDouble))
then, I wanted to save informations of my avglens RDD in a new file named avglens-output.
To do that, I have launched the following command:
avglens.saveAsTextFile("avglen-output")
But, it returns the following error:
21/06/17 13:15:44 ERROR Executor: Exception in task 1.0 in stage 0.0 (TID 1)/ 2]
java.lang.StringIndexOutOfBoundsException: String index out of range: 0
at java.lang.String.charAt(String.java:658)
at scala.collection.immutable.StringOps$.apply$extension(StringOps.scala:41)
at $line14.$read$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw.$anonfun$avglens$2(<console>:24)
at scala.collection.Iterator$$anon$10.next(Iterator.scala:459)
at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:156)
at org.apache.spark.shuffle.ShuffleWriteProcessor.write(ShuffleWriteProcessor.scala:59)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:52)
at org.apache.spark.scheduler.Task.run(Task.scala:131)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:497)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:500)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
21/06/17 13:15:44 WARN TaskSetManager: Lost task 1.0 in stage 0.0 (TID 1) (192.168.1.20 executor driver): java.lang.StringIndexOutOfBoundsException: String index out of range: 0
at java.lang.String.charAt(String.java:658)
at scala.collection.immutable.StringOps$.apply$extension(StringOps.scala:41)
at $line14.$read$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw.$anonfun$avglens$2(<console>:24)
at scala.collection.Iterator$$anon$10.next(Iterator.scala:459)
at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:156)
at org.apache.spark.shuffle.ShuffleWriteProcessor.write(ShuffleWriteProcessor.scala:59)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:52)
at org.apache.spark.scheduler.Task.run(Task.scala:131)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:497)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:500)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
21/06/17 13:15:44 ERROR TaskSetManager: Task 1 in stage 0.0 failed 1 times; aborting job
21/06/17 13:15:44 ERROR SparkHadoopWriter: Aborting job job_202106171315432560914192953511091_0007.
org.apache.spark.SparkException: Job aborted due to stage failure: Task 1 in stage 0.0 failed 1 times, most recent failure: Lost task 1.0 in stage 0.0 (TID 1) (192.168.1.20 executor driver): java.lang.StringIndexOutOfBoundsException: String index out of range: 0
at java.lang.String.charAt(String.java:658)
at scala.collection.immutable.StringOps$.apply$extension(StringOps.scala:41)
at $line14.$read$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw.$anonfun$avglens$2(<console>:24)
at scala.collection.Iterator$$anon$10.next(Iterator.scala:459)
at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:156)
at org.apache.spark.shuffle.ShuffleWriteProcessor.write(ShuffleWriteProcessor.scala:59)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:52)
at org.apache.spark.scheduler.Task.run(Task.scala:131)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:497)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:500)
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.failJobAndIndependentStages(DAGScheduler.scala:2253)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2202)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2201)
at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2201)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:1078)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:1078)
at scala.Option.foreach(Option.scala:407)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1078)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2440)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2382)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2371)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:868)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2202)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2223)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2255)
at org.apache.spark.internal.io.SparkHadoopWriter$.write(SparkHadoopWriter.scala:83)
at org.apache.spark.rdd.PairRDDFunctions.$anonfun$saveAsHadoopDataset$1(PairRDDFunctions.scala:1090)
at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:414)
at org.apache.spark.rdd.PairRDDFunctions.saveAsHadoopDataset(PairRDDFunctions.scala:1088)
at org.apache.spark.rdd.PairRDDFunctions.$anonfun$saveAsHadoopFile$4(PairRDDFunctions.scala:1061)
at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:414)
at org.apache.spark.rdd.PairRDDFunctions.saveAsHadoopFile(PairRDDFunctions.scala:1026)
at org.apache.spark.rdd.PairRDDFunctions.$anonfun$saveAsHadoopFile$3(PairRDDFunctions.scala:1008)
at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:414)
at org.apache.spark.rdd.PairRDDFunctions.saveAsHadoopFile(PairRDDFunctions.scala:1007)
at org.apache.spark.rdd.PairRDDFunctions.$anonfun$saveAsHadoopFile$2(PairRDDFunctions.scala:964)
at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:414)
at org.apache.spark.rdd.PairRDDFunctions.saveAsHadoopFile(PairRDDFunctions.scala:962)
at org.apache.spark.rdd.RDD.$anonfun$saveAsTextFile$2(RDD.scala:1578)
at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:414)
at org.apache.spark.rdd.RDD.saveAsTextFile(RDD.scala:1578)
at org.apache.spark.rdd.RDD.$anonfun$saveAsTextFile$1(RDD.scala:1564)
at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:414)
at org.apache.spark.rdd.RDD.saveAsTextFile(RDD.scala:1564)
at $line18.$read$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw.<init>(<console>:26)
at $line18.$read$$iw$$iw$$iw$$iw$$iw$$iw$$iw.<init>(<console>:30)
at $line18.$read$$iw$$iw$$iw$$iw$$iw$$iw.<init>(<console>:32)
at $line18.$read$$iw$$iw$$iw$$iw$$iw.<init>(<console>:34)
at $line18.$read$$iw$$iw$$iw$$iw.<init>(<console>:36)
at $line18.$read$$iw$$iw$$iw.<init>(<console>:38)
at $line18.$read$$iw$$iw.<init>(<console>:40)
at $line18.$read$$iw.<init>(<console>:42)
at $line18.$read.<init>(<console>:44)
at $line18.$read$.<init>(<console>:48)
at $line18.$read$.<clinit>(<console>)
at $line18.$eval$.$print$lzycompute(<console>:7)
at $line18.$eval$.$print(<console>:6)
at $line18.$eval.$print(<console>)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at scala.tools.nsc.interpreter.IMain$ReadEvalPrint.call(IMain.scala:745)
at scala.tools.nsc.interpreter.IMain$Request.loadAndRun(IMain.scala:1021)
at scala.tools.nsc.interpreter.IMain.$anonfun$interpret$1(IMain.scala:574)
at scala.reflect.internal.util.ScalaClassLoader.asContext(ScalaClassLoader.scala:41)
at scala.reflect.internal.util.ScalaClassLoader.asContext$(ScalaClassLoader.scala:37)
at scala.reflect.internal.util.AbstractFileClassLoader.asContext(AbstractFileClassLoader.scala:41)
at scala.tools.nsc.interpreter.IMain.loadAndRunReq$1(IMain.scala:573)
at scala.tools.nsc.interpreter.IMain.interpret(IMain.scala:600)
at scala.tools.nsc.interpreter.IMain.interpret(IMain.scala:570)
at scala.tools.nsc.interpreter.ILoop.interpretStartingWith(ILoop.scala:894)
at scala.tools.nsc.interpreter.ILoop.command(ILoop.scala:762)
at scala.tools.nsc.interpreter.ILoop.processLine(ILoop.scala:464)
at scala.tools.nsc.interpreter.ILoop.loop(ILoop.scala:485)
at org.apache.spark.repl.SparkILoop.process(SparkILoop.scala:239)
at org.apache.spark.repl.Main$.doMain(Main.scala:78)
at org.apache.spark.repl.Main$.main(Main.scala:58)
at org.apache.spark.repl.Main.main(Main.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.spark.deploy.JavaMainApplication.start(SparkApplication.scala:52)
at org.apache.spark.deploy.SparkSubmit.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:951)
at org.apache.spark.deploy.SparkSubmit.doRunMain$1(SparkSubmit.scala:180)
at org.apache.spark.deploy.SparkSubmit.submit(SparkSubmit.scala:203)
at org.apache.spark.deploy.SparkSubmit.doSubmit(SparkSubmit.scala:90)
at org.apache.spark.deploy.SparkSubmit$$anon$2.doSubmit(SparkSubmit.scala:1030)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:1039)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
Caused by: java.lang.StringIndexOutOfBoundsException: String index out of range: 0
at java.lang.String.charAt(String.java:658)
at scala.collection.immutable.StringOps$.apply$extension(StringOps.scala:41)
at $line14.$read$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw.$anonfun$avglens$2(<console>:24)
at scala.collection.Iterator$$anon$10.next(Iterator.scala:459)
at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:156)
at org.apache.spark.shuffle.ShuffleWriteProcessor.write(ShuffleWriteProcessor.scala:59)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:52)
at org.apache.spark.scheduler.Task.run(Task.scala:131)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:497)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:500)
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)
21/06/17 13:15:44 WARN TaskSetManager: Lost task 0.0 in stage 0.0 (TID 0) (192.168.1.20 executor driver): TaskKilled (Stage cancelled)
org.apache.spark.SparkException: Job aborted.
at org.apache.spark.internal.io.SparkHadoopWriter$.write(SparkHadoopWriter.scala:105)
at org.apache.spark.rdd.PairRDDFunctions.$anonfun$saveAsHadoopDataset$1(PairRDDFunctions.scala:1090)
at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
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:414)
at org.apache.spark.rdd.PairRDDFunctions.saveAsHadoopDataset(PairRDDFunctions.scala:1088)
at org.apache.spark.rdd.PairRDDFunctions.$anonfun$saveAsHadoopFile$4(PairRDDFunctions.scala:1061)
at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
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:414)
at org.apache.spark.rdd.PairRDDFunctions.saveAsHadoopFile(PairRDDFunctions.scala:1026)
at org.apache.spark.rdd.PairRDDFunctions.$anonfun$saveAsHadoopFile$3(PairRDDFunctions.scala:1008)
at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
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:414)
at org.apache.spark.rdd.PairRDDFunctions.saveAsHadoopFile(PairRDDFunctions.scala:1007)
at org.apache.spark.rdd.PairRDDFunctions.$anonfun$saveAsHadoopFile$2(PairRDDFunctions.scala:964)
at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
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:414)
at org.apache.spark.rdd.PairRDDFunctions.saveAsHadoopFile(PairRDDFunctions.scala:962)
at org.apache.spark.rdd.RDD.$anonfun$saveAsTextFile$2(RDD.scala:1578)
at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
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:414)
at org.apache.spark.rdd.RDD.saveAsTextFile(RDD.scala:1578)
at org.apache.spark.rdd.RDD.$anonfun$saveAsTextFile$1(RDD.scala:1564)
at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
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:414)
at org.apache.spark.rdd.RDD.saveAsTextFile(RDD.scala:1564)
... 47 elided
Caused by: org.apache.spark.SparkException: Job aborted due to stage failure: Task 1 in stage 0.0 failed 1 times, most recent failure: Lost task 1.0 in stage 0.0 (TID 1) (192.168.1.20 executor driver): java.lang.StringIndexOutOfBoundsException: String index out of range: 0
at java.lang.String.charAt(String.java:658)
at scala.collection.immutable.StringOps$.apply$extension(StringOps.scala:41)
at $anonfun$avglens$2(<console>:24)
at scala.collection.Iterator$$anon$10.next(Iterator.scala:459)
at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:156)
at org.apache.spark.shuffle.ShuffleWriteProcessor.write(ShuffleWriteProcessor.scala:59)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:52)
at org.apache.spark.scheduler.Task.run(Task.scala:131)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:497)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:500)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2253)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2202)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2201)
at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2201)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:1078)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:1078)
at scala.Option.foreach(Option.scala:407)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1078)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2440)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2382)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2371)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:868)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2202)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2223)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2255)
at org.apache.spark.internal.io.SparkHadoopWriter$.write(SparkHadoopWriter.scala:83)
... 83 more
Caused by: java.lang.StringIndexOutOfBoundsException: String index out of range: 0
at java.lang.String.charAt(String.java:658)
at scala.collection.immutable.StringOps$.apply$extension(StringOps.scala:41)
at $anonfun$avglens$2(<console>:24)
at scala.collection.Iterator$$anon$10.next(Iterator.scala:459)
at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:156)
at org.apache.spark.shuffle.ShuffleWriteProcessor.write(ShuffleWriteProcessor.scala:59)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:52)
at org.apache.spark.scheduler.Task.run(Task.scala:131)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:497)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:500)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Also, a new folder avglens-output is created in my C:\Program Files\spark-3.1.1-bin-hadoop2.7\bin folder, but it is empty.
I don't understand why this errors appears, I have however authorized the writing on the bin folder.
Your problem seems to be in the map with word(0), not in the saveAsTextFile.
Since you are doing the split in the flatMap, the output of that step is a RDD with each word as a row, there is not an array for each element, just single word.
FlatMap flattens the array.
Check the difference
flatMap
scala> val rdd = sc.textFile("/Users/my_name/Workspace/spark-3.0.2-bin-hadoop2.7/README.md").flatMap(line => line.split(' '))
scala> rdd.take(5).foreach(println)
#
Apache
Spark
Spark
map
scala> val rdd = sc.textFile("/Users/sergio.couto/Workspace/spark-3.0.2-bin-hadoop2.7/README.md").map(line => line.split(' '))
scala> rdd.take(5).foreach(println)
[Ljava.lang.String;#7cd1d235
[Ljava.lang.String;#1736262a
[Ljava.lang.String;#7252e063
[Ljava.lang.String;#5edd0a7e
[Ljava.lang.String;#2c6f2bea
So you don't need to do word(0), it's not an array, you can just do word => (word, word.length)
Full Example:
val rdd = sc.textFile("/Users/my_name/Workspace/spark-3.0.2-bin-hadoop2.7/README.md")
.flatMap(line => line.split(' '))
.map(word => (word, word.length))
.groupByKey()
.map(pair => (pair._1, pair._2.sum/pair._2.size.toDouble))
scala> rdd.take(10).foreach(println)
(package,7.0)
(this,4.0)
(integration,11.0)
(Python,6.0)
(cluster.,8.0)
(its,3.0)
([run,4.0)
(There,5.0)
(general,7.0)
(YARN,,5.0)
Then you will be able to perform saveAsTextFile or whichever method you need
I am passing a function to Spark. That function solves an optimization problem which takes about a half second for each data row to solve. However, If my dataset is only 10 samples, Spark will process everything just fine as expected. However, this error stack appears if I process a dataset of say 100 rows or more:
2018-06-23 21:42:16 WARN NativeCodeLoader:62 - Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).
2018-06-23 21:42:17 WARN Utils:66 - Service 'SparkUI' could not bind on port 4040. Attempting port 4041.
[Stage 0:> (0 + 1) / 1]2018-06-23 21:48:54 ERROR Executor:91 - Exception in task 0.0 in stage 0.0 (TID 0)
java.net.SocketException: Connection reset
at java.net.SocketInputStream.read(SocketInputStream.java:210)
at java.net.SocketInputStream.read(SocketInputStream.java:141)
at java.io.BufferedInputStream.read1(BufferedInputStream.java:284)
at java.io.BufferedInputStream.read(BufferedInputStream.java:345)
at java.io.DataInputStream.readFully(DataInputStream.java:195)
at java.io.DataInputStream.readFully(DataInputStream.java:169)
at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:431)
at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:421)
at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:252)
at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
at org.apache.spark.rdd.RDD$$anonfun$zip$1$$anonfun$apply$27$$anon$2.hasNext(RDD.scala:860)
at scala.collection.Iterator$class.foreach(Iterator.scala:893)
at org.apache.spark.rdd.RDD$$anonfun$zip$1$$anonfun$apply$27$$anon$2.foreach(RDD.scala:859)
at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:59)
at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:104)
at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:48)
at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:310)
at org.apache.spark.rdd.RDD$$anonfun$zip$1$$anonfun$apply$27$$anon$2.to(RDD.scala:859)
at scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:302)
at org.apache.spark.rdd.RDD$$anonfun$zip$1$$anonfun$apply$27$$anon$2.toBuffer(RDD.scala:859)
at scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:289)
at org.apache.spark.rdd.RDD$$anonfun$zip$1$$anonfun$apply$27$$anon$2.toArray(RDD.scala:859)
at org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$12.apply(RDD.scala:939)
at org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$12.apply(RDD.scala:939)
at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2074)
at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2074)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
at org.apache.spark.scheduler.Task.run(Task.scala:109)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
2018-06-23 21:48:54 WARN TaskSetManager:66 - Lost task 0.0 in stage 0.0 (TID 0, localhost, executor driver): java.net.SocketException: Connection reset
at java.net.SocketInputStream.read(SocketInputStream.java:210)
at java.net.SocketInputStream.read(SocketInputStream.java:141)
at java.io.BufferedInputStream.read1(BufferedInputStream.java:284)
at java.io.BufferedInputStream.read(BufferedInputStream.java:345)
at java.io.DataInputStream.readFully(DataInputStream.java:195)
at java.io.DataInputStream.readFully(DataInputStream.java:169)
at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:431)
at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:421)
at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:252)
at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
at org.apache.spark.rdd.RDD$$anonfun$zip$1$$anonfun$apply$27$$anon$2.hasNext(RDD.scala:860)
at scala.collection.Iterator$class.foreach(Iterator.scala:893)
at org.apache.spark.rdd.RDD$$anonfun$zip$1$$anonfun$apply$27$$anon$2.foreach(RDD.scala:859)
at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:59)
at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:104)
at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:48)
at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:310)
at org.apache.spark.rdd.RDD$$anonfun$zip$1$$anonfun$apply$27$$anon$2.to(RDD.scala:859)
at scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:302)
at org.apache.spark.rdd.RDD$$anonfun$zip$1$$anonfun$apply$27$$anon$2.toBuffer(RDD.scala:859)
at scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:289)
at org.apache.spark.rdd.RDD$$anonfun$zip$1$$anonfun$apply$27$$anon$2.toArray(RDD.scala:859)
at org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$12.apply(RDD.scala:939)
at org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$12.apply(RDD.scala:939)
at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2074)
at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2074)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
at org.apache.spark.scheduler.Task.run(Task.scala:109)
at org.apache.spark.executor.Executor$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)
2018-06-23 21:48:54 ERROR TaskSetManager:70 - Task 0 in stage 0.0 failed 1 times; aborting job
Traceback (most recent call last):
File "C:/Users/salman/PycharmProjects/TestingPySpark/testingUDF.py", line 68, in <module>
appended.collect()
File "C:\Users\salman\AppData\Local\Programs\Python\Python36\lib\site-packages\pyspark\rdd.py", line 834, in collect
sock_info = self.ctx._jvm.PythonRDD.collectAndServe(self._jrdd.rdd())
File "C:\Users\salman\AppData\Local\Programs\Python\Python36\lib\site-packages\py4j\java_gateway.py", line 1257, in __call__
answer, self.gateway_client, self.target_id, self.name)
File "C:\Users\salman\AppData\Local\Programs\Python\Python36\lib\site-packages\pyspark\sql\utils.py", line 63, in deco
return f(*a, **kw)
File "C:\Users\salman\AppData\Local\Programs\Python\Python36\lib\site-packages\py4j\protocol.py", line 328, in get_return_value
format(target_id, ".", name), value)
py4j.protocol.Py4JJavaError: An error occurred while calling z:org.apache.spark.api.python.PythonRDD.collectAndServe.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 0.0 failed 1 times, most recent failure: Lost task 0.0 in stage 0.0 (TID 0, localhost, executor driver): java.net.SocketException: Connection reset
at java.net.SocketInputStream.read(SocketInputStream.java:210)
at java.net.SocketInputStream.read(SocketInputStream.java:141)
at java.io.BufferedInputStream.read1(BufferedInputStream.java:284)
at java.io.BufferedInputStream.read(BufferedInputStream.java:345)
at java.io.DataInputStream.readFully(DataInputStream.java:195)
at java.io.DataInputStream.readFully(DataInputStream.java:169)
at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:431)
at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:421)
at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:252)
at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
at org.apache.spark.rdd.RDD$$anonfun$zip$1$$anonfun$apply$27$$anon$2.hasNext(RDD.scala:860)
at scala.collection.Iterator$class.foreach(Iterator.scala:893)
at org.apache.spark.rdd.RDD$$anonfun$zip$1$$anonfun$apply$27$$anon$2.foreach(RDD.scala:859)
at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:59)
at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:104)
at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:48)
at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:310)
at org.apache.spark.rdd.RDD$$anonfun$zip$1$$anonfun$apply$27$$anon$2.to(RDD.scala:859)
at scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:302)
at org.apache.spark.rdd.RDD$$anonfun$zip$1$$anonfun$apply$27$$anon$2.toBuffer(RDD.scala:859)
at scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:289)
at org.apache.spark.rdd.RDD$$anonfun$zip$1$$anonfun$apply$27$$anon$2.toArray(RDD.scala:859)
at org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$12.apply(RDD.scala:939)
at org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$12.apply(RDD.scala:939)
at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2074)
at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2074)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
at org.apache.spark.scheduler.Task.run(Task.scala:109)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$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$$anon$1.run(EventLoop.scala:48)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:642)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2034)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2055)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2074)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2099)
at org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:939)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:363)
at org.apache.spark.rdd.RDD.collect(RDD.scala:938)
at org.apache.spark.api.python.PythonRDD$.collectAndServe(PythonRDD.scala:162)
at org.apache.spark.api.python.PythonRDD.collectAndServe(PythonRDD.scala)
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.net.SocketException: Connection reset
at java.net.SocketInputStream.read(SocketInputStream.java:210)
at java.net.SocketInputStream.read(SocketInputStream.java:141)
at java.io.BufferedInputStream.read1(BufferedInputStream.java:284)
at java.io.BufferedInputStream.read(BufferedInputStream.java:345)
at java.io.DataInputStream.readFully(DataInputStream.java:195)
at java.io.DataInputStream.readFully(DataInputStream.java:169)
at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:431)
at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:421)
at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:252)
at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
at org.apache.spark.rdd.RDD$$anonfun$zip$1$$anonfun$apply$27$$anon$2.hasNext(RDD.scala:860)
at scala.collection.Iterator$class.foreach(Iterator.scala:893)
at org.apache.spark.rdd.RDD$$anonfun$zip$1$$anonfun$apply$27$$anon$2.foreach(RDD.scala:859)
at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:59)
at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:104)
at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:48)
at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:310)
at org.apache.spark.rdd.RDD$$anonfun$zip$1$$anonfun$apply$27$$anon$2.to(RDD.scala:859)
at scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:302)
at org.apache.spark.rdd.RDD$$anonfun$zip$1$$anonfun$apply$27$$anon$2.toBuffer(RDD.scala:859)
at scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:289)
at org.apache.spark.rdd.RDD$$anonfun$zip$1$$anonfun$apply$27$$anon$2.toArray(RDD.scala:859)
at org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$12.apply(RDD.scala:939)
at org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$12.apply(RDD.scala:939)
at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2074)
at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2074)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
at org.apache.spark.scheduler.Task.run(Task.scala:109)
at org.apache.spark.executor.Executor$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
Process finished with exit code 1
Here is my code:
spark = SparkSession \
.builder \
.appName("testingUDF") \
.getOrCreate()
temp_input = spark.read.text("demands_only.csv").rdd.map(myFunc2)
obj = SolveDemand.SolveDemand()
lines = spark.read.text("demands_only.csv").rdd.map(obj.solve)
appended = temp_input.zip(lines)
appended.collect()
any suggestion about the error?
Seems like memory issue and python process got OOM killed.
Add into your command
--executor-memory 10G
--driver-memory 10G
Example :
./bin/spark-submit \
--class org.apache.spark.examples.SparkPi \
--master spark://master.node:7077 \
--executor-memory 8G \
--total-executor-cores 100 \
/path/to/vaquarkhan-example.jar \
1000
https://community.hortonworks.com/articles/42803/spark-on-yarn-executor-resource-allocation-optimiz.html
http://blog.cloudera.com/blog/2015/03/how-to-tune-your-apache-spark-jobs-part-1/
http://blog.cloudera.com/blog/2015/03/how-to-tune-your-apache-spark-jobs-part-2/