Errors while trying to use collect() method in pyspark. (Windows 10) [duplicate] - apache-spark

This question already has answers here:
Python worker failed to connect back
(9 answers)
Closed last year.
So I've read a dozens of tutorials on how to set up pyspark.
I've set all enviremental variables like HADOOP_HOME, SPARK_HOME e.t.c.
I've downloaded winutils and put it to %SPARK_HOME%/bin.
I've checked that the version of pyspark is the same as spark, that I have downloaded from official site (3.2.1).
I am using Java JDK 8.
I've tried different versions of Java, Spark/Pyspark but everytime I use collect method on rdd I'm getting a tons of errors.
This is my sample program:
from pyspark.sql import SparkSession
ss = SparkSession.builder.master('local').appName('name').getOrCreate()
rd = ss.sparkContext.parallelize([1, 2, 3, 4, 5])
rd1 = rd.map(lambda x: x** 2).collect()
print(rd1)
And this is what I am getting. (I am sorry I have no idea how to put everything under spoiler)
Any help would be very appreciated!
Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).
22/02/05 21:03:53 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
22/02/05 21:04:06 WARN ProcfsMetricsGetter: Exception when trying to compute pagesize, as a result reporting of ProcessTree metrics is stopped
22/02/05 21:04:06 ERROR Executor: Exception in task 0.0 in stage 0.0 (TID 0)
org.apache.spark.SparkException: Python worker failed to connect back.
at org.apache.spark.api.python.PythonWorkerFactory.createSimpleWorker(PythonWorkerFactory.scala:188)
at org.apache.spark.api.python.PythonWorkerFactory.create(PythonWorkerFactory.scala:108)
at org.apache.spark.SparkEnv.createPythonWorker(SparkEnv.scala:121)
at org.apache.spark.api.python.BasePythonRunner.compute(PythonRunner.scala:162)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:65)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:337)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:131)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:506)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1462)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:509)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Caused by: java.net.SocketTimeoutException: Accept timed out
at java.net.DualStackPlainSocketImpl.waitForNewConnection(Native Method)
at java.net.DualStackPlainSocketImpl.socketAccept(DualStackPlainSocketImpl.java:131)
at java.net.AbstractPlainSocketImpl.accept(AbstractPlainSocketImpl.java:535)
at java.net.PlainSocketImpl.accept(PlainSocketImpl.java:189)
at java.net.ServerSocket.implAccept(ServerSocket.java:545)
at java.net.ServerSocket.accept(ServerSocket.java:513)
at org.apache.spark.api.python.PythonWorkerFactory.createSimpleWorker(PythonWorkerFactory.scala:175)
... 14 more
22/02/05 21:04:06 WARN TaskSetManager: Lost task 0.0 in stage 0.0 (TID 0) (WIN-CH4BAQ3PTMC executor driver): org.apache.spark.SparkException: Python worker failed to connect back.
at org.apache.spark.api.python.PythonWorkerFactory.createSimpleWorker(PythonWorkerFactory.scala:188)
at org.apache.spark.api.python.PythonWorkerFactory.create(PythonWorkerFactory.scala:108)
at org.apache.spark.SparkEnv.createPythonWorker(SparkEnv.scala:121)
at org.apache.spark.api.python.BasePythonRunner.compute(PythonRunner.scala:162)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:65)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:337)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:131)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:506)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1462)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:509)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Caused by: java.net.SocketTimeoutException: Accept timed out
at java.net.DualStackPlainSocketImpl.waitForNewConnection(Native Method)
at java.net.DualStackPlainSocketImpl.socketAccept(DualStackPlainSocketImpl.java:131)
at java.net.AbstractPlainSocketImpl.accept(AbstractPlainSocketImpl.java:535)
at java.net.PlainSocketImpl.accept(PlainSocketImpl.java:189)
at java.net.ServerSocket.implAccept(ServerSocket.java:545)
at java.net.ServerSocket.accept(ServerSocket.java:513)
at org.apache.spark.api.python.PythonWorkerFactory.createSimpleWorker(PythonWorkerFactory.scala:175)
... 14 more
22/02/05 21:04:06 ERROR TaskSetManager: Task 0 in stage 0.0 failed 1 times; aborting job
Traceback (most recent call last):
File "C:\Users\user\PycharmProjects\pythonProject\spark.py", line 6, in <module>
print(rd.map(lambda x: x ** 2).collect())
File "C:\Users\user\PycharmProjects\pythonProject\venv\lib\site-packages\pyspark\rdd.py", line 950, in collect
sock_info = self.ctx._jvm.PythonRDD.collectAndServe(self._jrdd.rdd())
File "C:\Users\user\PycharmProjects\pythonProject\venv\lib\site-packages\py4j\java_gateway.py", line 1321, in __call__
return_value = get_return_value(
File "C:\Users\user\PycharmProjects\pythonProject\venv\lib\site-packages\pyspark\sql\utils.py", line 111, in deco
return f(*a, **kw)
File "C:\Users\user\PycharmProjects\pythonProject\venv\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) (WIN-CH4BAQ3PTMC executor driver): org.apache.spark.SparkException: Python worker failed to connect back.
at org.apache.spark.api.python.PythonWorkerFactory.createSimpleWorker(PythonWorkerFactory.scala:188)
at org.apache.spark.api.python.PythonWorkerFactory.create(PythonWorkerFactory.scala:108)
at org.apache.spark.SparkEnv.createPythonWorker(SparkEnv.scala:121)
at org.apache.spark.api.python.BasePythonRunner.compute(PythonRunner.scala:162)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:65)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:337)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:131)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:506)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1462)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:509)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Caused by: java.net.SocketTimeoutException: Accept timed out
at java.net.DualStackPlainSocketImpl.waitForNewConnection(Native Method)
at java.net.DualStackPlainSocketImpl.socketAccept(DualStackPlainSocketImpl.java:131)
at java.net.AbstractPlainSocketImpl.accept(AbstractPlainSocketImpl.java:535)
at java.net.PlainSocketImpl.accept(PlainSocketImpl.java:189)
at java.net.ServerSocket.implAccept(ServerSocket.java:545)
at java.net.ServerSocket.accept(ServerSocket.java:513)
at org.apache.spark.api.python.PythonWorkerFactory.createSimpleWorker(PythonWorkerFactory.scala:175)
... 14 more
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2454)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2403)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2402)
at scala.collection.immutable.List.foreach(List.scala:333)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2402)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:1160)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:1160)
at scala.Option.foreach(Option.scala:437)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1160)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2642)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2584)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2573)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:938)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2214)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2235)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2254)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2279)
at org.apache.spark.rdd.RDD.$anonfun$collect$1(RDD.scala:1030)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:414)
at org.apache.spark.rdd.RDD.collect(RDD.scala:1029)
at org.apache.spark.api.python.PythonRDD$.collectAndServe(PythonRDD.scala:180)
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.ClientServerConnection.waitForCommands(ClientServerConnection.java:182)
at py4j.ClientServerConnection.run(ClientServerConnection.java:106)
at java.lang.Thread.run(Thread.java:748)
Caused by: org.apache.spark.SparkException: Python worker failed to connect back.
at org.apache.spark.api.python.PythonWorkerFactory.createSimpleWorker(PythonWorkerFactory.scala:188)
at org.apache.spark.api.python.PythonWorkerFactory.create(PythonWorkerFactory.scala:108)
at org.apache.spark.SparkEnv.createPythonWorker(SparkEnv.scala:121)
at org.apache.spark.api.python.BasePythonRunner.compute(PythonRunner.scala:162)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:65)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:337)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:131)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:506)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1462)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:509)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
... 1 more
Caused by: java.net.SocketTimeoutException: Accept timed out
at java.net.DualStackPlainSocketImpl.waitForNewConnection(Native Method)
at java.net.DualStackPlainSocketImpl.socketAccept(DualStackPlainSocketImpl.java:131)
at java.net.AbstractPlainSocketImpl.accept(AbstractPlainSocketImpl.java:535)
at java.net.PlainSocketImpl.accept(PlainSocketImpl.java:189)
at java.net.ServerSocket.implAccept(ServerSocket.java:545)
at java.net.ServerSocket.accept(ServerSocket.java:513)
at org.apache.spark.api.python.PythonWorkerFactory.createSimpleWorker(PythonWorkerFactory.scala:175)
... 14 more

Nothing wrong with your program.
Its looks like the issue in your spark setup. in the command prompt check if you are able to get pyspark prompt without any error.
and also check python version and env variable.

BIG thanks to #blackbishop for the tip!
Python worker failed to connect back
All I did is just added
import findspark
findspark.init()
Everything works now!

Related

Issue loading data set using spark-redis

I am trying to load a data set with spark-redis, but the operation always fail. The spark dataframe that I am trying to write has 85 million rows, but the write operation roughly fails after 25 million rows in. I wonder how to solve this kind of problem.
Here are the operations that I execute in my Python script:
SPARK_JARS = ['/home/jovyan/jedis-3.6.0.jar', '/home/jovyan/spark-redis_2.12-2.6.0.jar']
spark = (SparkSession.builder.master(master_uri).appName('redis.test')
.config('spark.executor.memory', '28g')
.config('spark.cores.max', 16)
.config('spark.redis.host', REDIS_HOST)
.config('spark.redis.port', 6379)
.config('spark.redis.db', 0)
.config('spark.sql.debug.maxToStringFields', 65535)
.config('spark.jars', ','.join(SPARK_JARS)).enableHiveSupport().getOrCreate())
df = spark.sql('select * from input_table')
df.write.format("org.apache.spark.sql.redis").option("table", "output_table").option("key.column", "id").option("dbNum", 0).save();
I am trying to store information from an Iceberg table to a Redis hash. The version of spark-redis I am using is spark-redis_2.12-2.6.0.jar. I am running my script on Spark 3.1.1 and the Redis cluster I am trying to access uses version 6.0.4. When I run the script, it starts loading the data in the hash from for a couple of minutes. Then, a SocketTimeoutException is raised. But the data continues to be loaded in the hash. However, after 10 minutes (this varies from session to session), there is an additional failure and from this point, I cannot connect to the Redis data store anymore (connection refused). This connection refusal state is temporary, but can last a few hours.
Here is the log (I had to skip parts of it because it was too long to fit in a message):
ANTLR Tool version 4.8 used for code generation does not match the current runtime version 4.7.1ANTLR Runtime version 4.8 used for parser compilation does not match the current runtime version 4.7.1ANTLR Tool version 4.8 used for code generation does not match the current runtime version 4.7.1ANTLR Runtime version 4.8 used for parser compilation does not match 21/06/07 17:26:08 WARN SessionState: METASTORE_FILTER_HOOK will be ignored, since hive.security.authorization.manager is set to instance of HiveAuthorizerFactory.
21/06/07 17:30:07 WARN TaskSetManager: Lost task 13.0 in stage 2.0 (TID 16) (x.x.x.x executor 0): redis.clients.jedis.exceptions.JedisConnectionException: java.net.SocketTimeoutException: Read timed out
at redis.clients.jedis.util.RedisInputStream.ensureFill(RedisInputStream.java:205)
at redis.clients.jedis.util.RedisInputStream.readByte(RedisInputStream.java:43)
at redis.clients.jedis.Protocol.process(Protocol.java:158)
at redis.clients.jedis.Protocol.read(Protocol.java:223)
at redis.clients.jedis.Connection.readProtocolWithCheckingBroken(Connection.java:352)
at redis.clients.jedis.Connection.getMany(Connection.java:364)
at redis.clients.jedis.Pipeline.sync(Pipeline.java:98)
at com.redislabs.provider.redis.util.PipelineUtils$.$anonfun$foreachWithPipeline$1(PipelineUtils.scala:71)
at com.redislabs.provider.redis.util.PipelineUtils$.$anonfun$foreachWithPipeline$1$adapted(PipelineUtils.scala:67)
at scala.collection.IndexedSeqOptimized.foreach(IndexedSeqOptimized.scala:36)
at scala.collection.IndexedSeqOptimized.foreach$(IndexedSeqOptimized.scala:33)
at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:198)
at com.redislabs.provider.redis.util.PipelineUtils$.foreachWithPipeline(PipelineUtils.scala:67)
at org.apache.spark.sql.redis.RedisSourceRelation.$anonfun$insert$8(RedisSourceRelation.scala:143)
at org.apache.spark.sql.redis.RedisSourceRelation.$anonfun$insert$8$adapted(RedisSourceRelation.scala:141)
at scala.collection.Iterator.foreach(Iterator.scala:941)
at scala.collection.Iterator.foreach$(Iterator.scala:941)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1429)
at org.apache.spark.sql.redis.RedisSourceRelation.$anonfun$insert$6(RedisSourceRelation.scala:141)
at org.apache.spark.sql.redis.RedisSourceRelation.$anonfun$insert$6$adapted(RedisSourceRelation.scala:138)
at scala.collection.Iterator.foreach(Iterator.scala:941)
at scala.collection.Iterator.foreach$(Iterator.scala:941)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1429)
at org.apache.spark.sql.redis.RedisSourceRelation.$anonfun$insert$5(RedisSourceRelation.scala:138)
at org.apache.spark.sql.redis.RedisSourceRelation.$anonfun$insert$5$adapted(RedisSourceRelation.scala:136)
at org.apache.spark.rdd.RDD.$anonfun$foreachPartition$2(RDD.scala:1020)
at org.apache.spark.rdd.RDD.$anonfun$foreachPartition$2$adapted(RDD.scala:1020)
at org.apache.spark.SparkContext.$anonfun$runJob$5(SparkContext.scala:2242)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:131)
at org.apache.spark.executor.Executor$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)
Caused by: java.net.SocketTimeoutException: Read timed out
at java.net.SocketInputStream.socketRead0(Native Method)
at java.net.SocketInputStream.socketRead(SocketInputStream.java:116)
at java.net.SocketInputStream.read(SocketInputStream.java:171)
at java.net.SocketInputStream.read(SocketInputStream.java:141)
at java.net.SocketInputStream.read(SocketInputStream.java:127)
at redis.clients.jedis.util.RedisInputStream.ensureFill(RedisInputStream.java:199)
… 35 more
21/06/07 17:41:57 WARN TaskSetManager: Lost task 19.0 in stage 2.0 (TID 22) (x.x.x.x executor 0): redis.clients.jedis.exceptions.JedisConnectionException: java.net.SocketTimeoutException: Read timed out
at redis.clients.jedis.util.RedisInputStream.ensureFill(RedisInputStream.java:205)
at redis.clients.jedis.util.RedisInputStream.readByte(RedisInputStream.java:43)
…
Caused by: java.net.SocketTimeoutException: Read timed out
at java.net.SocketInputStream.socketRead0(Native Method)
at java.net.SocketInputStream.socketRead(SocketInputStream.java:116)
at java.net.SocketInputStream.read(SocketInputStream.java:171)
at java.net.SocketInputStream.read(SocketInputStream.java:141)
at java.net.SocketInputStream.read(SocketInputStream.java:127)
at redis.clients.jedis.util.RedisInputStream.ensureFill(RedisInputStream.java:199)
… 35 more
21/06/07 17:52:54 WARN TaskSetManager: Lost task 4.2 in stage 2.0 (TID 42) (x.x.x.x executor 0): redis.clients.jedis.exceptions.JedisConnectionException: Unexpected end of stream.
at redis.clients.jedis.util.RedisInputStream.ensureFill(RedisInputStream.java:202)
at redis.clients.jedis.util.RedisInputStream.readByte(RedisInputStream.java:43)
…
21/06/07 17:52:54 WARN TaskSetManager: Lost task 2.1 in stage 2.0 (TID 46) (x.x.x.x executor 0): redis.clients.jedis.exceptions.JedisConnectionException: java.net.SocketException: Connection reset
at redis.clients.jedis.util.RedisInputStream.ensureFill(RedisInputStream.java:205)
…
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.net.SocketInputStream.read(SocketInputStream.java:127)
at redis.clients.jedis.util.RedisInputStream.ensureFill(RedisInputStream.java:199)
… 35 more
21/06/07 17:52:56 WARN TaskSetManager: Lost task 4.3 in stage 2.0 (TID 52) (x.x.x.x executor 0): redis.clients.jedis.exceptions.JedisConnectionException: Could not get a resource from the pool
at redis.clients.jedis.util.Pool.getResource(Pool.java:84)
…
Caused by: redis.clients.jedis.exceptions.JedisConnectionException: Failed to create socket.
at redis.clients.jedis.DefaultJedisSocketFactory.createSocket(DefaultJedisSocketFactory.java:110)
at redis.clients.jedis.Connection.connect(Connection.java:226)
…
Caused by: java.net.ConnectException: Connection refused (Connection refused)
at java.net.PlainSocketImpl.socketConnect(Native Method)
at java.net.AbstractPlainSocketImpl.doConnect(AbstractPlainSocketImpl.java:350)
at java.net.AbstractPlainSocketImpl.connectToAddress(AbstractPlainSocketImpl.java:206)
at java.net.AbstractPlainSocketImpl.connect(AbstractPlainSocketImpl.java:188)
at java.net.SocksSocketImpl.connect(SocksSocketImpl.java:392)
at java.net.Socket.connect(Socket.java:607)
at redis.clients.jedis.DefaultJedisSocketFactory.createSocket(DefaultJedisSocketFactory.java:80)
… 38 more
21/06/07 17:52:56 ERROR TaskSetManager: Task 4 in stage 2.0 failed 4 times; aborting job
Traceback (most recent call last):
File “redis_load.py”, line 106, in
df = spark.sql(‘select * from input_table’)
File “/opt/conda/lib/python3.8/site-packages/pyspark/sql/readwriter.py”, line 1107, in save
self._jwrite.save()
File “/opt/conda/lib/python3.8/site-packages/py4j/java_gateway.py”, line 1304, in call
return_value = get_return_value(
File “/opt/conda/lib/python3.8/site-packages/pyspark/sql/utils.py”, line 111, in deco
return f(*a, **kw)
File “/opt/conda/lib/python3.8/site-packages/py4j/protocol.py”, line 326, in get_return_value
raise Py4JJavaError(
py4j.protocol.Py4JJavaError: An error occurred while calling o90.save.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 4 in stage 2.0 failed 4 times, most recent failure: Lost task 4.3 in stage 2.0 (TID 52) (x.x.x.x executor 0): redis.clients.jedis.exceptions.JedisConnectionException: Could not get a resource from the pool
at redis.clients.jedis.util.Pool.getResource(Pool.java:84)
at redis.clients.jedis.JedisPool.getResource(JedisPool.java:366)
at com.redislabs.provider.redis.ConnectionPool$.connect(ConnectionPool.scala:35)
at com.redislabs.provider.redis.RedisEndpoint.connect(RedisConfig.scala:72)
at com.redislabs.provider.redis.RedisNode.connect(RedisConfig.scala:89)
at org.apache.spark.sql.redis.RedisSourceRelation.$anonfun$insert$8(RedisSourceRelation.scala:142)
at org.apache.spark.sql.redis.RedisSourceRelation.$anonfun$insert$8$adapted(RedisSourceRelation.scala:141)
at scala.collection.Iterator.foreach(Iterator.scala:941)
at scala.collection.Iterator.foreach$(Iterator.scala:941)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1429)
at org.apache.spark.sql.redis.RedisSourceRelation.$anonfun$insert$6(RedisSourceRelation.scala:141)
at org.apache.spark.sql.redis.RedisSourceRelation.$anonfun$insert$6$adapted(RedisSourceRelation.scala:138)
at scala.collection.Iterator.foreach(Iterator.scala:941)
at scala.collection.Iterator.foreach$(Iterator.scala:941)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1429)
at org.apache.spark.sql.redis.RedisSourceRelation.$anonfun$insert$5(RedisSourceRelation.scala:138)
at org.apache.spark.sql.redis.RedisSourceRelation.$anonfun$insert$5$adapted(RedisSourceRelation.scala:136)
at org.apache.spark.rdd.RDD.$anonfun$foreachPartition$2(RDD.scala:1020)
at org.apache.spark.rdd.RDD.$anonfun$foreachPartition$2$adapted(RDD.scala:1020)
at org.apache.spark.SparkContext.$anonfun$runJob$5(SparkContext.scala:2242)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:131)
at org.apache.spark.executor.Executor$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)
Caused by: redis.clients.jedis.exceptions.JedisConnectionException: Failed to create socket.
at redis.clients.jedis.DefaultJedisSocketFactory.createSocket(DefaultJedisSocketFactory.java:110)
at redis.clients.jedis.Connection.connect(Connection.java:226)
at redis.clients.jedis.BinaryClient.connect(BinaryClient.java:135)
at redis.clients.jedis.BinaryJedis.connect(BinaryJedis.java:309)
at redis.clients.jedis.BinaryJedis.initializeFromClientConfig(BinaryJedis.java:87)
at redis.clients.jedis.BinaryJedis.(BinaryJedis.java:292)
at redis.clients.jedis.Jedis.(Jedis.java:167)
at redis.clients.jedis.JedisFactory.makeObject(JedisFactory.java:177)
at org.apache.commons.pool2.impl.GenericObjectPool.create(GenericObjectPool.java:889)
at org.apache.commons.pool2.impl.GenericObjectPool.borrowObject(GenericObjectPool.java:424)
at org.apache.commons.pool2.impl.GenericObjectPool.borrowObject(GenericObjectPool.java:349)
at redis.clients.jedis.util.Pool.getResource(Pool.java:75)
… 27 more
Caused by: java.net.ConnectException: Connection refused (Connection refused)
at java.net.PlainSocketImpl.socketConnect(Native Method)
at java.net.AbstractPlainSocketImpl.doConnect(AbstractPlainSocketImpl.java:350)
at java.net.AbstractPlainSocketImpl.connectToAddress(AbstractPlainSocketImpl.java:206)
at java.net.AbstractPlainSocketImpl.connect(AbstractPlainSocketImpl.java:188)
at java.net.SocksSocketImpl.connect(SocksSocketImpl.java:392)
at java.net.Socket.connect(Socket.java:607)
at redis.clients.jedis.DefaultJedisSocketFactory.createSocket(DefaultJedisSocketFactory.java:80)
… 38 more
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$1.run(EventLoop.scala:49)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:868)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2202)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2223)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2242)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2267)
at org.apache.spark.rdd.RDD.$anonfun$foreachPartition$1(RDD.scala:1020)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:414)
at org.apache.spark.rdd.RDD.foreachPartition(RDD.scala:1018)
at org.apache.spark.sql.Dataset.$anonfun$foreachPartition$1(Dataset.scala:2906)
at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
at org.apache.spark.sql.Dataset.$anonfun$withNewRDDExecutionId$1(Dataset.scala:3676)
at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$5(SQLExecution.scala:103)
at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:163)
at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:90)
at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:772)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:64)
at org.apache.spark.sql.Dataset.withNewRDDExecutionId(Dataset.scala:3674)
at org.apache.spark.sql.Dataset.foreachPartition(Dataset.scala:2906)
at org.apache.spark.sql.redis.RedisSourceRelation.insert(RedisSourceRelation.scala:136)
at org.apache.spark.sql.redis.DefaultSource.createRelation(DefaultSource.scala:30)
at org.apache.spark.sql.execution.datasources.SaveIntoDataSourceCommand.run(SaveIntoDataSourceCommand.scala:46)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:70)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:68)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.doExecute(commands.scala:90)
at org.apache.spark.sql.execution.SparkPlan.$anonfun$execute$1(SparkPlan.scala:180)
at org.apache.spark.sql.execution.SparkPlan.$anonfun$executeQuery$1(SparkPlan.scala:218)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:215)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:176)
at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:132)
at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:131)
at org.apache.spark.sql.DataFrameWriter.$anonfun$runCommand$1(DataFrameWriter.scala:989)
at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$5(SQLExecution.scala:103)
at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:163)
at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:90)
at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:772)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:64)
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 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: redis.clients.jedis.exceptions.JedisConnectionException: Could not get a resource from the pool
at redis.clients.jedis.util.Pool.getResource(Pool.java:84)
at redis.clients.jedis.JedisPool.getResource(JedisPool.java:366)
at com.redislabs.provider.redis.ConnectionPool$.connect(ConnectionPool.scala:35)
at com.redislabs.provider.redis.RedisEndpoint.connect(RedisConfig.scala:72)
at com.redislabs.provider.redis.RedisNode.connect(RedisConfig.scala:89)
at org.apache.spark.sql.redis.RedisSourceRelation.$anonfun$insert$8(RedisSourceRelation.scala:142)
at org.apache.spark.sql.redis.RedisSourceRelation.$anonfun$insert$8$adapted(RedisSourceRelation.scala:141)
at scala.collection.Iterator.foreach(Iterator.scala:941)
at scala.collection.Iterator.foreach$(Iterator.scala:941)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1429)
at org.apache.spark.sql.redis.RedisSourceRelation.$anonfun$insert$6(RedisSourceRelation.scala:141)
at org.apache.spark.sql.redis.RedisSourceRelation.$anonfun$insert$6$adapted(RedisSourceRelation.scala:138)
at scala.collection.Iterator.foreach(Iterator.scala:941)
at scala.collection.Iterator.foreach$(Iterator.scala:941)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1429)
at org.apache.spark.sql.redis.RedisSourceRelation.$anonfun$insert$5(RedisSourceRelation.scala:138)
at org.apache.spark.sql.redis.RedisSourceRelation.$anonfun$insert$5$adapted(RedisSourceRelation.scala:136)
at org.apache.spark.rdd.RDD.$anonfun$foreachPartition$2(RDD.scala:1020)
at org.apache.spark.rdd.RDD.$anonfun$foreachPartition$2$adapted(RDD.scala:1020)
at org.apache.spark.SparkContext.$anonfun$runJob$5(SparkContext.scala:2242)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:131)
at org.apache.spark.executor.Executor$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
Caused by: redis.clients.jedis.exceptions.JedisConnectionException: Failed to create socket.
at redis.clients.jedis.DefaultJedisSocketFactory.createSocket(DefaultJedisSocketFactory.java:110)
at redis.clients.jedis.Connection.connect(Connection.java:226)
at redis.clients.jedis.BinaryClient.connect(BinaryClient.java:135)
at redis.clients.jedis.BinaryJedis.connect(BinaryJedis.java:309)
at redis.clients.jedis.BinaryJedis.initializeFromClientConfig(BinaryJedis.java:87)
at redis.clients.jedis.BinaryJedis.(BinaryJedis.java:292)
at redis.clients.jedis.Jedis.(Jedis.java:167)
at redis.clients.jedis.JedisFactory.makeObject(JedisFactory.java:177)
at org.apache.commons.pool2.impl.GenericObjectPool.create(GenericObjectPool.java:889)
at org.apache.commons.pool2.impl.GenericObjectPool.borrowObject(GenericObjectPool.java:424)
at org.apache.commons.pool2.impl.GenericObjectPool.borrowObject(GenericObjectPool.java:349)
at redis.clients.jedis.util.Pool.getResource(Pool.java:75)
… 27 more
Caused by: java.net.ConnectException: Connection refused (Connection refused)
at java.net.PlainSocketImpl.socketConnect(Native Method)
at java.net.AbstractPlainSocketImpl.doConnect(AbstractPlainSocketImpl.java:350)
at java.net.AbstractPlainSocketImpl.connectToAddress(AbstractPlainSocketImpl.java:206)
at java.net.AbstractPlainSocketImpl.connect(AbstractPlainSocketImpl.java:188)
at java.net.SocksSocketImpl.connect(SocksSocketImpl.java:392)
at java.net.Socket.connect(Socket.java:607)
at redis.clients.jedis.DefaultJedisSocketFactory.createSocket(DefaultJedisSocketFactory.java:80)
… 38 more
21/06/07 17:52:57 WARN TaskSetManager: Lost task 15.2 in stage 2.0 (TID 67) (x.x.x.x executor 0): TaskKilled (Stage cancelled)
It looks like there is some connection pool that gets exhausted, but I have no idea how you can tell spark-redis how connections should be allocated and when to recycle them. I also do not know if the problem arise because of the network configuration or maybe the Redis server configuration. Any pointers on how to troubleshoot this problems would be appreciated.
I am also getting similar problems when I run python script of Java app that uses the Redis API to read and write to Redis using pipelines.
I am seeing many of these logs:
Asynchronous AOF fsync is taking too long (disk is busy?)
It looks like while performing the write, because I have enabled persistence in my Redis server, the server is periodically writing the hash to disk which causes a delay in response from time to time. The socket (read) timeout is 2 seconds by default I believe. It seems like the sevrer may not respond within this limit at times. I have increased this to a much higher value doing .config("spark.redis.timeout", DEFAULT_TIMEOUT) on the Spark context (I could have also set the timeout on the dataframe adding the following option to the write operation: .option("timeout", DEFAULT_TIMEOUT).

how can I resolve following error while setting up Spark

I am setting up Spark framework.
I did put winutils.exe in C:\hadoop\bin folder and updated the binaries by editing the PATH variable. Still when I launch Spark, I get following error.
Could not locate executable null\bin\winutils.exe in the Hadoop binaries.
However, I can launch the Spark successfully despite of this above error. Please advise if the above error can cause any issues while running spark jobs.
next when I try to run wordcount.py file..get following error:
C:\python-spark\python-spark-tutorial>spark-submit rdd\WordCount.py
19/03/10 11:51:10 ERROR Shell: Failed to locate the winutils binary in the
hadoop binary path
java.io.IOException: Could not locate executable null\bin\winutils.exe in
the Hadoop binaries.
at org.apache.hadoop.util.Shell.getQualifiedBinPath(Shell.java:379)
at org.apache.hadoop.util.Shell.getWinUtilsPath(Shell.java:394)
at org.apache.hadoop.util.Shell.<clinit>(Shell.java:387)
at org.apache.hadoop.util.StringUtils.<clinit>(StringUtils.java:80)
at org.apache.hadoop.security.SecurityUtil.getAuthenticationMethod(SecurityUtil.java:611)
at org.apache.hadoop.security.UserGroupInformation.initialize(UserGroupInformation.java:273)
at org.apache.hadoop.security.UserGroupInformation.ensureInitialized(UserGroupInformation.java:261)
at org.apache.hadoop.security.UserGroupInformation.loginUserFromSubject(UserGroupInformation.java:791)
at org.apache.hadoop.security.UserGroupInformation.getLoginUser(UserGroupInformation.java:761)
at org.apache.hadoop.security.UserGroupInformation.getCurrentUser(UserGroupInformation.java:634)
at org.apache.spark.util.Utils$$anonfun$getCurrentUserName$1.apply(Utils.scala:2422)
at org.apache.spark.util.Utils$$anonfun$getCurrentUserName$1.apply(Utils.scala:2422)
at scala.Option.getOrElse(Option.scala:121)
at org.apache.spark.util.Utils$.getCurrentUserName(Utils.scala:2422)
at org.apache.spark.SecurityManager.<init>(SecurityManager.scala:79)
at org.apache.spark.deploy.SparkSubmit.secMgr$lzycompute$1(SparkSubmit.scala:359)
at org.apache.spark.deploy.SparkSubmit.org$apache$spark$deploy$SparkSubmit$$secMgr$1(SparkSubmit.scala:359)
at org.apache.spark.deploy.SparkSubmit$$anonfun$prepareSubmitEnvironment$7.apply(SparkSubmit.scala:367)
at org.apache.spark.deploy.SparkSubmit$$anonfun$prepareSubmitEnvironment$7.apply(SparkSubmit.scala:367)
at scala.Option.map(Option.scala:146)
at org.apache.spark.deploy.SparkSubmit.prepareSubmitEnvironment(SparkSubmit.scala:366)
at org.apache.spark.deploy.SparkSubmit.submit(SparkSubmit.scala:143)
at org.apache.spark.deploy.SparkSubmit.doSubmit(SparkSubmit.scala:86)
at org.apache.spark.deploy.SparkSubmit$$anon$2.doSubmit(SparkSubmit.scala:924)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:933)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
19/03/10 11:51:10 WARN NativeCodeLoader: Unable to load native-hadoop
library for your platform... using builtin-java classes where applicable
Traceback (most recent call last):
File "C:\Users\gabs\AppData\Local\Programs\Python\Python37-32\lib\runpy.py", line 193, in _run_module_as_main
"__main__", mod_spec)
File "C:\Users\gabs\AppData\Local\Programs\Python\Python37-32\lib\runpy.py", line 85, in _run_code
exec(code, run_globals)
File "C:\python-spark\spark-2.4.0-bin-
hadoop2.7\python\lib\pyspark.zip\pyspark\worker.py", line 25, in <module>
ModuleNotFoundError: No module named 'resource'
19/03/10 11:51:26 ERROR Executor: Exception in task 0.0 in stage 0.0 (TID 0)
org.apache.spark.SparkException: Python worker failed to connect back.
at org.apache.spark.api.python.PythonWorkerFactory.createSimpleWorker(PythonWorkerFactory.scala:170)
at org.apache.spark.api.python.PythonWorkerFactory.create(PythonWorkerFactory.scala:97)
at org.apache.spark.SparkEnv.createPythonWorker(SparkEnv.scala:117)
at org.apache.spark.api.python.BasePythonRunner.compute(PythonRunner.scala:108)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:65)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:121)
at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:402)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:408)
at java.util.concurrent.ThreadPoolExecutor.runWorker(Unknown Source)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(Unknown Source)
at java.lang.Thread.run(Unknown Source)
Caused by: java.net.SocketTimeoutException: Accept timed out
at java.net.DualStackPlainSocketImpl.waitForNewConnection(Native Method)
at java.net.DualStackPlainSocketImpl.socketAccept(Unknown Source)
at java.net.AbstractPlainSocketImpl.accept(Unknown Source)
at java.net.PlainSocketImpl.accept(Unknown Source)
at java.net.ServerSocket.implAccept(Unknown Source)
at java.net.ServerSocket.accept(Unknown Source)
at org.apache.spark.api.python.PythonWorkerFactory.createSimpleWorker(PythonWorkerFactory.scala:164)
... 14 more
19/03/10 11:51:26 ERROR TaskSetManager: Task 0 in stage 0.0 failed 1 times; aborting job
Traceback (most recent call last):
File "C:/python-spark/python-spark-tutorial/rdd/WordCount.py", line 12, in <module>
wordCounts = words.countByValue()
File "C:\python-spark\spark-2.4.0-bin-hadoop2.7\python\lib\pyspark.zip\pyspark\rdd.py", line 1261, in countByValue
File "C:\python-spark\spark-2.4.0-bin-hadoop2.7\python\lib\pyspark.zip\pyspark\rdd.py", line 844, in reduce
File "C:\python-spark\spark-2.4.0-bin-hadoop2.7\python\lib\pyspark.zip\pyspark\rdd.py", line 816, in collect
File "C:\python-spark\spark-2.4.0-bin-hadoop2.7\python\lib\py4j-0.10.7-src.zip\py4j\java_gateway.py", line 1257, in __call__
File "C:\python-spark\spark-2.4.0-bin-hadoop2.7\python\lib\py4j-0.10.7-
src.zip\py4j\protocol.py", line 328, in get_return_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): org.apache.spark.SparkException: Python
worker failed to connect back.
at org.apache.spark.api.python.PythonWorkerFactory.createSimpleWorker(PythonWorkerFactory.scala:170)
at org.apache.spark.api.python.PythonWorkerFactory.create(PythonWorkerFactory.scala:97)
at org.apache.spark.SparkEnv.createPythonWorker(SparkEnv.scala:117)
at org.apache.spark.api.python.BasePythonRunner.compute(PythonRunner.scala:108)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:65)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:121)
at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:402)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:408)
at java.util.concurrent.ThreadPoolExecutor.runWorker(Unknown Source)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(Unknown Source)
at java.lang.Thread.run(Unknown Source)
Caused by: java.net.SocketTimeoutException: Accept timed out
at java.net.DualStackPlainSocketImpl.waitForNewConnection(Native Method)
at java.net.DualStackPlainSocketImpl.socketAccept(Unknown Source)
at java.net.AbstractPlainSocketImpl.accept(Unknown Source)
at java.net.PlainSocketImpl.accept(Unknown Source)
at java.net.ServerSocket.implAccept(Unknown Source)
at java.net.ServerSocket.accept(Unknown Source)
at org.apache.spark.api.python.PythonWorkerFactory.createSimpleWorker(PythonWorkerFactory.scala:164)
... 14 more
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1887)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1875)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1874)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1874)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:926)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:926)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:926)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2108)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2057)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2046)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:737)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2061)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2082)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2101)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2126)
at org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:945)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:363)
at org.apache.spark.rdd.RDD.collect(RDD.scala:944)
at org.apache.spark.api.python.PythonRDD$.collectAndServe(PythonRDD.scala:166)
at org.apache.spark.api.python.PythonRDD.collectAndServe(PythonRDD.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(Unknown Source)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(Unknown Source)
at java.lang.reflect.Method.invoke(Unknown Source)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:282)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:238)
at java.lang.Thread.run(Unknown Source)
Caused by: org.apache.spark.SparkException: Python worker failed to connect back.
at org.apache.spark.api.python.PythonWorkerFactory.createSimpleWorker(PythonWorkerFactory.scala:170)
at org.apache.spark.api.python.PythonWorkerFactory.create(PythonWorkerFactory.scala:97)
at org.apache.spark.SparkEnv.createPythonWorker(SparkEnv.scala:117)
at org.apache.spark.api.python.BasePythonRunner.compute(PythonRunner.scala:108)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:65)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:121)
at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:402)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:408)
at java.util.concurrent.ThreadPoolExecutor.runWorker(Unknown Source)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(Unknown Source)
... 1 more
Caused by: java.net.SocketTimeoutException: Accept timed out
at java.net.DualStackPlainSocketImpl.waitForNewConnection(Native Method)
at java.net.DualStackPlainSocketImpl.socketAccept(Unknown Source)
at java.net.AbstractPlainSocketImpl.accept(Unknown Source)
at java.net.PlainSocketImpl.accept(Unknown Source)
at java.net.ServerSocket.implAccept(Unknown Source)
at java.net.ServerSocket.accept(Unknown Source)
at org.apache.spark.api.python.PythonWorkerFactory.createSimpleWorker(PythonWorkerFactory.scala:164)
... 14 more
You need to set the HADOOP_HOME environment variable to C:\hadoop.
SET HADOOP_HOME=C:\hadoop
spark-submit rdd\WordCount.py
The error is mostly annoying but can disrupt things that need to use your local filesystem instead of HDFS.

py4j.protocol.Py4JJavaError with PySpark [duplicate]

I'm trying to complete this Spark tutorial.
After installing Spark on local machine (Win10 64, Python 3, Spark 2.4.0) and setting all env variables (HADOOP_HOME, SPARK_HOME, etc) I'm trying to run a simple WordCount.py Spark application:
from pyspark import SparkContext, SparkConf
if __name__ == "__main__":
conf = SparkConf().setAppName("word count").setMaster("local[2]")
sc = SparkContext(conf = conf)
lines = sc.textFile("C:/Users/mjdbr/Documents/BigData/python-spark-tutorial/in/word_count.text")
words = lines.flatMap(lambda line: line.split(" "))
wordCounts = words.countByValue()
for word, count in wordCounts.items():
print("{} : {}".format(word, count))
After running it from the command line:
spark-submit WordCount.py
I get below error.
I checked (by commenting out line by line) that it crashes at
wordCounts = words.countByValue()
Any idea what should I check to make it work?
Traceback (most recent call last):
File "C:\Users\mjdbr\Anaconda3\lib\runpy.py", line 193, in _run_module_as_main
"__main__", mod_spec)
File "C:\Users\mjdbr\Anaconda3\lib\runpy.py", line 85, in _run_code
exec(code, run_globals)
File "C:\Spark\spark-2.4.0-bin-hadoop2.7\python\lib\pyspark.zip\pyspark\worker.py", line 25, in <module>
ModuleNotFoundError: No module named 'resource'
18/11/10 23:16:58 ERROR Executor: Exception in task 0.0 in stage 0.0 (TID 0)
org.apache.spark.SparkException: Python worker failed to connect back.
at org.apache.spark.api.python.PythonWorkerFactory.createSimpleWorker(PythonWorkerFactory.scala:170)
at org.apache.spark.api.python.PythonWorkerFactory.create(PythonWorkerFactory.scala:97)
at org.apache.spark.SparkEnv.createPythonWorker(SparkEnv.scala:117)
at org.apache.spark.api.python.BasePythonRunner.compute(PythonRunner.scala:108)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:65)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:121)
at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:402)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:408)
at java.util.concurrent.ThreadPoolExecutor.runWorker(Unknown Source)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(Unknown Source)
at java.lang.Thread.run(Unknown Source)
Caused by: java.net.SocketTimeoutException: Accept timed out
at java.net.DualStackPlainSocketImpl.waitForNewConnection(Native Method)
at java.net.DualStackPlainSocketImpl.socketAccept(Unknown Source)
at java.net.AbstractPlainSocketImpl.accept(Unknown Source)
at java.net.PlainSocketImpl.accept(Unknown Source)
at java.net.ServerSocket.implAccept(Unknown Source)
at java.net.ServerSocket.accept(Unknown Source)
at org.apache.spark.api.python.PythonWorkerFactory.createSimpleWorker(PythonWorkerFactory.scala:164)
... 14 more
18/11/10 23:16:58 ERROR TaskSetManager: Task 0 in stage 0.0 failed 1 times; aborting job
Traceback (most recent call last):
File "C:/Users/mjdbr/Documents/BigData/python-spark-tutorial/rdd/WordCount.py", line 19, in <module>
wordCounts = words.countByValue()
File "C:\Spark\spark-2.4.0-bin-hadoop2.7\python\lib\pyspark.zip\pyspark\rdd.py", line 1261, in countByValue
File "C:\Spark\spark-2.4.0-bin-hadoop2.7\python\lib\pyspark.zip\pyspark\rdd.py", line 844, in reduce
File "C:\Spark\spark-2.4.0-bin-hadoop2.7\python\lib\pyspark.zip\pyspark\rdd.py", line 816, in collect
File "C:\Spark\spark-2.4.0-bin-hadoop2.7\python\lib\py4j-0.10.7-src.zip\py4j\java_gateway.py", line 1257, in __call__
File "C:\Spark\spark-2.4.0-bin-hadoop2.7\python\lib\py4j-0.10.7-src.zip\py4j\protocol.py", line 328, in get_return_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): org.apache.spark.SparkException: Python worker failed to connect back.
at org.apache.spark.api.python.PythonWorkerFactory.createSimpleWorker(PythonWorkerFactory.scala:170)
at org.apache.spark.api.python.PythonWorkerFactory.create(PythonWorkerFactory.scala:97)
at org.apache.spark.SparkEnv.createPythonWorker(SparkEnv.scala:117)
at org.apache.spark.api.python.BasePythonRunner.compute(PythonRunner.scala:108)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:65)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:121)
at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:402)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:408)
at java.util.concurrent.ThreadPoolExecutor.runWorker(Unknown Source)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(Unknown Source)
at java.lang.Thread.run(Unknown Source)
Caused by: java.net.SocketTimeoutException: Accept timed out
at java.net.DualStackPlainSocketImpl.waitForNewConnection(Native Method)
at java.net.DualStackPlainSocketImpl.socketAccept(Unknown Source)
at java.net.AbstractPlainSocketImpl.accept(Unknown Source)
at java.net.PlainSocketImpl.accept(Unknown Source)
at java.net.ServerSocket.implAccept(Unknown Source)
at java.net.ServerSocket.accept(Unknown Source)
at org.apache.spark.api.python.PythonWorkerFactory.createSimpleWorker(PythonWorkerFactory.scala:164)
... 14 more
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1887)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1875)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1874)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1874)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:926)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:926)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:926)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2108)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2057)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2046)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:737)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2061)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2082)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2101)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2126)
at org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:945)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:363)
at org.apache.spark.rdd.RDD.collect(RDD.scala:944)
at org.apache.spark.api.python.PythonRDD$.collectAndServe(PythonRDD.scala:166)
at org.apache.spark.api.python.PythonRDD.collectAndServe(PythonRDD.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(Unknown Source)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(Unknown Source)
at java.lang.reflect.Method.invoke(Unknown Source)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:282)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:238)
at java.lang.Thread.run(Unknown Source)
Caused by: org.apache.spark.SparkException: Python worker failed to connect back.
at org.apache.spark.api.python.PythonWorkerFactory.createSimpleWorker(PythonWorkerFactory.scala:170)
at org.apache.spark.api.python.PythonWorkerFactory.create(PythonWorkerFactory.scala:97)
at org.apache.spark.SparkEnv.createPythonWorker(SparkEnv.scala:117)
at org.apache.spark.api.python.BasePythonRunner.compute(PythonRunner.scala:108)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:65)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:121)
at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:402)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:408)
at java.util.concurrent.ThreadPoolExecutor.runWorker(Unknown Source)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(Unknown Source)
... 1 more
Caused by: java.net.SocketTimeoutException: Accept timed out
at java.net.DualStackPlainSocketImpl.waitForNewConnection(Native Method)
at java.net.DualStackPlainSocketImpl.socketAccept(Unknown Source)
at java.net.AbstractPlainSocketImpl.accept(Unknown Source)
at java.net.PlainSocketImpl.accept(Unknown Source)
at java.net.ServerSocket.implAccept(Unknown Source)
at java.net.ServerSocket.accept(Unknown Source)
at org.apache.spark.api.python.PythonWorkerFactory.createSimpleWorker(PythonWorkerFactory.scala:164)
... 14 more
As suggested by theplatypus - checked if the 'resource' module can be imported directly from terminal - apparently not:
>>> import resource
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
ModuleNotFoundError: No module named 'resource'
In terms of installation resources - I followed instructions from this tutorial:
downloaded spark-2.4.0-bin-hadoop2.7.tgz from Apache Spark website
un-zipped it to my C-drive
already had Python_3 installed (Anaconda distribution) as well as Java
created local 'C:\hadoop\bin' folder to store winutils.exe
created 'C:\tmp\hive' folder and gave Spark access to it
added environment variables (SPARK_HOME, HADOOP_HOME etc)
Is there any extra resource I should install?
I got the same error. I solved it installing the previous version of Spark (2.3 instead of 2.4). Now it works perfectly, maybe it is an issue of the lastest version of pyspark.
Set Env PYSPARK_PYTHON=python To Fix It.
The heart of the problem is the connection between pyspark and python, solved by redefining the environment variable.
I´ve just changed the environment variable's values PYSPARK_DRIVER_PYTHON from ipython to jupyter and PYSPARK_PYTHON from python3 to python.
Now I'm using Jupyter Notebook, Python 3.7, Java JDK 11.0.6, Spark 2.4.2
I had the same issue. I had set all the environment variables correctly but still wasn't able to resolve it
In my case,
import findspark
findspark.init()
adding this before even creating the sparkSession helped.
I was using Visual Studio Code on Windows 10 and spark version was 3.2.0. Python version is 3.9 .
Note: Initially check if the paths for HADOOP_HOME SPARK_HOME PYSPARK_PYTHON have been set correctly
Downgrading Spark back to 2.3.2 from 2.4.0 was not enough for me. I don't know why but in my case I had to create SparkContext from SparkSession like
sc = spark.sparkContext
Then the very same error disappeared.
Looking at the source of the error (worker.py#L25), it seems that the python interpreter used to instanciate a pyspark worker doesn't have access to the resource module, a built-in module referred in Python's doc as part of "Unix Specific Services".
Are you sure you can run pyspark on Windows (without some additional software like GOW or MingW at least), and so that you didn't skip some Windows-specific installation steps ?
Could you open a python console (the one used by pyspark) and see if you can >>> import resource without getting the same ModuleNotFoundError ? If you don't, then could you provide the ressources you used to install it on W10 ?
When you run the python installer, on the Customize Python section, make sure that the option Add python.exe to Path is selected. If this option is not selected, some of the PySpark utilities such as pyspark and spark-submit might not work. This worked for me! Happy Sharing :)
There seems to be many reasons for this error to occur. I still had the same problem despite my environmental variables being all correctly set.
In my case adding this
import findspark
findspark.init()
solved the problem.
I'am withjupyter notebook on windows10 with spark-3.1.2, python3.6.
I had to set:
HADOOP_HOME = [..]\winutils\hadoop-3.0.0
PATH = [..]\winutils\hadoop-3.0.0\bin
PYSPARK_PYTHON = python
You can find winutils here. I use Hadoop 3.0.0 and PySpark 3.2.1.

Spark job fails with FileNotFoundException on Yarn after 7 hours

I am running a job with 4000 executors to process 3 years of data ~ 1 Petabyte. I run one query per day and process 2-3 days at the same time. Approx after processing 700 days total (~ 7 hours) it fails with some shuffle exception.
Caused by: org.apache.spark.SparkException: Job aborted due to stage failure: Task 10259 in stage 447.0 failed 4 times, most recent failure: Lost task 10259.3 in stage 447.0 (TID 1691674, machine0689.datacenter.domain.com, executor 2647): java.io.FileNotFoundException: /data4/yarn/nm/usercache/my_application/appcache/application_1535740315164_66119/blockmgr-10614d00-de24-4b2c-8bd6-2463ab4b358c/2e/temp_shuffle_6d6bae3b-d4c4-44e7-b2de-e0cdd71d35e0 (Read-only file system)
Has anyone seen this error or help figure it out? Here's the spark configuration:
spark.network.timeout=300s
spark.executor.heartbeatInterval=60s
spark.shuffle.service.enabled=true
spark.executor.instances=4000
spark.executor.cores=4
spark.executor.memory=32G
spark.executor.memoryOverhead=4G
spark.driver.cores=8
spark.driver.memory=32G
spark.driver.memoryOverhead=4G
Full StackTrace:
User class threw exception: org.apache.spark.SparkException: Job aborted.
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:224)
at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand.run(InsertIntoHadoopFsRelationCommand.scala:154)
at org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult$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$$anonfun$execute$1.apply(SparkPlan.scala:131)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:127)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:155)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:127)
at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:80)
at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:80)
at org.apache.spark.sql.DataFrameWriter$$anonfun$runCommand$1.apply(DataFrameWriter.scala:654)
at org.apache.spark.sql.DataFrameWriter$$anonfun$runCommand$1.apply(DataFrameWriter.scala:654)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:77)
at org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:654)
at org.apache.spark.sql.DataFrameWriter.saveToV1Source(DataFrameWriter.scala:273)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:267)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:225)
at org.apache.spark.sql.DataFrameWriter.parquet(DataFrameWriter.scala:547)
at com.mycompany.filter.Filter.process(Filter.scala:143)
at com.mycompany.filter.Filter$$anonfun$filterDataset$1.apply(Filter.scala:60)
at com.mycompany.filter.Filter$$anonfun$filterDataset$1.apply(Filter.scala:60)
at scala.collection.Iterator$class.foreach(Iterator.scala:893)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1336)
at scala.collection.parallel.ParIterableLike$Foreach.leaf(ParIterableLike.scala:972)
at scala.collection.parallel.Task$$anonfun$tryLeaf$1.apply$mcV$sp(Tasks.scala:49)
at scala.collection.parallel.Task$$anonfun$tryLeaf$1.apply(Tasks.scala:48)
at scala.collection.parallel.Task$$anonfun$tryLeaf$1.apply(Tasks.scala:48)
at scala.collection.parallel.Task$class.tryLeaf(Tasks.scala:51)
at scala.collection.parallel.ParIterableLike$Foreach.tryLeaf(ParIterableLike.scala:969)
at scala.collection.parallel.AdaptiveWorkStealingTasks$WrappedTask$class.internal(Tasks.scala:169)
at scala.collection.parallel.AdaptiveWorkStealingForkJoinTasks$WrappedTask.internal(Tasks.scala:443)
at scala.collection.parallel.AdaptiveWorkStealingTasks$WrappedTask$class.compute(Tasks.scala:149)
at scala.collection.parallel.AdaptiveWorkStealingForkJoinTasks$WrappedTask.compute(Tasks.scala:443)
at scala.concurrent.forkjoin.RecursiveAction.exec(RecursiveAction.java:160)
at scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
at scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)
at scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)
at scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)
Caused by: org.apache.spark.SparkException: Job aborted due to stage failure: Task 10259 in stage 447.0 failed 4 times, most recent failure: Lost task 10259.3 in stage 447.0 (TID 1691674, machine0689.datacenter.domain.com, executor 2647): java.io.FileNotFoundException: /data4/yarn/nm/usercache/my_application/appcache/application_1535740315164_66119/blockmgr-10614d00-de24-4b2c-8bd6-2463ab4b358c/2e/temp_shuffle_6d6bae3b-d4c4-44e7-b2de-e0cdd71d35e0 (Read-only file system)
at java.io.FileOutputStream.open0(Native Method)
at java.io.FileOutputStream.open(FileOutputStream.java:270)
at java.io.FileOutputStream.<init>(FileOutputStream.java:213)
at org.apache.spark.storage.DiskBlockObjectWriter.initialize(DiskBlockObjectWriter.scala:103)
at org.apache.spark.storage.DiskBlockObjectWriter.open(DiskBlockObjectWriter.scala:116)
at org.apache.spark.storage.DiskBlockObjectWriter.write(DiskBlockObjectWriter.scala:237)
at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:151)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:96)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53)
at org.apache.spark.scheduler.Task.run(Task.scala:109)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
The driver stacktrace looks like:
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$1.run(EventLoop.scala:48)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:642)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2034)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:194)
... 40 more
Caused by: java.io.FileNotFoundException: /data4/yarn/nm/usercache/my_application/appcache/application_1535740315164_66119/blockmgr-10614d00-de24-4b2c-8bd6-2463ab4b358c/2e/temp_shuffle_6d6bae3b-d4c4-44e7-b2de-e0cdd71d35e0 (Read-only file system)
at java.io.FileOutputStream.open0(Native Method)
at java.io.FileOutputStream.open(FileOutputStream.java:270)
at java.io.FileOutputStream.<init>(FileOutputStream.java:213)
at org.apache.spark.storage.DiskBlockObjectWriter.initialize(DiskBlockObjectWriter.scala:103)
at org.apache.spark.storage.DiskBlockObjectWriter.open(DiskBlockObjectWriter.scala:116)
at org.apache.spark.storage.DiskBlockObjectWriter.write(DiskBlockObjectWriter.scala:237)
at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:151)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:96)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53)
at org.apache.spark.scheduler.Task.run(Task.scala:109)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Supply below 2 properties to spark-submit-
spark.yarn.nodemanager.local-dirs=<fs path>
Spark.locak.dir=<fs path>
Read Spark WIKI for more details about these properties.

Spark connectivity issue

I am running a spark streaming program that connects to a DatahighWay and it works fine if i run the program via Run. But if I create a jar and run the jar via spark-submit I get the following error. Does this mean there are some issues in spark connecting to one of it's executor nodes? It is run in local machine.
18/05/02 22:52:20 ERROR TaskSetManager: Task 0 in stage 1.0 failed 1 times; aborting job
18/05/02 22:52:20 ERROR ReceiverTracker: Receiver has been stopped. Try to restart it.
org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 1.0 failed 1 times, most recent failure: Lost task 0.0 in stage 1.0 (TID 1, localhost, executor driver): java.io.IOException: Failed to connect to /10.184.199.182:62431
at org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:232)
at org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:182)
at org.apache.spark.rpc.netty.NettyRpcEnv.downloadClient(NettyRpcEnv.scala:366)
at org.apache.spark.rpc.netty.NettyRpcEnv.openChannel(NettyRpcEnv.scala:332)
at org.apache.spark.util.Utils$.doFetchFile(Utils.scala:654)
at org.apache.spark.util.Utils$.fetchFile(Utils.scala:480)
at org.apache.spark.executor.Executor$$anonfun$org$apache$spark$executor$Executor$$updateDependencies$5.apply(Executor.scala:696)
at org.apache.spark.executor.Executor$$anonfun$org$apache$spark$executor$Executor$$updateDependencies$5.apply(Executor.scala:688)
at scala.collection.TraversableLike$WithFilter$$anonfun$foreach$1.apply(TraversableLike.scala:733)
at scala.collection.Iterator$class.foreach(Iterator.scala:893)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1336)
at scala.collection.IterableLike$class.foreach(IterableLike.scala:72)
at scala.collection.AbstractIterable.foreach(Iterable.scala:54)
at scala.collection.TraversableLike$WithFilter.foreach(TraversableLike.scala:732)
at org.apache.spark.executor.Executor.org$apache$spark$executor$Executor$$updateDependencies(Executor.scala:688)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:308)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Caused by: io.netty.channel.AbstractChannel$AnnotatedConnectException: Operation timed out: /10.184.199.182:62431
at sun.nio.ch.SocketChannelImpl.checkConnect(Native Method)
at sun.nio.ch.SocketChannelImpl.finishConnect(SocketChannelImpl.java:717)
at io.netty.channel.socket.nio.NioSocketChannel.doFinishConnect(NioSocketChannel.java:257)
at io.netty.channel.nio.AbstractNioChannel$AbstractNioUnsafe.finishConnect(AbstractNioChannel.java:291)
at io.netty.channel.nio.NioEventLoop.processSelectedKey(NioEventLoop.java:631)
at io.netty.channel.nio.NioEventLoop.processSelectedKeysOptimized(NioEventLoop.java:566)
at io.netty.channel.nio.NioEventLoop.processSelectedKeys(NioEventLoop.java:480)
at io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:442)
at io.netty.util.concurrent.SingleThreadEventExecutor$2.run(SingleThreadEventExecutor.java:131)
at io.netty.util.concurrent.DefaultThreadFactory$DefaultRunnableDecorator.run(DefaultThreadFactory.java:144)
... 1 more
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1499)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1487)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1486)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1486)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:814)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:814)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:814)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1714)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1669)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1658)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
Caused by: java.io.IOException: Failed to connect to /10.184.199.182:62431
at org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:232)
at org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:182)
at org.apache.spark.rpc.netty.NettyRpcEnv.downloadClient(NettyRpcEnv.scala:366)
at org.apache.spark.rpc.netty.NettyRpcEnv.openChannel(NettyRpcEnv.scala:332)
at org.apache.spark.util.Utils$.doFetchFile(Utils.scala:654)
at org.apache.spark.util.Utils$.fetchFile(Utils.scala:480)
at org.apache.spark.executor.Executor$$anonfun$org$apache$spark$executor$Executor$$updateDependencies$5.apply(Executor.scala:696)
at org.apache.spark.executor.Executor$$anonfun$org$apache$spark$executor$Executor$$updateDependencies$5.apply(Executor.scala:688)
at scala.collection.TraversableLike$WithFilter$$anonfun$foreach$1.apply(TraversableLike.scala:733)
at scala.collection.Iterator$class.foreach(Iterator.scala:893)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1336)
at scala.collection.IterableLike$class.foreach(IterableLike.scala:72)
at scala.collection.AbstractIterable.foreach(Iterable.scala:54)
at scala.collection.TraversableLike$WithFilter.foreach(TraversableLike.scala:732)
at org.apache.spark.executor.Executor.org$apache$spark$executor$Executor$$updateDependencies(Executor.scala:688)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:308)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Caused by: io.netty.channel.AbstractChannel$AnnotatedConnectException: Operation timed out: /10.184.199.182:62431
at sun.nio.ch.SocketChannelImpl.checkConnect(Native Method)
at sun.nio.ch.SocketChannelImpl.finishConnect(SocketChannelImpl.java:717)
at io.netty.channel.socket.nio.NioSocketChannel.doFinishConnect(NioSocketChannel.java:257)
at io.netty.channel.nio.AbstractNioChannel$AbstractNioUnsafe.finishConnect(AbstractNioChannel.java:291)
at io.netty.channel.nio.NioEventLoop.processSelectedKey(NioEventLoop.java:631)
at io.netty.channel.nio.NioEventLoop.processSelectedKeysOptimized(NioEventLoop.java:566)
at io.netty.channel.nio.NioEventLoop.processSelectedKeys(NioEventLoop.java:480)
at io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:442)
at io.netty.util.concurrent.SingleThreadEventExecutor$2.run(SingleThreadEventExecutor.java:131)
at io.netty.util.concurrent.DefaultThreadFactory$DefaultRunnableDecorator.run(DefaultThreadFactory.java:144)
... 1 more
It seems like a connection issue, not sure how it is happening.

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