HelloSpark Tutorial Error: An error occurred while calling z:org.apache.spark.api.python.PythonRDD.collectAndServe.

[#1]

Hi there,

I am trying to follow this tutorial:

https://hortonworks.com/tutorial/setting-up-a-spark-development-environment-with-python/#create-a-sp...

Tutorial Name: Setting up a Spark Development Environment with Python

HCC Tags: tutorial-801 and hdp-2.6.0

However when I get to the running the code I initially got an error saying that winutils was not located, so I followed the instructions here:

https://stackoverflow.com/questions/34697744/spark-1-6-failed-to-locate-the-winutils-binary-in-the-h...

and downloaded WinUtils.exe and created a %HADOOP_HOME% environment variable to point to it.

Now when I run the code I get this:

E:\DataScience\pySpark\HelloSpark\venv\Scripts\python.exe E:/DataScience/pySpark/HelloSpark/main.py
WARNING: An illegal reflective access operation has occurred
2018-03-15 17:06:57 ERROR Shell:397 - Failed to locate the winutils binary in the hadoop binary path
WARNING: Illegal reflective access by org.apache.hadoop.security.authentication.util.KerberosUtil (file:/E:/DataScience/pySpark/HelloSpark/venv/Lib/site-packages/pyspark/jars/hadoop-auth-2.7.3.jar) to method sun.security.krb5.Config.getInstance()
java.io.IOException: Could not locate executable null\bin\winutils.exe in the Hadoop binaries.
WARNING: Please consider reporting this to the maintainers of org.apache.hadoop.security.authentication.util.KerberosUtil
at org.apache.hadoop.util.Shell.getQualifiedBinPath(Shell.java:379)
WARNING: Use --illegal-access=warn to enable warnings of further illegal reflective access operations
at org.apache.hadoop.util.Shell.getWinUtilsPath(Shell.java:394)

WARNING: All illegal access operations will be denied in a future release
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$1.apply(Utils.scala:2464)
at org.apache.spark.util.Utils$anonfun$getCurrentUserName$1.apply(Utils.scala:2464)
at scala.Option.getOrElse(Option.scala:121)
at org.apache.spark.util.Utils$.getCurrentUserName(Utils.scala:2464)
at org.apache.spark.SecurityManager.<init>(SecurityManager.scala:222)
at org.apache.spark.deploy.SparkSubmit$.secMgr$lzycompute$1(SparkSubmit.scala:393)
at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$secMgr$1(SparkSubmit.scala:393)
at org.apache.spark.deploy.SparkSubmit$anonfun$prepareSubmitEnvironment$7.apply(SparkSubmit.scala:401)
at org.apache.spark.deploy.SparkSubmit$anonfun$prepareSubmitEnvironment$7.apply(SparkSubmit.scala:401)
at scala.Option.map(Option.scala:146)
at org.apache.spark.deploy.SparkSubmit$.prepareSubmitEnvironment(SparkSubmit.scala:400)
at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:170)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:136)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
2018-03-15 17:06:57 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).
Traceback (most recent call last):
File "E:/DataScience/pySpark/HelloSpark/main.py", line 12, in <module>
print ("Number of elements: " + str(counts.count()))
File "E:\DataScience\pySpark\HelloSpark\venv\lib\site-packages\pyspark\rdd.py", line 1056, in count
return self.mapPartitions(lambda i: [sum(1 for _ in i)]).sum()
File "E:\DataScience\pySpark\HelloSpark\venv\lib\site-packages\pyspark\rdd.py", line 1047, in sum
return self.mapPartitions(lambda x: [sum(x)]).fold(0, operator.add)
File "E:\DataScience\pySpark\HelloSpark\venv\lib\site-packages\pyspark\rdd.py", line 921, in fold
vals = self.mapPartitions(func).collect()
File "E:\DataScience\pySpark\HelloSpark\venv\lib\site-packages\pyspark\rdd.py", line 824, in collect
port = self.ctx._jvm.PythonRDD.collectAndServe(self._jrdd.rdd())
File "E:\DataScience\pySpark\HelloSpark\venv\lib\site-packages\py4j\java_gateway.py", line 1160, in __call__
answer, self.gateway_client, self.target_id, self.name)
File "E:\DataScience\pySpark\HelloSpark\venv\lib\site-packages\py4j\protocol.py", line 320, 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.
: java.lang.IllegalArgumentException
at org.apache.xbean.asm5.ClassReader.<init>(Unknown Source)
at org.apache.xbean.asm5.ClassReader.<init>(Unknown Source)
at org.apache.xbean.asm5.ClassReader.<init>(Unknown Source)
at org.apache.spark.util.ClosureCleaner$.getClassReader(ClosureCleaner.scala:46)
at org.apache.spark.util.FieldAccessFinder$anon$3$anonfun$visitMethodInsn$2.apply(ClosureCleaner.scala:449)
at org.apache.spark.util.FieldAccessFinder$anon$3$anonfun$visitMethodInsn$2.apply(ClosureCleaner.scala:432)
at scala.collection.TraversableLike$WithFilter$anonfun$foreach$1.apply(TraversableLike.scala:733)
at scala.collection.mutable.HashMap$anon$1$anonfun$foreach$2.apply(HashMap.scala:103)
at scala.collection.mutable.HashMap$anon$1$anonfun$foreach$2.apply(HashMap.scala:103)
at scala.collection.mutable.HashTable$class.foreachEntry(HashTable.scala:230)
at scala.collection.mutable.HashMap.foreachEntry(HashMap.scala:40)
at scala.collection.mutable.HashMap$anon$1.foreach(HashMap.scala:103)
at scala.collection.TraversableLike$WithFilter.foreach(TraversableLike.scala:732)
at org.apache.spark.util.FieldAccessFinder$anon$3.visitMethodInsn(ClosureCleaner.scala:432)
at org.apache.xbean.asm5.ClassReader.a(Unknown Source)
at org.apache.xbean.asm5.ClassReader.b(Unknown Source)
at org.apache.xbean.asm5.ClassReader.accept(Unknown Source)
at org.apache.xbean.asm5.ClassReader.accept(Unknown Source)
at org.apache.spark.util.ClosureCleaner$anonfun$org$apache$spark$util$ClosureCleaner$clean$14.apply(ClosureCleaner.scala:262)
at org.apache.spark.util.ClosureCleaner$anonfun$org$apache$spark$util$ClosureCleaner$clean$14.apply(ClosureCleaner.scala:261)
at scala.collection.immutable.List.foreach(List.scala:381)
at org.apache.spark.util.ClosureCleaner$.org$apache$spark$util$ClosureCleaner$clean(ClosureCleaner.scala:261)
at org.apache.spark.util.ClosureCleaner$.clean(ClosureCleaner.scala:159)
at org.apache.spark.SparkContext.clean(SparkContext.scala:2292)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2066)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2092)
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:153)
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:564)
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:214)
at java.base/java.lang.Thread.run(Thread.java:844)

Process finished with exit code 1

Any ideas?

[#2]

Ok I found an excellent YouTube tutorial that provides a lot more detail about the setup than the original tutorial:

https://www.youtube.com/playlist?list=PLf0swTFhTI8pYbd8mr36LiYIOOY2xw5Iu

I am now getting this error:

WARNING: An illegal reflective access operation has occurred
WARNING: Illegal reflective access by org.apache.hadoop.security.authentication.util.KerberosUtil (file:/C:/spark-2.3.0-bin-hadoop2.7/jars/hadoop-auth-2.7.3.jar) to method sun.security.krb5.Config.getInstance()
WARNING: Please consider reporting this to the maintainers of org.apache.hadoop.security.authentication.util.KerberosUtil
WARNING: Use --illegal-access=warn to enable warnings of further illegal reflective access operations
WARNING: All illegal access operations will be denied in a future release
2018-03-15 19:42:54 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).
2018-03-15 19:42:54 WARN Utils:66 - Service 'SparkUI' could not bind on port 4040. Attempting port 4041.
Traceback (most recent call last):
File "E:/DataScience/pySpark/HelloSpark/main.py", line 13, in <module>
print ("Number of elements: " + str(counts.count()))
File "E:\DataScience\pySpark\HelloSpark\venv\lib\site-packages\pyspark\rdd.py", line 1056, in count
return self.mapPartitions(lambda i: [sum(1 for _ in i)]).sum()
File "E:\DataScience\pySpark\HelloSpark\venv\lib\site-packages\pyspark\rdd.py", line 1047, in sum
return self.mapPartitions(lambda x: [sum(x)]).fold(0, operator.add)
File "E:\DataScience\pySpark\HelloSpark\venv\lib\site-packages\pyspark\rdd.py", line 921, in fold
vals = self.mapPartitions(func).collect()
File "E:\DataScience\pySpark\HelloSpark\venv\lib\site-packages\pyspark\rdd.py", line 824, in collect
port = self.ctx._jvm.PythonRDD.collectAndServe(self._jrdd.rdd())
File "E:\DataScience\pySpark\HelloSpark\venv\lib\site-packages\py4j\java_gateway.py", line 1160, in __call__
answer, self.gateway_client, self.target_id, self.name)
File "E:\DataScience\pySpark\HelloSpark\venv\lib\site-packages\py4j\protocol.py", line 320, 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.
: java.lang.IllegalArgumentException
at org.apache.xbean.asm5.ClassReader.<init>(Unknown Source)
at org.apache.xbean.asm5.ClassReader.<init>(Unknown Source)
at org.apache.xbean.asm5.ClassReader.<init>(Unknown Source)
at org.apache.spark.util.ClosureCleaner$.getClassReader(ClosureCleaner.scala:46)
at org.apache.spark.util.FieldAccessFinder$anon$3$anonfun$visitMethodInsn$2.apply(ClosureCleaner.scala:449)
at org.apache.spark.util.FieldAccessFinder$anon$3$anonfun$visitMethodInsn$2.apply(ClosureCleaner.scala:432)
at scala.collection.TraversableLike$WithFilter$anonfun$foreach$1.apply(TraversableLike.scala:733)
at scala.collection.mutable.HashMap$anon$1$anonfun$foreach$2.apply(HashMap.scala:103)
at scala.collection.mutable.HashMap$anon$1$anonfun$foreach$2.apply(HashMap.scala:103)
at scala.collection.mutable.HashTable$class.foreachEntry(HashTable.scala:230)
at scala.collection.mutable.HashMap.foreachEntry(HashMap.scala:40)
at scala.collection.mutable.HashMap$anon$1.foreach(HashMap.scala:103)
at scala.collection.TraversableLike$WithFilter.foreach(TraversableLike.scala:732)
at org.apache.spark.util.FieldAccessFinder$anon$3.visitMethodInsn(ClosureCleaner.scala:432)
at org.apache.xbean.asm5.ClassReader.a(Unknown Source)
at org.apache.xbean.asm5.ClassReader.b(Unknown Source)
at org.apache.xbean.asm5.ClassReader.accept(Unknown Source)
at org.apache.xbean.asm5.ClassReader.accept(Unknown Source)
at org.apache.spark.util.ClosureCleaner$anonfun$org$apache$spark$util$ClosureCleaner$clean$14.apply(ClosureCleaner.scala:262)
at org.apache.spark.util.ClosureCleaner$anonfun$org$apache$spark$util$ClosureCleaner$clean$14.apply(ClosureCleaner.scala:261)
at scala.collection.immutable.List.foreach(List.scala:381)
at org.apache.spark.util.ClosureCleaner$.org$apache$spark$util$ClosureCleaner$clean(ClosureCleaner.scala:261)
at org.apache.spark.util.ClosureCleaner$.clean(ClosureCleaner.scala:159)
at org.apache.spark.SparkContext.clean(SparkContext.scala:2292)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2066)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2092)
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:153)
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:564)
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:214)
at java.base/java.lang.Thread.run(Thread.java:844)

Process finished with exit code 1