Why spark-shell fails with NullPointerException? - scala

Question

I try to execute spark-shell on Windows 10, but I keep getting this error every time I run it.
I used both latest and spark-1.5.0-bin-hadoop2.4 versions.
15/09/22 18:46:24 WARN Connection: BoneCP specified but not present in
CLASSPATH (or one of dependencies)
15/09/22 18:46:24 WARN Connection: BoneCP specified but not present in CLASSPATH (or one of dependencies)
15/09/22 18:46:27 WARN ObjectStore: Version information not found in
metastore. hive.metastore.schema.verification is not enabled so recording the schema version 1.2.0
15/09/22 18:46:27 WARN ObjectStore: Failed to get database default, returning NoSuchObjectException
15/09/22 18:46:27 WARN : Your hostname, DESKTOP-8JS2RD5 resolves to a loopback/non-reachable address: fe80:0:0:0:0:5efe:c0a8:103%net1, but we couldn't find any external IP address!
java.lang.RuntimeException: java.lang.NullPointerException
at org.apache.hadoop.hive.ql.session.SessionState.start(SessionState.java:522)
at org.apache.spark.sql.hive.client.ClientWrapper.<init> (ClientWrapper.scala:171)
at org.apache.spark.sql.hive.HiveContext.executionHive$lzycompute(HiveContext.scala :163)
at org.apache.spark.sql.hive.HiveContext.executionHive(HiveContext.scala:161)
at org.apache.spark.sql.hive.HiveContext.<init>(HiveContext.scala:168)
at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
at sun.reflect.NativeConstructorAccessorImpl.newInstance(Unknown Source)
at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(Unknown Source)
at java.lang.reflect.Constructor.newInstance(Unknown Source)
at org.apache.spark.repl.SparkILoop.createSQLContext(SparkILoop.scala:1028)
at $iwC$$iwC.<init>(<console>:9)
at $iwC.<init>(<console>:18)
at <init>(<console>:20)
at .<init>(<console>:24)
at .<clinit>(<console>)
at .<init>(<console>:7)
at .<clinit>(<console>)
at $print(<console>)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(Unknown Source)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(Unknown Source)
at java.lang.reflect.Method.invoke(Unknown Source)
at org.apache.spark.repl.SparkIMain$ReadEvalPrint.call(SparkIMain.scala:1065)
at org.apache.spark.repl.SparkIMain$Request.loadAndRun(SparkIMain.scala:1340)
at org.apache.spark.repl.SparkIMain.loadAndRunReq$1(SparkIMain.scala:840)
at org.apache.spark.repl.SparkIMain.interpret(SparkIMain.scala:871)
at org.apache.spark.repl.SparkIMain.interpret(SparkIMain.scala:819)
at org.apache.spark.repl.SparkILoop.reallyInterpret$1(SparkILoop.scala:857)
at org.apache.spark.repl.SparkILoop.interpretStartingWith(SparkILoop.scala:902)
at org.apache.spark.repl.SparkILoop.command(SparkILoop.scala:814)
at org.apache.spark.repl.SparkILoopInit$$anonfun$initializeSpark$1.apply(SparkILoopInit.scala:132)
at org.apache.spark.repl.SparkILoopInit$$anonfun$initializeSpark$1.apply(SparkILoopInit.scala:124)
at org.apache.spark.repl.SparkIMain.beQuietDuring(SparkIMain.scala:324)
at org.apache.spark.repl.SparkILoopInit$class.initializeSpark(SparkILoopInit.scala:124)
at org.apache.spark.repl.SparkILoop.initializeSpark(SparkILoop.scala:64)
at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1$$anonfun$apply$mcZ$sp$5.apply$mcV$sp(SparkILoop.scala:974)
at org.apache.spark.repl.SparkILoopInit$class.runThunks(SparkILoopInit.scala:159)
at org.apache.spark.repl.SparkILoop.runThunks(SparkILoop.scala:64)
at org.apache.spark.repl.SparkILoopInit$class.postInitialization(SparkILoopInit.sca la:108)
at org.apache.spark.repl.SparkILoop.postInitialization(SparkILoop.scala:64)
at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$proc ess$1.apply$mcZ$sp(SparkILoop.scala:991)
at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$proc ess$1.apply(SparkILoop.scala:945)
at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$proc ess$1.apply(SparkILoop.scala:945)
at scala.tools.nsc.util.ScalaClassLoader$.savingContextLoader(ScalaClassLoader.scal a:135)
at org.apache.spark.repl.SparkILoop.org$apache$spark$repl$SparkILoop$$process(SparkILoop.scala:945)
at org.apache.spark.repl.SparkILoop.process(SparkILoop.scala:1059)
at org.apache.spark.repl.Main$.main(Main.scala:31)
at org.apache.spark.repl.Main.main(Main.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(Unknown Source)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(Unknown Source)
at java.lang.reflect.Method.invoke(Unknown Source)
at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:672)
at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:180)
at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:205)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:120)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
Caused by: java.lang.NullPointerException
at java.lang.ProcessBuilder.start(Unknown Source)
at org.apache.hadoop.util.Shell.runCommand(Shell.java:445)
at org.apache.hadoop.util.Shell.run(Shell.java:418)
at org.apache.hadoop.util.Shell$ShellCommandExecutor.execute(Shell.java:650)
at org.apache.hadoop.util.Shell.execCommand(Shell.java:739)
at org.apache.hadoop.util.Shell.execCommand(Shell.java:722)
at org.apache.hadoop.fs.FileUtil.execCommand(FileUtil.java:1097)
at org.apache.hadoop.fs.RawLocalFileSystem$DeprecatedRawLocalFileStatus.loadPermissionInfo(RawLocalFileSystem.java:559)
at org.apache.hadoop.fs.RawLocalFileSystem$DeprecatedRawLocalFileStatus.getPermission(RawLocalFileSystem.java:534)
org.apache.hadoop.hive.ql.session.SessionState.createRootHDFSDir(SessionState.java:599)
at org.apache.hadoop.hive.ql.session.SessionState.createSessionDirs(SessionState.java:554)
org.apache.hadoop.hive.ql.session.SessionState.start(SessionState.java:508)
... 56 more
<console>:10: error: not found: value sqlContext
import sqlContext.implicits._
^
<console>:10: error: not found: value sqlContext
import sqlContext.sql
^

Answer 1

I used Spark 1.5.2 with Hadoop 2.6 and had similar problems. Solved by doing the following steps:
Download winutils.exe from the repository to some local folder, e.g. C:\hadoop\bin.
Set HADOOP_HOME to C:\hadoop.
Create c:\tmp\hive directory (using Windows Explorer or any other tool).
Open command prompt with admin rights.
Run C:\hadoop\bin\winutils.exe chmod 777 /tmp/hive
With that, I am still getting some warnings, but no ERRORs and can run Spark applications just fine.

Answer 2

I was facing a similar issue, got it resolved by putting the winutil inside bin folder. The Hadoop_home should be set as C:\Winutils and winutil to be placed in C:\Winutils\bin.
Windows 10 64 bit Winutils are available in https://github.com/steveloughran/winutils/tree/master/hadoop-2.6.0/bin
Also ensure that command line has administrative access.
Refer https://wiki.apache.org/hadoop/WindowsProblems

Answer 3

My guess is that you're running into https://issues.apache.org/jira/browse/SPARK-10528. I was seeing the same issue running on Windows 7. Initially I was getting the NullPointerException as you did. When I put winutils into the bin directory and set HADOOP_HOME to point to the Spark directory, I got the error described in the JIRA issue.

Answer 4

Or perhaps this link here below be easier to follow,
https://wiki.apache.org/hadoop/WindowsProblems
Basically download and copy winutils.exe to your spark\bin folder. Re-run spark-shell
If you have not set your /tmp/hive to a writable state, please do so.

Answer 5

You need to give permission to /tmp/hive directory to resolve this exception.
Hope you already have winutils.exe and set HADOOP_HOME environment variable. Then open the command prompt and run following command as administrator:
If winutils.exe is present in D:\winutils\bin location and \tmp\hive is also in D drive:
D:\winutils\bin\winutils.exe chmod 777 D:\tmp\hive
For more details,you can refer the following links :
Frequent Issues occurred during Spark Development
How to run Apache Spark on Windows7 in standalone mode

Answer 6

You can resolve this issue by placing mysqlconnector jar in spark-1.6.0/libs folder and restart it again.It works.
The important thing is here instead of running spark-shell you should do
spark-shell --driver-class-path /home/username/spark-1.6.0-libs-mysqlconnector.jar
Hope it should work.

Answer 7

For Python - Create a SparkSession in your python (This config section is only for Windows)
spark = SparkSession.builder.config("spark.sql.warehouse.dir", "C:/temp").appName("SparkSQL").getOrCreate()
Copy winutils.exe and keep in C:\winutils\bin and execute the bellow commands
C:\Windows\system32>C:\winutils\bin\winutils.exe chmod 777 C:/temp
Run command prompt in ADMIN mode ( Run as Administrator)

Answer 8

My issue was having other .exe's/Jars inside the winutils/bin folder. So I cleared all the others and was left with winutils.exe alone. Was using spark 2.1.1

Answer 9

Issue was resolved after installing correct Java version in my case its java 8 and setting the environmental variables. Make sure you run the winutils.exe to create a temporary directory as below.
c:\winutils\bin\winutils.exe chmod 777 \tmp\hive
Above should not return any error. Use java -version to verify the version of java you are using before invoking spark-shell.

Answer 10

In Windows, you need to clone "winutils"
git clone https://github.com/steveloughran/winutils.git
And
set var HADOOP_HOME to DIR_CLONED\hadoop-{version}
Remember to choose the version of your hadoop.

Answer 11

Setting SPARK_LOCAL_HOSTNAME as localhost (on Windows 10) resolved the problem for me