I have the following simple wordcount Python script.
from pyspark import SparkConf, SparkContext
conf = SparkConf().setMaster("local").setAppName("My App")
sc = SparkContext(conf = conf)
from operator import add
f=sc.textFile("C:/Spark/spark-1.2.0/README.md")
wc=f.flatMap(lambda x: x.split(" ")).map(lambda x: (x,1)).reduceByKey(add)
print wc
wc.saveAsTextFile("wc_out.txt")
I am launching this script using this command line:
spark-submit "C:/Users/Alexis/Desktop/SparkTest.py"
I am getting the following error:
Picked up _JAVA_OPTIONS: -Djava.net.preferIPv4Stack=true
15/04/20 18:58:01 WARN Utils: Your hostname, AE-LenovoUltra resolves to a loopba
ck address: 127.0.1.2; using 192.168.1.63 instead (on interface net0)
15/04/20 18:58:01 WARN Utils: Set SPARK_LOCAL_IP if you need to bind to another
address
15/04/20 18:58:10 WARN NativeCodeLoader: Unable to load native-hadoop library fo
r your platform... using builtin-java classes where applicable
15/04/20 18:58:11 ERROR Shell: Failed to locate the winutils binary in the hadoo
p binary path
java.io.IOException: Could not locate executable null\bin\winutils.exe in the Ha
doop binaries.
at org.apache.hadoop.util.Shell.getQualifiedBinPath(Shell.java:278)
at org.apache.hadoop.util.Shell.getWinUtilsPath(Shell.java:300)
at org.apache.hadoop.util.Shell.<clinit>(Shell.java:293)
at org.apache.hadoop.fs.FileUtil.chmod(FileUtil.java:867)
at org.apache.hadoop.fs.FileUtil.chmod(FileUtil.java:853)
at org.apache.spark.util.Utils$.fetchFile(Utils.scala:411)
at org.apache.spark.SparkContext.addFile(SparkContext.scala:969)
at org.apache.spark.SparkContext$$anonfun$12.apply(SparkContext.scala:28
0)
at org.apache.spark.SparkContext$$anonfun$12.apply(SparkContext.scala:28
0)
at scala.collection.immutable.List.foreach(List.scala:318)
at org.apache.spark.SparkContext.<init>(SparkContext.scala:280)
at org.apache.spark.api.java.JavaSparkContext.<init>(JavaSparkContext.sc
ala:61)
at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstruct
orAccessorImpl.java:57)
at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingC
onstructorAccessorImpl.java:45)
at java.lang.reflect.Constructor.newInstance(Constructor.java:526)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:234)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:379)
at py4j.Gateway.invoke(Gateway.java:214)
at py4j.commands.ConstructorCommand.invokeConstructor(ConstructorCommand
.java:79)
at py4j.commands.ConstructorCommand.execute(ConstructorCommand.java:68)
at py4j.GatewayConnection.run(GatewayConnection.java:207)
at java.lang.Thread.run(Thread.java:745)
Traceback (most recent call last):
File "C:/Users/Alexis/Desktop/SparkTest.py", line 3, in <module>
sc = SparkContext(conf = conf)
File "C:\Spark\spark-1.2.0\python\pyspark\context.py", line 105, in __init__
conf, jsc)
File "C:\Spark\spark-1.2.0\python\pyspark\context.py", line 153, in _do_init
self._jsc = jsc or self._initialize_context(self._conf._jconf)
File "C:\Spark\spark-1.2.0\python\pyspark\context.py", line 201, in _initializ
e_context
return self._jvm.JavaSparkContext(jconf)
File "C:\Spark\spark-1.2.0\python\lib\py4j-0.8.2.1-src.zip\py4j\java_gateway.p
y", line 701, in __call__
File "C:\Spark\spark-1.2.0\python\lib\py4j-0.8.2.1-src.zip\py4j\protocol.py",
line 300, in get_return_value
py4j.protocol.Py4JJavaError: An error occurred while calling None.org.apache.spa
rk.api.java.JavaSparkContext.
: java.lang.NullPointerException
at java.lang.ProcessBuilder.start(ProcessBuilder.java:1010)
at org.apache.hadoop.util.Shell.runCommand(Shell.java:404)
at org.apache.hadoop.util.Shell.run(Shell.java:379)
at org.apache.hadoop.util.Shell$ShellCommandExecutor.execute(Shell.java:
589)
at org.apache.hadoop.fs.FileUtil.chmod(FileUtil.java:873)
at org.apache.hadoop.fs.FileUtil.chmod(FileUtil.java:853)
at org.apache.spark.util.Utils$.fetchFile(Utils.scala:411)
at org.apache.spark.SparkContext.addFile(SparkContext.scala:969)
at org.apache.spark.SparkContext$$anonfun$12.apply(SparkContext.scala:28
0)
at org.apache.spark.SparkContext$$anonfun$12.apply(SparkContext.scala:28
0)
at scala.collection.immutable.List.foreach(List.scala:318)
at org.apache.spark.SparkContext.<init>(SparkContext.scala:280)
at org.apache.spark.api.java.JavaSparkContext.<init>(JavaSparkContext.sc
ala:61)
at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstruct
orAccessorImpl.java:57)
at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingC
onstructorAccessorImpl.java:45)
at java.lang.reflect.Constructor.newInstance(Constructor.java:526)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:234)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:379)
at py4j.Gateway.invoke(Gateway.java:214)
at py4j.commands.ConstructorCommand.invokeConstructor(ConstructorCommand
.java:79)
at py4j.commands.ConstructorCommand.execute(ConstructorCommand.java:68)
at py4j.GatewayConnection.run(GatewayConnection.java:207)
at java.lang.Thread.run(Thread.java:745)
To a Spark beginner like me, it seems that this is the problem: "ERROR Shell: Failed to locate the winutils binary in the hadoop binary path". However, the Spark documentation clearly states that a Hadoop installation is not necessary for Spark to run in standalone mode.
What am I doing wrong?
The good news is you're not doing anything wrong, and your code will run after the error is mitigated.
Despite the statement that Spark will run on Windows without Hadoop, it still looks for some Hadoop components. The bug has a JIRA ticket (SPARK-2356), and a patch is available. As of Spark 1.3.1, the patch hasn't been committed to the main branch yet.
Fortunately, there's a fairly easy work around.
Create a bin directory for winutils under your Spark installation directory. In my case, Spark is installed in D:\Languages\Spark, so I created the following path: D:\Languages\Spark\winutils\bin
Download the winutils.exe from Hortonworks and put it into the bin directory created in the first step. Download link for Win64: http://public-repo-1.hortonworks.com/hdp-win-alpha/winutils.exe
Create a "HADOOP_HOME" environment variable that points to the winutils directory (not the bin subdirectory). You can do this in a couple of ways:
a. Establish a permanent environment variable via the Control Panel -> System -> Advanced System Settings -> Advanced Tab -> Environment variables. You can create either a user variable or a system variable with the following parameters:
Variable Name=HADOOP_HOME
Variable Value=D:\Languages\Spark\winutils\
b. Set a temporary environment variable inside your command shell
before executing your script
set HADOOP_HOME=d:\\Languages\\Spark\\winutils
Run your code. It should work without error now.
Related
I am attempting to create a PySpark job via the Databricks UI (with spark-submit) using the spark-submit parameters below (dependencies are on the PEX file), but I am getting an exception that the PEX file does not exist. It's my understanding that the --files option puts the file in the working directory of the driver & every executor, so I am confused as to why I am encountering this issue.
Config
[
"--files","s3://some_path/my_pex.pex",
"--conf","spark.pyspark.python=./my_pex.pex",
"s3://some_path/main.py",
"--some_arg","2022-08-01"
]
Standard Error
OpenJDK 64-Bit Server VM warning: ignoring option MaxPermSize=512m; support was removed in 8.0
Warning: Ignoring non-Spark config property: libraryDownload.sleepIntervalSeconds
Warning: Ignoring non-Spark config property: libraryDownload.timeoutSeconds
Warning: Ignoring non-Spark config property: eventLog.rolloverIntervalSeconds
Exception in thread "main" java.io.IOException: Cannot run program "./my_pex.pex": error=2, No such file or directory
at java.lang.ProcessBuilder.start(ProcessBuilder.java:1048)
at org.apache.spark.deploy.PythonRunner$.main(PythonRunner.scala:97)
at org.apache.spark.deploy.PythonRunner.main(PythonRunner.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.spark.deploy.JavaMainApplication.start(SparkApplication.scala:52)
at org.apache.spark.deploy.SparkSubmit.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:951)
at org.apache.spark.deploy.SparkSubmit.doRunMain$1(SparkSubmit.scala:180)
at org.apache.spark.deploy.SparkSubmit.submit(SparkSubmit.scala:203)
at org.apache.spark.deploy.SparkSubmit.doSubmit(SparkSubmit.scala:90)
at org.apache.spark.deploy.SparkSubmit$$anon$2.doSubmit(SparkSubmit.scala:1039)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:1048)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
Caused by: java.io.IOException: error=2, No such file or directory
at java.lang.UNIXProcess.forkAndExec(Native Method)
at java.lang.UNIXProcess.<init>(UNIXProcess.java:247)
at java.lang.ProcessImpl.start(ProcessImpl.java:134)
at java.lang.ProcessBuilder.start(ProcessBuilder.java:1029)
... 14 more
What I have tried
Given that the PEX file doesn't seem to be visible, I have tried adding it via the following ways:
Adding the PEX via the --files option in Spark submit
Adding the PEX via the the spark.files config when starting up the actual cluster
Putting the PEX in DBFS (as opposed to s3)
Playing around with the configs (e.g. using spark.pyspark.driver.python instead of spark.pyspark.python)
Note: given that instructions at the bottom of this page, I believe PEX should work on Databricks; I'm just not sure as to the right configs: https://www.databricks.com/blog/2020/12/22/how-to-manage-python-dependencies-in-pyspark.html
Note also, the following spark submit command works on AWS EMR:
'HadoopJarStep': {
'Jar': 'command-runner.jar',
'Args': [
"spark-submit",
"--deploy-mode", "cluster",
"--master", "yarn",
"--files", "s3://some_path/my_pex.pex",
"--conf", "spark.pyspark.driver.python=./my_pex.pex",
"--conf", "spark.executorEnv.PEX_ROOT=./tmp",
"--conf", "spark.yarn.appMasterEnv.PEX_ROOT=./tmp",
"s3://some_path/main.py",
"--some_arg", "some-val"
]
Any help would be much appreciated, thanks.
i'm using PyCharm 2019.1, and Python 3.7 (in Project Interpreter)
On PyCharm, i've added Pyspark 2.4.2
when i run the following code (to create a Spark DataFrame), i get error
java.util.NoSuchElementException: key not found: _PYSPARK_DRIVER_CALLBACK_HOST
....
Exception: Java gateway process exited before sending its port number
from the other SO issues, it seems that it is related to version mismatch,
question is how to resolve this
my $SPARK_HOME points to Apache Spark 2.2.0,
when i try to install 2.2.0 on Pycharm, it gives error
Collecting pyspark==2.2.0
Could not find a version that satisfies the requirement pyspark==2.2.0 (from versions: 2.1.2, 2.1.3, 2.2.0.post0, 2.2.1, 2.2.2, 2.2.3, 2.3.0, 2.3.1, 2.3.2, 2.3.3, 2.4.0, 2.4.1, 2.4.2, 2.4.3)
No matching distribution found for pyspark==2.2.0
Any ideas on how to fix this ?
CODE ->
from pyspark.sql import SparkSession
d = {'a':1, 'b':2, 'c':3}
spark = SparkSession.builder.master("local").appName("CreatingDF").getOrCreate()
pandaDF = spark.createDataFrame(d)
print(pandaDF)
ERROR ->
Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).
19/05/06 23:21:45 ERROR SparkUncaughtExceptionHandler: Uncaught exception in thread Thread[main,5,main]
java.util.NoSuchElementException: key not found: _PYSPARK_DRIVER_CALLBACK_HOST
at scala.collection.MapLike$class.default(MapLike.scala:228)
at scala.collection.AbstractMap.default(Map.scala:59)
at scala.collection.MapLike$class.apply(MapLike.scala:141)
at scala.collection.AbstractMap.apply(Map.scala:59)
at org.apache.spark.api.python.PythonGatewayServer$$anonfun$main$1.apply$mcV$sp(PythonGatewayServer.scala:50)
at org.apache.spark.util.Utils$.tryOrExit(Utils.scala:1262)
at org.apache.spark.api.python.PythonGatewayServer$.main(PythonGatewayServer.scala:37)
at org.apache.spark.api.python.PythonGatewayServer.main(PythonGatewayServer.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:497)
at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:755)
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$.main(SparkSubmit.scala:119)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
Traceback (most recent call last):
File "/Users/karanalang/PycharmProjects/PythonFalcon/FalconIncremental/python_createDF2.py", line 28, in <module>
spark = SparkSession.builder.master("local").appName("CreatingDF").getOrCreate()
File "/Users/karanalang/anaconda3/lib/python3.7/site-packages/pyspark/sql/session.py", line 173, in getOrCreate
sc = SparkContext.getOrCreate(sparkConf)
File "/Users/karanalang/anaconda3/lib/python3.7/site-packages/pyspark/context.py", line 367, in getOrCreate
SparkContext(conf=conf or SparkConf())
File "/Users/karanalang/anaconda3/lib/python3.7/site-packages/pyspark/context.py", line 133, in __init__
SparkContext._ensure_initialized(self, gateway=gateway, conf=conf)
File "/Users/karanalang/anaconda3/lib/python3.7/site-packages/pyspark/context.py", line 316, in _ensure_initialized
SparkContext._gateway = gateway or launch_gateway(conf)
File "/Users/karanalang/anaconda3/lib/python3.7/site-packages/pyspark/java_gateway.py", line 46, in launch_gateway
return _launch_gateway(conf)
File "/Users/karanalang/anaconda3/lib/python3.7/site-packages/pyspark/java_gateway.py", line 108, in _launch_gateway
raise Exception("Java gateway process exited before sending its port number")
Exception: Java gateway process exited before sending its port number
Yes.It's versioning issue. Verify your python version on your command prompt/terminal. If default python version is 2.7 and pyCharm is pointing to python3.7 in it's interpreter then it should work.
mostly Anaconda3 and onwards cause this issue.
I installed Spark on my EC2 instance following this tutorial:
https://sparkour.urizone.net/recipes/installing-ec2/#03
but when I try to start pyspark shell, I get this error:
"Another SparkContext is being constructed"
Here is the full exception:
[ec2-user#ip-10-0-0-153 ~]$ pyspark
Python 2.7.12 (default, Sep 1 2016, 22:14:00)
[GCC 4.8.3 20140911 (Red Hat 4.8.3-9)] on linux2
Type "help", "copyright", "credits" or "license" for more information.
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).
17/08/22 11:46:16 WARN spark.SparkContext: Another SparkContext is being constructed (or threw an exception in its constructor). This may indicate an error, since only one SparkContext may be running in this JVM (see SPARK-2243). The other SparkContext was created at:
org.apache.spark.api.java.JavaSparkContext.<init>(JavaSparkContext.scala:58)
sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62)
sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
java.lang.reflect.Constructor.newInstance(Constructor.java:423)
py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:247)
py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
py4j.Gateway.invoke(Gateway.java:236)
py4j.commands.ConstructorCommand.invokeConstructor(ConstructorCommand.java:80)
py4j.commands.ConstructorCommand.execute(ConstructorCommand.java:69)
py4j.GatewayConnection.run(GatewayConnection.java:214)
java.lang.Thread.run(Thread.java:748)
Traceback (most recent call last):
File "/opt/spark/python/pyspark/shell.py", line 54, in <module>
spark = SparkSession.builder.getOrCreate()
File "/opt/spark/python/pyspark/sql/session.py", line 169, in getOrCreate
sc = SparkContext.getOrCreate(sparkConf)
File "/opt/spark/python/pyspark/context.py", line 334, in getOrCreate
SparkContext(conf=conf or SparkConf())
File "/opt/spark/python/pyspark/context.py", line 118, in __init__
conf, jsc, profiler_cls)
File "/opt/spark/python/pyspark/context.py", line 180, in _do_init
self._jsc = jsc or self._initialize_context(self._conf._jconf)
File "/opt/spark/python/pyspark/context.py", line 273, in _initialize_context
return self._jvm.JavaSparkContext(jconf)
File "/opt/spark/python/lib/py4j-0.10.4-src.zip/py4j/java_gateway.py", line 1401, in __call__
File "/opt/spark/python/lib/py4j-0.10.4-src.zip/py4j/protocol.py", line 319, in get_return_value
py4j.protocol.Py4JJavaError: An error occurred while calling None.org.apache.spark.api.java.JavaSparkContext.
: java.lang.NoClassDefFoundError: Could not initialize class org.apache.spark.internal.config.package$
at org.apache.spark.SparkConf.validateSettings(SparkConf.scala:546)
at org.apache.spark.SparkContext.<init>(SparkContext.scala:373)
at org.apache.spark.api.java.JavaSparkContext.<init>(JavaSparkContext.scala:58)
at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62)
at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
at java.lang.reflect.Constructor.newInstance(Constructor.java:423)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:247)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:236)
at py4j.commands.ConstructorCommand.invokeConstructor(ConstructorCommand.java:80)
at py4j.commands.ConstructorCommand.execute(ConstructorCommand.java:69)
at py4j.GatewayConnection.run(GatewayConnection.java:214)
at java.lang.Thread.run(Thread.java:748)
I googled a lot and tried everything with no solution. I used this code to get a list of all running Contexts:
>>> from pyspark import SparkConf
>>> conf = SparkConf()
>>> conf.getAll()
And I got this:
[(u'spark.master', u'local[*]'), (u'spark.submit.deployMode', u'client'), (u'spark.app.name', u'PySparkShell')]
Any ideas how can I solve this issue?
I encountered the same error while trying to run PySpark in Jupyter Notebook (on macOS). The problem seems related to a Java version incompatibility and it only works with Java 8. I fixed the issue by changing the java version:
check java (JVM) installation versions. If you don't have java 8 installed, install it following instructions for your OS.
/usr/libexec/java_home -V
change the version to Java 8 (it is enough to do it for the current session)
export JAVA_HOME=/usr/libexec/java_home -v 1.8....
check:
java -version
run PySpark. that should solve the issue.
I solved the problem by setting the SPARK_MASTER_HOST=127.0.0.1 in spark-env.sh file
Navigate to Spark config folder:
cd $SPARK_HOME/conf
Open spark-env.sh file using an editor (is this file does not exist copy the spark-env-template file):
vi spark-env.sh
edit the SPARK_LOCAL_IP value to your machine IP (e.g. 205.210.42.205) :
SPARK_LOCAL_IP="205.210.42.205"
Hope this helps.
I'm trying to add S3DistCp to my local, standalone Spark install. I've downloaded S3DistCp:
aws s3 cp s3://elasticmapreduce/libs/s3distcp/1.latest/s3distcp.jar .
And the AWS SDK as well:
wget http://sdk-for-java.amazonwebservices.com/latest/aws-java-sdk.zip
I extracted the AWS SDK:
unzip aws-java-sdk.zip
Then added s3distcp.jar to my spark-defaults.conf:
spark.driver.extraClassPath /Users/mark.miller/.ivy2/jars/s3distcp.jar
spark.executor.extraClassPath /Users/mark.miller/.ivy2/jars/s3distcp.jar
Then I added the AWS SDK and all it's dependencies to $LIBJARS and $HADOOP_CLASSPATH
export $LIBJARS=/Users/mark.miller/Downloads/aws-java-sdk-1.11.86/lib/aws-java-sdk-1.11.86.jar,/Users/mark.miller/Downloads/aws-java-sdk-1.11.86/third-party/lib/aspectjrt-1.8.2.jar,/Users/mark.miller/Downloads/aws-java-sdk-1.11.86/third-party/lib/aspectjweaver.jar,/Users/mark.miller/Downloads/aws-java-sdk-1.11.86/third-party/lib/commons-codec-1.9.jar,/Users/mark.miller/Downloads/aws-java-sdk-1.11.86/third-party/lib/commons-logging-1.1.3.jar,/Users/mark.miller/Downloads/aws-java-sdk-1.11.86/third-party/lib/freemarker-2.3.9.jar,/Users/mark.miller/Downloads/aws-java-sdk-1.11.86/third-party/lib/httpclient-4.5.2.jar,/Users/mark.miller/Downloads/aws-java-sdk-1.11.86/third-party/lib/httpcore-4.4.4.jar,/Users/mark.miller/Downloads/aws-java-sdk-1.11.86/third-party/lib/ion-java-1.0.1.jar,/Users/mark.miller/Downloads/aws-java-sdk-1.11.86/third-party/lib/jackson-annotations-2.6.0.jar,/Users/mark.miller/Downloads/aws-java-sdk-1.11.86/third-party/lib/jackson-core-2.6.6.jar,/Users/mark.miller/Downloads/aws-java-sdk-1.11.86/third-party/lib/jackson-databind-2.6.6.jar,/Users/mark.miller/Downloads/aws-java-sdk-1.11.86/third-party/lib/jackson-dataformat-cbor-2.6.6.jar,/Users/mark.miller/Downloads/aws-java-sdk-1.11.86/third-party/lib/javax.mail-api-1.4.6.jar,/Users/mark.miller/Downloads/aws-java-sdk-1.11.86/third-party/lib/jmespath-java-1.11.86.jar,/Users/mark.miller/Downloads/aws-java-sdk-1.11.86/third-party/lib/joda-time-2.8.1.jar,/Users/mark.miller/Downloads/aws-java-sdk-1.11.86/third-party/lib/json-path-2.2.0.jar,/Users/mark.miller/Downloads/aws-java-sdk-1.11.86/third-party/lib/slf4j-api-1.7.16.jar,/Users/mark.miller/Downloads/aws-java-sdk-1.11.86/third-party/lib/spring-beans-3.0.7.RELEASE.jar,/Users/mark.miller/Downloads/aws-java-sdk-1.11.86/third-party/lib/spring-context-3.0.7.RELEASE.jar,/Users/mark.miller/Downloads/aws-java-sdk-1.11.86/third-party/lib/spring-core-3.0.7.RELEASE.jar,/Users/mark.miller/Downloads/aws-java-sdk-1.11.86/third-party/lib/spring-test-3.0.7.RELEASE.jar
export HADOOP_CLASSPATH=$LIBJARS
But when I try to start the pyspark shell:
$ pyspark
I get the following error:
Python 2.7.13 (default, Dec 18 2016, 07:03:39)
[GCC 4.2.1 Compatible Apple LLVM 8.0.0 (clang-800.0.42.1)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
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).
17/02/06 17:48:50 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
17/02/06 17:48:50 WARN SparkContext: Another SparkContext is being constructed (or threw an exception in its constructor). This may indicate an error, since only one SparkContext may be running in this JVM (see SPARK-2243). The other SparkContext was created at:
org.apache.spark.api.java.JavaSparkContext.<init>(JavaSparkContext.scala:58)
sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62)
sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
java.lang.reflect.Constructor.newInstance(Constructor.java:423)
py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:247)
py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
py4j.Gateway.invoke(Gateway.java:236)
py4j.commands.ConstructorCommand.invokeConstructor(ConstructorCommand.java:80)
py4j.commands.ConstructorCommand.execute(ConstructorCommand.java:69)
py4j.GatewayConnection.run(GatewayConnection.java:214)
java.lang.Thread.run(Thread.java:745)
Traceback (most recent call last):
File "/usr/local/Cellar/apache-spark/2.1.0/libexec/python/pyspark/shell.py", line 47, in <module>
spark = SparkSession.builder.getOrCreate()
File "/usr/local/Cellar/apache-spark/2.1.0/libexec/python/pyspark/sql/session.py", line 169, in getOrCreate
sc = SparkContext.getOrCreate(sparkConf)
File "/usr/local/Cellar/apache-spark/2.1.0/libexec/python/pyspark/context.py", line 307, in getOrCreate
SparkContext(conf=conf or SparkConf())
File "/usr/local/Cellar/apache-spark/2.1.0/libexec/python/pyspark/context.py", line 118, in __init__
conf, jsc, profiler_cls)
File "/usr/local/Cellar/apache-spark/2.1.0/libexec/python/pyspark/context.py", line 179, in _do_init
self._jsc = jsc or self._initialize_context(self._conf._jconf)
File "/usr/local/Cellar/apache-spark/2.1.0/libexec/python/pyspark/context.py", line 246, in _initialize_context
return self._jvm.JavaSparkContext(jconf)
File "/usr/local/Cellar/apache-spark/2.1.0/libexec/python/lib/py4j-0.10.4-src.zip/py4j/java_gateway.py", line 1401, in __call__
File "/usr/local/Cellar/apache-spark/2.1.0/libexec/python/lib/py4j-0.10.4-src.zip/py4j/protocol.py", line 319, in get_return_value
py4j.protocol.Py4JJavaError: An error occurred while calling None.org.apache.spark.api.java.JavaSparkContext.
: java.lang.NoClassDefFoundError: Could not initialize class com.google.common.cache.LocalCache
at com.google.common.cache.LocalCache$LocalLoadingCache.<init>(LocalCache.java:4867)
at com.google.common.cache.CacheBuilder.build(CacheBuilder.java:785)
at org.apache.hadoop.security.Groups.<init>(Groups.java:101)
at org.apache.hadoop.security.Groups.<init>(Groups.java:74)
at org.apache.hadoop.security.Groups.getUserToGroupsMappingService(Groups.java:303)
at org.apache.hadoop.security.UserGroupInformation.initialize(UserGroupInformation.java:284)
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$$anonfun$getCurrentUserName$1.apply(Utils.scala:2373)
at org.apache.spark.util.Utils$$anonfun$getCurrentUserName$1.apply(Utils.scala:2373)
at scala.Option.getOrElse(Option.scala:121)
at org.apache.spark.util.Utils$.getCurrentUserName(Utils.scala:2373)
at org.apache.spark.SparkContext.<init>(SparkContext.scala:295)
at org.apache.spark.api.java.JavaSparkContext.<init>(JavaSparkContext.scala:58)
at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62)
at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
at java.lang.reflect.Constructor.newInstance(Constructor.java:423)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:247)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:236)
at py4j.commands.ConstructorCommand.invokeConstructor(ConstructorCommand.java:80)
at py4j.commands.ConstructorCommand.execute(ConstructorCommand.java:69)
at py4j.GatewayConnection.run(GatewayConnection.java:214)
at java.lang.Thread.run(Thread.java:745)
If I remove s3distcp.jar from spark-defaults.conf the error goes away. There just doesn't seem to be much documentation on how to deploy this since it's provided as part of EMR.
I was able to get this working by passing --driver-class-path to pyspark:
$ pyspark \
--driver-class-path \
~/Downloads/aws-java-sdk-1.11.86/lib/aws-java-sdk-1.11.86.jar:\
~/Downloads/aws-java-sdk-1.11.86/third-party/lib/*
To set this up in spark-defaults.conf I had to do it this way:
spark.jars /Users/mark.miller/.ivy2/jars/s3distcp.jar
spark.driver.extraClassPath /Users/mark.miller/Downloads/aws-java-sdk-1.11.86/lib/aws-java-sdk-1.11.86.jar:/Users/mark.miller/Downloads/aws-java-sdk-1.11.86/third-party/lib/*
I also learned that spark.executor.extraClassPath is only needed for backwards-compatibility with older versions of spark (https://spark.apache.org/docs/latest/configuration.html#runtime-environment)
I have referred the following links in order to understand how to export spark sql dataframe in python
https://github.com/databricks/spark-csv
How to export data from Spark SQL to CSV
My code:
df = sqlContext.createDataFrame(routeRDD, ['Consigner', 'AverageScore', 'Trips'])
df.select('Consigner', 'AverageScore', 'Trips').write.format('com.databricks.spark.csv').options(header='true').save('file:///opt/BIG-DATA/VisualCargo/output/top_consigner.csv')
I load the job with spark-submit passing the following jars on master url
spark-csv_2.11-1.5.0.jar, commons-csv-1.4.jar
I am getting the following error
df.select('Consigner', 'AverageScore', 'Trips').write.format('com.databricks.spark.csv').options(header='true').save('file:///opt/BIG-DATA/VisualCargo/output/top_consigner.csv')
File "/opt/cloudera/parcels/CDH-5.5.1-1.cdh5.5.1.p0.11/lib/spark/python/lib/pyspark.zip/pyspark/sql/readwriter.py", line 332, in save
File "/opt/cloudera/parcels/CDH-5.5.1-1.cdh5.5.1.p0.11/lib/spark/python/lib/py4j-0.8.2.1-src.zip/py4j/java_gateway.py", line 538, in __call__
File "/opt/cloudera/parcels/CDH-5.5.1-1.cdh5.5.1.p0.11/lib/spark/python/lib/pyspark.zip/pyspark/sql/utils.py", line 36, in deco
File "/opt/cloudera/parcels/CDH-5.5.1-1.cdh5.5.1.p0.11/lib/spark/python/lib/py4j-0.8.2.1-src.zip/py4j/protocol.py", line 300, in get_return_value
py4j.protocol.Py4JJavaError: An error occurred while calling o156.save.
py4j.protocol.Py4JJavaError: An error occurred while calling o156.save.
: java.lang.NoSuchMethodError: scala.Predef$.$conforms()Lscala/Predef$$less$colon$less;
at com.databricks.spark.csv.util.CompressionCodecs$.<init>(CompressionCodecs.scala:29)
at com.databricks.spark.csv.util.CompressionCodecs$.<clinit>(CompressionCodecs.scala)
at com.databricks.spark.csv.DefaultSource.createRelation(DefaultSource.scala:198)
at org.apache.spark.sql.execution.datasources.ResolvedDataSource$.apply(ResolvedDataSource.scala:170)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:146)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:137)
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:231)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:379)
at py4j.Gateway.invoke(Gateway.java:259)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:133)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:207)
at java.lang.Thread.run(Thread.java:745)
Spark version 1.5.0-cdh5.5.1 is built with Scala 2.10 - default Scala version for Spark < 2.0. Your spark-csv is built with Scala 2.10 - spark-csv_2.11-1.5.0.jar.
Please update spark-csv to version with Scala 2.10 or update Spark to Scala 2.11. You will know Scala version by number after artifactId, i.e. spark-csv_2.10-1.5.0 will be for Scala 2.10
I am running Spark on Windows and I faced the similar issue of not able to write to file(CSV or Parquet). Upon reading more into Spark website, I found the below error, and it is because of the winutils version that I am using. I changed it to 64bit and it worked. Hope this helps some one.
Spark Log