I'm trying to get started with pyspark, but having some trouble. I have python 3.10 installed and an M1 MacBook Pro. I installed pyspark using the command:
python3 -m pip install pyspark
This seemed to work okay.
aaronwright ~ % pyspark --version
Welcome to
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/___/ .__/\_,_/_/ /_/\_\ version 3.2.0
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Using Scala version 2.12.15, Java HotSpot(TM) 64-Bit Server VM, 17.0.1
Branch HEAD
Compiled by user ubuntu on 2021-10-06T12:46:30Z
Revision 5d45a415f3a29898d92380380cfd82bfc7f579ea
Url https://github.com/apache/spark
Type --help for more information.
I also installed Java from here: https://www.oracle.com/java/technologies/downloads/
aaronwright ~ % java --version
java 17.0.1 2021-10-19 LTS
Java(TM) SE Runtime Environment (build 17.0.1 12-LTS-39)
Java HotSpot(TM) 64-Bit Server VM (build 17.0.1 12-LTS-39, mixed mode, sharing)
Then tried running pyspark with the command:
pyspark
However I received a number of errors here.
Below is the output. Does anyone have any ideas? There may have a been a configuration step missed as this is the first time I've worked with spark. It could also be an incompatibility somewhere as I'm using a new Mac and new version of Python.
aaronwright ~ % pyspark
Python 3.10.0 (v3.10.0:b494f5935c, Oct 4 2021, 14:59:19) [Clang 12.0.5 (clang-1205.0.22.11)] 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).
21/12/02 16:28:34 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
21/12/02 16:28:34 WARN SparkContext: Another SparkContext is being constructed (or threw an exception in its constructor). This may indicate an error, since only one SparkContext should be running in this JVM (see SPARK-2243). The other SparkContext was created at:
org.apache.spark.api.java.JavaSparkContext.<init>(JavaSparkContext.scala:58)
java.base/jdk.internal.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
java.base/jdk.internal.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:77)
java.base/jdk.internal.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
java.base/java.lang.reflect.Constructor.newInstanceWithCaller(Constructor.java:499)
java.base/java.lang.reflect.Constructor.newInstance(Constructor.java:480)
py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:247)
py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
py4j.Gateway.invoke(Gateway.java:238)
py4j.commands.ConstructorCommand.invokeConstructor(ConstructorCommand.java:80)
py4j.commands.ConstructorCommand.execute(ConstructorCommand.java:69)
py4j.ClientServerConnection.waitForCommands(ClientServerConnection.java:182)
py4j.ClientServerConnection.run(ClientServerConnection.java:106)
java.base/java.lang.Thread.run(Thread.java:833)
/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pyspark/python/pyspark/shell.py:42: UserWarning: Failed to initialize Spark session.
warnings.warn("Failed to initialize Spark session.")
Traceback (most recent call last):
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pyspark/python/pyspark/shell.py", line 38, in <module>
spark = SparkSession._create_shell_session() # type: ignore
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pyspark/sql/session.py", line 553, in _create_shell_session
return SparkSession.builder.getOrCreate()
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pyspark/sql/session.py", line 228, in getOrCreate
sc = SparkContext.getOrCreate(sparkConf)
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pyspark/context.py", line 392, in getOrCreate
SparkContext(conf=conf or SparkConf())
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pyspark/context.py", line 146, in __init__
self._do_init(master, appName, sparkHome, pyFiles, environment, batchSize, serializer,
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pyspark/context.py", line 209, in _do_init
self._jsc = jsc or self._initialize_context(self._conf._jconf)
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pyspark/context.py", line 329, in _initialize_context
return self._jvm.JavaSparkContext(jconf)
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pyspark/python/lib/py4j-0.10.9.2-src.zip/py4j/java_gateway.py", line 1573, in __call__
return_value = get_return_value(
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pyspark/python/lib/py4j-0.10.9.2-src.zip/py4j/protocol.py", line 326, in get_return_value
raise Py4JJavaError(
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.storage.StorageUtils$
at org.apache.spark.storage.BlockManagerMasterEndpoint.<init>(BlockManagerMasterEndpoint.scala:110)
at org.apache.spark.SparkEnv$.$anonfun$create$9(SparkEnv.scala:348)
at org.apache.spark.SparkEnv$.registerOrLookupEndpoint$1(SparkEnv.scala:287)
at org.apache.spark.SparkEnv$.create(SparkEnv.scala:336)
at org.apache.spark.SparkEnv$.createDriverEnv(SparkEnv.scala:191)
at org.apache.spark.SparkContext.createSparkEnv(SparkContext.scala:277)
at org.apache.spark.SparkContext.<init>(SparkContext.scala:460)
at org.apache.spark.api.java.JavaSparkContext.<init>(JavaSparkContext.scala:58)
at java.base/jdk.internal.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
at java.base/jdk.internal.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:77)
at java.base/jdk.internal.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
at java.base/java.lang.reflect.Constructor.newInstanceWithCaller(Constructor.java:499)
at java.base/java.lang.reflect.Constructor.newInstance(Constructor.java:480)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:247)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:238)
at py4j.commands.ConstructorCommand.invokeConstructor(ConstructorCommand.java:80)
at py4j.commands.ConstructorCommand.execute(ConstructorCommand.java:69)
at py4j.ClientServerConnection.waitForCommands(ClientServerConnection.java:182)
at py4j.ClientServerConnection.run(ClientServerConnection.java:106)
at java.base/java.lang.Thread.run(Thread.java:833)
EDIT: To get this working, I needed to use Java 8:
brew install --cask homebrew/cask-versions/adoptopenjdk8
Then in my ~/.zshrc file added the line:
export JAVA_HOME='/Library/Java/JavaVirtualMachines/adoptopenjdk-8.jdk/Contents/Home/'
CodePudding user response：
You need to setup JAVA_HOME and SPARK_DIST_CLASSPATH as well. You can download Hadoop from the main website https://hadoop.apache.org/releases.html
export JAVA_HOME='/Library/Java/JavaVirtualMachines/adoptopenjdk-8.jdk/Contents/Home/'
export SPARK_DIST_CLASSPATH="/Volumes/Work/code/jars/hadoop-3.2.2/share/hadoop/tools/lib/*"
EDIT #1: You also might want to downgrade your Java or install another version. This is the official document of installing/setting up Spark https://spark.apache.org/docs/latest/index.html#downloading
Users can also download a “Hadoop free” binary and run Spark with any Hadoop version by augmenting Spark’s classpath.
Spark runs on Java 8/11, Scala 2.12, Python 3.6 and R 3.5 .
And one more docs about pip install pyspark