使用pip在Mac上安装PySpark时出现初始化错误

Question

使用pip在Mac上安装PySpark时出现初始化错误

pythonpython-3.xapache-sparkpysparkapple-m1

3

我想开始学习pyspark，但遇到了一些问题。我已经安装了Python 3.10和M1 MacBook Pro。我使用以下命令安装了pyspark：

python3 -m pip install pyspark

这似乎运行良好。

aaronwright ~ % pyspark --version

Welcome to
      ____              __
     / __/__  ___ _____/ /__
    _\ \/ _ \/ _ `/ __/  '_/
   /___/ .__/\_,_/_/ /_/\_\   version 3.2.0
      /_/
                        
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.

我也从这里安装了Java： 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)

然后尝试使用以下命令运行pyspark：

pyspark

但是我在这里收到了一些错误信息。

下面是输出结果。有人有什么想法吗？可能会有遗漏的配置步骤，因为这是我第一次使用spark。也可能是某个地方不兼容，因为我正在使用新Mac和新版本的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)

编辑：要使其正常工作，我需要使用Java 8：

brew install --cask homebrew/cask-versions/adoptopenjdk8

然后在~/.zshrc文件中添加以下行：

export JAVA_HOME='/Library/Java/JavaVirtualMachines/adoptopenjdk-8.jdk/Contents/Home/'

- user14380579

2个回答

0

我遇到了类似的问题（在我的Mac上）。我也安装了Anaconda。我尝试通过执行以下命令从Anaconda中卸载pyspark包：

conda uninstall pyspark

但它没有完全删除pyspark。虽然pyspark bin已经消失，但是留下了一些残留文件。所以我手动移动了pyspark文件夹，然后使用以下命令安装了pyspark：

pip install pyspark

之后，pyspark可以正常工作。

- ManojPatra

网页内容由stack overflow 提供, 点击上面的

可以查看英文原文，
原文链接

- pltc · Accepted Answer

您还需要设置JAVA_HOME和SPARK_DIST_CLASSPATH。您可以从主网站https://hadoop.apache.org/releases.html下载Hadoop。

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/*"

编辑 #1：您可能还想降级Java版本或安装其他版本。这是安装/设置Spark的官方文档：https://spark.apache.org/docs/latest/index.html#downloading

用户也可以下载“无Hadoop”二进制文件，并通过增加Spark的类路径运行任何Hadoop版本。

Spark支持Java 8/11、Scala 2.12、Python 3.6+和R 3.5+。

还有更多关于pip install pyspark的文档。