我正在嘗試開始使用 pyspark，但遇到了一些麻煩。我安裝了 python 3.10 和 M1 MacBook Pro。我使用以下命令安裝了 pyspark：
python3 -m pip install pyspark
這似乎作業正常。
aaronwright ~ % pyspark --version
Welcome to
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/ __/__ ___ _____/ /__
_\ \/ _ \/ _ `/ __/ '_/
/___/ .__/\_,_/_/ /_/\_\ 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.
我還從這里安裝了 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)
然后嘗試使用以下命令運行 pyspark：
pyspark
但是我在這里收到了一些錯誤。
下面是輸出。有沒有人有任何想法？可能遺漏了一個配置步驟，因為這是我第一次使用 spark。當我使用新的 Mac 和新版本的 Python 時，它也可能在某處不兼容。
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)
編輯：為了讓它作業，我需要使用 Java 8：
brew install --cask homebrew/cask-versions/adoptopenjdk8
然后在我的~/.zshrc檔案中添加了以下行：
export JAVA_HOME='/Library/Java/JavaVirtualMachines/adoptopenjdk-8.jdk/Contents/Home/'
uj5u.com熱心網友回復：
您需要設定JAVA_HOME，SPARK_DIST_CLASSPATH以及。您可以從主網站https://hadoop.apache.org/releases.html下載 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/*"
編輯 #1：您可能還想降級 Java 或安裝另一個版本。這是安裝/設定 Spark 的官方檔案https://spark.apache.org/docs/latest/index.html#downloading
用戶還可以下載“Hadoop free”二進制檔案，并通過增加 Spark 的類路徑來使用任何 Hadoop 版本運行 Spark 。
Spark 在 Java 8/11、Scala 2.12、Python 3.6 和 R 3.5 上運行。
還有一個關于 pip install pyspark
轉載請註明出處，本文鏈接：https://www.uj5u.com/shujuku/372255.html
標籤：Python 蟒蛇-3.x 阿帕奇火花 火花 苹果-m1