我正在尝试通过Visual Studio代码在EC2 Linux机器上的Jupyter Notebook中运行一个spark会话。我的代码如下所示:
from pyspark.sql import SparkSession
spark = SparkSession.builder.appName("spark_app").getOrCreate()
错误为:
{
"name": "Py4JError",
"message": "An error occurred while calling None.org.apache.spark.sql.SparkSession. Trace:\npy4j.Py4JException: Constructor org.apache.spark.sql.SparkSession([class org.apache.spark.SparkContext, class java.util.HashMap]) does not exist\n\tat py4j.reflection.ReflectionEngine.getConstructor(ReflectionEngine.java:179)\n\tat py4j.reflection.ReflectionEngine.getConstructor(ReflectionEngine.java:196)\n\tat py4j.Gateway.invoke(Gateway.java:237)\n\tat py4j.commands.ConstructorCommand.invokeConstructor(ConstructorCommand.java:80)\n\tat py4j.commands.ConstructorCommand.execute(ConstructorCommand.java:69)\n\tat py4j.GatewayConnection.run(GatewayConnection.java:238)\n\tat java.base/java.lang.Thread.run(Thread.java:829)\n\n",
"stack": "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[0;31mPy4JError\u001b[0m Traceback (most recent call last)\n\u001b[1;32mc:\\Users\\IrinaKaerkkaenen\\Projekte\\ZugPortal\\test.ipynb Cell 3'\u001b[0m in \u001b[0;36m<cell line: 2>\u001b[0;34m()\u001b[0m\n\u001b[1;32m <a href='vscode-notebook-cell:/c%3A/Users/IrinaKaerkkaenen/Projekte/ZugPortal/test.ipynb#ch0000002?line=0'>1</a>\u001b[0m \u001b[39mfrom\u001b[39;00m \u001b[39mpyspark\u001b[39;00m\u001b[39m.\u001b[39;00m\u001b[39msql\u001b[39;00m \u001b[39mimport\u001b[39;00m SparkSession\n\u001b[0;32m----> <a href='vscode-notebook-cell:/c%3A/Users/IrinaKaerkkaenen/Projekte/ZugPortal/test.ipynb#ch0000002?line=1'>2</a>\u001b[0m spark \u001b[39m=\u001b[39m SparkSession\u001b[39m.\u001b[39;49mbuilder\u001b[39m.\u001b[39;49mappName(\u001b[39m\"\u001b[39;49m\u001b[39mspark_app\u001b[39;49m\u001b[39m\"\u001b[39;49m)\u001b[39m.\u001b[39;49mgetOrCreate()\n\nFile \u001b[0;32m~/anaconda3/lib/python3.9/site-packages/pyspark/sql/session.py:272\u001b[0m, in \u001b[0;36mSparkSession.Builder.getOrCreate\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 269\u001b[0m sc \u001b[39m=\u001b[39m SparkContext\u001b[39m.\u001b[39mgetOrCreate(sparkConf)\n\u001b[1;32m 270\u001b[0m \u001b[39m# Do not update `SparkConf` for existing `SparkContext`, as it's shared\u001b[39;00m\n\u001b[1;32m 271\u001b[0m \u001b[39m# by all sessions.\u001b[39;00m\n\u001b[0;32m--> 272\u001b[0m session \u001b[39m=\u001b[39m SparkSession(sc, options\u001b[39m=\u001b[39;49m\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_options)\n\u001b[1;32m 273\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[1;32m 274\u001b[0m \u001b[39mgetattr\u001b[39m(\n\u001b[1;32m 275\u001b[0m \u001b[39mgetattr\u001b[39m(session\u001b[39m.\u001b[39m_jvm, \u001b[39m\"\u001b[39m\u001b[39mSparkSession$\u001b[39m\u001b[39m\"\u001b[39m), \u001b[39m\"\u001b[39m\u001b[39mMODULE$\u001b[39m\u001b[39m\"\u001b[39m\n\u001b[1;32m 276\u001b[0m )\u001b[39m.\u001b[39mapplyModifiableSettings(session\u001b[39m.\u001b[39m_jsparkSession, \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_options)\n\nFile \u001b[0;32m~/anaconda3/lib/python3.9/site-packages/pyspark/sql/session.py:307\u001b[0m, in \u001b[0;36mSparkSession.__init__\u001b[0;34m(self, sparkContext, jsparkSession, options)\u001b[0m\n\u001b[1;32m 303\u001b[0m \u001b[39mgetattr\u001b[39m(\u001b[39mgetattr\u001b[39m(\u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_jvm, \u001b[39m\"\u001b[39m\u001b[39mSparkSession$\u001b[39m\u001b[39m\"\u001b[39m), \u001b[39m\"\u001b[39m\u001b[39mMODULE$\u001b[39m\u001b[39m\"\u001b[39m)\u001b[39m.\u001b[39mapplyModifiableSettings(\n\u001b[1;32m 304\u001b[0m jsparkSession, options\n\u001b[1;32m 305\u001b[0m )\n\u001b[1;32m 306\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[0;32m--> 307\u001b[0m jsparkSession \u001b[39m=\u001b[39m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_jvm\u001b[39m.\u001b[39;49mSparkSession(\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_jsc\u001b[39m.\u001b[39;49msc(), options)\n\u001b[1;32m 308\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[1;32m 309\u001b[0m \u001b[39mgetattr\u001b[39m(\u001b[39mgetattr\u001b[39m(\u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_jvm, \u001b[39m\"\u001b[39m\u001b[39mSparkSession$\u001b[39m\u001b[39m\"\u001b[39m), \u001b[39m\"\u001b[39m\u001b[39mMODULE$\u001b[39m\u001b[39m\"\u001b[39m)\u001b[39m.\u001b[39mapplyModifiableSettings(\n\u001b[1;32m 310\u001b[0m jsparkSession, options\n\u001b[1;32m 311\u001b[0m )\n\nFile \u001b[0;32m~/anaconda3/lib/python3.9/site-packages/py4j/java_gateway.py:1585\u001b[0m, in \u001b[0;36mJavaClass.__call__\u001b[0;34m(self, *args)\u001b[0m\n\u001b[1;32m 1579\u001b[0m command \u001b[39m=\u001b[39m proto\u001b[39m.\u001b[39mCONSTRUCTOR_COMMAND_NAME \u001b[39m+\u001b[39m\\\n\u001b[1;32m 1580\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_command_header \u001b[39m+\u001b[39m\\\n\u001b[1;32m 1581\u001b[0m args_command \u001b[39m+\u001b[39m\\\n\u001b[1;32m 1582\u001b[0m proto\u001b[39m.\u001b[39mEND_COMMAND_PART\n\u001b[1;32m 1584\u001b[0m answer \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_gateway_client\u001b[39m.\u001b[39msend_command(command)\n\u001b[0;32m-> 1585\u001b[0m return_value \u001b[39m=\u001b[39m get_return_value(\n\u001b[1;32m 1586\u001b[0m answer, \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_gateway_client, \u001b[39mNone\u001b[39;49;00m, \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_fqn)\n\u001b[1;32m 1588\u001b[0m \u001b[39mfor\u001b[39;00m temp_arg \u001b[39min\u001b[39;00m temp_args:\n\u001b[1;32m 1589\u001b[0m temp_arg\u001b[39m.\u001b[39m_detach()\n\nFile \u001b[0;32m~/anaconda3/lib/python3.9/site-packages/py4j/protocol.py:330\u001b[0m, in \u001b[0;36mget_return_value\u001b[0;34m(answer, gateway_client, target_id, name)\u001b[0m\n\u001b[1;32m 326\u001b[0m \u001b[39mraise\u001b[39;00m Py4JJavaError(\n\u001b[1;32m 327\u001b[0m \u001b[39m\"\u001b[39m\u001b[39mAn error occurred while calling \u001b[39m\u001b[39m{0}\u001b[39;00m\u001b[39m{1}\u001b[39;00m\u001b[39m{2}\u001b[39;00m\u001b[39m.\u001b[39m\u001b[39m\\n\u001b[39;00m\u001b[39m\"\u001b[39m\u001b[39m.\u001b[39m\n\u001b[1;32m 328\u001b[0m \u001b[39mformat\u001b[39m(target_id, \u001b[39m\"\u001b[39m\u001b[39m.\u001b[39m\u001b[39m\"\u001b[39m, name), value)\n\u001b[1;32m 329\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[0;32m--> 330\u001b[0m \u001b[39mraise\u001b[39;00m Py4JError(\n\u001b[1;32m 331\u001b[0m \u001b[39m\"\u001b[39m\u001b[39mAn error occurred while calling \u001b[39m\u001b[39m{0}\u001b[39;00m\u001b[39m{1}\u001b[39;00m\u001b[39m{2}\u001b[39;00m\u001b[39m. Trace:\u001b[39m\u001b[39m\\n\u001b[39;00m\u001b[39m{3}\u001b[39;00m\u001b[39m\\n\u001b[39;00m\u001b[39m\"\u001b[39m\u001b[39m.\u001b[39m\n\u001b[1;32m 332\u001b[0m \u001b[39mformat\u001b[39m(target_id, \u001b[39m\"\u001b[39m\u001b[39m.\u001b[39m\u001b[39m\"\u001b[39m, name, value))\n\u001b[1;32m 333\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[1;32m 334\u001b[0m \u001b[39mraise\u001b[39;00m Py4JError(\n\u001b[1;32m 335\u001b[0m \u001b[39m\"\u001b[39m\u001b[39mAn error occurred while calling \u001b[39m\u001b[39m{0}\u001b[39;00m\u001b[39m{1}\u001b[39;00m\u001b[39m{2}\u001b[39;00m\u001b[39m\"\u001b[39m\u001b[39m.\u001b[39m\n\u001b[1;32m 336\u001b[0m \u001b[39mformat\u001b[39m(target_id, \u001b[39m\"\u001b[39m\u001b[39m.\u001b[39m\u001b[39m\"\u001b[39m, name))\n\n\u001b[0;31mPy4JError\u001b[0m: An error occurred while calling None.org.apache.spark.sql.SparkSession. Trace:\npy4j.Py4JException: Constructor org.apache.spark.sql.SparkSession([class org.apache.spark.SparkContext, class java.util.HashMap]) does not exist\n\tat py4j.reflection.ReflectionEngine.getConstructor(ReflectionEngine.java:179)\n\tat py4j.reflection.ReflectionEngine.getConstructor(ReflectionEngine.java:196)\n\tat py4j.Gateway.invoke(Gateway.java:237)\n\tat py4j.commands.ConstructorCommand.invokeConstructor(ConstructorCommand.java:80)\n\tat py4j.commands.ConstructorCommand.execute(ConstructorCommand.java:69)\n\tat py4j.GatewayConnection.run(GatewayConnection.java:238)\n\tat java.base/java.lang.Thread.run(Thread.java:829)\n\n"
}
在文本编辑器中读取完整错误之前运行单元格的输出如下
Output exceeds the size limit. Open the full output data in a text editor
---------------------------------------------------------------------------
Py4JError Traceback (most recent call last)
/tmp/ipykernel_5260/8684085.py in <module>
1 from pyspark.sql import SparkSession
----> 2 spark = SparkSession.builder.appName("spark_app").getOrCreate()
~/anaconda3/envs/zupo_env_test1/lib64/python3.7/site-packages/pyspark/sql/session.py in getOrCreate(self)
270 # Do not update `SparkConf` for existing `SparkContext`, as it's shared
271 # by all sessions.
--> 272 session = SparkSession(sc, options=self._options)
273 else:
274 getattr(
~/anaconda3/envs/zupo_env_test1/lib64/python3.7/site-packages/pyspark/sql/session.py in __init__(self, sparkContext, jsparkSession, options)
305 )
306 else:
--> 307 jsparkSession = self._jvm.SparkSession(self._jsc.sc(), options)
308 else:
309 getattr(getattr(self._jvm, "SparkSession$"), "MODULE$").applyModifiableSettings(
~/anaconda3/envs/zupo_env_test1/lib64/python3.7/site-packages/py4j/java_gateway.py in __call__(self, *args)
1584 answer = self._gateway_client.send_command(command)
1585 return_value = get_return_value(
-> 1586 answer, self._gateway_client, None, self._fqn)
1587
...
at py4j.commands.ConstructorCommand.execute(ConstructorCommand.java:69)
at py4j.GatewayConnection.run(GatewayConnection.java:238)
at java.base/java.lang.Thread.run(Thread.java:829)
我在谷歌上搜索了很多都没有成功。有人知道哪里出了问题吗?
我使用IPython内核,并安装了Python 3.9。
出现错误前的警告:
WARNING: An illegal reflective access operation has occurred
WARNING: Illegal reflective access by org.apache.spark.unsafe.Platform (file:/home/ec2-user/spark/spark-3.1.2-bin-hadoop2.7/jars/spark-unsafe_2.12-3.1.2.jar) to constructor java.nio.DirectByteBuffer(long,int)
WARNING: Please consider reporting this to the maintainers of org.apache.spark.unsafe.Platform
WARNING: Use --illegal-access=warn to enable warnings of further illegal reflective access operations
WARNING: All illegal access operations will be denied in a future release
22/07/05 21:06:22 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
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).
2条答案
按热度按时间vlju58qv1#
我有同样的问题,我已经修复了它安装相同版本的pyspark从pip和Spark。你应该检查如果你安装的版本是相同的。
btqmn9zl2#
您的计算机中安装的
spark
版本似乎与pyspark
版本不匹配。使用以下命令检查spark的版本:
现在,如示例输出所示,安装的Spark版本是3.1.3,因此您需要通过执行以下命令来安装相同版本的spark(pyspark)的python库: