[Python] error while defining SparkContext in jupyter notebooke(Python 3 (ipykernel))

sc = SparkContext(conf=conf) error

using anaconda`s Jupyter notebook, this is my first time using pyspark. what I am trying to do is defining the spark environment to read a csv file on the local disk.

Edit: added the text as user2314737 asked for text instead of an image and now StackOverflow wants me to add more details as my text body Is mostly code XD so i have to chat with you all in this part you can ignore this text body, but i do have to write until i can press save edits.

Input:


from pyspark import SparkContext, SparkConf
conf = SparkConf().setAppName("PrdectiveModel")
sc = SparkContext(conf=conf) ----> the error is in this line


Output:

Py4JJavaError Traceback (most recent call last)
Input In [13], in <cell line: 3>()
1 from pyspark import SparkContext, SparkConf
2 conf = SparkConf().setAppName("PrdectiveModel")
----> 3 sc = SparkContext(conf=conf)

File E:\anaconda3\lib\site-packages\pyspark\context.py:146, in SparkContext.__init__(self, master, appName, sparkHome, pyFiles, environment, batchSize, serializer, conf, gateway, jsc, profiler_cls)
144 SparkContext._ensure_initialized(self, gateway=gateway, conf=conf)
145 try:
--> 146 self._do_init(master, appName, sparkHome, pyFiles, environment, batchSize, serializer,
147 conf, jsc, profiler_cls)
148 except:
149 # If an error occurs, clean up in order to allow future SparkContext creation:
150 self.stop()

File E:\anaconda3\lib\site-packages\pyspark\context.py:209, in SparkContext._do_init(self, master, appName, sparkHome, pyFiles, environment, batchSize, serializer, conf, jsc, profiler_cls)
206 self.environment["PYTHONHASHSEED"] = os.environ.get("PYTHONHASHSEED", "0")
208 # Create the Java SparkContext through Py4J
--> 209 self._jsc = jsc or self._initialize_context(self._conf._jconf)
210 # Reset the SparkConf to the one actually used by the SparkContext in JVM.
211 self._conf = SparkConf(_jconf=self._jsc.sc().conf())

File E:\anaconda3\lib\site-packages\pyspark\context.py:329, in SparkContext._initialize_context(self, jconf)
325 def _initialize_context(self, jconf):
326 """
327 Initialize SparkContext in function to allow subclass specific initialization
328 """
--> 329 return self._jvm.JavaSparkContext(jconf)

File E:\anaconda3\lib\site-packages\py4j\java_gateway.py:1585, in JavaClass.__call__(self, *args)
1579 command = proto.CONSTRUCTOR_COMMAND_NAME +\
1580 self._command_header +\
1581 args_command +\
1582 proto.END_COMMAND_PART
1584 answer = self._gateway_client.send_command(command)
-> 1585 return_value = get_return_value(
1586 answer, self._gateway_client, None, self._fqn)
1588 for temp_arg in temp_args:
1589 temp_arg._detach()

File E:\anaconda3\lib\site-packages\py4j\protocol.py:326, in get_return_value(answer, gateway_client, target_id, name)
324 value = OUTPUT_CONVERTER[type](answer[2:], gateway_client)
325 if answer[1] == REFERENCE_TYPE:
--> 326 raise Py4JJavaError(
327 "An error occurred while calling {0}{1}{2}.\n".
328 format(target_id, ".", name), value)
329 else:
330 raise Py4JError(
331 "An error occurred while calling {0}{1}{2}. Trace:\n{3}\n".
332 format(target_id, ".", name, value))

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)


so I did as you have said checked the environment and such. even used findsprak

input

import findspark

findspark.init()
findspark.find()


output

'C:\\spark-3.2.1-bin-hadoop3.2'


so it is correctly installed and can be imported without any problems.

YET!!!!!!!!!!!!! my error still remains

sc = SparkContext(conf=conf)


why does this single line cause the error

..............

So I tried a different code

import pyspark

from pyspark.sql import SparkSession

spark = SparkSession.builder.getOrCreate()

df = spark.sql("select 'spark' as hello ")

df.show()


and now a different error appears

iRuntimeError Traceback (most recent call last)
Input In [6], in <cell line: 5>()
1 import pyspark
3 from pyspark.sql import SparkSession
----> 5 spark = SparkSession.builder.getOrCreate()
7 df = spark.sql("select 'spark' as hello ")
9 df.show()

File C:\spark-3.2.1-bin-hadoop3.2\python\pyspark\sql\session.py:228, in SparkSession.Builder.getOrCreate(self)
226 sparkConf.set(key, value)
227 # This SparkContext may be an existing one.
--> 228 sc = SparkContext.getOrCreate(sparkConf)
229 # Do not update `SparkConf` for existing `SparkContext`, as it's shared
230 # by all sessions.
231 session = SparkSession(sc)

File C:\spark-3.2.1-bin-hadoop3.2\python\pyspark\context.py:392, in SparkContext.getOrCreate(cls, conf)
390 with SparkContext._lock:
391 if SparkContext._active_spark_context is None:
--> 392 SparkContext(conf=conf or SparkConf())
393 return SparkContext._active_spark_context

File C:\spark-3.2.1-bin-hadoop3.2\python\pyspark\context.py:144, in SparkContext.__init__(self, master, appName, sparkHome, pyFiles, environment, batchSize, serializer, conf, gateway, jsc, profiler_cls)
139 if gateway is not None and gateway.gateway_parameters.auth_token is None:
140 raise ValueError(
141 "You are trying to pass an insecure Py4j gateway to Spark. This"
142 " is not allowed as it is a security risk.")
--> 144 SparkContext._ensure_initialized(self, gateway=gateway, conf=conf)
145 try:
146 self._do_init(master, appName, sparkHome, pyFiles, environment, batchSize, serializer,
147 conf, jsc, profiler_cls)

File C:\spark-3.2.1-bin-hadoop3.2\python\pyspark\context.py:339, in SparkContext._ensure_initialized(cls, instance, gateway, conf)
337 with SparkContext._lock:
338 if not SparkContext._gateway:
--> 339 SparkContext._gateway = gateway or launch_gateway(conf)
340 SparkContext._jvm = SparkContext._gateway.jvm
342 if instance:

File C:\spark-3.2.1-bin-hadoop3.2\python\pyspark\java_gateway.py:108, in launch_gateway(conf, popen_kwargs)
105 time.sleep(0.1)
107 if not os.path.isfile(conn_info_file):
--> 108 raise RuntimeError("Java gateway process exited before sending its port number")
110 with open(conn_info_file, "rb") as info:
111 gateway_port = read_int(info)

RuntimeError: Java gateway process exited before sending its port number


hope there is a relation to the two errors

Thanks for taking your time reading this, hope it gets solved

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