我一直在尝试配置jupyter笔记本和pyspark内核。我实际上是这个和ubuntu操作系统的新手。当我尝试使用pyspark内核在jupyter笔记本中运行一些代码时，收到以下错误日志。
请注意，它以前曾经可以运行，但是没有SQL魔术。在我安装了sparkmagic以使用SQL magic之后，这发生了。
感谢您的帮助，谢谢。
ID YARN Application ID Kind State Spark UI Driver log Current session?
1 None pyspark idle ✔
The code failed because of a fatal error:
Session 1 unexpectedly reached final status 'error'. See logs:
stdout:
stderr:
19/10/12 16:47:57 WARN Utils: Your hostname, majd-desktop resolves to a loopback address: 127.0.1.1; using 192.168.1.6 instead (on interface enp1s0)
19/10/12 16:47:57 WARN Utils: Set SPARK_LOCAL_IP if you need to bind to another address
19/10/12 16:47:58 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
log4j:WARN No appenders could be found for logger (io.netty.util.internal.logging.InternalLoggerFactory).
log4j:WARN Please initialize the log4j system properly.
log4j:WARN See http://logging.apache.org/log4j/1.2/faq.html#noconfig for more info.
Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
19/10/12 16:48:00 INFO SparkContext: Running Spark version 2.4.4
19/10/12 16:48:00 INFO SparkContext: Submitted application: livy-session-1
19/10/12 16:48:00 INFO SecurityManager: Changing view acls to: majd
19/10/12 16:48:00 INFO SecurityManager: Changing modify acls to: majd
19/10/12 16:48:00 INFO SecurityManager: Changing view acls groups to:
19/10/12 16:48:00 INFO SecurityManager: Changing modify acls groups to:
19/10/12 16:48:00 INFO SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users with view permissions: Set(majd); groups with view permissions: Set(); users with modify permissions: Set(majd); groups with modify permissions: Set()
19/10/12 16:48:00 INFO Utils: Successfully started service 'sparkDriver' on port 33779.
19/10/12 16:48:00 INFO SparkEnv: Registering MapOutputTracker
19/10/12 16:48:00 INFO SparkEnv: Registering BlockManagerMaster
19/10/12 16:48:00 INFO BlockManagerMasterEndpoint: Using org.apache.spark.storage.DefaultTopologyMapper for getting topology information
19/10/12 16:48:00 INFO BlockManagerMasterEndpoint: BlockManagerMasterEndpoint up
19/10/12 16:48:00 INFO DiskBlockManager: Created local directory at /tmp/blockmgr-d9d22c37-be4c-4498-b115-2011ee176dbf
19/10/12 16:48:00 INFO MemoryStore: MemoryStore started with capacity 366.3 MB
19/10/12 16:48:00 INFO SparkEnv: Registering OutputCommitCoordinator
19/10/12 16:48:00 WARN Utils: Service 'SparkUI' could not bind on port 4040. Attempting port 4041.
19/10/12 16:48:00 INFO Utils: Successfully started service 'SparkUI' on port 4041.
19/10/12 16:48:00 INFO SparkUI: Bound SparkUI to 0.0.0.0, and started at http://192.168.1.6:4041
19/10/12 16:48:00 INFO SparkContext: Added JAR file:///home/majd/anaconda3/share/apache-livy-0.4.0.60ee047/rsc/target/jars/livy-api-0.4.0-incubating-SNAPSHOT.jar at spark://192.168.1.6:33779/jars/livy-api-0.4.0-incubating-SNAPSHOT.jar with timestamp 1570888080918
19/10/12 16:48:00 INFO SparkContext: Added JAR file:///home/majd/anaconda3/share/apache-livy-0.4.0.60ee047/rsc/target/jars/livy-rsc-0.4.0-incubating-SNAPSHOT.jar at spark://192.168.1.6:33779/jars/livy-rsc-0.4.0-incubating-SNAPSHOT.jar with timestamp 1570888080919
19/10/12 16:48:00 INFO SparkContext: Added JAR file:///home/majd/anaconda3/share/apache-livy-0.4.0.60ee047/rsc/target/jars/netty-all-4.0.29.Final.jar at spark://192.168.1.6:33779/jars/netty-all-4.0.29.Final.jar with timestamp 1570888080919
19/10/12 16:48:00 INFO SparkContext: Added JAR file:///home/majd/anaconda3/share/apache-livy-0.4.0.60ee047/repl/scala-2.11/target/jars/commons-codec-1.9.jar at spark://192.168.1.6:33779/jars/commons-codec-1.9.jar with timestamp 1570888080919
19/10/12 16:48:00 INFO SparkContext: Added JAR file:///home/majd/anaconda3/share/apache-livy-0.4.0.60ee047/repl/scala-2.11/target/jars/livy-core_2.11-0.4.0-incubating-SNAPSHOT.jar at spark://192.168.1.6:33779/jars/livy-core_2.11-0.4.0-incubating-SNAPSHOT.jar with timestamp 1570888080920
19/10/12 16:48:00 INFO SparkContext: Added JAR file:///home/majd/anaconda3/share/apache-livy-0.4.0.60ee047/repl/scala-2.11/target/jars/livy-repl_2.11-0.4.0-incubating-SNAPSHOT.jar at spark://192.168.1.6:33779/jars/livy-repl_2.11-0.4.0-incubating-SNAPSHOT.jar with timestamp 1570888080920
19/10/12 16:48:00 INFO Executor: Starting executor ID driver on host localhost
19/10/12 16:48:01 INFO Utils: Successfully started service 'org.apache.spark.network.netty.NettyBlockTransferService' on port 38259.
19/10/12 16:48:01 INFO NettyBlockTransferService: Server created on 192.168.1.6:38259
19/10/12 16:48:01 INFO BlockManager: Using org.apache.spark.storage.RandomBlockReplicationPolicy for block replication policy
19/10/12 16:48:01 INFO BlockManagerMaster: Registering BlockManager BlockManagerId(driver, 192.168.1.6, 38259, None)
19/10/12 16:48:01 INFO BlockManagerMasterEndpoint: Registering block manager 192.168.1.6:38259 with 366.3 MB RAM, BlockManagerId(driver, 192.168.1.6, 38259, None)
19/10/12 16:48:01 INFO BlockManagerMaster: Registered BlockManager BlockManagerId(driver, 192.168.1.6, 38259, None)
19/10/12 16:48:01 INFO BlockManager: Initialized BlockManager: BlockManagerId(driver, 192.168.1.6, 38259, None).
Some things to try:
a) Make sure Spark has enough available resources for Jupyter to create a Spark context.
b) Contact your Jupyter administrator to make sure the Spark magics library is configured correctly.
c) Restart the kernel.