Pyspark & Jupyter: Unsupported major.minor version 52.0 - pyspark

Question

I downgraded from JDK 1.8 to 1.7 as I'm trying to deal with another problem for which one suggestion was to use 1.7.
However I'm now finding that my Juypyter notebook now hangs on this line:
spark = SparkSession.builder.appName("Basic").master("local[*]").config("spark.network.timeout","50s").config("spark.executor.heartbeatInterval", "50s").getOrCreate();
Looking at the console I see:
Exception in thread "main" java.lang.UnsupportedClassVersionError: org/apache/spark/launcher/Main : Unsupported major.minor version 52.0
at java.lang.ClassLoader.defineClass1(Native Method)
at java.lang.ClassLoader.defineClass(Unknown Source)
at java.security.SecureClassLoader.defineClass(Unknown Source)
at java.net.URLClassLoader.defineClass(Unknown Source)
at java.net.URLClassLoader.access$100(Unknown Source)
at java.net.URLClassLoader$1.run(Unknown Source)
at java.net.URLClassLoader$1.run(Unknown Source)
at java.security.AccessController.doPrivileged(Native Method)
at java.net.URLClassLoader.findClass(Unknown Source)
at java.lang.ClassLoader.loadClass(Unknown Source)
at sun.misc.Launcher$AppClassLoader.loadClass(Unknown Source)
at java.lang.ClassLoader.loadClass(Unknown Source)
at sun.launcher.LauncherHelper.checkAndLoadMain(Unknown Source)
Which from searching I understand is due to different versions of Java being used. However both my path and Java_Home are pointing to 1.7 not 1.8 and I rebooted my machine. What else should I do? Should I remove and re-do my pip install of pyspark?

Answer 1

Just use a Docker container from: https://github.com/jupyter/docker-stacks
Why make it difficult for yourself?