Mixing
Pspark & Jupyter: Unsupported major.minor version 52.0
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?
pyspark
asked Jan 2 at 16:16
user1761806user1761806
2,27711633
add a comment |
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?
pyspark
asked Jan 2 at 16:16
user1761806user1761806
2,27711633
It appears that you are using Spark 2. As per my understanding, Spark 2 works with JDK 1.8 whereas in your system, you configured to use JDK 1.7 which is causing the issue. If possible, try using Spark 1.6 if you want to stick to JDK 1.7.
– Irfan Elahi
Jan 7 at 3:49
add a comment |
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?
pyspark
asked Jan 2 at 16:16
user1761806user1761806
2,27711633
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?
pyspark
pyspark
asked Jan 2 at 16:16
user1761806user1761806
2,27711633
asked Jan 2 at 16:16
user1761806user1761806
2,27711633
edited Jan 2 at 16:23
user1761806
asked Jan 2 at 16:16
user1761806user1761806
2,27711633
asked Jan 2 at 16:16
user1761806user1761806
2,27711633
asked Jan 2 at 16:16
user1761806user1761806
2,27711633
2,27711633
It appears that you are using Spark 2. As per my understanding, Spark 2 works with JDK 1.8 whereas in your system, you configured to use JDK 1.7 which is causing the issue. If possible, try using Spark 1.6 if you want to stick to JDK 1.7.
– Irfan Elahi
Jan 7 at 3:49
add a comment |
It appears that you are using Spark 2. As per my understanding, Spark 2 works with JDK 1.8 whereas in your system, you configured to use JDK 1.7 which is causing the issue. If possible, try using Spark 1.6 if you want to stick to JDK 1.7.
– Irfan Elahi
Jan 7 at 3:49
It appears that you are using Spark 2. As per my understanding, Spark 2 works with JDK 1.8 whereas in your system, you configured to use JDK 1.7 which is causing the issue. If possible, try using Spark 1.6 if you want to stick to JDK 1.7.
– Irfan Elahi
Jan 7 at 3:49
It appears that you are using Spark 2. As per my understanding, Spark 2 works with JDK 1.8 whereas in your system, you configured to use JDK 1.7 which is causing the issue. If possible, try using Spark 1.6 if you want to stick to JDK 1.7.
– Irfan Elahi
Jan 7 at 3:49
add a comment |
1 Answer
1
active
oldest
votes
Just use a Docker container from: https://github.com/jupyter/docker-stacks
Why make it difficult for yourself?
answered Jan 7 at 2:04
user9382513user9382513
211
add a comment |
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
Just use a Docker container from: https://github.com/jupyter/docker-stacks
Why make it difficult for yourself?
answered Jan 7 at 2:04
user9382513user9382513
211
add a comment |
Just use a Docker container from: https://github.com/jupyter/docker-stacks
Why make it difficult for yourself?
answered Jan 7 at 2:04
user9382513user9382513
211
add a comment |
Just use a Docker container from: https://github.com/jupyter/docker-stacks
Why make it difficult for yourself?
answered Jan 7 at 2:04
user9382513user9382513
211
Just use a Docker container from: https://github.com/jupyter/docker-stacks
Why make it difficult for yourself?
answered Jan 7 at 2:04
user9382513user9382513
211
answered Jan 7 at 2:04
user9382513user9382513
211
answered Jan 7 at 2:04
user9382513user9382513
211
answered Jan 7 at 2:04
user9382513user9382513
211
211
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It appears that you are using Spark 2. As per my understanding, Spark 2 works with JDK 1.8 whereas in your system, you configured to use JDK 1.7 which is causing the issue. If possible, try using Spark 1.6 if you want to stick to JDK 1.7.
– Irfan Elahi
Jan 7 at 3:49