Pspark & Jupyter: Unsupported major.minor version 52.0

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

share|improve this question

edited Jan 2 at 16:23

user1761806

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 | 

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

share|improve this question

edited Jan 2 at 16:23

user1761806

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 | 

0

0

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

share|improve this question

edited Jan 2 at 16:23

user1761806

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

share|improve this question

edited Jan 2 at 16:23

user1761806

asked Jan 2 at 16:16

user1761806user1761806

2,27711633

share|improve this question

edited Jan 2 at 16:23

user1761806

asked Jan 2 at 16:16

user1761806user1761806

2,27711633

share|improve this question

share|improve this question

edited Jan 2 at 16:23

user1761806

edited Jan 2 at 16:23

user1761806

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

share|improve this answer

answered Jan 7 at 2:04

user9382513user9382513

211

add a comment | 

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1 Answer
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1 Answer
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oldest

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oldest

votes

0

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

share|improve this answer

answered Jan 7 at 2:04

user9382513user9382513

211

add a comment | 

0

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

share|improve this answer

answered Jan 7 at 2:04

user9382513user9382513

211

add a comment | 

0

0

0

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

share|improve this answer

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?

share|improve this answer

answered Jan 7 at 2:04

user9382513user9382513

211

share|improve this answer

share|improve this answer

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

add a comment | 

add a comment | 

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