Git Zeppelin on Spark 1.5.0

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Git Zeppelin on Spark 1.5.0

ÐΞ€ρ@Ҝ (๏̯͡๏)
I am unable to get zeppelin to run on Spark 1.5.0 
I have the latest code from git for zeppelin..


Error:
Driver failed to launch

SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/hadoop/yarn/local/usercache/zeppelin/filecache/18/spark-assembly-1.5.0-hadoop2.4.0.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/usr/hdp/2.3.1.0-2574/hadoop/lib/slf4j-log4j12-1.7.10.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation.
SLF4J: Actual binding is of type [org.slf4j.impl.Log4jLoggerFactory]
15/09/24 19:18:29 INFO yarn.ApplicationMaster: Registered signal handlers for [TERM, HUP, INT]
Unknown/unsupported param List(--num-executors, 18)

Usage: org.apache.spark.deploy.yarn.ApplicationMaster [options]
Options:
  --jar JAR_PATH       Path to your application's JAR file
  --class CLASS_NAME   Name of your application's main class
  --primary-py-file    A main Python file
  --primary-r-file     A main R file
  --py-files PY_FILES  Comma-separated list of .zip, .egg, or .py files to
                       place on the PYTHONPATH for Python apps.
  --args ARGS          Arguments to be passed to your application's main class.
                       Multiple invocations are possible, each will be passed in order.
  --num-executors NUM    Number of executors to start (Default: 2)
  --executor-cores NUM   Number of cores for the executors (Default: 1)
  --executor-memory MEM  Memory per executor (e.g. 1000M, 2G) (Default: 1G)
      

Log Type: stdout

Log Upload Time: Thu Sep 24 19:18:30 -0700 2015

Log Length: 0


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Deepak

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Re: Git Zeppelin on Spark 1.5.0

Randy Gelhausen-2
Here are the steps I use to build and run on HDP 2.3.0: https://gist.github.com/randerzander/5c6ca7bdd06876c9b247

Specifically, you need to set spark.driver.extraJavaOptions and spark.yarn.am.extraJavaOptions, else YARN will reject your application launch.

On Thu, Sep 24, 2015 at 10:20 PM, ÐΞ€ρ@Ҝ (๏̯͡๏) <[hidden email]> wrote:
I am unable to get zeppelin to run on Spark 1.5.0 
I have the latest code from git for zeppelin..


Error:
Driver failed to launch

SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/hadoop/yarn/local/usercache/zeppelin/filecache/18/spark-assembly-1.5.0-hadoop2.4.0.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/usr/hdp/2.3.1.0-2574/hadoop/lib/slf4j-log4j12-1.7.10.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation.
SLF4J: Actual binding is of type [org.slf4j.impl.Log4jLoggerFactory]
15/09/24 19:18:29 INFO yarn.ApplicationMaster: Registered signal handlers for [TERM, HUP, INT]
Unknown/unsupported param List(--num-executors, 18)

Usage: org.apache.spark.deploy.yarn.ApplicationMaster [options]
Options:
  --jar JAR_PATH       Path to your application's JAR file
  --class CLASS_NAME   Name of your application's main class
  --primary-py-file    A main Python file
  --primary-r-file     A main R file
  --py-files PY_FILES  Comma-separated list of .zip, .egg, or .py files to
                       place on the PYTHONPATH for Python apps.
  --args ARGS          Arguments to be passed to your application's main class.
                       Multiple invocations are possible, each will be passed in order.
  --num-executors NUM    Number of executors to start (Default: 2)
  --executor-cores NUM   Number of cores for the executors (Default: 1)
  --executor-memory MEM  Memory per executor (e.g. 1000M, 2G) (Default: 1G)
      

Log Type: stdout

Log Upload Time: Thu Sep 24 19:18:30 -0700 2015

Log Length: 0


--
Deepak