How to turn off INFO logging in Spark?

I installed Spark using the AWS EC2 guide and I can launch the program fine using the bin/pyspark script to get to the spark prompt and can also do the Quick Start quide successfully.

However, I cannot for the life of me figure out how to stop all of the verbose INFO logging after each command.

I have tried nearly every possible scenario in the below code (commenting out, setting to OFF) within my log4j.properties file in the conf folder in where I launch the application from as well as on each node and nothing is doing anything. I still get the logging INFO statements printing after executing each statement.

I am very confused with how this is supposed to work.

    #Set everything to be logged to the console log4j.rootCategory=INFO, console                                                                        
    log4j.appender.console=org.apache.log4j.ConsoleAppender 
    log4j.appender.console.target=System.err     
    log4j.appender.console.layout=org.apache.log4j.PatternLayout 
    log4j.appender.console.layout.ConversionPattern=%d{yy/MM/dd HH:mm:ss} %p %c{1}: %m%n

    # Settings to quiet third party logs that are too verbose
    log4j.logger.org.eclipse.jetty=WARN
    log4j.logger.org.apache.spark.repl.SparkIMain$exprTyper=INFO
    log4j.logger.org.apache.spark.repl.SparkILoop$SparkILoopInterpreter=INFO

Here is my full classpath when I use SPARK_PRINT_LAUNCH_COMMAND:

Spark Command: /Library/Java/JavaVirtualMachines/jdk1.8.0_05.jdk/Contents/Home/bin/java -cp :/root/spark-1.0.1-bin-hadoop2/conf:/root/spark-1.0.1-bin-hadoop2/conf:/root/spark-1.0.1-bin-hadoop2/lib/spark-assembly-1.0.1-hadoop2.2.0.jar:/root/spark-1.0.1-bin-hadoop2/lib/datanucleus-api-jdo-3.2.1.jar:/root/spark-1.0.1-bin-hadoop2/lib/datanucleus-core-3.2.2.jar:/root/spark-1.0.1-bin-hadoop2/lib/datanucleus-rdbms-3.2.1.jar -XX:MaxPermSize=128m -Djava.library.path= -Xms512m -Xmx512m org.apache.spark.deploy.SparkSubmit spark-shell --class org.apache.spark.repl.Main

contents of spark-env.sh:

    #!/usr/bin/env bash

    # This file is sourced when running various Spark programs.
    # Copy it as spark-env.sh and edit that to configure Spark for your site.

    # Options read when launching programs locally with 
    # ./bin/run-example or ./bin/spark-submit
    # - HADOOP_CONF_DIR, to point Spark towards Hadoop configuration files
    # - SPARK_LOCAL_IP, to set the IP address Spark binds to on this node
    # - SPARK_PUBLIC_DNS, to set the public dns name of the driver program
    # - SPARK_CLASSPATH=/root/spark-1.0.1-bin-hadoop2/conf/

    # Options read by executors and drivers running inside the cluster
    # - SPARK_LOCAL_IP, to set the IP address Spark binds to on this node
    # - SPARK_PUBLIC_DNS, to set the public DNS name of the driver program
    # - SPARK_CLASSPATH, default classpath entries to append
    # - SPARK_LOCAL_DIRS, storage directories to use on this node for shuffle and RDD data
    # - MESOS_NATIVE_LIBRARY, to point to your libmesos.so if you use Mesos

    # Options read in YARN client mode
    # - HADOOP_CONF_DIR, to point Spark towards Hadoop configuration files
    # - SPARK_EXECUTOR_INSTANCES, Number of workers to start (Default: 2)
    # - SPARK_EXECUTOR_CORES, Number of cores for the workers (Default: 1).
    # - SPARK_EXECUTOR_MEMORY, Memory per Worker (e.g. 1000M, 2G) (Default: 1G)
    # - SPARK_DRIVER_MEMORY, Memory for Master (e.g. 1000M, 2G) (Default: 512 Mb)
    # - SPARK_YARN_APP_NAME, The name of your application (Default: Spark)
    # - SPARK_YARN_QUEUE, The hadoop queue to use for allocation requests (Default: ‘default’)
    # - SPARK_YARN_DIST_FILES, Comma separated list of files to be distributed with the job.
    # - SPARK_YARN_DIST_ARCHIVES, Comma separated list of archives to be distributed with the job.

    # Options for the daemons used in the standalone deploy mode:
    # - SPARK_MASTER_IP, to bind the master to a different IP address or hostname
    # - SPARK_MASTER_PORT / SPARK_MASTER_WEBUI_PORT, to use non-default ports for the master
    # - SPARK_MASTER_OPTS, to set config properties only for the master (e.g. "-Dx=y")
    # - SPARK_WORKER_CORES, to set the number of cores to use on this machine
    # - SPARK_WORKER_MEMORY, to set how much total memory workers have to give executors (e.g. 1000m, 2g)
    # - SPARK_WORKER_PORT / SPARK_WORKER_WEBUI_PORT, to use non-default ports for the worker
    # - SPARK_WORKER_INSTANCES, to set the number of worker processes per node
    # - SPARK_WORKER_DIR, to set the working directory of worker processes
    # - SPARK_WORKER_OPTS, to set config properties only for the worker (e.g. "-Dx=y")
    # - SPARK_HISTORY_OPTS, to set config properties only for the history server (e.g. "-Dx=y")
    # - SPARK_DAEMON_JAVA_OPTS, to set config properties for all daemons (e.g. "-Dx=y")
    # - SPARK_PUBLIC_DNS, to set the public dns name of the master or workers

    export SPARK_SUBMIT_CLASSPATH="$FWDIR/conf"

Just execute this command in the spark directory:

    cp conf/log4j.properties.template conf/log4j.properties

Edit log4j.properties:

    # Set everything to be logged to the console
    log4j.rootCategory=INFO, console
    log4j.appender.console=org.apache.log4j.ConsoleAppender
    log4j.appender.console.target=System.err
    log4j.appender.console.layout=org.apache.log4j.PatternLayout
    log4j.appender.console.layout.ConversionPattern=%d{yy/MM/dd HH:mm:ss} %p %c{1}: %m%n

    # Settings to quiet third party logs that are too verbose
    log4j.logger.org.eclipse.jetty=WARN
    log4j.logger.org.eclipse.jetty.util.component.AbstractLifeCycle=ERROR
    log4j.logger.org.apache.spark.repl.SparkIMain$exprTyper=INFO
    log4j.logger.org.apache.spark.repl.SparkILoop$SparkILoopInterpreter=INFO

Replace at the first line:

    log4j.rootCategory=INFO, console

by:

    log4j.rootCategory=WARN, console

Save and restart your shell. It works for me for Spark 1.1.0 and Spark 1.5.1 on OS X.

From: stackoverflow.com/q/25193488

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