I\'d like to stop various messages that are coming on spark shell.
I tried to edit the log4j.properties file in order to stop these message.
Her
An interesting idea is to use the RollingAppender as suggested here: http://shzhangji.com/blog/2015/05/31/spark-streaming-logging-configuration/ so that you don't "polute" the console space, but still be able to see the results under $YOUR_LOG_PATH_HERE/${dm.logging.name}.log.
log4j.rootLogger=INFO, rolling
log4j.appender.rolling=org.apache.log4j.RollingFileAppender
log4j.appender.rolling.layout=org.apache.log4j.PatternLayout
log4j.appender.rolling.layout.conversionPattern=[%d] %p %m (%c)%n
log4j.appender.rolling.maxFileSize=50MB
log4j.appender.rolling.maxBackupIndex=5
log4j.appender.rolling.file=$YOUR_LOG_PATH_HERE/${dm.logging.name}.log
log4j.appender.rolling.encoding=UTF-8
Another method that solves the cause is to observe what kind of loggings do you usually have (coming from different modules and dependencies), and set for each the granularity for the logging, while turning "quiet" third party logs that are too verbose:
For instance,
# Silence akka remoting
log4j.logger.Remoting=ERROR
log4j.logger.akka.event.slf4j=ERROR
log4j.logger.org.spark-project.jetty.server=ERROR
log4j.logger.org.apache.spark=ERROR
log4j.logger.com.anjuke.dm=${dm.logging.level}
log4j.logger.org.eclipse.jetty=WARN
log4j.logger.org.eclipse.jetty.util.component.AbstractLifeCycle=ERROR
log4j.logger.org.apache.spark.repl.SparkIMain$exprTyper=INFO
log4j.logger.org.apache.spark.repl.SparkILoop$SparkILoopInterpreter=INFO