log4j.properties

# Set everything to be logged to the console

log4j.appender.stdout=org.apache.log4j.ConsoleAppender
log4j.appender.stdout.Target=System.out
log4j.appender.stdout.layout=org.apache.log4j.PatternLayout
log4j.appender.stdout.layout.ConversionPattern=%d{HH:mm:ss} %-5p %c{1}:%L - %m%n

log4j.rootLogger=WARN, stdout
log4j.logger.org.apache.spark=WARN, stdout
log4j.logger.com.yourcompany=INFO, stdout

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



# Set the default spark-shell log level to WARN. When running the spark-shell, the

# log level for this class is used to overwrite the root logger's log level, so that

# the user can have different defaults for the shell and regular Spark apps.

log4j.logger.org.apache.spark.repl.Main=WARN



# Settings to quiet third party logs that are too verbose

log4j.logger.org.sparkproject.jetty=WARN

log4j.logger.org.sparkproject.jetty.util.component.AbstractLifeCycle=ERROR

log4j.logger.org.apache.spark.repl.SparkIMain$exprTyper=INFO

log4j.logger.org.apache.spark.repl.SparkILoop$SparkILoopInterpreter=INFO



# SPARK-9183: Settings to avoid annoying messages when looking up nonexistent UDFs

# in SparkSQL with Hive support

log4j.logger.org.apache.hadoop.hive.metastore.RetryingHMSHandler=FATAL

log4j.logger.org.apache.hadoop.hive.ql.exec.FunctionRegistry=ERROR



# Parquet related logging

log4j.logger.org.apache.parquet.CorruptStatistics=ERROR

log4j.logger.parquet.CorruptStatistics=ERROR