spark 修改默认log4j.properties 配置

 spark-submit \
--files ${CONF_DIR}/log4j-driver.properties,${CONF_DIR}/log4j-executor.properties \
--driver-java-options "-Dlog4j.configuration=log4j-driver.properties" \
--conf spark.executor.extraJavaOptions="-Dlog4j.configuration=log4j-executor.properties" \

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# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
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# Set everything to be logged to the console
log4j.rootLogger=INFO, file
log4j.appender.file=org.apache.log4j.RollingFileAppender
log4j.appender.file.append=true
log4j.appender.file.file=${spark.yarn.app.container.log.dir}/spark.log
log4j.appender.file.MaxFileSize=50MB
log4j.appender.file.MaxBackupIndex=5
log4j.logger.org.apache.spark=INFO
log4j.appender.file.layout=org.apache.log4j.PatternLayout
log4j.appender.file.layout.ConversionPattern=%d{yyyy-MM-dd HH:mm:ss,SSS} %p [%t] %c{1}:%L - %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=INFO

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

# 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

说明:用户 xxx.jar 中的resources/log4j.properties 会覆盖集群配置，如果用户无resources/log4j.properties 那么加载 --files 中的classpath的 log4j.properties.