如何在Spark中关闭INFO日志记录？

Question

我使用AWS
EC2指南安装了Spark，并且可以使用bin/pyspark脚本正常启动该程序以获取Spark提示，并且还可以成功执行快速入门Quide。

但是，我无法终生解决如何INFO在每个命令后停止所有冗长的日志记录。

我在下面的代码（注释掉，设置为OFF）中的几乎所有可能的情况下都尝试了log4j.properties该conf文件夹，该文件夹位于我从中以及在每个节点上启动应用程序的文件夹中，没有任何反应。INFO执行每个语句后，我仍然可以打印日志记录语句。

我对应该如何工作感到非常困惑。

#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

这是我使用时的完整类路径SPARK_PRINT_LAUNCH_COMMAND：

Spark命令：/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.Spark提交spark-shell –class
org.apache.spark。代表主

的内容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"

Answer 1

只需在spark目录中执行以下命令：

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

编辑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

在第一行替换：

log4j.rootCategory=INFO, console

通过：

log4j.rootCategory=WARN, console

保存并重新启动您的shell。它适用于OS X上的Spark 1.1.0和Spark 1.5.1。