如何设置默认的火花记录级别? [英] How can set the default spark logging level?

问题描述

我将pyspark应用程序从自己工作站上的pycharm启动到8节点集群.此集群还具有在spark-defaults.conf和spark-env.sh

I launch pyspark applications from pycharm on my own workstation, to a 8 node cluster. This cluster also has settings encoded in spark-defaults.conf and spark-env.sh

这就是我获取spark上下文变量的方式.

This is how I obtain my spark context variable.

spark = SparkSession \
        .builder \
        .master("spark://stcpgrnlp06p.options-it.com:7087") \
        .appName(__SPARK_APP_NAME__) \
        .config("spark.executor.memory", "50g") \
        .config("spark.eventlog.enabled", "true") \
        .config("spark.eventlog.dir", r"/net/share/grid/bin/spark/UAT/SparkLogs/") \
        .config("spark.cores.max", 128) \
        .config("spark.sql.crossJoin.enabled", "True") \
        .config("spark.executor.extraLibraryPath","/net/share/grid/bin/spark/UAT/bin/vertica-jdbc-8.0.0-0.jar") \
        .config("spark.serializer", "org.apache.spark.serializer.KryoSerializer") \
        .config("spark.logConf", "true") \
        .getOrCreate()

    sc = spark.sparkContext
    sc.setLogLevel("INFO")

我想查看日志中正在使用的有效配置.这行

I want to see the effective config that is being used in my log. This line

        .config("spark.logConf", "true") \

应该导致spark api将其有效配置作为INFO记录到日志中，但是默认日志级别设置为WARN，因此我看不到任何消息.

should cause the spark api to log its effective config to the log as INFO, but the default log level is set to WARN, and as such I don't see any messages.

设置此行

sc.setLogLevel("INFO")

显示前进的INFO消息，但到那时为时已晚.

shows INFO messages going forward, but its too late by then.

如何设置spark起始的默认日志记录级别?

How can I set the default logging level that spark starts with?

推荐答案

http://spark.apache.org/docs/latest/configuration.html#configuring-logging

配置日志记录

Spark使用log4j进行日志记录. 您可以通过在conf目录中添加log4j.properties文件来配置它.一种开始的方法是复制位于那里的现有log4j.properties.template.

Spark uses log4j for logging. You can configure it by adding a log4j.properties file in the conf directory. One way to start is to copy the existing log4j.properties.template located there.

以下有关如何登录Spark"的博客

The following blog about "How to log in spark" https://www.mapr.com/blog/how-log-apache-spark suggest a way to configure log4j, and provide suggestion which includes directing INFO level logs into a file.

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