[jira] [Resolved] (SPARK-15344) Unable to set default log level for PySpark

["Marcelo Vanzin (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-15344?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Marcelo Vanzin resolved SPARK-15344.
------------------------------------
    Resolution: Not A Problem

See Felix's reply above.

> Unable to set default log level for PySpark
> -------------------------------------------
>
>                 Key: SPARK-15344
>                 URL: https://issues.apache.org/jira/browse/SPARK-15344
>             Project: Spark
>          Issue Type: Bug
>          Components: PySpark
>    Affects Versions: 2.0.0
>            Reporter: Maciej Bryński
>            Priority: Minor
>
> After this patch:
> https://github.com/apache/spark/pull/12648
> I'm unable to set default log level for Pyspark.
> It's always WARN.
> Below setting doesn't work: 
> {code}
> mbrynski@jupyter:~/spark$ cat conf/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
> # 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
> {code}



--
This message was sent by Atlassian JIRA
(v6.3.4#6332)

---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org