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From "Jacek Laskowski (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (SPARK-21728) Allow SparkSubmit to use logging
Date Wed, 30 Aug 2017 18:57:01 GMT

    [ https://issues.apache.org/jira/browse/SPARK-21728?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16147840#comment-16147840
] 

Jacek Laskowski commented on SPARK-21728:
-----------------------------------------

The idea behind the custom {{conf/log4j.properties}} is to disable all the logging and enable
only {{org.apache.spark.sql.execution.streaming}} currently.

{code}
$ cat conf/log4j.properties

# Set everything to be logged to the console
log4j.rootCategory=OFF, 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.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

#log4j.logger.org.apache.spark=OFF

log4j.logger.org.apache.spark.metrics.MetricsSystem=WARN

# Structured Streaming
log4j.logger.org.apache.spark.sql.execution.streaming.StreamExecution=DEBUG
log4j.logger.org.apache.spark.sql.execution.streaming.ProgressReporter=INFO
log4j.logger.org.apache.spark.sql.execution.streaming.RateStreamSource=DEBUG
log4j.logger.org.apache.spark.sql.kafka010.KafkaSource=DEBUG
log4j.logger.org.apache.spark.sql.kafka010.KafkaOffsetReader=DEBUG

log4j.logger.org.apache.spark.sql.execution.streaming.FlatMapGroupsWithStateExec=INFO
{code}

> Allow SparkSubmit to use logging
> --------------------------------
>
>                 Key: SPARK-21728
>                 URL: https://issues.apache.org/jira/browse/SPARK-21728
>             Project: Spark
>          Issue Type: Improvement
>          Components: Spark Core
>    Affects Versions: 2.3.0
>            Reporter: Marcelo Vanzin
>            Assignee: Marcelo Vanzin
>            Priority: Minor
>             Fix For: 2.3.0
>
>
> Currently, code in {{SparkSubmit}} cannot call classes or methods that initialize the
Spark {{Logging}} framework. That is because at that time {{SparkSubmit}} doesn't yet know
which application will run, and logging is initialized differently for certain special applications
(notably, the shells).
> It would be better if either {{SparkSubmit}} did logging initialization earlier based
on the application to be run, or did it in a way that could be overridden later when the app
initializes.
> Without this, there are currently a few parts of {{SparkSubmit}} that duplicates code
from other parts of Spark just to avoid logging. For example:
> * [downloadFiles|https://github.com/apache/spark/blob/master/core/src/main/scala/org/apache/spark/deploy/SparkSubmit.scala#L860]
replicates code from Utils.scala
> * [createTempDir|https://github.com/apache/spark/blob/master/core/src/main/scala/org/apache/spark/deploy/DependencyUtils.scala#L54]
replicates code from Utils.scala and installs its own shutdown hook
> * a few parts of the code could use {{SparkConf}} but can't right now because of the
logging issue.



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