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