Is the env/dev/log4j-executor.properties file within your jar file? Is the path
matching with what you specified as env/dev/log4j-executor.properties?
If you read the log4j document here:
https://logging.apache.org/log4j/1.2/manual.html
When you specify the log4j.configuration=my_custom.properties, you have 2
option:
1) the my_custom.properties has to be in the jar (or in the classpath). In your
case, since you specify the package path, you need to make sure they are
matched in your jar file2) use like
log4j.configuration=file:///tmp/my_custom.properties. In this way, you need to
make sure file my_custom.properties exists in /tmp folder on ALL of your worker
nodes.
Yong
Date: Wed, 13 Apr 2016 14:18:24 -0300
Subject: Re: Logging in executors
From: cma...@despegar.com
To: yuzhih...@gmail.com
CC: user@spark.apache.org
Thanks for your response Ted. You're right, there was a typo. I changed it, now
I'm executing:
bin/spark-submit --master spark://localhost:7077 --conf
"spark.driver.extraJavaOptions=-Dlog4j.configuration=env/dev/log4j-driver.properties"
--conf
"spark.executor.extraJavaOptions=-Dlog4j.configuration=env/dev/log4j-executor.properties"
--class....
The content of this file is:
# Set everything to be logged to the consolelog4j.rootCategory=INFO,
FILElog4j.appender.console=org.apache.log4j.ConsoleAppenderlog4j.appender.console.target=System.errlog4j.appender.console.layout=org.apache.log4j.PatternLayoutlog4j.appender.console.layout.ConversionPattern=%d{yy/MM/dd
HH:mm:ss} %p %c{1}: %m%n
log4j.appender.FILE=org.apache.log4j.RollingFileAppenderlog4j.appender.FILE.File=/tmp/executor.loglog4j.appender.FILE.ImmediateFlush=truelog4j.appender.FILE.Threshold=debuglog4j.appender.FILE.Append=truelog4j.appender.FILE.MaxFileSize=100MBlog4j.appender.FILE.MaxBackupIndex=5log4j.appender.FILE.layout=org.apache.log4j.PatternLayoutlog4j.appender.FILE.layout.ConversionPattern=%d{yy/MM/dd
HH:mm:ss} %p %c{1}: %m%n
# Settings to quiet third party logs that are too
verboselog4j.logger.org.spark-project.jetty=WARNlog4j.logger.org.spark-project.jetty.util.component.AbstractLifeCycle=ERRORlog4j.logger.org.apache.spark.repl.SparkIMain$exprTyper=INFOlog4j.logger.org.apache.spark.repl.SparkILoop$SparkILoopInterpreter=INFOlog4j.logger.org.apache.parquet=ERRORlog4j.logger.parquet=ERRORlog4j.logger.com.despegar.p13n=DEBUG
# SPARK-9183: Settings to avoid annoying messages when looking up nonexistent
UDFs in SparkSQL with Hive
supportlog4j.logger.org.apache.hadoop.hive.metastore.RetryingHMSHandler=FATALlog4j.logger.org.apache.hadoop.hive.ql.exec.FunctionRegistry=ERROR
Finally, the code on which I'm using logging in the executor is:
def groupAndCount(keys: DStream[(String, List[String])])(handler:
ResultHandler) = {
val result = keys.reduceByKey((prior, current) => {
(prior ::: current)
}).flatMap {
case (date, keys) =>
val rs = keys.groupBy(x => x).map(
obs =>{
val (d,t) = date.split("@") match {
case Array(d,t) => (d,t)
}
import org.apache.log4j.Logger
import scala.collection.JavaConverters._
val logger: Logger = Logger.getRootLogger
logger.info(s"Metric retrieved $d")
Metric("PV", d, obs._1, t, obs._2.size)
}
)
rs
}
result.foreachRDD((rdd: RDD[Metric], time: Time) => {
handler(rdd, time)
})
}
Originally the import and logger object was outside the map function. I'm also
using the root logger just to see if it's working, but nothing gets logged.
I've checked that the property is set correctly on the executor side through
println(System.getProperty("log4j.configuration")) and is OK, but still not
working.
Thanks again,-carlos.
