Apache Spark logging within Scala

Question

I am looking for a solution to be able to log additional data when executing code on Apache Spark Nodes that could help investigate later some issues that might appear during execution. Trying to use a traditional solution like for example com.typesafe.scalalogging.LazyLogging fails because the log instance cannot be serialized on a distributed environment like Apache Spark.

I've investigated this problem and for now the solution that I found was to use the org.apache.spark.Logging trait like this :

class SparkExample with Logging {
  val someRDD = ...
  someRDD.map {
    rddElement => logInfo(s"$rddElement will be processed.")
    doSomething(rddElement)
  }
}

However it looks like the Logging trait is not a permanent solution for Apache Spark because it's marked as @DeveloperApi and the class documentation mentions:

This will likely be changed or removed in future releases.

I am wondering - are they any known logging solution that I can use and will allow me to log data when the RDDs are executed on Apache Spark nodes ?

@Later Edit : Some of the comments from below suggest to use Log4J. I've tried using Log4J but I'm still having issues when using logger from a Scala class (and not a Scala object). Here is my full code :

import org.apache.log4j.Logger
import org.apache.spark._

object Main {
 def main(args: Array[String]) {
  new LoggingTestWithRDD().doTest()
 }
}

class LoggingTestWithRDD extends Serializable {

  val log = Logger.getLogger(getClass.getName)

  def doTest(): Unit = {
   val conf = new SparkConf().setMaster("local[4]").setAppName("LogTest")
   val spark = new SparkContext(conf)

   val someRdd = spark.parallelize(List(1, 2, 3))
   someRdd.map {
     element =>
       log.info(s"$element will be processed")
       element + 1
    }
   spark.stop()
 }

}

The exception that I'm seeing is :

Exception in thread "main" org.apache.spark.SparkException: Task not serializable -> Caused by: java.io.NotSerializableException: org.apache.log4j.Logger

Answer 1

You can use Akhil's solution proposed in
https://www.mail-archive.com/[email protected]/msg29010.html. I have used by myself and it works.

Akhil Das Mon, 25 May 2015 08:20:40 -0700
Try this way:

object Holder extends Serializable {      
   @transient lazy val log = Logger.getLogger(getClass.getName)    
}


val someRdd = spark.parallelize(List(1, 2, 3)).foreach { element =>
   Holder.log.info(element)
}