Try this way:
object Holder extends Serializable { @transient lazy val log =
Logger.getLogger(getClass.getName) }
val someRdd = spark.parallelize(List(1, 2, 3))
someRdd.map {
element =>
Holder.*log.info <http://log.info/>(s"$element will be processed")*
element + 1
}
Thanks
Best Regards
On Mon, May 25, 2015 at 8:35 PM, Spico Florin <spicoflo...@gmail.com> wrote:
> Hello!
> I would like to use the logging mechanism provided by the log4j, but I'm
> getting the
> Exception in thread "main" org.apache.spark.SparkException: Task not
> serializable -> Caused by: java.io.NotSerializableException:
> org.apache.log4j.Logger
>
> The code (and the problem) that I'm using resembles the one used here :
> http://stackoverflow.com/questions/29208844/apache-spark-logging-within-scala,
> meaning:
>
> val log = Logger.getLogger(getClass.getName)
>
> def doTest() {
> val conf = new SparkConf().setMaster("local[4]").setAppName("LogTest")
> val spark = new SparkContext(conf)
>
> val someRdd = spark.parallelize(List(1, 2, 3))
> someRdd.map {
> element =>
> *log.info <http://log.info>(s"$element will be processed")*
> element + 1
> }
> I'm posting the same problem due to the fact that the one from
> stackoverflow didn't get any answer.
> In this case, can you please tell us what is the best way to use logging?
> Is any solution that is not using the rdd.forEachPartition?
>
> I look forward for your answers.
> Regards,
> Florin
>
>
>
>
>
>
