The Source class is private <https://github.com/apache/spark/blob/v1.4.1/core/src/main/scala/org/apache/spark/metrics/source/Source.scala#L22-L25> to the spark package and any new Sources added to the metrics registry must be of type Source <https://github.com/apache/spark/blob/v1.4.1/core/src/main/scala/org/apache/spark/metrics/MetricsSystem.scala#L144-L152>. So unless I'm mistaken, we can't define a custom source. I linked to 1.4.1 code, but the same is true in 1.6.1.
On Mon, 21 Mar 2016 at 12:05 Silvio Fiorito <silvio.fior...@granturing.com> wrote: > You could use the metric sources and sinks described here: > http://spark.apache.org/docs/latest/monitoring.html#metrics > > If you want to push the metrics to another system you can define a custom > sink. You can also extend the metrics by defining a custom source. > > From: Mike Sukmanowsky <mike.sukmanow...@gmail.com> > Date: Monday, March 21, 2016 at 11:54 AM > To: "user@spark.apache.org" <user@spark.apache.org> > Subject: Spark Metrics Framework? > > We make extensive use of the elasticsearch-hadoop library for > Hadoop/Spark. In trying to troubleshoot our Spark applications, it'd be > very handy to have access to some of the many metrics > <https://www.elastic.co/guide/en/elasticsearch/hadoop/current/metrics.html> > that the library makes available when running in map reduce mode. The > library's > author noted > <https://discuss.elastic.co/t/access-es-hadoop-stats-from-spark/44913> > that Spark doesn't offer any kind of a similar metrics API where by these > metrics could be reported or aggregated on. > > Are there any plans to bring a metrics framework similar to Hadoop's > Counter system to Spark or is there an alternative means for us to grab > metrics exposed when using Hadoop APIs to load/save RDDs? > > Thanks, > Mike >
