Bump the python worker memory limit to 10g, since its doing all the work
Fix java.util.MissingFormatArgumentException in statsd module

I noticed the following stacktraces in some Spark jobs

14/11/06 20:50:24 ERROR OneForOneStrategy: Format specifier 's'
java.util.MissingFormatArgumentException: Format specifier 's'
    at java.util.Formatter.format(Formatter.java:2487)
    at java.util.Formatter.format(Formatter.java:2423)
    at java.lang.String.format(String.java:2790)
    at com.bealetech.metrics.reporting.Statsd.send(Statsd.java:75)
    at com.bealetech.metrics.reporting.StatsdReporter.reportGauge(StatsdReporter.java:268)
    at com.bealetech.metrics.reporting.StatsdReporter.report(StatsdReporter.java:139)
    at com.codahale.metrics.ScheduledReporter.report(ScheduledReporter.java:107)
    at org.apache.spark.metrics.sink.StatsdSink.report(StatsdSink.scala:87)
    at org.apache.spark.metrics.MetricsSystem$$anonfun$report$1.apply(MetricsSystem.scala:95)
    at org.apache.spark.metrics.MetricsSystem$$anonfun$report$1.apply(MetricsSystem.scala:95)
    at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
    at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
    at org.apache.spark.metrics.MetricsSystem.report(MetricsSystem.scala:95)
    at org.apache.spark.executor.Executor.stop(Executor.scala:132)
    at org.apache.spark.executor.CoarseGrainedExecutorBackend$$anonfun$receiveWithLogging$1.applyOrElse(CoarseGrainedExecutorBackend.scala:92)
    at scala.runtime.AbstractPartialFunction$mcVL$sp.apply$mcVL$sp(AbstractPartialFunction.scala:33)
    at scala.runtime.AbstractPartialFunction$mcVL$sp.apply(AbstractPartialFunction.scala:33)
    at scala.runtime.AbstractPartialFunction$mcVL$sp.apply(AbstractPartialFunction.scala:25)
    at org.apache.spark.util.ActorLogReceive$$anon$1.apply(ActorLogReceive.scala:53)
    at org.apache.spark.util.ActorLogReceive$$anon$1.apply(ActorLogReceive.scala:42)
    at scala.PartialFunction$class.applyOrElse(PartialFunction.scala:118)
    at org.apache.spark.util.ActorLogReceive$$anon$1.applyOrElse(ActorLogReceive.scala:42)
    at akka.actor.ActorCell.receiveMessage(ActorCell.scala:498)
    at akka.actor.ActorCell.invoke(ActorCell.scala:456)
    at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:237)
    at akka.dispatch.Mailbox.run(Mailbox.scala:219)
    at akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:386)
    at scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
    at scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)
    at scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)
    at scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)

The cause was that we were expecting an executor name with at least three components but there
are cases when that's not the case.

This PR does no longer expect three components but instead creates a single string of maximal the the first three
components.
Merge pull request #16 from Shopify/statsd-bug

Fix java.util.MissingFormatArgumentException in statsd module
Merge tag 'shopify-1'

Start of Shopify deploy tracking

Conflicts:
	python/pyspark/daemon.py