Application Error - Out of Java Heap Space

I have an application running in the Mendix cloud that pretty regularly runs out of of Java heap space and throws an error. I have copied the stack trace below. The log message is as follows: Level: Critical Node: M2EE Message: An unhandled error occurred in the MxRuntime Stack Trace: java.lang.OutOfMemoryError: Java heap space at java.lang.StringCoding$StringEncoder.encode( at java.lang.StringCoding.encode( at java.lang.String.getBytes( at ku.b(SourceFile:104) at kv.a(SourceFile:79) at ku.a(SourceFile:82) at ks.a(SourceFile:89) at ks.a(SourceFile:56) at lj.a(SourceFile:109) at mq.a(SourceFile:72) at mp.a(SourceFile:151) at mp.executeAction(SourceFile:98) at com.mendix.systemwideinterfaces.core.UserAction.execute(SourceFile:57) at at hA.b(SourceFile:193) at com.mendix.core.Core.execute(SourceFile:219) at gl.execute(SourceFile:186) at ja.a(SourceFile:319) at com.mendix.externalinterface.connector.RequestDispatching$Worker.a(SourceFile:157) at com.mendix.externalinterface.connector.RequestDispatching$Worker$a.a(SourceFile:148) at com.mendix.externalinterface.connector.RequestDispatching$Worker$a.apply(SourceFile:147) at$class.apply(Actor.scala:545) at com.mendix.externalinterface.connector.RequestDispatching$Worker.apply(SourceFile:143) at at akka.dispatch.MessageInvocation.invoke(MessageHandling.scala:25) at akka.dispatch.ExecutableMailbox$class.processMailbox(ExecutorBasedEventDrivenDispatcher.scala:223) at akka.dispatch.ExecutorBasedEventDrivenDispatcher$$anon$4.processMailbox(ExecutorBasedEventDrivenDispatcher.scala:123) at akka.dispatch.ExecutableMailbox$ at akka.dispatch.ExecutorBasedEventDrivenDispatcher$$anon$ at java.util.concurrent.ThreadPoolExecutor$Worker.runTask( at java.util.concurrent.ThreadPoolExecutor$ at Any ideas about how to troubleshoot this problem? Thanks!
1 answers

This is happening while you're generating a document. I guess you are generating fairly big documents and don't have a lot of memory on your cloud slot. You could file a ticket so we could try to make this process a bit more efficient in terms of memory, but the immediate solution would be to a) render smaller documents or b) get more memory in your cloud slot.