Which version of Java are you using ? And release of Spark, please.
Thanks On Fri, Sep 18, 2015 at 9:15 AM, swetha <swethakasire...@gmail.com> wrote: > Hi, > > When I try to recover my Spark Streaming job from a checkpoint directory, I > get a StackOverFlow Error as shown below. Any idea as to why this is > happening? > > 15/09/18 09:02:20 ERROR streaming.StreamingContext: Error starting the > context, marking it as stopped > java.lang.StackOverflowError > at java.util.Date.getTimeImpl(Date.java:887) > at java.util.Date.getTime(Date.java:883) > at java.util.Calendar.setTime(Calendar.java:1106) > at java.text.SimpleDateFormat.format(SimpleDateFormat.java:955) > at java.text.SimpleDateFormat.format(SimpleDateFormat.java:948) > at java.text.DateFormat.format(DateFormat.java:298) > at java.text.Format.format(Format.java:157) > at > org.apache.spark.streaming.ui.UIUtils$.formatBatchTime(UIUtils.scala:113) > at > > org.apache.spark.streaming.dstream.DStream$$anonfun$makeScope$1.apply(DStream.scala:137) > at > > org.apache.spark.streaming.dstream.DStream$$anonfun$makeScope$1.apply(DStream.scala:136) > at scala.Option.map(Option.scala:145) > at > org.apache.spark.streaming.dstream.DStream.makeScope(DStream.scala:136) > at > > org.apache.spark.streaming.dstream.DStream.createRDDWithLocalProperties(DStream.scala:394) > at > > org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:344) > at > > org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:342) > at scala.Option.orElse(Option.scala:257) > at > org.apache.spark.streaming.dstream.DStream.getOrCompute(DStream.scala:339) > at > > org.apache.spark.streaming.dstream.StateDStream.compute(StateDStream.scala:67) > at > > org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1$$anonfun$apply$7.apply(DStream.scala:350) > at > > org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1$$anonfun$apply$7.apply(DStream.scala:350) > at scala.util.DynamicVariable.withValue(DynamicVariable.scala:57) > at > > org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1.apply(DStream.scala:349) > at > > org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1.apply(DStream.scala:349) > at > > org.apache.spark.streaming.dstream.DStream.createRDDWithLocalProperties(DStream.scala:399) > at > > org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:344) > at > > org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:342) > at scala.Option.orElse(Option.scala:257) > at > org.apache.spark.streaming.dstream.DStream.getOrCompute(DStream.scala:339) > at > > org.apache.spark.streaming.dstream.StateDStream.compute(StateDStream.scala:67) > at > > org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1$$anonfun$apply$7.apply(DStream.scala:350) > at > > org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1$$anonfun$apply$7.apply(DStream.scala:350) > at scala.util.DynamicVariable.withValue(DynamicVariable.scala:57) > at > > org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1.apply(DStream.scala:349) > at > > org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1.apply(DStream.scala:349) > at > > org.apache.spark.streaming.dstream.DStream.createRDDWithLocalProperties(DStream.scala:399) > at > > org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:344) > at > > org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:342) > at scala.Option.orElse(Option.scala:257) > > > > > -- > View this message in context: > http://apache-spark-user-list.1001560.n3.nabble.com/Spark-Streaming-checkpoint-recovery-throws-Stack-Overflow-Error-tp24737.html > Sent from the Apache Spark User List mailing list archive at Nabble.com. > > --------------------------------------------------------------------- > To unsubscribe, e-mail: user-unsubscr...@spark.apache.org > For additional commands, e-mail: user-h...@spark.apache.org > >
