Searched on Google with the first line of a JAVA stack trace?

We can recommend more relevant solutions and speed up debugging when you paste your entire stack trace with the exception message. Try a sample exception.

Recommended solutions based on your search

Solutions on the web

via Stack Overflow by Ajeet
, 1 year ago
via GitHub by lufenghuan
, 2 years ago
GC overhead limit exceeded
via Google Groups by Rita, 10 months ago
GC overhead limit exceeded
java.lang.OutOfMemoryError: GC overhead limit exceeded at java.util.HashMap.createEntry(HashMap.java:897) at java.util.HashMap.addEntry(HashMap.java:884) at java.util.HashMap.put(HashMap.java:505) at java.util.HashSet.add(HashSet.java:217) at com.pb.hadoop.spark.hexgen.function.HexGenMapFunction.call(HexGenMapFunction.java:56) at com.pb.hadoop.spark.hexgen.function.HexGenMapFunction.call(HexGenMapFunction.java:21) at org.apache.spark.api.java.JavaRDDLike$$anonfun$fn$1$1.apply(JavaRDDLike.scala:129) at org.apache.spark.api.java.JavaRDDLike$$anonfun$fn$1$1.apply(JavaRDDLike.scala:129) at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371) at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327) at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327) at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327) at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopDataset$1$$anonfun$13$$anonfun$apply$6.apply$mcV$sp(PairRDDFunctions.scala:1197) at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopDataset$1$$anonfun$13$$anonfun$apply$6.apply(PairRDDFunctions.scala:1197) at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopDataset$1$$anonfun$13$$anonfun$apply$6.apply(PairRDDFunctions.scala:1197) at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1251) at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopDataset$1$$anonfun$13.apply(PairRDDFunctions.scala:1205) at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopDataset$1$$anonfun$13.apply(PairRDDFunctions.scala:1185) at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66) at org.apache.spark.scheduler.Task.run(Task.scala:89) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615) at java.lang.Thread.run(Thread.java:745)