Hi
I am new to Spark and trying to develop an application that loads data from
Hive. Here is my setup:
* Spark-1.1.0 (built using -Pyarn -Phadoop-2.4 -Dhadoop.version=2.4.0
-Phive)
* Executing Spark-shell on a box with 16 GB RAM
* 4 Cores Single Processor
* OpenCSV library (SerDe)
* Hive table has 100K records
While trying to execute a query that does a group-by ("select ... group by
...") on a hive table, I get an OOM error. I tried setting the following
parameters, but they don't seem to help:
spark.executor.memory 2g
spark.shuffle.memoryFraction 0.8
spark.storage.memoryFraction 0.1
spark.default.parallelism 24
Any help is appreciated. The stack trace of the error is given below.
- Ranga
========== Stack trace ==============
java.lang.OutOfMemoryError: GC overhead limit exceeded
at java.util.Arrays.copyOf(Arrays.java:3332)
at
java.lang.AbstractStringBuilder.expandCapacity(AbstractStringBuilder.java:137)
at
java.lang.AbstractStringBuilder.ensureCapacityInternal(AbstractStringBuilder.java:121)
at
java.lang.AbstractStringBuilder.append(AbstractStringBuilder.java:569)
at java.lang.StringBuffer.append(StringBuffer.java:369)
at java.io.BufferedReader.readLine(BufferedReader.java:370)
at java.io.BufferedReader.readLine(BufferedReader.java:389)
at au.com.bytecode.opencsv.CSVReader.getNextLine(CSVReader.java:266)
at au.com.bytecode.opencsv.CSVReader.readNext(CSVReader.java:233)
at com.bizo.hive.serde.csv.CSVSerde.deserialize(CSVSerde.java:129)
at
org.apache.spark.sql.hive.HadoopTableReader$$anonfun$fillObject$1.apply(TableReader.scala:279)
at
org.apache.spark.sql.hive.HadoopTableReader$$anonfun$fillObject$1.apply(TableReader.scala:278)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
at
org.apache.spark.sql.execution.Aggregate$$anonfun$execute$1$$anonfun$7.apply(Aggregate.scala:157)
at
org.apache.spark.sql.execution.Aggregate$$anonfun$execute$1$$anonfun$7.apply(Aggregate.scala:151)
at org.apache.spark.rdd.RDD$$anonfun$13.apply(RDD.scala:596)
at org.apache.spark.rdd.RDD$$anonfun$13.apply(RDD.scala:596)
at
org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:229)
at
org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:229)
at
org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:68)
at
org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
at org.apache.spark.scheduler.Task.run(Task.scala:54)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:177)
at
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
================================
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