Github user uhonnavarkar commented on the pull request:
https://github.com/apache/spark/pull/8808#issuecomment-185122533
I have 2 question below.
1) I have downloaded pre-build version of spark-1.5.2-bin-hadoop2.6.tgz
from spark website(http://spark.apache.org/downloads.html). still I see
stack-trace in #2 below. Is this package contains fix?
2) When I try to query the table(Dataframe) getting the exception. Also it
is inconsistent, some time it works some time not.
**Stack Trace:**
Job aborted due to stage failure: Task 0 in stage 1063.0 failed 4 times,
most recent failure: Lost task 0.3 in stage 1063.0 (TID 15469, XX.XXX.XX.XXX):
org.apache.spark.SparkException: Kryo serialization failed: Buffer overflow.
Available: 0, required: 2. To avoid this, increase
spark.kryoserializer.buffer.max value. at
org.apache.spark.serializer.KryoSerializerInstance.serialize(KryoSerializer.scala:263)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:240) at
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745) Driver stacktrace:
And this is how I am creating **Spark Context:**
sparkConf = new SparkConf().setMaster(sparkMaster)
.setAppName("ABCTesting")
.set("spark.home", spark_home)
.set("spark.shuffle.consolidateFiles","true")
.set("spark.shuffle.manager","sort")
.set("spark.shuffle.spill", "false")
.set("spark.executor.memory", spark_executor_memory)
.set("spark.executor.extraClassPath",
spark_executor_extra_classpath)
.set("spark.cores.max", spark_cores_max)
.set("spark.sql.shuffle.partitions", "15")
.set("spark.driver.memory", spark_driver_memory)
.set("spark.default.parallelism", "90")
.set("spark.serializer",
"org.apache.spark.serializer.KryoSerializer");
sparkContext = new JavaSparkContext(sparkConf);
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