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JVM Errors/Java Nullpointer exceptions #154
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Why does nullpointer exception point to these scala codes |
Hmm, not too sure, but one possible source is multiple partitions trying to write to the same place in Spark. Has the input DataFrame been sorted?
Sorry this is on a branch that is not supported and being worked on right now. Current architecture is very different.
…On May 16 2018, at 10:10 am, PallaviPersistent ***@***.***> wrote:
Why does nullpointer exception point to these scala codes
at org.velvia.filo.vectors.DictUTF8Vector$.shouldMakeDict(DictUTF8Vector.scala:46)
at org.velvia.filo.vectors.UTF8PtrAppendable.optimizedVector(UTF8Vector.scala:304)
at org.velvia.filo.vectors.UTF8PtrAppendable.suboptimize(UTF8Vector.scala:294)
at org.velvia.filo.vectors.ObjectVector.optimize(ObjectVector.scala:59)
at org.velvia.filo.BinaryVectorBuilder.toFiloBuffer(BinaryVector.scala:314)
at org.velvia.filo.RowToVectorBuilder$$anonfun$2.apply(RowToVectorBuilder.scala:86)
at org.velvia.filo.RowToVectorBuilder$$anonfun$2.apply(RowToVectorBuilder.scala:86)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
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Thanks for your reply .. |
NPE and JVM crash errors are coming intermittently. Sorting the dataframe did help but the error recurred. Also the pid logs generated during JVM crash point to Java thread filo-spark-akka.actor.default-dispatcher-23 |
hs_err_pid20721.log |
Branch, version, commit
OS and Environment
CentOS Linux 7.3
JVM version
JDK 1.8
Scala version
Scala version 2.11
Kafka and Cassandra versions and setup
Cassandra version 3.2
Spark version if used
Spark 2.0
Deployed mode
(client/cluster on Spark Standalone/YARN/Mesos/EMR or default)
Standalone
Actual (wrong) behavior
scala> dfResult.write.format("filodb.spark").option("dataset", "flow_raw").option("row_keys", "exportMs").option("partition_keys", "protocolId").mode(SaveMode.Append).save()
[INFO] [05/10/2018 23:15:15.943] [main] [StatsDExtension(akka://kamon)] Starting the Kamon(StatsD) extension
[Stage 8:====> (1 + 11) / 12]#
A fatal error has been detected by the Java Runtime Environment:
SIGSEGV (0xb) at pc=0x00007f5204acf802, pid=3245, tid=0x00007f5041dca700
JRE version: OpenJDK Runtime Environment (8.0_131-b12) (build 1.8.0_131-b12)
Java VM: OpenJDK 64-Bit Server VM (25.131-b12 mixed mode linux-amd64 compressed oops)
Problematic frame:
J 22484 C1 org.velvia.filo.ZeroCopyBinary$class.cachedHash64(Lorg/velvia/filo/ZeroCopyBinary;)J (140 bytes) @ 0x00007f5204acf802 [0x00007f5204acf760+0xa2]
Failed to write core dump. Core dumps have been disabled. To enable core dumping, try "ulimit -c unlimited" before starting Java again
An error report file with more information is saved as:
/root/spark-2.0.0-bin-hadoop2.6/hs_err_pid3245.log
If you would like to submit a bug report, please visit:
http://bugreport.java.com/bugreport/crash.jsp
bin/spark-shell: line 44: 3245 Aborted (core dumped) "${SPARK_HOME}"/bin/spark-submit --class org.apache.spark.repl.Main --name "Spark shell" "$@"
scala> dfResult1.write.format("filodb.spark").option("dataset", "flow_raw").option("row_keys", "exportMs").option("partition_keys", "protocolId").mode(SaveMode.Append).save()
18/05/10 23:09:35 ERROR OneForOneStrategy:
java.lang.NullPointerException
at org.velvia.filo.ZeroCopyBinary$class.cachedHash64(ZeroCopyBinary.scala:77)
at org.velvia.filo.ZeroCopyUTF8String.cachedHash64(ZeroCopyBinary.scala:101)
at org.velvia.filo.ZeroCopyBinary$class.hashCode(ZeroCopyBinary.scala:85)
at org.velvia.filo.ZeroCopyUTF8String.hashCode(ZeroCopyBinary.scala:101)
at java.util.HashMap.hash(HashMap.java:338)
at java.util.HashMap.putIfAbsent(HashMap.java:1061)
at org.velvia.filo.vectors.DictUTF8Vector$.shouldMakeDict(DictUTF8Vector.scala:49)
at org.velvia.filo.vectors.UTF8PtrAppendable.optimizedVector(UTF8Vector.scala:304)
at org.velvia.filo.vectors.UTF8PtrAppendable.suboptimize(UTF8Vector.scala:294)
at org.velvia.filo.vectors.ObjectVector.optimize(ObjectVector.scala:59)
Steps to reproduce
scala> val files=Seq("file:/root/parquetfiles/fragment1523366588968000000.dat","file:/root/parquetfiles/fragment1523350809009000000.dat")
scala> val sqlContext = new org.apache.spark.sql.SQLContext(sc)
scala> val parDF=sqlContext.read.parquet(files:_*)
scala> parDF1.count
res2: Long = 1168530
val dfResult = parDF.withColumn("exporterIp", inetToString(parDF("exporterIp"))).withColumn("srcIp", inetToString(parDF("srcIp"))).withColumn("dstIp", inetToString(parDF("dstIp"))).withColumn("nextHopIp", inetToString(parDF("nextHopIp"))).withColumn("bgpNextHopIp", inetToString(parDF("bgpNextHopIp"))).withColumn("appId", inetToString(parDF("appId"))).withColumn("policyQosClassificationHierarchy", inetToString(parDF("policyQosClassificationHierarchy"))).withColumn("protocolId", parDF("protocolId").cast(IntegerType)).withColumn("srcTos", parDF("srcTos").cast(IntegerType)).withColumn("dstTos", parDF("dstTos").cast(IntegerType)).withColumn("srcMask", parDF("srcMask").cast(StringType)).withColumn("dstMask", parDF("dstMask").cast(StringType)).withColumn("direction", parDF("direction").cast(StringType))
dfResult.write.format("filodb.spark").option("dataset", "flow_metric_raw_new").option("row_keys", "exportMs").option("partition_keys", "protocolId").mode(SaveMode.Append).save()
It throws either JVM errors or null pointer exceptions
Logs
or as attached file (see below)
Unused parts of this template should be removed (including this line).
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