ML Spark Exception for processing logs with IPv6 Addresses

Jon_Davis — Fri, 17 Aug 2018 14:35:29 GMT

Getting the following error when trying to process CSV:

Exception:

Caused by: java.lang.NumberFormatException: For input string: "2001:470:ba7e:20::254"
at java.lang.NumberFormatException.forInputString(NumberFormatException.java:65)

Full trace:

(/opt/Spark/spark/bin/spark-submit --class com.paloaltonetworks.tbd.LogCollectorCompacter --deploy-mode client --supervise /var/www/html/OS/spark/packages/LogCoCo-1.2.4-SNAPSHOT.jar MLServer='10.10.50.100', master='local[3]', debug='false', taskID='65', user='admin', dbUser='root', dbPass='paloalto', dbServer='10.10.50.100:3306', timeZone='Europe/Helsinki', mode='Expedition', input='007254000047808:8.0.3:/var/backup/fw1_traffic_2018_08_17_last_calendar_day.csv', output='/var/expedition/connections.parquet', tempFolder='/var/expedition'; echo /var/backup/fw1_traffic_2018_08_17_last_calendar_day.csv; )>> "/tmp/error_logCoCo" 2>>/tmp/error_logCoCo &
---- CREATING SPARK Session:
warehouseLocation:/PALogs/spark-warehouse
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/opt/Spark/extraLibraries/slf4j-nop-1.7.25.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/opt/Spark/spark-2.1.1-bin-hadoop2.7/jars/slf4j-log4j12-1.7.16.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation.
SLF4J: Actual binding is of type [org.slf4j.helpers.NOPLoggerFactory]
+--------------------+---------------+--------+--------------------+
| rowLine| fwSerial|panosver| csvpath|
+--------------------+---------------+--------+--------------------+
|007254000047808:8...|007254000047808| 8.0.3|/var/backup/fw1_t...|
+--------------------+---------------+--------+--------------------+

8.0.0:/var/backup/fw1_traffic_2018_08_17_last_calendar_day.csv
LogCollector&Compacter called with the following parameters:
Parameters for execution
Master[processes]:............ local[3]
User:......................... admin
debug:........................ false
Parameters for Job Connections
Task ID:...................... 65
My IP:........................ 10.10.50.100
Expedition IP:................ 10.10.50.100:3306
Time Zone:.................... Europe/Helsinki
dbUser (dbPassword):.......... root (************)
projectName:.................. demo
Parameters for Data Sources
App Categories (source):........ (Expedition)
CSV Files Path:.................007254000047808:8.0.3:/var/backup/fw1_traffic_2018_08_17_last_calendar_day.csv
Parquet output path:.......... file:///var/expedition/connections.parquet
Temporary folder:............. /var/expedition
---- AppID DB LOAD:
Application Categories loading...
DONE

Logs of format 7.1.x NOT found
Logs of format 8.0.2 found
Logs of format 8.1.0-beta17 NOT found
Logs of format 8.1.0 NOT found
Size of trafficExtended: 50 MB
[Stage 44:> (0 + 3) / 3]Exception in thread "main" org.apache.spark.SparkException: Job aborted due to stage failure: Task 2 in stage 44.0 failed 1 times, most recent failure: Lost task 2.0 in stage 44.0 (TID 936, localhost, executor driver): org.apache.spark.SparkException: Failed to execute user defined function(anonfun$18: (string) => bigint)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.agg_doAggregateWithKeys$(Unknown Source)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:377)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:126)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:96)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53)
at org.apache.spark.scheduler.Task.run(Task.scala:99)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:322)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Caused by: java.lang.NumberFormatException: For input string: "2001:470:ba7e:20::254"
at java.lang.NumberFormatException.forInputString(NumberFormatException.java:65)
at java.lang.Integer.parseInt(Integer.java:580)
at java.lang.Integer.parseInt(Integer.java:615)
at scala.collection.immutable.StringLike$class.toInt(StringLike.scala:272)
at scala.collection.immutable.StringOps.toInt(StringOps.scala:29)
at com.paloaltonetworks.tbd.LogCollectorCompacter$.com$paloaltonetworks$tbd$LogCollectorCompacter$$IPv4ToLong$1(LogCollectorCompacter.scala:275)
at com.paloaltonetworks.tbd.LogCollectorCompacter$$anonfun$18.apply(LogCollectorCompacter.scala:886)
at com.paloaltonetworks.tbd.LogCollectorCompacter$$anonfun$18.apply(LogCollectorCompacter.scala:886)
... 13 more

Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1435)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1423)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1422)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1422)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:802)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:802)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:802)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1650)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1605)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1594)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:628)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1925)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1938)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1951)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1965)
at org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:936)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:362)
at org.apache.spark.rdd.RDD.collect(RDD.scala:935)
at com.paloaltonetworks.tbd.LogCollectorCompacter$.main(LogCollectorCompacter.scala:1039)
at com.paloaltonetworks.tbd.LogCollectorCompacter.main(LogCollectorCompacter.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:743)
at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:187)
at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:212)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:126)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
Caused by: org.apache.spark.SparkException: Failed to execute user defined function(anonfun$18: (string) => bigint)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.agg_doAggregateWithKeys$(Unknown Source)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:377)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:126)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:96)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53)
at org.apache.spark.scheduler.Task.run(Task.scala:99)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:322)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Caused by: java.lang.NumberFormatException: For input string: "2001:470:ba7e:20::254"
at java.lang.NumberFormatException.forInputString(NumberFormatException.java:65)
at java.lang.Integer.parseInt(Integer.java:580)
at java.lang.Integer.parseInt(Integer.java:615)
at scala.collection.immutable.StringLike$class.toInt(StringLike.scala:272)
at scala.collection.immutable.StringOps.toInt(StringOps.scala:29)
at com.paloaltonetworks.tbd.LogCollectorCompacter$.com$paloaltonetworks$tbd$LogCollectorCompacter$$IPv4ToLong$1(LogCollectorCompacter.scala:275)
at com.paloaltonetworks.tbd.LogCollectorCompacter$$anonfun$18.apply(LogCollectorCompacter.scala:886)
at com.paloaltonetworks.tbd.LogCollectorCompacter$$anonfun$18.apply(LogCollectorCompacter.scala:886)
... 13 more
/var/backup/fw1_traffic_2018_08_17_last_calendar_day.csv

Re: ML Spark Exception for processing logs with IPv6 Addresses

alestevez — Fri, 17 Aug 2018 14:44:28 GMT

Hi,

thanks we are working to fix it. By now ipv6 analisys will not be supported yet. But we will prevent spark to quit when an ipv6 address is found.

Re: ML Spark Exception for processing logs with IPv6 Addresses

aaron.howell — Wed, 05 Sep 2018 22:57:48 GMT

Are we still working on being able to ingest IPv6 addressing in logs, or are you still working on having Spark not quit thus aborting the whole process via stacktrace? It has been 3 weeks and I have not seen an update here. I am running Expedition-Beta versoin 1.0.104.

Thanks in advance,

topic Re: ML Spark Exception for processing logs with IPv6 Addresses in Expedition Discussions

ML Spark Exception for processing logs with IPv6 Addresses

Re: ML Spark Exception for processing logs with IPv6 Addresses

Re: ML Spark Exception for processing logs with IPv6 Addresses