thanks Divya,
I tried that and still get same error - array out of bounds.
Full code.
import org.apache.spark.sql.sources.EqualTo
import com.couchbase.spark.sql._
import com.couchbase.spark.sql.N1QLRelation
\val bkEvent = Map("bucket" -> "events")
val eve = sqlc.read.couchbase(schemaFilter =
EqualTo("doctype","BusinessEvent"), bkEvent)
*RESULT*
bkEvent: scala.collection.immutable.Map[String,String] = Map(bucket ->
events)
eve: org.apache.spark.sql.DataFrame = [META_ID: string, businessEventType:
string, customerEvent:
struct<customerContext:struct<anonymousCustomerChanges:struct<analyticsId:struct<id:string,system:string>,device:array<struct<browser:string,browserVersion:string,dateAdded:string,id:string,model:string,os:string,osVersion:string,source:string,type:string>>,doctype:string,id:string,referral:array<struct<accountOperator:string,mappedAccountId:string,referralDate:string,referralSource:string,
I am wondering if its because the way I am loading the schema? Should I be
doing this manually?
Thanks,
Mark
On Mon, Oct 17, 2016 at 7:10 AM, Divya Gehlot <divya.htco...@gmail.com>
wrote:
> Try with
> eve.select(col("id"),col("customerEvent.customerContext.anon
> ymousCustomerChanges.analyticsId.id
> <http://customerevent.customercontext.anonymouscustomerchanges.analyticsid.id/>
> ")).show
>
>
>
> This should work
>
>
> Thanks,
> Divya
>
> On 16 October 2016 at 19:59, Mark Mikolajczak - 07855 306 064 <
> m...@flayranalytics.co.uk> wrote:
>
>> Thanks Kim.
>>
>> Sorry It was a typo as I was doing the second part from my phone (Laptop
>> battery died).
>>
>>
>> The code I was using in zeppelin is:
>> eve.select($"id",$"customerEvent.customerContext.anonymousCu
>> stomerChanges.analyticsId.id").show
>>
>> I tried with and with out the $ sign but still get the same error.
>>
>> Any advice?
>>
>>
>> On 16 Oct 2016, at 12:41, Jun Kim <i2r....@gmail.com> wrote:
>>
>> Hi, Mark Mikolajczak
>>
>> I think it should be
>>
>> eve.select("id", "customerEvent.customerContext
>> .anonymousCustomerChanges.analyticsId.id
>> <http://customerevent.customercontext.anonymouscustomerchanges.analyticsid.id/>
>> ")
>>
>> You missed 'customerEvent'!
>>
>> :-)
>>
>> 2016년 10월 16일 (일) 오후 8:32, Flayranalytics <m...@flayranalytics.co.uk>님이
>> 작성:
>>
>> Hi,
>> Sorry forgot to include the code.
>>
>> eve.select($"id",$"customerContext.anonymousCustomerChanges.
>> analyticsId.id
>> <http://customercontext.anonymouscustomerchanges.analyticsid.id/>
>> ").show()
>>
>> If I just use Id it works. I am seeing this happen when the data is an
>> array within my data.
>>
>>
>>
>> Sent from my 📲
>>
>> On 16 Oct 2016, at 12:03, Mark Mikolajczak - 07855 306 064 <
>> m...@flayranalytics.co.uk> wrote:
>>
>>
>>
>> down votefavorite
>> <http://stackoverflow.com/questions/40064621/dataframe-in-apache-spark-error-java-lang-arrayindexoutofboundsexception#>
>>
>> <http://stackoverflow.com/questions/40064621/dataframe-in-apache-spark-error-java-lang-arrayindexoutofboundsexception#>
>>
>> Hi,
>>
>> I have setup a spark dataframe but I have issues when trying to run query
>> on some of the data. If I run on META_ID it will work but when I try to run
>> on any of the customerEvent it fails. I am running apache Zeppelin in EMR
>> with Spark 1.6.2. I not sure why this error is happening so let me know if
>> you have seen this before? I was thinking that its possibly the automatic
>> data frame not creating the correct schema so should this be done manually?
>>
>> Scheme
>>
>> root
>> |-- META_ID: string (nullable = true)
>> |-- businessEventType: string (nullable = true)
>> |-- customerEvent: struct (nullable = true)
>> | |-- customerContext: struct (nullable = true)
>> | | |-- anonymousCustomerChanges: struct (nullable = true)
>> | | | |-- analyticsId: struct (nullable = true)
>> | | | | |-- id: string (nullable = true)
>> | | | | |-- system: string (nullable = true)
>>
>>
>> Error
>>
>> org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in
>> stage 92.0 failed 4 times, most recent failure: Lost task 0.3 in stage 92.0
>> (TID 137, ip-10-90-200-51.eu-west-1.compute.internal):
>> java.lang.ArrayIndexOutOfBoundsException: 1
>> at
>> org.apache.spark.sql.catalyst.CatalystTypeConverters$StructConverter.toCatalystImpl(CatalystTypeConverters.scala:260)
>> at
>> org.apache.spark.sql.catalyst.CatalystTypeConverters$StructConverter.toCatalystImpl(CatalystTypeConverters.scala:250)
>> at
>> org.apache.spark.sql.catalyst.CatalystTypeConverters$CatalystTypeConverter.toCatalyst(CatalystTypeConverters.scala:102)
>> at
>> org.apache.spark.sql.catalyst.CatalystTypeConverters$$anonfun$createToCatalystConverter$2.apply(CatalystTypeConverters.scala:401)
>> at
>> org.apache.spark.sql.execution.RDDConversions$$anonfun$rowToRowRdd$1$$anonfun$apply$2.apply(ExistingRDD.scala:59)
>> at
>> org.apache.spark.sql.execution.RDDConversions$$anonfun$rowToRowRdd$1$$anonfun$apply$2.apply(ExistingRDD.scala:56)
>> at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
>> at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
>> at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
>> at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
>> at scala.collection.Iterator$$anon$10.next(Iterator.scala:312)
>> at scala.collection.Iterator$class.foreach(Iterator.scala:727)
>> at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
>> at
>> scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:48)
>> at
>> scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:103)
>> at
>> scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:47)
>> at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:273)
>> at scala.collection.AbstractIterator.to
>> <http://scala.collection.abstractiterator.to/>(Iterator.scala:1157)
>> at
>> scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:265)
>> at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1157)
>> at
>> scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:252)
>> at scala.collection.AbstractIterator.toArray(Iterator.scala:1157)
>> at
>> org.apache.spark.sql.execution.SparkPlan$$anonfun$5.apply(SparkPlan.scala:212)
>> at
>> org.apache.spark.sql.execution.SparkPlan$$anonfun$5.apply(SparkPlan.scala:212)
>> at
>> org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1858)
>> at
>> org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1858)
>> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
>> at org.apache.spark.scheduler.Task.run(Task.scala:89)
>> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:227)
>> at
>> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
>> at
>> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
>> at java.lang.Thread.run(Thread.java:745)
>> Driver stacktrace:
>> at org.apache.spark.scheduler.DAGScheduler.org
>> <http://org.apache.spark.scheduler.dagscheduler.org/>$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1431)
>> at
>> org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1419)
>> at
>> org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1418)
>> at
>> scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
>> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
>> at
>> org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1418)
>> at
>> org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:799)
>> at
>> org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:799)
>> at scala.Option.foreach(Option.scala:236)
>> at
>> org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:799)
>> at
>> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1640)
>> at
>> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1599)
>> at
>> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1588)
>> at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
>> at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:620)
>> at org.apache.spark.SparkContext.runJob(SparkContext.scala:1832)
>> at org.apache.spark.SparkContext.runJob(SparkContext.scala:1845)
>> at org.apache.spark.SparkContext.runJob(SparkContext.scala:1858)
>> at
>> org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:212)
>> at
>> org.apache.spark.sql.execution.Limit.executeCollect(basicOperators.scala:165)
>> at
>> org.apache.spark.sql.execution.SparkPlan.executeCollectPublic(SparkPlan.scala:174)
>> at
>> org.apache.spark.sql.DataFrame$$anonfun$org$apache$spark$sql$DataFrame$$execute$1$1.apply(DataFrame.scala:1499)
>> at
>> org.apache.spark.sql.DataFrame$$anonfun$org$apache$spark$sql$DataFrame$$execute$1$1.apply(DataFrame.scala:1499)
>> at
>> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:56)
>> at
>> org.apache.spark.sql.DataFrame.withNewExecutionId(DataFrame.scala:2086)
>> at org.apache.spark.sql.DataFrame.org
>> <http://org.apache.spark.sql.dataframe.org/>$apache$spark$sql$DataFrame$$execute$1(DataFrame.scala:1498)
>> at org.apache.spark.sql.DataFrame.org
>> <http://org.apache.spark.sql.dataframe.org/>$apache$spark$sql$DataFrame$$collect(DataFrame.scala:1505)
>> at
>> org.apache.spark.sql.DataFrame$$anonfun$head$1.apply(DataFrame.scala:1375)
>> at
>> org.apache.spark.sql.DataFrame$$anonfun$head$1.apply(DataFrame.scala:1374)
>> at org.apache.spark.sql.DataFrame.withCallback(DataFrame.scala:2099)
>> at org.apache.spark.sql.DataFrame.head(DataFrame.scala:1374)
>> at org.apache.spark.sql.DataFrame.take(DataFrame.scala:1456)
>> at org.apache.spark.sql.DataFrame.showString(DataFrame.scala:170)
>> at org.apache.spark.sql.DataFrame.show(DataFrame.scala:350)
>> at org.apache.spark.sql.DataFrame.show(DataFrame.scala:311)
>> at org.apache.spark.sql.DataFrame.show(DataFrame.scala:319)
>> at
>> $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:43)
>> at
>> $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:48)
>> at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:50)
>> at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:52)
>> at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:54)
>> at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:56)
>> at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:58)
>> at $iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:60)
>> at $iwC$$iwC$$iwC$$iwC.<init>(<console>:62)
>> at $iwC$$iwC$$iwC.<init>(<console>:64)
>> at $iwC$$iwC.<init>(<console>:66)
>> at $iwC.<init>(<console>:68)
>> at <init>(<console>:70)
>> at .<init>(<console>:74)
>> at .<clinit>(<console>)
>> at .<init>(<console>:7)
>> at .<clinit>(<console>)
>> at $print(<console>)
>> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
>> at
>> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
>> at
>> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
>> at java.lang.reflect.Method.invoke(Method.java:606)
>> at
>> org.apache.spark.repl.SparkIMain$ReadEvalPrint.call(SparkIMain.scala:1065)
>> at
>> org.apache.spark.repl.SparkIMain$Request.loadAndRun(SparkIMain.scala:1346)
>> at org.apache.spark.repl.SparkIMain.loadAndRunReq$1(SparkIMain.scala:840)
>> at org.apache.spark.repl.SparkIMain.interpret(SparkIMain.scala:871)
>> at org.apache.spark.repl.SparkIMain.interpret(SparkIMain.scala:819)
>> at
>> org.apache.zeppelin.spark.SparkInterpreter.interpretInput(SparkInterpreter.java:709)
>> at
>> org.apache.zeppelin.spark.SparkInterpreter.interpret(SparkInterpreter.java:674)
>> at
>> org.apache.zeppelin.spark.SparkInterpreter.interpret(SparkInterpreter.java:667)
>> at
>> org.apache.zeppelin.interpreter.ClassloaderInterpreter.interpret(ClassloaderInterpreter.java:57)
>> at
>> org.apache.zeppelin.interpreter.LazyOpenInterpreter.interpret(LazyOpenInterpreter.java:93)
>> at
>> org.apache.zeppelin.interpreter.remote.RemoteInterpreterServer$InterpretJob.jobRun(RemoteInterpreterServer.java:300)
>> at org.apache.zeppelin.scheduler.Job.run(Job.java:169)
>> at org.apache.zeppelin.scheduler.FIFOScheduler$1.run(FIFOScheduler.java:134)
>> at
>> java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:471)
>> at java.util.concurrent.FutureTask.run(FutureTask.java:262)
>> at
>> java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.access$201(ScheduledThreadPoolExecutor.java:178)
>> at
>> java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.run(ScheduledThreadPoolExecutor.java:292)
>> at
>> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
>> at
>> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
>> at java.lang.Thread.run(Thread.java:745)
>> Caused by: java.lang.ArrayIndexOutOfBoundsException: 1
>> at
>> org.apache.spark.sql.catalyst.CatalystTypeConverters$StructConverter.toCatalystImpl(CatalystTypeConverters.scala:260)
>> at
>> org.apache.spark.sql.catalyst.CatalystTypeConverters$StructConverter.toCatalystImpl(CatalystTypeConverters.scala:250)
>> at
>> org.apache.spark.sql.catalyst.CatalystTypeConverters$CatalystTypeConverter.toCatalyst(CatalystTypeConverters.scala:102)
>> at
>> org.apache.spark.sql.catalyst.CatalystTypeConverters$$anonfun$createToCatalystConverter$2.apply(CatalystTypeConverters.scala:401)
>> at
>> org.apache.spark.sql.execution.RDDConversions$$anonfun$rowToRowRdd$1$$anonfun$apply$2.apply(ExistingRDD.scala:59)
>> at
>> org.apache.spark.sql.execution.RDDConversions$$anonfun$rowToRowRdd$1$$anonfun$apply$2.apply(ExistingRDD.scala:56)
>> at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
>> at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
>> at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
>> at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
>> at scala.collection.Iterator$$anon$10.next(Iterator.scala:312)
>> at scala.collection.Iterator$class.foreach(Iterator.scala:727)
>> at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
>> at
>> scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:48)
>> at
>> scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:103)
>> at
>> scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:47)
>> at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:273)
>> at scala.collection.AbstractIterator.to
>> <http://scala.collection.abstractiterator.to/>(Iterator.scala:1157)
>> at
>> scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:265)
>> at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1157)
>> at
>> scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:252)
>> at scala.collection.AbstractIterator.toArray(Iterator.scala:1157)
>> at
>> org.apache.spark.sql.execution.SparkPlan$$anonfun$5.apply(SparkPlan.scala:212)
>> at
>> org.apache.spark.sql.execution.SparkPlan$$anonfun$5.apply(SparkPlan.scala:212)
>> at
>> org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1858)
>> at
>> org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1858)
>> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
>>
>>
>>
>>
>>
>> --
>> Taejun Kim
>>
>> Data Mining Lab.
>> School of Electrical and Computer Engineering
>> University of Seoul
>>
>>
>>
>
