Spark throws Exception when constructing Dataframe - scala

I could construct the HbaseRdd from the Hbase table.After this,I am trying to convert it to a Scala case class DF.But getting Exception when converting from Bytes.toInt. Appricate the help from the experts
Scala case class:
case class UserProfile(User_Id: String, Card_Account_Number: Long, First_name: String, Last_name: String, email: String, gender: String, ip_address: String, user_name: String, address: String,phone:String,No_Transactions_in_24_hrs:Int,No_IPs_In_24_hrs:Int,TotalAmount_spent_in_24_hrs:Float,AvgAmount_spent_in_24_hrs:Float,Total_No_Transactions:Int,Amount_spent_so_far:Float)
// function to parse input
object UserProfile extends Serializable{
def parseUserProfile(result: Result): UserProfile = {
val p0=Bytes.toString(result.getValue(User_PersonalProfileBytes, Bytes.toBytes("User_Id")))
val p1 =Bytes.toLong(result.getValue(User_PersonalProfileBytes, Bytes.toBytes("Card_Account_Number")))
val p2=Bytes.toString(result.getValue(User_PersonalProfileBytes, Bytes.toBytes("First_name")))
val p3=Bytes.toString(result.getValue(User_PersonalProfileBytes, Bytes.toBytes("Last_name")))
val p4=Bytes.toString(result.getValue(User_PersonalProfileBytes, Bytes.toBytes("email")))
val p5=Bytes.toString(result.getValue(User_PersonalProfileBytes, Bytes.toBytes("gender")))
val p6=Bytes.toString(result.getValue(User_PersonalProfileBytes, Bytes.toBytes("ip_address")))
val p7=Bytes.toString(result.getValue(User_PersonalProfileBytes, Bytes.toBytes("user_name")))
val p8=Bytes.toString(result.getValue(User_PersonalProfileBytes, Bytes.toBytes("address")))
val p9=Bytes.toString(result.getValue(User_PersonalProfileBytes, Bytes.toBytes("phone")))
val p10=Bytes.toInt(result.getValue(User_TransactionHistoryBytes, Bytes.toBytes("No_Transactions_in_24_hrs")))
val p11=Bytes.toInt(result.getValue(User_TransactionHistoryBytes, Bytes.toBytes("No_Ips_In_24_hrs")))
val p12=Bytes.toFloat(result.getValue(User_TransactionHistoryBytes, Bytes.toBytes("TotalAmount_spent_in_24_hrs")))
val p13=Bytes.toFloat(result.getValue(User_TransactionHistoryBytes, Bytes.toBytes("AvgAmount_spent_in_24_hrs")))
val p14=Bytes.toInt(result.getValue(User_TransactionHistoryBytes, Bytes.toBytes("Total_No_Transactions")))
val p15=Bytes.toFloat(result.getValue(User_TransactionHistoryBytes, Bytes.toBytes("Amount_spent_so_far")))
UserProfile(p0, p1, p2, p3, p4, p5, p6,p7,p8,p9,p10,p11,p12,p13,p14,p15)
}}
**Spark-Hbase code :**
val sc = new SparkContext(sparkConf)
val sqlContext = new org.apache.spark.sql.SQLContext(sc)
import sqlContext.implicits._
val sparkConf1 = HBaseConfiguration.create()
val tableName = "UserProfile"
sparkConf1.set(TableInputFormat.INPUT_TABLE, tableName)
sparkConf1.set("hbase.zookeeper.property.clientPort","2182");
sparkConf1.set(TableInputFormat.SCAN_COLUMNS,
"User_PersonalProfile","User_TransactionHistory");
val hBaseRDD = sc.newAPIHadoopRDD(sparkConf1, classOf[TableInputFormat],
classOf[org.apache.hadoop.hbase.io.ImmutableBytesWritable],
classOf[org.apache.hadoop.hbase.client.Result])
println("Number of Records found : " + hBaseRDD.count())
val count = hBaseRDD.count
val resultRDD = hBaseRDD.map(tuple => tuple._2)
println(resultRDD)
val profileRdd=resultRDD.map(UserProfile.parseUserProfile)
val userProfileDF = profileRdd.toDF()
userProfileDF.printSchema()
userProfileDF.show()
userProfileDF.registerTempTable("UserProfileRow")
sc.stop()
Exception thrown:
Exception in thread "main" org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 2.0 failed 1 times, most recent failure: Lost task 0.0 in stage 2.0 (TID 2, localhost): java.lang.NullPointerException
at org.apache.hadoop.hbase.util.Bytes.toInt(Bytes.java:801)
at org.apache.hadoop.hbase.util.Bytes.toInt(Bytes.java:778)
at com.research.spark.PaymentProcessor$UserProfile$.parseUserProfile(PaymentProcessor.scala:75)
at com.research.spark.PaymentProcessor$$anonfun$5.apply(PaymentProcessor.scala:193)
at com.research.spark.PaymentProcessor$$anonfun$5.apply(PaymentProcessor.scala:193)
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$class.to(TraversableOnce.scala:273)
at scala.collection.AbstractIterator.to(Iterator.scala:1157)
at scala.collection.TraversableOnce$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:214)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$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$apache$spark$sql$DataFrame$$execute$1(DataFrame.scala:1498)
at org.apache.spark.sql.DataFrame.org$apache$spark$sql$DataFrame$$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$1.apply(DataFrame.scala:1374)
at org.apache.spark.sql.DataFrame.withCallback(DataFrame.scala:2099)
at org.apache.spark.sql.DataFrame.head(DataFrame.scala:1374)
at org.apache.spark.sql.DataFrame.take(DataFrame.scala:1456)
at org.apache.spark.sql.DataFrame.showString(DataFrame.scala:170)
at org.apache.spark.sql.DataFrame.show(DataFrame.scala:350)
at org.apache.spark.sql.DataFrame.show(DataFrame.scala:311)
at org.apache.spark.sql.DataFrame.show(DataFrame.scala:319)
at com.research.spark.PaymentProcessor$.main(PaymentProcessor.scala:197)
at com.research.spark.PaymentProcessor.main(PaymentProcessor.scala)
Caused by: java.lang.NullPointerException
at org.apache.hadoop.hbase.util.Bytes.toInt(Bytes.java:801)
at org.apache.hadoop.hbase.util.Bytes.toInt(Bytes.java:778)
at com.research.spark.PaymentProcessor$UserProfile$.parseUserProfile(PaymentProcessor.scala:75)
at com.research.spark.PaymentProcessor$$anonfun$5.apply(PaymentProcessor.scala:193)
at com.research.spark.PaymentProcessor$$anonfun$5.apply(PaymentProcessor.scala:193)
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$class.to(TraversableOnce.scala:273)
at scala.collection.AbstractIterator.to(Iterator.scala:1157)
at scala.collection.TraversableOnce$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:214)
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)

Related

java.lang.NumberFormatException error in spark scala

i am new to spark and machine learning, so to practice i was trying to write a k-means algorithm in spark 1.6.0 using a dataset.
i was doing as specified in example on apache spark website.
while doing so i got this error :
java.lang.NumberFormatException: For input string: "2014-03-15:10:10:20,Sorrento,8cc3b47e-bd01-4482-b500-28f2342679af,33.6894754264,-1
17.543308253"
my code in which i got this error:
scala> val rdd = sc.textFile("/user/rohitchopra32_gmail/Project2_Dataset")
rdd: org.apache.spark.rdd.RDD[String] = MapPartitionsRDD[1] at textFile at <console>:28
scala> rdd.count()
res0: Long = 459540
scala> val parsedData = rdd.map(s => Vectors.dense(s.split(' ').map(_.toDouble))).cache()
parsedData: org.apache.spark.rdd.RDD[org.apache.spark.mllib.linalg.Vector] = MapPartitionsRDD[2] at map at <console>:30
scala> parsedData.count()
17/08/21 16:22:50 ERROR TaskSetManager: Task 0 in stage 2.0 failed 4 times; aborting job
org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 2.0 failed 4 times, most recent failure: Lost task 0.3 in stage 2.0 (TID 10, ip-
172-31-58-214.ec2.internal): java.lang.NumberFormatException: For input string: "2014-03-15:10:10:20,Sorrento,8cc3b47e-bd01-4482-b500-28f2342679af,33.6894754264,-1
17.543308253"
full traceback:
scala> parsedData.count()
17/08/21 16:22:50 ERROR TaskSetManager: Task 0 in stage 2.0 failed 4 times; aborting job
org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 2.0 failed 4 times, most recent failure: Lost task 0.3 in stage 2.0 (TID 10, ip-
172-31-58-214.ec2.internal): java.lang.NumberFormatException: For input string: "2014-03-15:10:10:20,Sorrento,8cc3b47e-bd01-4482-b500-28f2342679af,33.6894754264,-1
17.543308253"
at sun.misc.FloatingDecimal.readJavaFormatString(FloatingDecimal.java:2043)
at sun.misc.FloatingDecimal.parseDouble(FloatingDecimal.java:110)
at java.lang.Double.parseDouble(Double.java:538)
at scala.collection.immutable.StringLike$class.toDouble(StringLike.scala:232)
at scala.collection.immutable.StringOps.toDouble(StringOps.scala:31)
at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$anonfun$1$$anonfun$apply$1.apply(<console>:30)
at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$anonfun$1$$anonfun$apply$1.apply(<console>:30)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
at scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:108)
at scala.collection.TraversableLike$class.map(TraversableLike.scala:244)
at scala.collection.mutable.ArrayOps$ofRef.map(ArrayOps.scala:108)
at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$anonfun$1.apply(<console>:30)
at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$anonfun$1.apply(<console>:30)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
at org.apache.spark.storage.MemoryStore.unrollSafely(MemoryStore.scala:283)
at org.apache.spark.CacheManager.putInBlockManager(CacheManager.scala:171)
at org.apache.spark.CacheManager.getOrCompute(CacheManager.scala:78)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:268)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
at org.apache.spark.scheduler.Task.run(Task.scala:89)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$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$$anon$1.run(EventLoop.scala:48)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:620)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1832)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1845)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1858)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1929)
at org.apache.spark.rdd.RDD.count(RDD.scala:1143)
at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:33)
at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:38)
at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:40)
at $iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:42)
at $iwC$$iwC$$iwC$$iwC.<init>(<console>:44)
at $iwC$$iwC$$iwC.<init>(<console>:46)
at $iwC$$iwC.<init>(<console>:48)
at $iwC.<init>(<console>:50)
at <init>(<console>:52)
at .<init>(<console>:56)
at .<clinit>(<console>)
at .<init>(<console>:7)
at .<clinit>(<console>)
at $print(<console>)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:497)
at org.apache.spark.repl.SparkIMain$ReadEvalPrint.call(SparkIMain.scala:1065)
at org.apache.spark.repl.SparkIMain$Request.loadAndRun(SparkIMain.scala:1346)
at org.apache.spark.repl.SparkIMain.loadAndRunReq$1(SparkIMain.scala:840)
at org.apache.spark.repl.SparkIMain.interpret(SparkIMain.scala:871)
at org.apache.spark.repl.SparkIMain.interpret(SparkIMain.scala:819)
at org.apache.spark.repl.SparkILoop.reallyInterpret$1(SparkILoop.scala:857)
at org.apache.spark.repl.SparkILoop.interpretStartingWith(SparkILoop.scala:902)
at org.apache.spark.repl.SparkILoop.command(SparkILoop.scala:814)
at org.apache.spark.repl.SparkILoop.processLine$1(SparkILoop.scala:657)
at org.apache.spark.repl.SparkILoop.innerLoop$1(SparkILoop.scala:665)
at org.apache.spark.repl.SparkILoop.org$apache$spark$repl$SparkILoop$$loop(SparkILoop.scala:670)
at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply$mcZ$sp(SparkILoop.scala:997)
at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply(SparkILoop.scala:945)
at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply(SparkILoop.scala:945)
at scala.tools.nsc.util.ScalaClassLoader$.savingContextLoader(ScalaClassLoader.scala:135)
at org.apache.spark.repl.SparkILoop.org$apache$spark$repl$SparkILoop$$process(SparkILoop.scala:945)
at org.apache.spark.repl.SparkILoop.process(SparkILoop.scala:1059)
at org.apache.spark.repl.Main$.main(Main.scala:31)
at org.apache.spark.repl.Main.main(Main.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:497)
at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:731)
at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:181)
at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:206)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:121)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
Caused by: java.lang.NumberFormatException: For input string: "2014-03-15:10:10:20,Sorrento,8cc3b47e-bd01-4482-b500-28f2342679af,33.6894754264,-117.543308253"
at sun.misc.FloatingDecimal.readJavaFormatString(FloatingDecimal.java:2043)
at sun.misc.FloatingDecimal.parseDouble(FloatingDecimal.java:110)
at java.lang.Double.parseDouble(Double.java:538)
at scala.collection.immutable.StringLike$class.toDouble(StringLike.scala:232)
at scala.collection.immutable.StringOps.toDouble(StringOps.scala:31)
at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$anonfun$1$$anonfun$apply$1.apply(<console>:30)
at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$anonfun$1$$anonfun$apply$1.apply(<console>:30)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
at scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:108)
at scala.collection.TraversableLike$class.map(TraversableLike.scala:244)
at scala.collection.mutable.ArrayOps$ofRef.map(ArrayOps.scala:108)
at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$anonfun$1.apply(<console>:30)
at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$anonfun$1.apply(<console>:30)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
at org.apache.spark.storage.MemoryStore.unrollSafely(MemoryStore.scala:283)
at org.apache.spark.CacheManager.putInBlockManager(CacheManager.scala:171)
at org.apache.spark.CacheManager.getOrCompute(CacheManager.scala:78)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:268)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
at org.apache.spark.scheduler.Task.run(Task.scala:89)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213)
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)
here is the link for data set: dataset
help me guys fix this error.
thanks in advance.
Referring to your input data
2014-03-15:10:10:20,Sorrento,8cc3b47e-bd01-4482-b500-28f2342679af,33.6894754264,-1 17.543308253
You are trying to get the double value (17.543308253), convert it to double and use it for Vectors.dense for machine learning.
If thats the case then you should be doing
val parsedData = rdd.map(s => Vectors.dense(s.split(' ')(1).toDouble)).cache()
If you do Vectors.dense(s.split(' ').map(_.toDouble)), you are trying to convert the 2014-03-15:10:10:20,Sorrento,8cc3b47e-bd01-4482-500-28f2342679af,33.6894754264,-1 of your data to double too, which would give you NumberFormatException
I hope the answer is helpful

scala user define function not working in sparksql

I have written a UDF which basically computes whether given IP address is in cidr list. i am able to call my UDF from scala and it works fine but when I call udf from spark sql it was throwing this error. please help me.
%spark
def isinlist = (ip:String) => {
import org.apache.commons.net.util.SubnetUtils
def checkipinrange = (cidr:String,ip:String) => {
val utils = new SubnetUtils(cidr);
val isInRange = utils.getInfo().isInRange(ip);
if (isInRange) {
true
} else {
false
}
}
sqlContext.udf.register("checkipinrange",checkipinrange)
val query=s"""select *
from tag_ip
where checkipinrange(tag_ip.cidr, '$ip') """
val validrange = sqlContext.sql(query)
if(validrange.count > 0) {
true
} else {
false
}
}
isinlist("5.9.29.73")
sqlContext.udf.register("isinlist",isinlist)
tag_ip is a list of cidr ip ranges . Here isinlist function works fine. But when i call isinlist function from spark sql it shows error below.
java.lang.NullPointerException
at $line926276415525.$read$$iwC$$iwC$$iwC$$iwC$$iwC$$$$3baf9f919752f0ab1f5a31ad94af9f4$$$$$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$anonfun$isinlist$1.apply(<console>:198)
at $line926276415525.$read$$iwC$$iwC$$iwC$$iwC$$iwC$$$$3baf9f919752f0ab1f5a31ad94af9f4$$$$$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$anonfun$isinlist$1.apply(<console>:184)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificUnsafeProjection.apply(Unknown Source)
at org.apache.spark.sql.execution.Project$$anonfun$1$$anonfun$apply$1.apply(basicOperators.scala:51)
at org.apache.spark.sql.execution.Project$$anonfun$1$$anonfun$apply$1.apply(basicOperators.scala:49)
at scala.collection.Iterator$$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$$anon$10.next(Iterator.scala:312)
at scala.collection.Iterator$class.foreach(Iterator.scala:727)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:48)
at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:103)
at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:47)
at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:273)
at scala.collection.AbstractIterator.to(Iterator.scala:1157)
at scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:265)
at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1157)
at scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:252)
at scala.collection.AbstractIterator.toArray(Iterator.scala:1157)
at org.apache.spark.sql.execution.SparkPlan$$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)
can someone help me what is the issue?
You should check for null values. For example:
val isInRange = ip != null && utils.getInfo().isInRange(ip);

Inserting Dataframe Data into RDD

I currently have a dataframe containing the results of the SQL query. The dataframe has columns patientID, date, and code.
val res1 = sqlContext.sql("select encounter.Member_ID AS patientID, encounter.Encounter_DateTime AS date, diag.code from encounter join diag on encounter.Encounter_ID = diag.Encounter_ID")
I am attempting to take this dataframe and place it into an RDD of the format RDD[Diagnostic] where Diagnostic is a case class of the form:
case class Diagnostic(patientID:String, date: Date, code: String)
Is this possible? My current attempt is throwing back a scala.MatchError coming from the below line.
val diagnostic: RDD[Diagnostic] = res1.map {
case Row(patientID:String, date:java.util.Date, code:String) => Diagnostic(patientID=patientID, date=date, code=code)
}
Schema:
root
|-- patientID: string (nullable = true)
|-- date: string (nullable = true)
|-- code: string (nullable = true)
Error message from res1.as[Diagnostic]:
Main.scala:170: overloaded method value as with alternatives:
[error] (alias: Symbol)org.apache.spark.sql.DataFrame <and>
[error] (alias: String)org.apache.spark.sql.DataFrame
[error] does not take type parameters
[error] val testlol: RDD[Diagnostic] = res1.as[Diagnostic]
[error] ^
[error] one error found
[error] (compile:compileIncremental) Compilation failed
[error] Total time: 3 s, completed Oct 9, 2016 3:16:38 PM
Entire error message:
[Stage 4:=======================================> (2 +
1) / 3]16/10/09 14:23:32 ERROR Executor: Exception in task 0.0 in stage 6.0 (TID 8)
scala.MatchError: [000961291-01,2005-06-21T19:45:00Z,584.9] (of class org.apache.spark.sql.catalyst.expressions.GenericRowWithSchema)
at edu.gatech.cse8803.main.Main$$anonfun$11.apply(Main.scala:168)
at edu.gatech.cse8803.main.Main$$anonfun$11.apply(Main.scala:168)
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$class.to(TraversableOnce.scala:273)
at scala.collection.AbstractIterator.to(Iterator.scala:1157)
at scala.collection.TraversableOnce$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.rdd.RDD$$anonfun$33.apply(RDD.scala:1177)
at org.apache.spark.rdd.RDD$$anonfun$33.apply(RDD.scala:1177)
at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1498)
at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1498)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:61)
at org.apache.spark.scheduler.Task.run(Task.scala:64)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:203)
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)
16/10/09 14:23:32 WARN TaskSetManager: Lost task 0.0 in stage 6.0 (TID 8, localhost): scala.MatchError: [000961291-01,2005-06-21T19:45:00Z,584.9] (of class org.apache.spark.sql.catalyst.expressions.GenericRowWithSchema)
at edu.gatech.cse8803.main.Main$$anonfun$11.apply(Main.scala:168)
at edu.gatech.cse8803.main.Main$$anonfun$11.apply(Main.scala:168)
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$class.to(TraversableOnce.scala:273)
at scala.collection.AbstractIterator.to(Iterator.scala:1157)
at scala.collection.TraversableOnce$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.rdd.RDD$$anonfun$33.apply(RDD.scala:1177)
at org.apache.spark.rdd.RDD$$anonfun$33.apply(RDD.scala:1177)
at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1498)
at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1498)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:61)
at org.apache.spark.scheduler.Task.run(Task.scala:64)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:203)
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)
16/10/09 14:23:32 ERROR TaskSetManager: Task 0 in stage 6.0 failed 1 times; aborting job
[error] (run-main-0) org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 6.0 failed 1 times, most recent failure: Lost task 0.0 in stage 6.0 (TID 8, localhost): scala.MatchError: [000961291-01,2005-06-21T19:45:00Z,584.9] (of class org.apache.spark.sql.catalyst.expressions.GenericRowWithSchema)
[error] at edu.gatech.cse8803.main.Main$$anonfun$11.apply(Main.scala:168)
[error] at edu.gatech.cse8803.main.Main$$anonfun$11.apply(Main.scala:168)
[error] at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
[error] at scala.collection.Iterator$$anon$10.next(Iterator.scala:312)
[error] at scala.collection.Iterator$class.foreach(Iterator.scala:727)
[error] at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
[error] at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:48)
[error] at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:103)
[error] at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:47)
[error] at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:273)
[error] at scala.collection.AbstractIterator.to(Iterator.scala:1157)
[error] at scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:265)
[error] at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1157)
[error] at scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:252)
[error] at scala.collection.AbstractIterator.toArray(Iterator.scala:1157)
[error] at org.apache.spark.rdd.RDD$$anonfun$33.apply(RDD.scala:1177)
[error] at org.apache.spark.rdd.RDD$$anonfun$33.apply(RDD.scala:1177)
[error] at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1498)
[error] at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1498)
[error] at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:61)
[error] at org.apache.spark.scheduler.Task.run(Task.scala:64)
[error] at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:203)
[error] at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
[error] at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
[error] at java.lang.Thread.run(Thread.java:745)
[error]
[error] Driver stacktrace:
org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 6.0 failed 1 times, most recent failure: Lost task 0.0 in stage 6.0 (TID 8, localhost): scala.MatchError: [000961291-01,2005-06-21T19:45:00Z,584.9] (of class org.apache.spark.sql.catalyst.expressions.GenericRowWithSchema)
at edu.gatech.cse8803.main.Main$$anonfun$11.apply(Main.scala:168)
at edu.gatech.cse8803.main.Main$$anonfun$11.apply(Main.scala:168)
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$class.to(TraversableOnce.scala:273)
at scala.collection.AbstractIterator.to(Iterator.scala:1157)
at scala.collection.TraversableOnce$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.rdd.RDD$$anonfun$33.apply(RDD.scala:1177)
at org.apache.spark.rdd.RDD$$anonfun$33.apply(RDD.scala:1177)
at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1498)
at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1498)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:61)
at org.apache.spark.scheduler.Task.run(Task.scala:64)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:203)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:745)
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1204)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1193)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1192)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1192)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:693)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:693)
at scala.Option.foreach(Option.scala:236)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:693)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1393)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1354)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
[trace] Stack trace suppressed: run last compile:run for the full output.
16/10/09 14:23:32 ERROR ContextCleaner: Error in cleaning thread
java.lang.InterruptedException
at java.lang.Object.wait(Native Method)
at java.lang.ref.ReferenceQueue.remove(ReferenceQueue.java:135)
at org.apache.spark.ContextCleaner$$anonfun$org$apache$spark$ContextCleaner$$keepCleaning$1.apply$mcV$sp(ContextCleaner.scala:146)
at org.apache.spark.ContextCleaner$$anonfun$org$apache$spark$ContextCleaner$$keepCleaning$1.apply(ContextCleaner.scala:144)
at org.apache.spark.ContextCleaner$$anonfun$org$apache$spark$ContextCleaner$$keepCleaning$1.apply(ContextCleaner.scala:144)
at org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1618)
at org.apache.spark.ContextCleaner.org$apache$spark$ContextCleaner$$keepCleaning(ContextCleaner.scala:143)
at org.apache.spark.ContextCleaner$$anon$3.run(ContextCleaner.scala:65)
16/10/09 14:23:32 ERROR Utils: Uncaught exception in thread SparkListenerBus
java.lang.InterruptedException
at java.util.concurrent.locks.AbstractQueuedSynchronizer.doAcquireSharedInterruptibly(AbstractQueuedSynchronizer.java:996)
at java.util.concurrent.locks.AbstractQueuedSynchronizer.acquireSharedInterruptibly(AbstractQueuedSynchronizer.java:1303)
at java.util.concurrent.Semaphore.acquire(Semaphore.java:317)
at org.apache.spark.util.AsynchronousListenerBus$$anon$1$$anonfun$run$1.apply$mcV$sp(AsynchronousListenerBus.scala:62)
at org.apache.spark.util.AsynchronousListenerBus$$anon$1$$anonfun$run$1.apply(AsynchronousListenerBus.scala:61)
at org.apache.spark.util.AsynchronousListenerBus$$anon$1$$anonfun$run$1.apply(AsynchronousListenerBus.scala:61)
at org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1618)
at org.apache.spark.util.AsynchronousListenerBus$$anon$1.run(AsynchronousListenerBus.scala:60)
java.lang.RuntimeException: Nonzero exit code: 1
at scala.sys.package$.error(package.scala:27)
[trace] Stack trace suppressed: run last compile:run for the full output.
[error] (compile:run) Nonzero exit code: 1
[error] Total time: 13 s, completed Oct 9, 2016 2:23:32 PM
java.util.Date is not data type that can be stored in a DataFrame. From the looks of it date is a Timestamp String. If I am right case class should be defined as:
case class Diagnostic(patientID: String, date: java.sql.Timestamp, code: String)
you should replace pattern:
case Row(patientID: String, date: java.util.Date, code: String)
with:
case Row(patientID: String, date: java.sql.Timestamp, code: String)
and cast date to timestamp:
res1.select($"patientID", $"date".cast("timestamp"), $"code")
Finally you should use rdd method before mapping for the forward compatibility:
res1.select($"patientID", $"date".cast("timestamp"), $"code").rdd.map {
...
}
In general I would recommend using as method:
res1.as[Diagnostic].rdd

SPARK-5063 RDD transformations and actions can only be invoked by the driver

I have a RDD[Row] which I am trying to see:
val pairMap = itemMapping.map(x=> {
val countryInfo = MappingUtils.getCountryInfo(x);
(countryInfo.getId(), countryInfo)
})
pairMap: org.apache.spark.rdd.RDD[(String, com.model.item.CountryInfo)] = MapPartitionsRDD[8]
val itemList = df.filter(not($"newItemType" === "Unknown Type")).map(row => {
val customerId = row.getAs[String](0);
val itemId = row.getAs[String](1);
val itemType = row.getAs[String](4);
val priceType = if (StringUtils.isNotBlank(pairMap.lookup(itemType).head.getpriceType)) pairMap.lookup(itemType).head.getpriceType else "unknown"
val kidsAdults = if (pairMap.lookup(itemType).head.getItems.size() > 0) "Kids" else "Adults"
val tvMovie = if (pairMap.lookup(itemType).head.getbarCode != barCode) "TV" else "Movie"
Row(customerId ,itemId,itemType,priceType,kidsAdults,tvMovie)
})
When I did :
itemList.first()
But keep getting this error :
org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 10.0 failed 4 times, most recent failure: Lost task 0.3 in stage 10.0 (TID 34, ip-172-31-0-28.ec2.internal): org.apache.spark.SparkException: RDD transformations and actions can only be invoked by the driver, not inside of other transformations; for example, rdd1.map(x => rdd2.values.count() * x) is invalid because the values transformation and count action cannot be performed inside of the rdd1.map transformation. For more information, see SPARK-5063.
at org.apache.spark.rdd.RDD.org$apache$spark$rdd$RDD$$sc(RDD.scala:87)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:316)
at org.apache.spark.rdd.PairRDDFunctions.lookup(PairRDDFunctions.scala:928)
at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$anonfun$1.apply(<console>:89)
at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$anonfun$1.apply(<console>:83)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
at scala.collection.Iterator$$anon$10.next(Iterator.scala:312)
at scala.collection.Iterator$class.foreach(Iterator.scala:727)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:48)
at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:103)
at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:47)
at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:273)
at scala.collection.AbstractIterator.to(Iterator.scala:1157)
at scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:265)
at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1157)
at scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:252)
at scala.collection.AbstractIterator.toArray(Iterator.scala:1157)
at org.apache.spark.rdd.RDD$$anonfun$take$1$$anonfun$28.apply(RDD.scala:1314)
at org.apache.spark.rdd.RDD$$anonfun$take$1$$anonfun$28.apply(RDD.scala:1314)
at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1858)
at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1858)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
at org.apache.spark.scheduler.Task.run(Task.scala:89)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$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$$anon$1.run(EventLoop.scala:48)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:620)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1832)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1845)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1858)
at org.apache.spark.rdd.RDD$$anonfun$take$1.apply(RDD.scala:1314)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:150)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:111)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:316)
at org.apache.spark.rdd.RDD.take(RDD.scala:1288)
at org.apache.spark.rdd.RDD$$anonfun$first$1.apply(RDD.scala:1328)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:150)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:111)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:316)
at org.apache.spark.rdd.RDD.first(RDD.scala:1327)
at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:86)
at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:91)
at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:93)
at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:95)
at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:97)
at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:99)
at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:101)
at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:103)
at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:105)
at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:107)
at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:109)
at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:111)
at $iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:113)
at $iwC$$iwC$$iwC$$iwC.<init>(<console>:115)
at $iwC$$iwC$$iwC.<init>(<console>:117)
at $iwC$$iwC.<init>(<console>:119)
at $iwC.<init>(<console>:121)
at <init>(<console>:123)
at .<init>(<console>:127)
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:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:483)
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:664)
at org.apache.zeppelin.spark.SparkInterpreter.interpret(SparkInterpreter.java:629)
at org.apache.zeppelin.spark.SparkInterpreter.interpret(SparkInterpreter.java:622)
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:276)
at org.apache.zeppelin.scheduler.Job.run(Job.java:170)
at org.apache.zeppelin.scheduler.FIFOScheduler$1.run(FIFOScheduler.java:118)
at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
at java.util.concurrent.FutureTask.run(FutureTask.java:266)
at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.access$201(ScheduledThreadPoolExecutor.java:180)
at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.run(ScheduledThreadPoolExecutor.java:293)
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)
Caused by: org.apache.spark.SparkException: RDD transformations and actions can only be invoked by the driver, not inside of other transformations; for example, rdd1.map(x => rdd2.values.count() * x) is invalid because the values transformation and count action cannot be performed inside of the rdd1.map transformation. For more information, see SPARK-5063.
at org.apache.spark.rdd.RDD.org$apache$spark$rdd$RDD$$sc(RDD.scala:87)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:316)
at org.apache.spark.rdd.PairRDDFunctions.lookup(PairRDDFunctions.scala:928)
at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$anonfun$1.apply(<console>:89)
at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$anonfun$1.apply(<console>:83)
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$class.to(TraversableOnce.scala:273)
at scala.collection.AbstractIterator.to(Iterator.scala:1157)
at scala.collection.TraversableOnce$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.rdd.RDD$$anonfun$take$1$$anonfun$28.apply(RDD.scala:1314)
at org.apache.spark.rdd.RDD$$anonfun$take$1$$anonfun$28.apply(RDD.scala:1314)
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:213)
... 3 more
I also tried :
val tvMovieUDF = udf {( itemType: String) => if (StringUtils.isNotBlank(pairMap.lookup(itemType).head.getpriceType)) pairMap.lookup(itemType).head.getpriceType else "unknown" }
val priceUDF = udf {( itemType: String) => if (pairMap.lookup(itemType).head.getItems.size() > 0) "Kids" else "Adults" }
val kidsUDF = udf {( itemType: String) => if (pairMap.lookup(itemType).head.getbarCode != barCode) "TV" else "Movie" }
val broDF = df.filter(not($"newItemType" === "Unknown Type")).withColumn("tvMovie",tvMovieUDF($"newItemType")).withColumn("priceType",priceUDF($"newItemType")).withColumn("kids",kidsUDF($"newItemType"))
But still same error. Can someone tell me how do I resolve it ? I want to see the data also want to save it as gzipped file :
val json = itemList.toJSON
json.saveAsTextFile("s3://...", classOf[GzipCodec])
Well, you cannot access another RDD from a transformation. That is not allowed. I think what you are trying to achieve is to send out pairMap to the function, so that the lookup can be done. If yes, then you can use a broadcast.
b = sc.broadcast(pairMap.collect())
And, instead of pairMap.lookup, you can use b.value.lookup

custom partitioner in apache spark

I am following an example from the book Learning Spark: Lightning-Fast Big Data Analysis:
// custom partitioner
class DomainNamePartitioner(numParts: Int) extends Partitioner {
override def numPartitions: Int = numParts
override def getPartition(key: Any): Int = {
val domain = new URI(key.toString).getHost
val code = (domain.hashCode % numPartitions)
if(code < 0) {
code + numPartitions
} else {
code
}
}
override def equals(other: Any): Boolean = other match {
case dnp: DomainNamePartitioner => dnp.numPartitions == numPartitions
case _ => false
}
}
The project is here: https://github.com/kindlychung/learnSpark
I got the following error when running the main function:
16/02/02 21:25:04 ERROR Executor: Exception in task 1.0 in stage 49.0 (TID 193)
java.lang.NullPointerException
at DomainNamePartitioner.getPartition(HasRun.scala:20)
at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:151)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:73)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
at org.apache.spark.scheduler.Task.run(Task.scala:89)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
16/02/02 21:25:04 ERROR Executor: Exception in task 3.0 in stage 49.0 (TID 195)
java.lang.NullPointerException
at DomainNamePartitioner.getPartition(HasRun.scala:20)
at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:151)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:73)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
at org.apache.spark.scheduler.Task.run(Task.scala:89)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
16/02/02 21:25:04 ERROR Executor: Exception in task 0.0 in stage 49.0 (TID 192)
java.lang.NullPointerException
at DomainNamePartitioner.getPartition(HasRun.scala:20)
at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:151)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:73)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
at org.apache.spark.scheduler.Task.run(Task.scala:89)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
16/02/02 21:25:04 ERROR Executor: Exception in task 2.0 in stage 49.0 (TID 194)
java.lang.NullPointerException
at DomainNamePartitioner.getPartition(HasRun.scala:20)
at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:151)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:73)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
at org.apache.spark.scheduler.Task.run(Task.scala:89)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
16/02/02 21:25:04 WARN TaskSetManager: Lost task 0.0 in stage 49.0 (TID 192, localhost): java.lang.NullPointerException
at DomainNamePartitioner.getPartition(HasRun.scala:20)
at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:151)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:73)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
at org.apache.spark.scheduler.Task.run(Task.scala:89)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
16/02/02 21:25:04 ERROR TaskSetManager: Task 0 in stage 49.0 failed 1 times; aborting job
Exception in thread "main" org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 49.0 failed 1 times, most recent failure: Lost task 0.0 in stage 49.0 (TID 192, localhost): java.lang.NullPointerException
at DomainNamePartitioner.getPartition(HasRun.scala:20)
at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:151)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:73)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
at org.apache.spark.scheduler.Task.run(Task.scala:89)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Driver stacktrace:
at 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$$anonfun$abortStage$1.apply(DAGScheduler.scala:1418)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1418)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:799)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:799)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:799)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1640)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1599)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1588)
at org.apache.spark.util.EventLoop$$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.SparkContext.runJob(SparkContext.scala:1929)
at org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:927)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:150)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:111)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:316)
at org.apache.spark.rdd.RDD.collect(RDD.scala:926)
at Intro$$anon$14.run(Intro.scala:248)
at Intro$.main(Intro.scala:270)
at Intro.main(Intro.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 com.intellij.rt.execution.application.AppMain.main(AppMain.java:144)
Caused by: java.lang.NullPointerException
at DomainNamePartitioner.getPartition(HasRun.scala:20)
at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:151)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:73)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
at org.apache.spark.scheduler.Task.run(Task.scala:89)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Process finished with exit code 1
Quite cryptic. Anyone can help? Thanks!
It looks like things are failing at this line
val code = (domain.hashCode % numPartitions)
Likely because domain is null. This is probably happening because the keys you're passing into the constructor for URI in the previous line are ill-formed.