Spark Scala - rdd distinct nullpointerexception

Question

I'm doing baby steps with spark and my exercise loads a JSON file into RDD, select a column, and then use the distinct to get unique values. The column I'm filtering contains multiple values (CSV line) and has to be split.

val sqlContext = spark.sqlContext
import org.apache.spark.sql.hive.HiveContext
val hiveCtx = new HiveContext(sc)
import hiveCtx.implicits._
val bizDF = hiveCtx.jsonFile("/home/xpto/Documents/PersonalProjects/Yelp_P1/yelp_academic_dataset_business.json")
val catRdd = bizDF.select("categories").rdd.flatMap(row => (row.getString(0).split(",").map(_.trim))).distinct

When I run the statement "catRdd.take (10).foreach (println)" returns an exception:

org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 234.0 failed 1 times, most recent failure: Lost task 0.0 in stage 234.0 (TID 682, 192.168.0.122, executor driver):

java.lang.NullPointerException
    at $anonfun$catRdd$1(<console>:39)
    at $anonfun$catRdd$1$adapted(<console>:39)
    at scala.collection.Iterator$$anon$11.nextCur(Iterator.scala:484)
    at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:490)
    at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:458)
    at org.apache.spark.util.collection.ExternalSorter.insertAll(ExternalSorter.scala:192)
    at org.apache.spark.shuffle.sort.SortShuffleWriter.write(SortShuffleWriter.scala:62)
    at org.apache.spark.shuffle.ShuffleWriteProcessor.write(ShuffleWriteProcessor.scala:59)
    at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99)
    at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:52)
    at org.apache.spark.scheduler.Task.run(Task.scala:127)
    at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:446)
    at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1377)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:449)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
    at java.lang.Thread.run(Thread.java:748)

Driver stacktrace:
  at org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2059)
  at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2008)
  at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2007)
  at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
  at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)
  at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)
  at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2007)
  at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:973)
  at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:973)
  at scala.Option.foreach(Option.scala:407)
  at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:973)
  at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2239)
  at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2188)
  at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2177)
  at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
  at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:775)
  at org.apache.spark.SparkContext.runJob(SparkContext.scala:2099)
  at org.apache.spark.SparkContext.runJob(SparkContext.scala:2120)
  at org.apache.spark.SparkContext.runJob(SparkContext.scala:2139)
  at org.apache.spark.rdd.RDD.$anonfun$take$1(RDD.scala:1423)
  at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
  at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
  at org.apache.spark.rdd.RDD.withScope(RDD.scala:388)
  at org.apache.spark.rdd.RDD.take(RDD.scala:1396)
  ... 48 elided
Caused by: java.lang.NullPointerException
  at $anonfun$catRdd$1(<console>:39)
  at $anonfun$catRdd$1$adapted(<console>:39)
  at scala.collection.Iterator$$anon$11.nextCur(Iterator.scala:484)
  at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:490)
  at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:458)
  at org.apache.spark.util.collection.ExternalSorter.insertAll(ExternalSorter.scala:192)
  at org.apache.spark.shuffle.sort.SortShuffleWriter.write(SortShuffleWriter.scala:62)
  at org.apache.spark.shuffle.ShuffleWriteProcessor.write(ShuffleWriteProcessor.scala:59)
  at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99)
  at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:52)
  at org.apache.spark.scheduler.Task.run(Task.scala:127)
  at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:446)
  at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1377)
  at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:449)
  ... 3 more

The spark version I'm running is 2.12-3.0.1

Answer 1

I found a solution that fits for my requirement:

import org.apache.spark.sql.functions._
import org.apache.spark.sql.expressions.Window
val v1 = bizDF.withColumn("categories", split(col("categories"), ","))
  .select(col("categories")(0).as("description"))
  .distinct
  .coalesce(1)
  .orderBy(asc("description"))

val windowSpec = Window.orderBy("description")
val v2 = v1.withColumn("id",row_number.over(windowSpec))
val v3 = v2.select("id","description")

Answer 2

Your json file has multiple lines and is not supported by HiveCtx. Try this instead using spark session:

val bizDF = spark.read.format("json").option("multiline", "true").load("/home/xpto/Documents/PersonalProjects/Yelp_P1/yelp_academic_dataset_business.json")
val catRdd = bizDF.select("categories").rdd.flatMap(row => (row.getString(0).split(",").map(_.trim))).distinct
catRdd.take(10).foreach(println)