1
我正在測試由我在我的代碼中定義的簡單字符串分析器函數,但其中一個工作器節點在執行時總是失敗。這裏是我一直在測試假人代碼:Spark集羣中的RDD映射函數內調用函數
/* JUST A SIMPLE PARSER TO CLEAN PARENTHESIS */
def parseString(field: String): String = {
val Pattern = "(.*.)".r
field match{
case "null" => "null"
case Pattern(field) => field.replace('(',' ').replace(')',' ').replace(" ", "")
}
}
/* CREATE TWO DISTRIBUTED RDDs TO JOIN THEM */
val emp = sc.parallelize(Seq((1,"jordan",10), (2,"ricky",20), (3,"matt",30), (4,"mince",35), (5,"rhonda",30)), 6)
val dept = sc.parallelize(Seq(("hadoop",10), ("spark",20), ("hive",30), ("sqoop",40)), 6)
val manipulated_emp = emp.keyBy(t => t._3)
val manipulated_dept = dept.keyBy(t => t._2)
val left_outer_join_data = manipulated_emp.leftOuterJoin(manipulated_dept)
/* OUTPUT */
left_outer_join_data.collect.foreach(println)
/*
(30,((3,matt,30),Some((hive,30))))
(30,((5,rhonda,30),Some((hive,30))))
(20,((2,ricky,20),Some((spark,20))))
(10,((1,jordan,10),Some((hadoop,10))))
(35,((4,mince,35),None))
*/
val res = left_outer_join_data
.map(f => (f._2._1._1, f._2._1._2, f._2._2.getOrElse("null").toString))
.collect
res
.map(f => (f._1, f._2, parseString(f._3)))
.foreach(println)
/* DESIRED OUTPUT */
/*
(3,matt,hive,30)
(5,rhonda,hive,30)
(2,ricky,spark,20)
(1,jordan,hadoop,10)
(4,mince,null)
*/
此代碼的工作,如果我先收集的資源驅動程序中的結果。由於這是一個測試,所以這樣做沒有問題,但是我的實際應用會處理數百萬行,並且不鼓勵在驅動程序中收集結果。所以,如果我做同樣的而不收集它首先,就像這樣:
val res = left_outer_join_data
.map(f => (f._2._1._1, f._2._1._2, f._2._2.getOrElse("null").toString))
res
.map(f => (f._1, f._2, parseString(f._3)))
.foreach(println)
我得到如下:
ERROR TaskSetManager: Task 5 in stage 17.0 failed 4 times; aborting job
Exception in thread "main" org.apache.spark.SparkException: Job aborted due to stage failure: Task 5 in stage 17.0 failed 4 times, most recent failure: Lost task 5.3 in stage 17.0 (TID 166, 192.168.28.101, executor 1): java.lang.NoClassDefFoundError: Could not initialize class tele.com.SimcardMsisdn$
at tele.com.SimcardMsisdn$$anonfun$main$1.apply(SimcardMsisdn.scala:249)
at tele.com.SimcardMsisdn$$anonfun$main$1.apply(SimcardMsisdn.scala:249)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:409)
at scala.collection.Iterator$class.foreach(Iterator.scala:893)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1336)
at org.apache.spark.rdd.RDD$$anonfun$foreach$1$$anonfun$apply$28.apply(RDD.scala:918)
at org.apache.spark.rdd.RDD$$anonfun$foreach$1$$anonfun$apply$28.apply(RDD.scala:918)
at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1951)
at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1951)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
at org.apache.spark.scheduler.Task.run(Task.scala:99)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:322)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala: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$foreach$1.apply(RDD.scala:918)
at org.apache.spark.rdd.RDD$$anonfun$foreach$1.apply(RDD.scala:916)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:362)
at org.apache.spark.rdd.RDD.foreach(RDD.scala:916)
at tele.com.SimcardMsisdn$.main(SimcardMsisdn.scala:249)
at tele.com.SimcardMsisdn.main(SimcardMsisdn.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$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$.main(SparkSubmit.scala:126)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
Caused by: java.lang.NoClassDefFoundError: Could not initialize class tele.com.SimcardMsisdn$
at tele.com.SimcardMsisdn$$anonfun$main$1.apply(SimcardMsisdn.scala:249)
at tele.com.SimcardMsisdn$$anonfun$main$1.apply(SimcardMsisdn.scala:249)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:409)
at scala.collection.Iterator$class.foreach(Iterator.scala:893)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1336)
at org.apache.spark.rdd.RDD$$anonfun$foreach$1$$anonfun$apply$28.apply(RDD.scala:918)
at org.apache.spark.rdd.RDD$$anonfun$foreach$1$$anonfun$apply$28.apply(RDD.scala:918)
at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1951)
at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1951)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
at org.apache.spark.scheduler.Task.run(Task.scala:99)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:322)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
爲什麼星火未能執行節點上我的解析器?你能否推薦一個解決方案或解決方法?
UPDATE
我找到了解決這個問題(貼在下面),儘管如此,我還是感到困惑這個問題,也許是我做錯了什麼。
您還可以在'left_outer_join_data'中使用'case(a,((b,c,d),Some((e,f,g))=>(b,c,...)''。地圖'以提高可讀性。 :) – philantrovert
確實。謝謝你的提示 ;) – Emiliano