解决java中joda DateTime导致的空指针异常

异常消息如下

用户类引发异常：作业因阶段失败而中止：阶段1.0中的任务0失败4次，最近失败：阶段1.0中丢失任务0.3(TID 11,10.215.155.82)：org.joda中的java.lang.NullPointerException .time.tz.CachedDateTimeZone.getInfo(CachedDateTimeZone.java:143)org.joda.time.ff.DachedTimeZone.getOffset(CachedDateTimeZone.java:103)org.joda.time.format.DateTimeFormatter.printTo(DateTimeFormatter.java) ：org.joda.time.base的org.joda.time.format.DateTimeFormatter.printTo(DateTimeFormatter.java:521)org.joda.time.base上的org.joda.time.format.DateTimeFormatter.print(DateTimeFormatter.java:625) . AbstractDateTime.toString(AbstractDateTime.java:328)at com.xxx.ieg.face.demo.DateTimeNullReferenceReappear

$$anonfun $ 3$$ anonfun $ apply $ 1.apply(DateTimeNullReferenceReappear.scala：41)at com.xxx.ieg.face . demo.DateTimeNullReferenceReappear $$anonfun $ 3$$ anonfun $ apply $ 1.apply(DateTimeNullReferenceReappear.scala：41)at scala.collection.TraversableLike $$anonfun $ groupBy $ 1.apply(TraversableLike . scala：328)at scala.collection.TraversableLike$$ anonfun $ groupBy $ 1.apply(TraversableLike.scala：327)at scala.collection.Iterator $ class.foreach(Iterator.scala：727)at org.apache.spark.util .collection.CompactBuffer $$anon $ 1.foreach(CompactBuffer.scala：113)at scala.collection.IterableLike $ class.foreach(IterableLike.scala：72)at org.apache.spark.util.collection.CompactBuffer.foreach(CompactBuffer) .scala：28)at scala.collection.TraversableLike $ class.groupBy(TraversableLike.scala：327)atg.apache.spark.util.collection.CompactBuffer.groupBy(CompactBuffer.scala：28)at com.xxx.ieg . face.demo.DateTimeNullReferenceReappear$$ anonfun $ 3.apply(DateTimeNullReferenceReappear.scala：41)at com.xxx.ieg.face.demo.DateTimeNullReferenceReappear $$anonfun $ 3.apply(DateTimeNullReferenceReappear.scala：40)at scala.collection.Iterator $ $ anon $ 11.next(Iterator.scala：328)at scala.collection.Iterator$$ anon $ 10.next(Iterator.scala：312)at scala.collection.Iterator $ class.foreach(Iterator.scala：727)at scala .collection.Abs tractIterator.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)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)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 org.apache.spark.rdd.RDD $$anonfun $ 26.apply(RDD.scala：1081)的scala.collection.AbstractIterator.toArray(Iterator.scala：1157) . apache.spark.rdd.RDD$$ anonfun $ 26.apply(RDD.scala：1081)org.apache.spark.SparkContext $$anonfun $ runJob $ 4.apply(SparkContext.scala：1314)org.apache.spark . org.apache.spark上的SparkContext$$ anonfun $ runJob $ 4.apply(SparkContext.scala：1314) .scheduler.ResultTask.runTask(ResultTask.scala：61)atg.apache.spark.scheduler.Task.run(Task.scala：56)at org.apache.spark.executor.Executor $ TaskRunner.run(Executor.scala) ：196)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的：744)

我的代码如下：

import org.apache.hadoop.conf.Configuration

import org.apache.spark.rdd.RDD

import org.apache.spark.SparkContext._

import org.apache.spark.{ SparkConf, SparkContext }

import org.joda.time.DateTime

import org.joda.time.format.{ DateTimeFormat, DateTimeFormatter }

object DateTimeNullReferenceReappear extends App {

case class Record(uin: String = "", date: DateTime = null, value: Double = 0.0)

val cfg = new Configuration

val sparkConf = new SparkConf()

sparkConf.setAppName("bourne_exception_reappear")

val sc = new SparkContext(sparkConf)

val data = TDWSparkContext.tdwTable( // this function just read data from an data warehouse

sc,

tdwuser = FaceConf.TDW_USER,

tdwpasswd = FaceConf.TDW_PASSWORD,

dbName = "my_db",

tblName = "my_table",

parts = Array("p_20150323", "p_20150324", "p_20150325", "p_20150326", "p_20150327", "p_20150328", "p_20150329"))

.map(row => {

Record(uin = row(2),

date = DateTimeFormat.forPattern("yyyyMMdd").parseDateTime(row(0)),

value = row(4).toDouble)

}).map(x => (x.uin, (x.date, x.value)))

.groupByKey

.map(x => {

x._2.groupBy(_._1.toString("yyyyMMdd")).mapValues(_.map(_._2).sum) // throw exception here

})

// val data = TDWSparkContext.tdwTable( // It works, as I don't user datetime toString in the groupBy

// sc,

// tdwuser = FaceConf.TDW_USER,

// tdwpasswd = FaceConf.TDW_PASSWORD,

// dbName = "hy",

// tblName = "t_dw_cf_oss_tblogin",

// parts = Array("p_20150323", "p_20150324", "p_20150325", "p_20150326", "p_20150327", "p_20150328", "p_20150329"))

// .map(row => {

// Record(uin = row(2),

// date = DateTimeFormat.forPattern("yyyyMMdd").parseDateTime(row(0)),

// value = row(4).toDouble)

// }).map(x => (x.uin, (x.date.toString("yyyyMMdd"), x.value)))

// .groupByKey

// .map(x => {

// x._2.groupBy(_._1).mapValues(_.map(_._2).sum)

// })

data.take(10).map(println)

}

所以，似乎在 groupBy 中调用 toString 会导致异常，所以有人可以解释一下吗？

谢谢