如何修复“ org.apache.spark.sql.execution.datasources.orc.OrcColumnVector.getLong(OrcColumnVector.java:141)上的java.lang.NullPointerException”

时间:2019-07-29 07:52:07

标签: dataframe apache-spark orc

我正在尝试将数据帧中的所有列合并为一个名为value的列。

我的代码:

    val df = sparkSession.sql(sql)

    val dfwithValue = df.withColumn("value",df.col("topic"))

    dfwithValue.selectExpr("CAST(value AS STRING)").show() // no error

    import org.apache.spark.sql.functions._

    val cols = df.columns.map({ col =>
      df.col(col)
    }).toSeq

     val newdf = df.withColumn("value", struct(cols : _*))

     newdf.selectExpr("CAST(value AS STRING)").show() // error

当我使用第二种方法时,遇到错误

Caused by: java.lang.NullPointerException
    at org.apache.spark.sql.execution.datasources.orc.OrcColumnVector.getLong(OrcColumnVector.java:141)
    at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
    at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
    at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$13$$anon$1.hasNext(WholeStageCodegenExec.scala:636)
    at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409)
    at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:125)
    at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99)
    at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:55)
    at org.apache.spark.scheduler.Task.run(Task.scala:121)
    at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:403)
    at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:409)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
    at java.lang.Thread.run(Thread.java:748)

有人可以帮忙吗?

2 个答案:

答案 0 :(得分:0)

这两种方法都不会出错,但是我发现该解决方案过于复杂。同样,此代码返回Row [WarappedArray [String]]行而不是Row [String]

的数据帧

尝试:

df.map(_.mkString("")).toDF("value").show()

答案 1 :(得分:0)

当无法访问该值时,还会出现空指针异常,请检查变量的范围以解决此问题。