Question

我编写了这段代码，使用Spark（1.3.0），Scala（2.10.4）和Spark Avro（1.0.0）将Spark数据帧保存到avro文件中

  def getMatchingLine(line: String) : Option[Row] = {
    val regex = "^.*&50=(\\w+)&.*&62-\\d=8&63-\\d=(\\w+)&.*timestamp=(\\d+).*$".r
    line match {
      case regex(a, b, c) => Some(Row(a, b, c))
      case _ => None
    }
  }

    val schema = StructType(List(StructField("a", StringType, true), StructField("b", StringType, true), StructField("c", LongType, true)))
    val rdd = sc.textFile(inputPath).cache()
    val rdd = rdd.map(getMatchingLine).filter(_.isDefined).flatMap(x => x)
    val df = sqlSc.createDataFrame(rdd, schema)
    df.save("/user/foo/", "com.databricks.spark.avro")

错误消息的堆栈跟踪是

ion: org.apache.avro.UnresolvedUnionException: Not in union ["long","null"]: 1426647603695
        at org.apache.avro.file.DataFileWriter.append(DataFileWriter.java:296)
        at org.apache.avro.mapred.AvroOutputFormat$1.write(AvroOutputFormat.java:169)
        at org.apache.avro.mapred.AvroOutputFormat$1.write(AvroOutputFormat.java:166)
        at org.apache.spark.SparkHadoopWriter.write(SparkHadoopWriter.scala:96)
        at org.apache.spark.rdd.PairRDDFunctions$$anonfun$13.apply(PairRDDFunctions.scala:1073)
        at org.apache.spark.rdd.PairRDDFunctions$$anonfun$13.apply(PairRDDFunctions.scala:1059)
        at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:61)
        at org.apache.spark.scheduler.Task.run(Task.scala:64)
        at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:203)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
        at java.lang.Thread.run(Thread.java:745)

Answer 1

尝试将元组中的3位转换为long。它可能是Integer，不能转换为Long。

一些（行（a，b，（长）c））

org.apache.avro.UnresolvedUnionException：不在union [“long”，“null”]

1 个答案: