scala - 使用 Spark 处理 txt 文件

Question

我需要将文本文件读入 Spark 中的数据集[T]。该文件的格式不正确，因为它有一些空白字段，并且很难定义参数来分割字符串。我一直在尝试将数据读入 RDD，然后将其转换为案例类类型，但是，并非所有字段都被正确解析，并且出现错误:

java.lang.NumberFormatException: empty String
        at sun.misc.FloatingDecimal.readJavaFormatString(FloatingDecimal.java:1842)
        at sun.misc.FloatingDecimal.parseDouble(FloatingDecimal.java:110)
        at java.lang.Double.parseDouble(Double.java:538)
        at scala.collection.immutable.StringLike.toDouble(StringLike.scala:321)
        at scala.collection.immutable.StringLike.toDouble$(StringLike.scala:321)
        at scala.collection.immutable.StringOps.toDouble(StringOps.scala:33)
        at captify.test.spark.Stats$$anonfun$2.apply(Stats.scala:53)
        at captify.test.spark.Stats$$anonfun$2.apply(Stats.scala:53)
        at scala.collection.Iterator$$anon$10.next(Iterator.scala:459)
        at scala.collection.Iterator$$anon$10.next(Iterator.scala:459)
        at scala.collection.Iterator$$anon$10.next(Iterator.scala:459)
        at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
        at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
        at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$2.hasNext(WholeStageCodegenExec.scala:636)
        at org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:255)
        at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:836)
        at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:836)
        at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
        at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
        at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
        at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
        at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
        at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
        at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
        at org.apache.spark.scheduler.Task.run(Task.scala:121)
        at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:411)
        at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
        at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:414)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
        at java.lang.Thread.run(Thread.java:748)

我该如何正确处理该文件？我的 .txt 文件如下所示(匿名随机数据，但格式相同):

NEW50752085  84.0485 -76.3851  85.1   THE NAME OF AN OBJECT                       
DEM00752631  51.9581 -85.3315  98.5   THE NAME OF AN OBJECT                                  
KI004867205  40.8518  15.9351 276.5   THE NAME OF AN OBJECT           FHG   41196

我尝试以这样的方式处理它:

    val dataRdd = spark.sparkContext
      .textFile("file.txt")

    val dataArray = dataRdd
      .map(_.split(" "))

  case class caseClass(
    c1: String,
    c2: Double,
    c3: Double,
    c4: Double,
    c5: String,
    c6: String,
    c7: String
  )

    val df = dataArray
      .map(record => (record(0), record(1).toDouble, record(2).toDouble, record(3).toDouble, record(4), record(5), record(6)))
      .map{case (c1, c2, c3, c4, c5, c6, c7) => CaseClass(c1, c2, c3, c4, c5, c6, c7)
      }.toDF()

Answer 1

我将在此答案中做出一些可能不正确的假设，但根据您提供的数据和提供的错误，我相信它们是正确的。

• 假设 1:您的数据以空格分隔，由多个空格组成。我根据您提供的空字符串的 NumberFormatException 得出了这个假设。如果您的文件是用制表符分隔的，我们就不会遇到这种情况。
• 假设 2(这是出于我自己的考虑，但可能不正确):每个数据元素均由相同数量的空格分隔。对于这个答案的其余部分，我将假设空格数为四个。如果情况并非如此，这将成为一个更加困难的问题。
• 假设3:7个数据元素中只有最后2个是可选的，有时不会出现。

您的 NumberFormatException 是由您用一个空格分割引起的。假设以下行由空格分隔:

NEW50752085    84.0485    -76.3851    85.1    THE NAME OF AN OBJECT 

当您拆分为一个空格时，这一行将转换为以下数组:

Array(NEW50752085, "", "", "", 84.0485, "", "", "", -76.3851, "", "", "", 85.1, "", "", "", THE, NAME, OF, AN, OBJECT)

该数组的第二个元素是一个空字符串，是您尝试转换为 Double 的元素。这就是空字符串上出现 NumberFormatException 的原因。

.map(_.split("    "))

当您将其更改为分成 4 个空格时(根据我的假设，这可能是真的，也可能不是)，您会得到以下结果:

Array(NEW50752085, 84.0485, -76.3851, 85.1, THE NAME OF AN OBJECT)

但是现在我们遇到了另一个问题 - 这只有五个元素!我们想要七个。

我们可以通过修改您以后的代码来更改此设置:

val df = dataArray.map(record => {
  (record(0), record(1).toDouble, record(2).toDouble, record(3).toDouble, record(4), 
  if(record.size > 5) record(5) else "",
  if(record.size > 6) record(6) else "")
}).map{case (c1, c2, c3, c4, c5, c6, c7) => caseClass(c1, c2, c3, c4, c5, c6, c7)}.toDF

df.show
+-----------+-------+--------+----+--------------------+---+-----+
|         c1|     c2|      c3|  c4|                  c5| c6|   c7|
+-----------+-------+--------+----+--------------------+---+-----+
|NEW50752085|84.0485|-76.3851|85.1|THE NAME OF AN OB...|   |     |
|DEM00752631|51.9581|-85.3315|98.5|THE NAME OF AN OB...|   |     |
|KI004867205|40.8518| 15.9351|76.5|THE NAME OF AN OB...|FHG|41196|
+-----------+-------+--------+----+--------------------+---+-----+

同样，只有当所有元素都由相同数量的空格分隔时，此方法才有效。