无法读取，稍后在 Apache Spark 中查询文本文件

Question

所以我正在尝试使用我们提供的数据集来实现示例Spark Programming Example。它是一个以| 分隔的文件。但是，即使按照给出的说明进行操作，它也会引发以下错误。

我可以看到它无法将一个实例的对象“转换”到另一个实例中，任何关于如何处理该场景的建议。

Caused by: java.lang.ClassCastException: cannot assign instance of scala.collection.immutable.List$SerializationProxy to field org.apache.spark.rdd.RDD.org$apache$spark$rdd$RDD$$dependencies_ of type scala.collection.Seq in instance of org.apache.spark.rdd.MapPartitionsRDD
    at java.io.ObjectStreamClass$FieldReflector.setObjFieldValues(ObjectStreamClass.java:2133)
    at java.io.ObjectStreamClass.setObjFieldValues(ObjectStreamClass.java:1305)
    at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:2024)
    at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1942)
    at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1808)
    at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1353)
    at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:2018)
    at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1942)
    at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1808)
    at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1353)
    at java.io.ObjectInputStream.readObject(ObjectInputStream.java:373)
    at scala.collection.immutable.List$SerializationProxy.readObject(List.scala:479)
    at sun.reflect.GeneratedMethodAccessor3.invoke(Unknown Source)
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.lang.reflect.Method.invoke(Method.java:498)
    at java.io.ObjectStreamClass.invokeReadObject(ObjectStreamClass.java:1058)
    at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1909)
    at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1808)
    at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1353)
    at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:2018)
    at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1942)
    at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1808)
    at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1353)
    at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:2018)
    at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1942)
    at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1808)
    at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1353)
    at java.io.ObjectInputStream.readObject(ObjectInputStream.java:373)
    at scala.collection.immutable.List$SerializationProxy.readObject(List.scala:479)
    at sun.reflect.GeneratedMethodAccessor3.invoke(Unknown Source)
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.lang.reflect.Method.invoke(Method.java:498)
    at java.io.ObjectStreamClass.invokeReadObject(ObjectStreamClass.java:1058)
    at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1909)
    at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1808)
    at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1353)
    at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:2018)
    at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1942)
    at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1808)
    at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1353)
    at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:2018)
    at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1942)
    at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1808)
    at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1353)
    at java.io.ObjectInputStream.readObject(ObjectInputStream.java:373)
    at scala.collection.immutable.List$SerializationProxy.readObject(List.scala:479)
    at sun.reflect.GeneratedMethodAccessor3.invoke(Unknown Source)
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.lang.reflect.Method.invoke(Method.java:498)
    at java.io.ObjectStreamClass.invokeReadObject(ObjectStreamClass.java:1058)
    at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1909)
    at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1808)
    at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1353)
    at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:2018)
    at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1942)
    at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1808)
    at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1353)
    at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:2018)
    at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1942)
    at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1808)
    at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1353)
    at java.io.ObjectInputStream.readObject(ObjectInputStream.java:373)
    at org.apache.spark.serializer.JavaDeserializationStream.readObject(JavaSerializer.scala:75)
    at org.apache.spark.serializer.JavaSerializerInstance.deserialize(JavaSerializer.scala:114)
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
    at org.apache.spark.scheduler.Task.run(Task.scala:85)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
    at java.lang.Thread.run(Thread.java:745)

还有一个附属问题，什么是镶木地板？

编辑：所以我仍然不确定出了什么问题，现在我已经转移到另一个项目。但我觉得我试图摄取的数据有些邪恶。请不要对这个问题投反对票。一旦我对问题有了更清晰的了解，我将接受以下批次中的最佳答案或我自己回答问题（如果是这种情况）。

Answer 1

要使用 cast api，您需要使用 $"columnname".cast() api 在数据框内的列对象上调用它

Parquet 是 Hadoop 常用的一种文件格式。它是一种列式数据存储格式。这意味着我们将列而不是行存储在一起。这将有助于后续的阅读，只需要我们阅读重要的列。因此，如果您有 10 个列表，而您只想读取其中的 2 个，我们可以利用 parquet（或 orc）格式，只读取重要的列，跳过其他 8 个。

Answer 2

有更好的选项可用于读取分隔文件。你只需要额外的库。

这方面有很好的文件。检查这个link。

在 Java

中

Dataset<Row> people  =  spark.read()
                .format("com.databricks.spark.csv")
                .schema(customSchema)    
                .option("header", "true").option("delimiter", "|")
                .load("file.csv");

在 Scala

中

val df = sqlContext.read
    .format("com.databricks.spark.csv")
    .option("header", "true") // Use first line of all files as header
    .schema(customSchema)
    .option("delimiter", "|")
    .load("file.csv")