如何从自定义类Person创建数据集?

时间:2016-01-23 14:17:16

标签: apache-spark apache-spark-sql apache-spark-dataset

我试图在Java中创建Dataset,所以我编写了以下代码:

public Dataset createDataset(){
  List<Person> list = new ArrayList<>();
  list.add(new Person("name", 10, 10.0));
  Dataset<Person> dateset = sqlContext.createDataset(list, Encoders.bean(Person.class));
  return dataset;
}

Person类是一个内部类。

然而,

Spark引发了以下异常:

org.apache.spark.sql.AnalysisException: Unable to generate an encoder for inner class `....` without access to the scope that this class was defined in. Try moving this class out of its parent class.;

at org.apache.spark.sql.catalyst.encoders.ExpressionEncoder$$anonfun$2.applyOrElse(ExpressionEncoder.scala:264)
at org.apache.spark.sql.catalyst.encoders.ExpressionEncoder$$anonfun$2.applyOrElse(ExpressionEncoder.scala:260)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:243)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:243)
at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:53)
at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:242)

如何正确地做到这一点?

3 个答案:

答案 0 :(得分:12)

tl; dr (仅限Spark shell)定义案例类 first ,一旦定义,就使用它们。在Spark / Scala应用程序中使用案例类应该可以正常工作。

在Spark shell的 2.0.1 中,您应首先定义案例类,然后才能访问它们以创建Dataset

$ ./bin/spark-shell --version
Welcome to
      ____              __
     / __/__  ___ _____/ /__
    _\ \/ _ \/ _ `/ __/  '_/
   /___/ .__/\_,_/_/ /_/\_\   version 2.1.0-SNAPSHOT
      /_/

Using Scala version 2.11.8, Java HotSpot(TM) 64-Bit Server VM, 1.8.0_102
Branch master
Compiled by user jacek on 2016-10-25T04:20:04Z
Revision 483c37c581fedc64b218e294ecde1a7bb4b2af9c
Url https://github.com/apache/spark.git
Type --help for more information.

$ ./bin/spark-shell
scala> :pa
// Entering paste mode (ctrl-D to finish)

case class Person(id: Long)

Seq(Person(0)).toDS // <-- this won't work

// Exiting paste mode, now interpreting.

<console>:15: error: value toDS is not a member of Seq[Person]
       Seq(Person(0)).toDS // <-- it won't work
                      ^
scala> case class Person(id: Long)
defined class Person

scala> // the following implicit conversion *will* work

scala> Seq(Person(0)).toDS
res1: org.apache.spark.sql.Dataset[Person] = [id: bigint]

43ebf7a9cbd70d6af75e140a6fc91bf0ffc2b877提交(3月21日Spark 2.0.0-SNAPSHOT)中,添加了解决方案以解决此问题。

在Scala REPL中,我必须添加OuterScopes.addOuterScope(this):paste完整代码段如下:

scala> :pa
// Entering paste mode (ctrl-D to finish)

import sqlContext.implicits._
case class Token(name: String, productId: Int, score: Double)
val data = Token("aaa", 100, 0.12) ::
  Token("aaa", 200, 0.29) ::
  Token("bbb", 200, 0.53) ::
  Token("bbb", 300, 0.42) :: Nil
org.apache.spark.sql.catalyst.encoders.OuterScopes.addOuterScope(this)
val ds = data.toDS

答案 1 :(得分:4)

解决方案是在方法的开头添加这段代码:

org.apache.spark.sql.catalyst.encoders.OuterScopes.addOuterScope(this);

答案 2 :(得分:0)

对于scala中的类似问题,我的解决方案是完全按照AnalysisException建议的那样做。将case类移出其父类。 例如,我在Streaming_Base.scala中有类似下面的内容:

abstract class Streaming_Base {
    case class EventBean(id:String, command:String, recordType:String)
    ...
}

我将其更改为以下内容:

case class EventBean(id:String, command:String, recordType:String)
abstract class Streaming_Base {        
    ...
}