Spark：sqlContext 和 dataFrame 错误

Question

我有来自 Spark 示例网站的以下代码，试图从 Eclipse 运行它，但似乎代码甚至无法编译。

import org.apache.spark._
import org.apache.spark.SparkContext._

object DataFrameExample {

  def main(args: Array[String]) {

    case class Person(name: String, age: Int)

    val conf = new SparkConf().setAppName("wordCount"); //.setMaster("local")
    conf.setMaster("local");

    val sc = new SparkContext(conf)
    val sqlContext = new org.apache.spark.sql.SQLContext(sc)

    import sqlContext._
    import sqlContext.implicits._

    val people = sc.textFile("examples/src/main/resources/people.txt").map(_.split(",")).map(p => Person(p(0), p(1).trim.toInt)).toDF()
    people.registerTempTable("people")

    val teenagers = sqlContext.sql("SELECT name, age FROM people WHERE age >= 13 AND age <= 19")

    // The results of SQL queries are DataFrames and support all the normal RDD operations.
    // The columns of a row in the result can be accessed by field index:
    teenagers.map(t => "Name: " + t(0)).collect().foreach(println)

    // or by field name:
    teenagers.map(t => "Name: " + t.getAs[String]("name")).collect().foreach(println)

    // row.getValuesMap[T] retrieves multiple columns at once into a Map[String, T]
    teenagers.map(_.getValuesMap[Any](List("name", "age"))).collect().foreach(println)
    // Map("name" -> "Justin", "age" -> 19)
  }
}

但后来我得到了以下错误。我在这里错过了什么吗？谢谢！

同样的错误（作为文本，来自 IntelliJ）

Error:(18, 93) No TypeTag available for Person val people = sc.textFile("examples/src/main/resources/people.txt").map(_.split(",")).map(p => Person(p(0), p(1).trim.toInt)).toDF() ^

Answer 1

移动class的定义Person:

case class Person(name: String, age: Int)

object DataFrameExample {
  def main(args: Array[String]) {
    // [...]
  }
}

该定义必须在使用它的方法之外。

至于原因：看看this，引自那里：

2- Move case class outside of the method:

case class, by use of which you define the schema of the DataFrame, should be defined outside of the method needing it.

它引用了 https://issues.scala-lang.org/browse/SI-6649

Spark：sqlContext 和 dataFrame 错误

Spark: sqlContext and dataFrame errors

scala

apache-spark

apache-spark-sql

spark-dataframe