CODEWITHSUNDEEP
scalaapache-sparkapache-spark-sql
Edamame
Edamame

Reputation: 25396

Spark: sqlContext and dataFrame errors

I have the following code from the Spark example website, trying to run it from Eclipse, but it seems the code doesn't even compile.

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)
  }
}

But then I got the following errors. Did I miss anything here? Thanks!

enter image description here

The same error (as text, from 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() ^

Upvotes: 0

Views: 1305

Answers (1)

Beryllium
Beryllium

Reputation: 13008

Move the definition of class Person:

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

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

That definition must be outside of the method using it.

As for the reason: Have a look at this, a quote from there:

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.

And it references https://issues.scala-lang.org/browse/SI-6649

Upvotes: 2

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