CODEWITHSUNDEEP
scalaapache-sparkapache-spark-sql
Priyaranjan Swain
Priyaranjan Swain

Reputation: 361

Facing "scala.MatchError: 1201 (of class java.lang.Integer)" while creating Data frame

I am executing following code to create a data frame from a text file .

    import org.apache.spark.SparkContext
import org.apache.spark.SparkConf
import org.apache.spark.sql.{SQLContext, Row}
import org.apache.spark.sql.types.{StructType, StringType, StructField}


/**
  * Created by PSwain on 6/19/2016.
  */
object RddToDataframe extends App {

  val scnf=new SparkConf().setAppName("RddToDataFrame").setMaster("local[1]")
  val sc = new SparkContext(scnf)
  val sqlContext = new SQLContext(sc)

  val employeeRdd=sc.textFile("C:\\Users\\pswain\\IdeaProjects\\test1\\src\\main\\resources\\employee")

  //Creating schema

  val employeeSchemaString="id name age"
  val schema = StructType(employeeSchemaString.split(",").map( colNmae => StructField(colNmae,StringType,true)))

  //Creating  RowRdd
  val rowRdd= employeeRdd.map(row => row.split(",")).map(row => Row(row(0).trim.toInt,row(1),row(2).trim.toInt))

  //Creating dataframe = RDD[rowRdd] + schema
  val employeeDF=sqlContext.createDataFrame(rowRdd,schema). registerTempTable("Employee")

  sqlContext.sql("select * from Employee").show()


}

But while executing in InteliJ I am finding type mismatch error as below . Not able to identify why this error is comming I am just converting string to integer . Employee file has below input , they are showing all in one line , but they are one line each .

1201, satish, 25 1202, krishna, 28 1203, amith, 39 1204, javed, 23 1205, prudvi, 23

16/06/19 15:18:58 ERROR Executor: Exception in task 0.0 in stage 0.0 (TID 0)
scala.MatchError: 1201 (of class java.lang.Integer)
    at org.apache.spark.sql.catalyst.CatalystTypeConverters$StringConverter$.toCatalystImpl(CatalystTypeConverters.scala:295)
    at org.apache.spark.sql.catalyst.CatalystTypeConverters$StringConverter$.toCatalystImpl(CatalystTypeConverters.scala:294)
    at org.apache.spark.sql.catalyst.CatalystTypeConverters$CatalystTypeConverter.toCatalyst(CatalystTypeConverters.scala:102)

Upvotes: 2

Views: 6671

Answers (1)

Dazzler
Dazzler

Reputation: 847

The schema is created with all the column types are defined as StringType.

val schema = StructType(employeeSchemaString.split(",").map( colNmae => StructField(colNmae,StringType,true)))

But the rowRDD has columns of type int, string and int.

Here is the working code

val structType= {
    val id = StructField("id", IntegerType)
    val name = StructField("name", StringType)
    val age = StructField("age", IntegerType)
    new StructType(Array(id, name , age))
}

val rowRdd= employeeRdd.map(row => row.split(",")).map(row => Row(row(0).trim().toInt,row(1),row(2).trim().toInt))

sqlContext.createDataFrame(rowRdd,structType). registerTempTable("Employee")

sqlContext.sql("select * from Employee").show()

Upvotes: 6

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