CODEWITHSUNDEEP
scalaapache-sparkapache-spark-sqluser-defined-functions
Markus
Markus

Reputation: 3782

Task serialization error when using UDF in Spark

When I create UDF function as shown above, I get Task Serialization error. This error appears only when I run the code in the cluster deploy mode using spark-submit. However, it works well in spark-shell.

import org.apache.spark.sql.expressions.Window
import org.apache.spark.sql.SparkSession
import org.apache.spark.sql.functions._
import scala.collection.mutable.WrappedArray

def mfnURL(arr: WrappedArray[String]): String = {
  val filterArr = arr.filterNot(_ == null)
  if (filterArr.length == 0)
    return null
  else {
    filterArr.groupBy(identity).maxBy(_._2.size)._1
  }
}

val mfnURLUDF = udf(mfnURL _)

def windowSpec = Window.partitionBy("nodeId", "url", "typology")                                                     
val result = df.withColumn("count", count("url").over(windowSpec))
  .orderBy($"count".desc)                                                                                            
  .groupBy("nodeId","typology")                                                                                      
  .agg(
  first("url"),
  mfnURLUDF(collect_list("source_url")),
  min("minTimestamp"),
  max("maxTimestamp")
)

I tried to add spark.udf.register("mfnURLUDF",mfnURLUDF), but it did not solve the problem.

Upvotes: 2

Views: 1228

Answers (1)

merenptah
merenptah

Reputation: 476

You can also try to create udf this way:

val mfnURL = udf { arr: WrappedArray[String] =>
  val filterArr = arr.filterNot(_ == null)
  if (filterArr.length == 0)
    return null
  else {
    filterArr.groupBy(identity).maxBy(_._2.size)._1
  }
}

Upvotes: 2

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