Pass array as an UDF parameter in Spark SQL

Question

I'm trying to transform a dataframe via a function that takes an array as a parameter. My code looks something like this:

def getCategory(categories:Array[String], input:String): String = { 
  categories(input.toInt) 
} 

val myArray = Array("a", "b", "c") 

val myCategories =udf(getCategory _ ) 

val df = sqlContext.parquetFile("myfile.parquet) 

val df1 = df.withColumn("newCategory", myCategories(lit(myArray), col("myInput"))

However, lit doesn't like arrays and this script errors. I tried definining a new partially applied function and then the udf after that :

val newFunc = getCategory(myArray,  _:String) 
val myCategories = udf(newFunc) 

val df1 = df.withColumn("newCategory", myCategories(col("myInput")))

This doesn't work either as I get a nullPointer exception and it appears myArray is not being recognized. Any ideas on how I pass an array as a parameter to a function with a dataframe?

On a separate note, any explanation as to why doing something simple like using a function on a dataframe is so complicated (define function, redefine it as UDF, etc, etc)?

Community · Accepted Answer · 2017-05-23 12:10:05Z

9

Most likely not the prettiest solution but you can try something like this:

def getCategory(categories: Array[String]) = {
    udf((input:String) => categories(input.toInt))
}

df.withColumn("newCategory", getCategory(myArray)(col("myInput")))

You could also try an array of literals:

val getCategory = udf(
   (input:String, categories: Array[String]) => categories(input.toInt))

df.withColumn(
  "newCategory", getCategory($"myInput", array(myArray.map(lit(_)): _*)))

On a side note using Map instead of Array is probably a better idea:

def mapCategory(categories: Map[String, String], default: String) = {
    udf((input:String) =>  categories.getOrElse(input, default))
}

val myMap = Map[String, String]("1" -> "a", "2" -> "b", "3" -> "c")

df.withColumn("newCategory", mapCategory(myMap, "foo")(col("myInput")))

Since Spark 1.5.0 you can also use an array function:

import org.apache.spark.sql.functions.array

val colArray = array(myArray map(lit  _): _*)
myCategories(lit(colArray), col("myInput"))

1 Comment

EDZ Over a year ago

You can use typedLit now. Also, your input should be immutable (Seq).

Collectives™ on Stack Overflow

Pass array as an UDF parameter in Spark SQL

1 Answer 1

1 Comment

Your Answer

Linked

Hot Network Questions

Collectives™ on Stack Overflow

1 Answer 1

1 Comment

Your Answer

Sign up or log in

Post as a guest

Linked

Related