How to pass in a map into UDF in spark - sql

Question

Here is my problem, I have a map of Map[Array[String],String], and I want to pass that into a UDF.
Here is my UDF:
def lookup(lookupMap:Map[Array[String],String]) =
udf((input:Array[String]) => lookupMap.lift(input))
And here is my Map variable:
val srdd = df.rdd.map { row => (
Array(row.getString(1),row.getString(5),row.getString(8)).map(_.toString),
row.getString(7)
)}
Here is how I call the function:
val combinedDF = dftemp.withColumn("a",lookup(lookupMap))(Array($"b",$"c","d"))
I first got an error about immutable array, so I changed my array into immutable type, then I got an error about type mismatch. I googled a bit, apparently I can't pass in non-column type directly into a UDF. Can somebody help? Kudos.
Update: So I did convert everything to a wrapped array. Here is what I did:
val srdd = df.rdd.map{row => (WrappedArray.make[String](Array(row.getString(1),row.getString(5),row.getString(8))),row.getString(7))}
val lookupMap = srdd.collectAsMap()
def lookup(lookupMap:Map[collection.mutable.WrappedArray[String],String]) = udf((input:collection.mutable.WrappedArray[String]) => lookupMap.lift(input))
val combinedDF = dftemp.withColumn("a",lookup(lookupMap))(Array($"b",$"c",$"d"))
Now I am having an error like this:
required: Map[scala.collection.mutable.WrappedArray[String],String]
-ksh: Map[scala.collection.mutable.WrappedArray[String],String]: not found [No such file or directory]
I tried to do something like this:
val m = collection.immutable.Map(1->"one",2->"Two")
val n = collection.mutable.Map(m.toSeq: _*)
but then I just got back to the error of column type.

Answer 1

First, you have to pass a Column as an argument of the UDF; Since you want this argument to be an array, you should use the array function in org.apache.spark.sql.functions, which creates an array Column from a series of other Columns. So the UDF call would be:
lookup(lookupMap)(array($"b",$"c",$"d"))
Now, since array columns are deserialized into mutable.WrappedArray, in order for the map lookup to succeed you'd best make sure that's the type used by your UDF:
def lookup(lookupMap: Map[mutable.WrappedArray[String],String]) =
udf((input: mutable.WrappedArray[String]) => lookupMap.lift(input))
So altogether:
import spark.implicits._
import org.apache.spark.sql.functions._
// Create an RDD[(mutable.WrappedArray[String], String)]:
val srdd = df.rdd.map { row: Row => (
mutable.WrappedArray.make[String](Array(row.getString(1), row.getString(5), row.getString(8))),
row.getString(7)
)}
// collect it into a map (I assume this is what you're doing with srdd...)
val lookupMap: Map[mutable.WrappedArray[String], String] = srdd.collectAsMap()
def lookup(lookupMap: Map[mutable.WrappedArray[String],String]) =
udf((input: mutable.WrappedArray[String]) => lookupMap.lift(input))
val combinedDF = dftemp.withColumn("a",lookup(lookupMap)(array($"b",$"c",$"d")))

Answer 2

Anna your code for srdd/lookupmap is of type org.apache.spark.rdd.RDD[(Array[String], String)]
val srdd = df.rdd.map { row => (
Array(row.getString(1),row.getString(5),row.getString(8)).map(_.toString),
row.getString(7)
)}
Where as in lookup method you are expecting a Map as a parameter
def lookup(lookupMap:Map[Array[String],String]) =
udf((input:Array[String]) => lookupMap.lift(input))
That is the reason why you are getting type mismatch error.
First make srdd from RDD[tuple] to a RDD[Map] and then try converting the RDD to Map to resolve this error.
val srdd = df.rdd.map { row => Map(
Array(row.getString(1),row.getString(5),row.getString(8)).map(_.toString) ->
row.getString(7)
)}