I was thinking about a nice way to convert a List of tuple with duplicate key [(\"a\",\"b\"),(\"c\",\"d\"),(\"a\",\"f\")] into map (\"a\" -> [\"b\", \"
Group and then project:
scala> val x = List("a" -> "b", "c" -> "d", "a" -> "f")
//x: List[(java.lang.String, java.lang.String)] = List((a,b), (c,d), (a,f))
scala> x.groupBy(_._1).map { case (k,v) => (k,v.map(_._2))}
//res1: scala.collection.immutable.Map[java.lang.String,List[java.lang.String]] = Map(c -> List(d), a -> List(b, f))
More scalish way to use fold, in the way like there (skip map f step).
Below you can find a few solutions. (GroupBy, FoldLeft, Aggregate, Spark)
val list: List[(String, String)] = List(("a","b"),("c","d"),("a","f"))
GroupBy variation
list.groupBy(_._1).map(v => (v._1, v._2.map(_._2)))
Fold Left variation
list.foldLeft[Map[String, List[String]]](Map())((acc, value) => {
acc.get(value._1).fold(acc ++ Map(value._1 -> List(value._2))){ v =>
acc ++ Map(value._1 -> (value._2 :: v))
}
})
Aggregate Variation - Similar to fold Left
list.aggregate[Map[String, List[String]]](Map())(
(acc, value) => acc.get(value._1).fold(acc ++ Map(value._1 ->
List(value._2))){ v =>
acc ++ Map(value._1 -> (value._2 :: v))
},
(l, r) => l ++ r
)
Spark Variation - For big data sets (Conversion to a RDD and to a Plain Map from RDD)
import org.apache.spark.rdd._
import org.apache.spark.{SparkContext, SparkConf}
val conf: SparkConf = new
SparkConf().setAppName("Spark").setMaster("local")
val sc: SparkContext = new SparkContext (conf)
// This gives you a rdd of the same result
val rdd: RDD[(String, List[String])] = sc.parallelize(list).combineByKey(
(value: String) => List(value),
(acc: List[String], value) => value :: acc,
(accLeft: List[String], accRight: List[String]) => accLeft ::: accRight
)
// To convert this RDD back to a Map[(String, List[String])] you can do the following
rdd.collect().toMap
You can try this
scala> val b = new Array[Int](3)
// b: Array[Int] = Array(0, 0, 0)
scala> val c = b.map(x => (x -> x * 2))
// c: Array[(Int, Int)] = Array((1,2), (2,4), (3,6))
scala> val d = Map(c : _*)
// d: scala.collection.immutable.Map[Int,Int] = Map(1 -> 2, 2 -> 4, 3 -> 6)
Starting Scala 2.13, most collections are provided with the groupMap method which is (as its name suggests) an equivalent (more efficient) of a groupBy followed by mapValues:
List("a" -> "b", "c" -> "d", "a" -> "f").groupMap(_._1)(_._2)
// Map[String,List[String]] = Map(a -> List(b, f), c -> List(d))
This:
groups elements based on the first part of tuples (group part of groupMap)
maps grouped values by taking their second tuple part (map part of groupMap)
This is an equivalent of list.groupBy(_._1).mapValues(_.map(_._2)) but performed in one pass through the List.
Here's another alternative:
x.groupBy(_._1).mapValues(_.map(_._2))
For Googlers that don't expect duplicates or are fine with the default duplicate handling policy:
List("a" -> 1, "b" -> 2).toMap
// Result: Map(a -> 1, c -> 2)
As of 2.12, the default policy reads:
Duplicate keys will be overwritten by later keys: if this is an unordered collection, which key is in the resulting map is undefined.