[SPARK-7488] [ML] Feature Parity in PySpark for ml.recommendation

Adds Python Api for `ALS` under `ml.recommendation` in PySpark. Also adds seed as a settable parameter in the Scala Implementation of ALS.

Author: Burak Yavuz <brkyvz@gmail.com>

Closes #6015 from brkyvz/ml-rec and squashes the following commits:

be6e931 [Burak Yavuz] addressed comments
eaed879 [Burak Yavuz] readd numFeatures
0bd66b1 [Burak Yavuz] fixed seed
7f6d964 [Burak Yavuz] merged master
52e2bda [Burak Yavuz] added ALS

1 files changed, 8 insertions, 4 deletions

diff --git a/mllib/src/main/scala/org/apache/spark/ml/recommendation/ALS.scala b/mllib/src/main/scala/org/apache/spark/ml/recommendation/ALS.scala
index 6cf4b40075..d7cbffc3be 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/recommendation/ALS.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/recommendation/ALS.scala
@@ -49,7 +49,7 @@ import org.apache.spark.util.random.XORShiftRandom
  * Common params for ALS.
  */
 private[recommendation] trait ALSParams extends Params with HasMaxIter with HasRegParam
-  with HasPredictionCol with HasCheckpointInterval {
+  with HasPredictionCol with HasCheckpointInterval with HasSeed {
 
   /**
    * Param for rank of the matrix factorization (>= 1).
@@ -147,7 +147,7 @@ private[recommendation] trait ALSParams extends Params with HasMaxIter with HasR
 
   setDefault(rank -> 10, maxIter -> 10, regParam -> 0.1, numUserBlocks -> 10, numItemBlocks -> 10,
     implicitPrefs -> false, alpha -> 1.0, userCol -> "user", itemCol -> "item",
-    ratingCol -> "rating", nonnegative -> false, checkpointInterval -> 10)
+    ratingCol -> "rating", nonnegative -> false, checkpointInterval -> 10, seed -> 0L)
 
   /**
    * Validates and transforms the input schema.
@@ -278,6 +278,9 @@ class ALS extends Estimator[ALSModel] with ALSParams {
   /** @group setParam */
   def setCheckpointInterval(value: Int): this.type = set(checkpointInterval, value)
 
+  /** @group setParam */
+  def setSeed(value: Long): this.type = set(seed, value)
+
   /**
    * Sets both numUserBlocks and numItemBlocks to the specific value.
    * @group setParam
@@ -290,7 +293,8 @@ class ALS extends Estimator[ALSModel] with ALSParams {
 
   override def fit(dataset: DataFrame): ALSModel = {
     val ratings = dataset
-      .select(col($(userCol)), col($(itemCol)), col($(ratingCol)).cast(FloatType))
+      .select(col($(userCol)).cast(IntegerType), col($(itemCol)).cast(IntegerType),
+        col($(ratingCol)).cast(FloatType))
       .map { row =>
         Rating(row.getInt(0), row.getInt(1), row.getFloat(2))
       }
@@ -298,7 +302,7 @@ class ALS extends Estimator[ALSModel] with ALSParams {
       numUserBlocks = $(numUserBlocks), numItemBlocks = $(numItemBlocks),
       maxIter = $(maxIter), regParam = $(regParam), implicitPrefs = $(implicitPrefs),
       alpha = $(alpha), nonnegative = $(nonnegative),
-      checkpointInterval = $(checkpointInterval))
+      checkpointInterval = $(checkpointInterval), seed = $(seed))
     copyValues(new ALSModel(this, $(rank), userFactors, itemFactors))
   }