Github user MLnick commented on a diff in the pull request:
https://github.com/apache/spark/pull/12660#discussion_r61391861
--- Diff:
mllib/src/test/scala/org/apache/spark/ml/recommendation/ALSSuite.scala ---
@@ -512,6 +514,55 @@ class ALSSuite
assert(getFactors(model.userFactors) ===
getFactors(model2.userFactors))
assert(getFactors(model.itemFactors) ===
getFactors(model2.itemFactors))
}
+
+ test("StorageLevel param") {
+ // test invalid param values
+ intercept[IllegalArgumentException] {
+ new ALS().setIntermediateRDDStorageLevel("foo")
+ }
+ intercept[IllegalArgumentException] {
+ new ALS().setIntermediateRDDStorageLevel("NONE")
+ }
+ intercept[IllegalArgumentException] {
+ new ALS().setFinalRDDStorageLevel("foo")
+ }
+ // test StorageLevels
+ val sqlContext = this.sqlContext
+ import sqlContext.implicits._
+ val (ratings, _) = genExplicitTestData(numUsers = 2, numItems = 2,
rank = 1)
+ val data = ratings.toDF
+ val als = new ALS().setMaxIter(1)
+ als.fit(data)
--- End diff --
What do you mean exactly?
The intermediate RDDs (and the final factor RDDs) are always "out of
scope", e.g.
```
scala> val model = als.fit(df)
scala> model.userFactors.rdd.getStorageLevel
res30: org.apache.spark.storage.StorageLevel = StorageLevel(disk=false,
memory=false, offheap=false, deserialized=false, replication=1)
```
Because `df.rdd` returns an `RDD[Row]` that is not cached
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