Dong Wang created SPARK-29828:
---------------------------------
Summary: Missing persist on ratings on ratings in
ml.recommendation.ALS.train
Key: SPARK-29828
URL: https://issues.apache.org/jira/browse/SPARK-29828
Project: Spark
Issue Type: Sub-task
Components: ML
Affects Versions: 2.4.3
Reporter: Dong Wang
There is a ratings.isEmpty() in ml.recommendation.ALS.train(). Actually,
isEmpty() has an action operator.
{code:scala}
def isEmpty(): Boolean = withScope {
partitions.length == 0 || take(1).length == 0
}
{code}
So rdd ratings will be used by multi actions, it should be persisted, and
unpersisted after its child rdd has been persisted.
{code:scala}
def train[ID: ClassTag]( // scalastyle:ignore
ratings: RDD[Rating[ID]],
...
require(!ratings.isEmpty(), s"No ratings available from $ratings") // first
use ratings
...
val blockRatings = partitionRatings(ratings, userPart, itemPart)
.persist(intermediateRDDStorageLevel)
val (userInBlocks, userOutBlocks) =
makeBlocks("user", blockRatings, userPart, itemPart,
intermediateRDDStorageLevel)
userOutBlocks.count() // materialize blockRatings and user blocks
// ratings should be unpersisted here
{code}
This issue is reported by our tool CacheCheck, which is used to dynamically
detecting persist()/unpersist() api misuses.
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