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https://issues.apache.org/jira/browse/SPARK-18781?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15787786#comment-15787786
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Liang-Chi Hsieh commented on SPARK-18781:
-----------------------------------------

[~eyal] Do you have estimated time cost of the approximate count? Since it is 
just an approximation, I think it should not take big portion of the whole time 
of predict.

If the batches are large, as [~sowen] said, this overhead is trivial compared 
with the predication. And I agreed that this is the predicate method is meant 
for.

Even if the batches are small, I don't think the approximation will largely 
increase the time of running predict. I can't image that the given 
usersProducts will cost much more time in approximating count than the joining 
+ ddot in predication.


> Allow MatrixFactorizationModel.predict to skip user/product approximation 
> count
> -------------------------------------------------------------------------------
>
>                 Key: SPARK-18781
>                 URL: https://issues.apache.org/jira/browse/SPARK-18781
>             Project: Spark
>          Issue Type: Improvement
>          Components: MLlib
>            Reporter: Eyal Allweil
>            Priority: Minor
>
> When 
> [MatrixFactorizationModel.predict|https://spark.apache.org/docs/1.6.1/api/java/org/apache/spark/mllib/recommendation/MatrixFactorizationModel.html#predict(org.apache.spark.rdd.RDD)]
>  is used, it first calculates an approximation count of the users and 
> products in order to determine the most efficient way to proceed. In many 
> cases, the answer to this question is fixed (typically there are more users 
> than products by an order of magnitude) and this check is unnecessary. Adding 
> a parameter to this predict method to allow choosing the implementation (and 
> skipping the check) would be nice.
> It would be especially nice in development cycles when you are repeatedly 
> tweaking your model and which pairs you're predicting for and this 
> approximate count represents a meaningful portion of the time you wait for 
> results.
> I can provide a pull request with this ability added that preserves the 
> existing behavior.



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