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https://issues.apache.org/jira/browse/SPARK-6407?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15896190#comment-15896190
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Sean Owen commented on SPARK-6407:
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I did some work on this, but it's not a paper or anything, just some code, in
and around these bits of code, which try to compute new user/item updates on
the fly:
https://github.com/OryxProject/oryx/blob/master/app/oryx-app/src/main/java/com/cloudera/oryx/app/speed/als/ALSSpeedModelManager.java#L198
https://github.com/OryxProject/oryx/blob/master/app/oryx-app-common/src/main/java/com/cloudera/oryx/app/als/ALSUtils.java
The choices about the semantics of the updates are in ALSUtils. If you dig into
it, we can discuss offline and I can probably write more in the docs to make it
clearer what's happening.
> Streaming ALS for Collaborative Filtering
> -----------------------------------------
>
> Key: SPARK-6407
> URL: https://issues.apache.org/jira/browse/SPARK-6407
> Project: Spark
> Issue Type: New Feature
> Components: DStreams
> Reporter: Felix Cheung
> Priority: Minor
>
> Like MLLib's ALS implementation for recommendation, and applying to streaming.
> Similar to streaming linear regression, logistic regression, could we apply
> gradient updates to batches of data and reuse existing MLLib implementation?
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