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| author | Patrick Wendell <pwendell@gmail.com> | 2014-01-07 16:57:08 -0800 |
|---|---|---|
| committer | Patrick Wendell <pwendell@gmail.com> | 2014-01-07 16:57:08 -0800 |
| commit | b2e690f839e7ee47f405135d35170173386c5d13 (patch) | |
| tree | 5681d525890580439b60de14c298ce65620a8814 /docs | |
| parent | 6ccf8ce705f13b5c6993675ee034db64363caa31 (diff) | |
| parent | 3a8beb46cb53cf6807f39cca54b1efdbbc303f41 (diff) | |
| download | spark-b2e690f839e7ee47f405135d35170173386c5d13.tar.gz spark-b2e690f839e7ee47f405135d35170173386c5d13.tar.bz2 spark-b2e690f839e7ee47f405135d35170173386c5d13.zip | |
Merge pull request #328 from falaki/MatrixFactorizationModel-fix
SPARK-1012: DAGScheduler Exception Fix
Added a predict method to MatrixFactorizationModel to enable bulk prediction. This method takes and RDD[(Int, Int)] of users and products and return an RDD with a Rating element per each element in the input RDD.
Also added python bindings to the new bulk prediction methods to address SPARK-1011 issue.
This is ready to be merged now.
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