Description
After adding recommendUsersForProducts and recommendProductsForUsers to ALS in spark-perf, I noticed that it takes much longer than ALS itself. Looking at the monitoring page, I can see it is spending about 8min doing GC for each 10min task. That sounds fixable. Looking at the implementation, there is clearly an opportunity to avoid extra allocations: https://github.com/apache/spark/blob/e6dd237463d2de8c506f0735dfdb3f43e8122513/mllib/src/main/scala/org/apache/spark/mllib/recommendation/MatrixFactorizationModel.scala#L283
CC: mengxr
Attachments
Issue Links
- is duplicated by
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SPARK-20446 Optimize the process of MLLIB ALS recommendForAll
- Closed
- is related to
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SPARK-3066 Support recommendAll in matrix factorization model
- Resolved
- relates to
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SPARK-13857 Feature parity for ALS ML with MLLIB
- Closed
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SPARK-20587 Improve performance of ML ALS recommendForAll
- Resolved
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SPARK-10802 Let ALS recommend for subset of data
- Resolved
- links to