Nick Pentreath created SPARK-20587:
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Summary: Improve performance of ML ALS recommendForAll
Key: SPARK-20587
URL: https://issues.apache.org/jira/browse/SPARK-20587
Project: Spark
Issue Type: Improvement
Components: ML
Affects Versions: 2.2.0
Reporter: Nick Pentreath
Assignee: Nick Pentreath
SPARK-11968 relates to excessive GC pressure from using the "blocked BLAS 3"
approach for generating top-k recommendations in
{{mllib.recommendation.MatrixFactorizationModel}}.
The solution there is still based on blocking factors, but efficiently computes
the top-k elements *per block* first (using {{BoundedPriorityQueue}}) and then
computes the global top-k elements.
This improves performance and GC pressure substantially for {{mllib}}'s ALS
model. The same approach is also a lot more efficient than the current
"crossJoin and score per-row" used in {{ml}}'s {{DataFrame}}-based method. This
adapts the solution in SPARK-11968 for {{DataFrame}}.
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