Github user hqzizania commented on the issue:
https://github.com/apache/spark/pull/13891
@yanboliang So sorry for my late response.
Some regression performance test results:
Datasets: using
[genExplicitTestData](https://github.com/apache/spark/pull/13891/files#diff-2c1dd810bcfabf444a0ecdcd613e954aR393)
to generate with numUsers = 20000, numItems = 2000
Single-node cluster: 16 physical cores, 100GB memory
ALS: numUserBlocks = 30, numItemBlocks = 30
It will run
[computeFactors](https://github.com/apache/spark/pull/13891/files#diff-be65dd1d6adc53138156641b610fcadaR1291)
with 30 partitions in parallel.
====================================================
ALS: rank = 1024
Computing time and used memory for computeFactors:
=====================================================
ALS: rank = 129
Computing time for computeFactors:
=====================================================
ALS: rank = 512
Computing time for computeFactors:
The results shows this patch makes it faster very much when rank is large,
but we should reset the two threshold values of "doStack".
However, a following problem is that the unit test for this patch will take
much time as rank must be larger than 1024. Should I just remove the unit test?
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