echauchot commented on issue #11055: [BEAM-9436] Improve GBK in spark structured streaming runner URL: https://github.com/apache/beam/pull/11055#issuecomment-605020089 > Yes, I agree that materialisation and out of memory should be addressed in different Jira/PR > Could you post the Nexmark results before and after your fix to compare? Thanks Sure, here are nexmark results. They are not very relevant because the results are quite the same before and after the change. Note that 0.2s difference is not a real difference because I usually get 0.2s difference between 2 consequent runs on the same code base. This is because these nexmark results are not very relevant that I ran the load tests above. Indeed, nexmark does a lot more than just a GBK, so I used GroupByKeyLoadTest as a pure GBK test. after the change: Conf Runtime(sec) (Baseline) Events(/sec) (Baseline) Results (Baseline) 0000 1,6 61349,7 100000 0001 0,9 107758,6 92000 0002 0,5 201612,9 351 0003 *** not run *** 0004 1,8 11415,5 40 0005 1,6 60864,3 12 0006 0,8 25641,0 103 0007 2,2 91116,2 1 0008 0,9 219298,2 6000 0009 0,6 32894,7 298 0010 1,1 88028,2 1 0011 0,9 110375,3 1919 0012 0,6 160771,7 1919 0013 0,6 180505,4 92000 0014 1,0 99304,9 92000 ============================================================================ before the change: 0000 1,8 56243,0 100000 0001 0,8 120481,9 92000 0002 0,4 223713,6 351 0003 *** not run *** 0004 1,6 12232,4 40 0005 1,4 71275,8 12 0006 0,9 23148,1 103 0007 2,1 96711,8 1 0008 1,1 183486,2 6000 0009 0,6 34843,2 298 0010 1,2 85543,2 1 0011 0,9 114547,5 1919 0012 0,6 156006,2 1919 0013 0,5 203666,0 92000 0014 1,0 102145,0 92000 ===========================================================================
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