zhengruifeng opened a new pull request #26396: [SPARK-29754][ML] LoR/AFT/LiR/SVC use Summarizer instead of MultivariateOnlineSummarizer URL: https://github.com/apache/spark/pull/26396 ### What changes were proposed in this pull request? 1, change the scope of `ml.SummarizerBuffer` and add a method `createSummarizerBuffer` for it, so it can be used as an aggregator like `MultivariateOnlineSummarizer`; 2, In LoR/AFT/LiR/SVC, use Summarizer instead of MultivariateOnlineSummarizer ### Why are the changes needed? The computation of summary before learning iterations is a bottleneck in high-dimension cases, since `MultivariateOnlineSummarizer` compute much more than needed. In the [ticket](https://issues.apache.org/jira/browse/SPARK-29754) is an example, with `--driver-memory=4G` LoR will always fail on KDDA dataset. If we swith to `ml.Summarizer`, then `--driver-memory=3G` is enough to train a model. ### Does this PR introduce any user-facing change? No ### How was this patch tested? existing testsuites & manual test in REPL
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