[ https://issues.apache.org/jira/browse/SPARK-30641?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
zhengruifeng updated SPARK-30641: --------------------------------- Summary: Project Matrix: Linear Models revisit and refactor (was: ML algs blockify input vectors) > Project Matrix: Linear Models revisit and refactor > -------------------------------------------------- > > Key: SPARK-30641 > URL: https://issues.apache.org/jira/browse/SPARK-30641 > Project: Spark > Issue Type: New Feature > Components: ML, PySpark > Affects Versions: 3.1.0, 3.2.0 > Reporter: zhengruifeng > Assignee: zhengruifeng > Priority: Major > > stacking input vectors into blocks will benefit ML algs: > 1, less RAM to persist datasets, since the overhead of object header is > reduced; > 2, optimization potential for impl, since high-level BLAS can be used; Proven > in ALS/MLP; > 3, maybe a way to perform efficient mini-batch sampling (To be confirmed) -- This message was sent by Atlassian Jira (v8.3.4#803005) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org