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Siddharth Murching commented on SPARK-21972: -------------------------------------------- Link to old PR containing work on this: https://github.com/apache/spark/pull/17014 > Allow users to control input data persistence in ML Estimators via a > handlePersistence ml.Param > ----------------------------------------------------------------------------------------------- > > Key: SPARK-21972 > URL: https://issues.apache.org/jira/browse/SPARK-21972 > Project: Spark > Issue Type: Improvement > Components: ML, MLlib > Affects Versions: 2.2.0 > Reporter: Siddharth Murching > > Several Spark ML algorithms (LogisticRegression, LinearRegression, KMeans, > etc) call {{cache()}} on uncached input datasets to improve performance. > Unfortunately, these algorithms a) check input persistence inaccurately > ([SPARK-18608|https://issues.apache.org/jira/browse/SPARK-18608]) and b) > check the persistence level of the input dataset but not any of its parents. > These issues can result in unwanted double-caching of input data & degraded > performance (see > [SPARK-21799|https://issues.apache.org/jira/browse/SPARK-21799]). > This ticket proposes adding a boolean {{handlePersistence}} param > (org.apache.spark.ml.param) so that users can specify whether an ML algorithm > should try to cache un-cached input data. {{handlePersistence}} will be > {{true}} by default, corresponding to existing behavior (always persisting > uncached input), but users can achieve finer-grained control over input > persistence by setting {{handlePersistence}} to {{false}}. -- This message was sent by Atlassian JIRA (v6.4.14#64029) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org