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Shivaram Venkataraman commented on SPARK-18131: ----------------------------------------------- Hmm - this is tricky. We ran into a similar issue in SQL and we added a reader, writer object in SQL that was registered to the method in core. See https://github.com/apache/spark/blob/ce112cec4f9bff222aa256893f94c316662a2a7e/sql/core/src/main/scala/org/apache/spark/sql/api/r/SQLUtils.scala#L39 for how we did that. We could do a similar thing in MLlib as well ? cc [~mengxr] > Support returning Vector/Dense Vector from backend > -------------------------------------------------- > > Key: SPARK-18131 > URL: https://issues.apache.org/jira/browse/SPARK-18131 > Project: Spark > Issue Type: New Feature > Components: SparkR > Reporter: Miao Wang > > For `spark.logit`, there is a `probabilityCol`, which is a vector in the > backend (scala side). When we do collect(select(df, "probabilityCol")), > backend returns the java object handle (memory address). We need to implement > a method to convert a Vector/Dense Vector column as R vector, which can be > read in SparkR. It is a followup JIRA of adding `spark.logit`. -- This message was sent by Atlassian JIRA (v6.3.15#6346) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org