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Posted to issues@spark.apache.org by "Felix Cheung (JIRA)" <ji...@apache.org> on 2017/09/18 04:45:00 UTC
[jira] [Commented] (SPARK-18131) Support returning Vector/Dense
Vector from backend
[ https://issues.apache.org/jira/browse/SPARK-18131?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16169579#comment-16169579 ]
Felix Cheung commented on SPARK-18131:
--------------------------------------
bump. I think this is a real big problem - results from mllib is basically unusable for R user:
{code}
ead(predict(model, test))$probability
[[1]]
Java ref type org.apache.spark.ml.linalg.DenseVector id 130
[[2]]
Java ref type org.apache.spark.ml.linalg.DenseVector id 131
[[3]]
Java ref type org.apache.spark.ml.linalg.DenseVector id 132
[[4]]
Java ref type org.apache.spark.ml.linalg.DenseVector id 133
[[5]]
Java ref type org.apache.spark.ml.linalg.DenseVector id 134
[[6]]
Java ref type org.apache.spark.ml.linalg.DenseVector id 135
> head(predict(model, test))$feature
[[1]]
Java ref type org.apache.spark.ml.linalg.SparseVector id 161
[[2]]
Java ref type org.apache.spark.ml.linalg.SparseVector id 162
[[3]]
Java ref type org.apache.spark.ml.linalg.SparseVector id 163
[[4]]
Java ref type org.apache.spark.ml.linalg.SparseVector id 164
[[5]]
Java ref type org.apache.spark.ml.linalg.SparseVector id 165
[[6]]
Java ref type org.apache.spark.ml.linalg.SparseVector id 166
> head(predict(model, test))$rawPrediction
[[1]]
Java ref type org.apache.spark.ml.linalg.DenseVector id 210
[[2]]
Java ref type org.apache.spark.ml.linalg.DenseVector id 211
[[3]]
Java ref type org.apache.spark.ml.linalg.DenseVector id 212
[[4]]
Java ref type org.apache.spark.ml.linalg.DenseVector id 213
...
{code}
> 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`.
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