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https://issues.apache.org/jira/browse/MAHOUT-1896?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15762884#comment-15762884
]
ASF GitHub Bot commented on MAHOUT-1896:
----------------------------------------
Github user andrewpalumbo commented on a diff in the pull request:
https://github.com/apache/mahout/pull/263#discussion_r93156323
--- Diff:
spark/src/test/scala/org/apache/mahout/sparkbindings/drm/DrmLikeSuite.scala ---
@@ -63,6 +65,65 @@ class DrmLikeSuite extends FunSuite with
DistributedSparkSuite with DrmLikeSuite
throw new AssertionError("Block must be dense.")
keys -> block
}).norm should be < 1e-4
+
+ }
+
+ test("DRM wrap labeled points") {
+
+ import org.apache.spark.mllib.linalg.{Vectors => SparkVector}
+ import org.apache.spark.mllib.regression.LabeledPoint
+
+ val sc = mahoutCtx.asInstanceOf[SparkDistributedContext].sc
--- End diff --
A `MahoutDistributedContext` should be implicitly converted into a
SparkDistributedContext when it is needed. This could be written as :
``` val sc:SparkDistributedContext```
> Add convenience methods for interacting with Spark ML
> -----------------------------------------------------
>
> Key: MAHOUT-1896
> URL: https://issues.apache.org/jira/browse/MAHOUT-1896
> Project: Mahout
> Issue Type: Bug
> Affects Versions: 0.12.2
> Reporter: Trevor Grant
> Assignee: Trevor Grant
> Priority: Minor
> Fix For: 0.13.0
>
>
> Currently the method for ingesting RDDs to DRM is `drmWrap`. This is a
> flexible method, however there are many cases when the RDD to be wrapped is
> either RDD[org.apache.spark.mllib.lingalg.Vector],
> RDD[org.apache.spark.mllib.regression.LabeledPoint], or DataFrame[Row] (as is
> the case when working with SparkML. It makes sense to create convenience
> methods for converting these types to DRM.
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