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ASF GitHub Bot commented on MAHOUT-1570: ---------------------------------------- Github user dlyubimov commented on a diff in the pull request: https://github.com/apache/mahout/pull/137#discussion_r40707550 --- Diff: math-scala/src/main/scala/org/apache/mahout/math/drm/logical/CheckpointAction.scala --- @@ -44,5 +44,6 @@ abstract class CheckpointAction[K: ClassTag] extends DrmLike[K] { case Some(cp) => cp } + val classTag = implicitly[ClassTag[K]] --- End diff -- yes you can't put implementation into trait. we'd have to make it optional for the trait (=???) and override in the concrete things. Concrete things are of course just of two types: logical operators based on the classes i already mentioned, that already have this support, and the checkpoint implementation, which probably does not yet. let me play with your branch a little to see what we can do. On Tue, Sep 29, 2015 at 11:10 AM, Alexey Grigorev <notificati...@github.com> wrote: > In > math-scala/src/main/scala/org/apache/mahout/math/drm/logical/CheckpointAction.scala > <https://github.com/apache/mahout/pull/137#discussion_r40706926>: > > > @@ -44,5 +44,6 @@ abstract class CheckpointAction[K: ClassTag] extends DrmLike[K] { > > case Some(cp) => cp > > } > > > > + val classTag = implicitly[ClassTag[K]] > > I remember trying to attach it to DrmLike, but I had some problems because > it's a trait > > — > Reply to this email directly or view it on GitHub > <https://github.com/apache/mahout/pull/137/files#r40706926>. > > Adding support for Apache Flink as a backend for the Mahout DSL > --------------------------------------------------------------- > > Key: MAHOUT-1570 > URL: https://issues.apache.org/jira/browse/MAHOUT-1570 > Project: Mahout > Issue Type: Improvement > Reporter: Till Rohrmann > Assignee: Alexey Grigorev > Labels: DSL, flink, scala > Fix For: 0.11.1 > > > With the finalized abstraction of the Mahout DSL plans from the backend > operations (MAHOUT-1529), it should be possible to integrate further backends > for the Mahout DSL. Apache Flink would be a suitable candidate to act as a > good execution backend. > With respect to the implementation, the biggest difference between Spark and > Flink at the moment is probably the incremental rollout of plans, which is > triggered by Spark's actions and which is not supported by Flink yet. > However, the Flink community is working on this issue. For the moment, it > should be possible to circumvent this problem by writing intermediate results > required by an action to HDFS and reading from there. -- This message was sent by Atlassian JIRA (v6.3.4#6332)