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https://issues.apache.org/jira/browse/SPARK-15027?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15269218#comment-15269218
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Xiangrui Meng commented on SPARK-15027:
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Ah, I see the problems now. We do need the hash partitioner to accelerate
queries from the driver and probably joins. What if we convert the factors
using `repartition(blocks, "id")` before we return the factors? It should come
with a hash partitioner, but it might be different from the one we used in ALS.
#2 seems like a bug. Could you provide a minimal example that can reproduce it?
Given the pending issues, it seems that we should target this to 2.1. Sounds
good?
> ALS.train should use DataFrame instead of RDD
> ---------------------------------------------
>
> Key: SPARK-15027
> URL: https://issues.apache.org/jira/browse/SPARK-15027
> Project: Spark
> Issue Type: Improvement
> Components: ML, PySpark
> Affects Versions: 2.0.0
> Reporter: Xiangrui Meng
>
> We should also update `ALS.train` to use `Dataset/DataFrame` instead of `RDD`
> to be consistent with other APIs under spark.ml and it also leaves space for
> Tungsten-based optimization.
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