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https://issues.apache.org/jira/browse/SPARK-1247?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Sean Owen resolved SPARK-1247.
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Resolution: Not a Problem
Yes, this already works on {{RDD[Int]}} for example via implicits, which
existed since 0.9 at least:
{code}
scala> val ints = sc.parallelize(Array(1,2,3))
ints: org.apache.spark.rdd.RDD[Int] = ParallelCollectionRDD[0] at parallelize
at <console>:21
scala> ints.mean
...
2.0
{code}
I think it may be prohibitive to specialize all this in Java, but, an RDD can
easily be manually mapped to {{Double}}s in Java.
> Support some of the RDD double functions on float and int as well.
> ------------------------------------------------------------------
>
> Key: SPARK-1247
> URL: https://issues.apache.org/jira/browse/SPARK-1247
> Project: Spark
> Issue Type: New Feature
> Components: Documentation, Java API, PySpark, Spark Core
> Affects Versions: 1.0.0
> Reporter: prashant
> Assignee: prashant
> Priority: Minor
>
> Pyspark is already agnostic, but currently Java and scala provides the
> implicit functions like stats/ histogram etc only if the RDD is on Double.
> This can be extended easily to support more numeric types.
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