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https://issues.apache.org/jira/browse/SPARK-6168?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Mridul Muralidharan updated SPARK-6168:
---------------------------------------
    Description: 
It would be very useful to mark some of the collection and util classes we have 
as @DeveloperApi or even @Experimental.
For example :
- org.apache.spark.util.BoundedPriorityQueue
- org.apache.spark.util.collection.Utils
- org.apache.spark.util.collection.CompactBuffer

Usecases for these are for example to do a treeAggregate and/or treeReduce impl 
for common api's within RDD which fail due to limitations of aggregate/reduce 
at scale (ref: SPARK-6165).

Ofcourse, they are useful for other things too :-)

  was:

It would be very useful to mark some of the collection and util classes we have 
as @DeveloperApi or even @Experimental.
For example :
- org.apache.spark.util.BoundedPriorityQueue
- org.apache.spark.util.collection.Utils

Usecases for these are for example to do a treeAggregate and/or treeReduce impl 
for common api's within RDD which fail due to limitations of aggregate/reduce 
at scale (ref: SPARK-6165).

Ofcourse, they are useful for other things too :-)


> Expose some of the collection classes as DeveloperApi
> -----------------------------------------------------
>
>                 Key: SPARK-6168
>                 URL: https://issues.apache.org/jira/browse/SPARK-6168
>             Project: Spark
>          Issue Type: Improvement
>          Components: Spark Core
>    Affects Versions: 1.4.0
>            Reporter: Mridul Muralidharan
>            Priority: Minor
>
> It would be very useful to mark some of the collection and util classes we 
> have as @DeveloperApi or even @Experimental.
> For example :
> - org.apache.spark.util.BoundedPriorityQueue
> - org.apache.spark.util.collection.Utils
> - org.apache.spark.util.collection.CompactBuffer
> Usecases for these are for example to do a treeAggregate and/or treeReduce 
> impl for common api's within RDD which fail due to limitations of 
> aggregate/reduce at scale (ref: SPARK-6165).
> Ofcourse, they are useful for other things too :-)



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