GitHub user viirya opened a pull request:
https://github.com/apache/spark/pull/16633
[SPARK-19274][SQL] Make GlobalLimit without shuffling data to single
partition
## What changes were proposed in this pull request?
A logical `Limit` is performed actually by two physical operations
`LocalLimit` and `GlobalLimit`.
In most of time, before `GlobalLimit`, we will perform a shuffle exchange
to shuffle data to single partition. When the limit number is not trivially
small, this shuffling is costing.
This change tried to perform `GlobalLimit` without shuffling data to single
partition. The approach is similar to `SparkPlan.executeTake`. It iterates part
of partitions until it reaches enough data.
## How was this patch tested?
Jenkins tests.
Please review http://spark.apache.org/contributing.html before opening a
pull request.
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/viirya/spark-1 globallimit-without-shuffle
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/16633.patch
To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:
This closes #16633
----
commit b26488f77acf442db768b41f94bbda9773b523a2
Author: Liang-Chi Hsieh <[email protected]>
Date: 2017-01-18T08:21:17Z
Make GlobalLimit without shuffling data to single partition.
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