GitHub user Ru-Xiang opened a pull request:
https://github.com/apache/spark/pull/16033
SPARK-18607 get a result on a percent of the tasks succeed
## What changes were proposed in this pull request?
In this patch, we modify the codes corresponding to runApproximateJob so
that we can get a result when the specified percent of tasks succeed.
In a production environment, 'long tail' is a common urgent problem. In
practice, as long as we can get a specified percent of tasks' results, we can
guarantee the final results. And this is a common requirement in the practice
of machine learning algorithms.
## How was this patch tested?
We compile the codes by dev/make-distribution.sh, and deploy it on a
cluster. and run a test codes reduce on the cluster, and we get the desired
results.
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/Ru-Xiang/spark my_change
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/16033.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 #16033
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