GitHub user zsxwing opened a pull request:
https://github.com/apache/spark/pull/15820
[SPARK-18373][SS][Kafka]Make failOnDataLoss=false work with Spark jobs
## What changes were proposed in this pull request?
This PR adds `CachedKafkaConsumer.getAndIgnoreLostData` to handle corner
cases of `failOnDataLoss=false`. I listed all kinds of cases we should support
in the code comment.
## How was this patch tested?
Because I cannot find any way to manually control the Kafka server to clean
up logs, it's impossible to write unit tests for each corner cases. Therefore,
I just created `test("stress test for failOnDataLoss=false")` which should
cover most of corner cases.
I also modified some existing tests to test for both `failOnDataLoss=false`
and `failOnDataLoss=true` to make sure it doesn't break existing logic.
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/zsxwing/spark failOnDataLoss
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/15820.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 #15820
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commit e8eff9ff3b32320ab8d969089cded97e9ec29a52
Author: Shixiong Zhu <[email protected]>
Date: 2016-10-28T17:46:54Z
Make failOnDataLoss=false stable for Spark jobs
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