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[SPARK-15123] upgrade org.json4s to 3.2.11 version - #12901
Conversation
srowen
commented
May 4, 2016
I think this will fail because this doesn't update the dependencies file. It doesn't look like there are any incompatible changes, so this seems OK. |
srowen
commented
May 4, 2016
Jenkins test this please |
SparkQA
commented
May 4, 2016
Test build #57783 has finished for PR 12901 at commit
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liningalex
commented
May 4, 2016
pushed the changes: commit 23fb07f dev/deps/spark-deps-hadoop-2.2 On Wed, May 4, 2016 at 11:36 AM, Apache Spark QA notifications@github.com
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srowen
commented
May 4, 2016
I can tell you you'll need to update all of the deps files, not just one. You also don't have to post a message about the commits. |
liningalex
commented
May 4, 2016
should have pushed all deps files. thanks. On Wed, May 4, 2016 at 11:59 AM, Sean Owen notifications@github.com wrote:
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srowen
commented
May 4, 2016
Jenkins retest this please |
SparkQA
commented
May 4, 2016
Test build #57789 has finished for PR 12901 at commit
|
srowen
commented
May 4, 2016
Jenkins retest this please |
SparkQA
commented
May 4, 2016
Test build #57792 has finished for PR 12901 at commit
|
## What changes were proposed in this pull request? We had the issue when using snowplow in our Spark applications. Snowplow requires json4s version 3.2.11 while Spark still use a few years old version 3.2.10. The change is to upgrade json4s jar to 3.2.11. ## How was this patch tested? We built Spark jar and successfully ran our applications in local and cluster modes. Author: Lining Sun <lining@gmail.com> Closes#12901 from liningalex/master. (cherry picked from commit 592fc45) Signed-off-by: Sean Owen <sowen@cloudera.com>
srowen
commented
May 5, 2016
merged to master/2.0 |
What changes were proposed in this pull request?
We had the issue when using snowplow in our Spark applications. Snowplow requires json4s version 3.2.11 while Spark still use a few years old version 3.2.10. The change is to upgrade json4s jar to 3.2.11.
How was this patch tested?
We built Spark jar and successfully ran our applications in local and cluster modes.