Github user tgravescs commented on the pull request: https://github.com/apache/spark/pull/7943#issuecomment-128126795 So Yarn Resourcemanager, Nodemanager and MapReduce shuffle handler all use level db. We have been running them for quite while and doing rolling upgrades without problems so I'm pretty confident in levelDB at this point. Also on the stopApplications, the MapReduce shuffle handler is relying on that and we run tens to hundreds of thousands of jobs a day and haven't seen any issues. I'll take another look at the MR code to make sure I didn't miss anything special they were doing. That combined with machines going down frequently and us doing rolling upgrades makes me pretty confident its working there too. One of the main things I want to do is make sure whatever we do if compatible with various versions of Spark. The nodemanagers are only going to be running one version of the shuffle handler so it has to work across versions (Spark 1.4, 1.5, 16, etc). At some point we may have to change the format and we can do this by storing some sort of version and schema of the data store and checking for compatibility when upgrading. We wouldn't have to do that now as long as the next version that changes handles it. The MR shuffle handles has code in there for this now but I don't think its ever changed versions at this point.
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