Hi Roman, I am not absolutely convinced of #1, #2 and #3 to be the right way:
There must be a way to try out new versions and see the full mess without ploughing to all the big data universe. Right now I am seeing the mess. I was seriously running out of time: Having an unsupported spark1 version hanging around for some emergency situations seems a lot more worthwile than not to have spark2 at all. I seriously doubt anyone will support spark1 any more. If the majority likes to stay at the old versions, please revert. Olaf > Am 30.12.2016 um 06:46 schrieb Roman Shaposhnik <[email protected]>: > > Hi! > > as BIGTOP-2282 indicated it seems that we have a bit > of a difference in opinion on how major version bumps > in the stack need to be handled. Spark 1 vs 2 and Hive > 1 vs 2 are a good examples. > > Since JIRA is not always the best medium for a discussion > I wanted to get this back to the mailing list. > > My biggest question is actually around the goals/assumptions > that I wanted to validate with y'all. > > So, am I right in assuming that: > #1 our implicit bias is to NOT have multiple version of > the same component in a stack? > > #2 we try to figure out what version is THE version based > on how ready the component is to be integrated with the > rest of the stack > > #3 if somebody wants to do the work to support an extra > version -- that's fine, but that version gets the digit > as in spark1 and also that person gets to do all the work > > Thanks, > Roman.
