+1 on longer release cycle at schedule and more maintenance releases.
_____________________________ From: Mark Hamstra <m...@clearstorydata.com<mailto:m...@clearstorydata.com>> Sent: Tuesday, September 27, 2016 2:01 PM Subject: Re: [discuss] Spark 2.x release cadence To: Reynold Xin <r...@databricks.com<mailto:r...@databricks.com>> Cc: <dev@spark.apache.org<mailto:dev@spark.apache.org>> +1 And I'll dare say that for those with Spark in production, what is more important is that maintenance releases come out in a timely fashion than that new features are released one month sooner or later. On Tue, Sep 27, 2016 at 12:06 PM, Reynold Xin <r...@databricks.com<mailto:r...@databricks.com>> wrote: We are 2 months past releasing Spark 2.0.0, an important milestone for the project. Spark 2.0.0 deviated (took 6 month from the regular release cadence we had for the 1.x line, and we never explicitly discussed what the release cadence should look like for 2.x. Thus this email. During Spark 1.x, roughly every three months we make a new 1.x feature release (e.g. 1.5.0 comes out three months after 1.4.0). Development happened primarily in the first two months, and then a release branch was cut at the end of month 2, and the last month was reserved for QA and release preparation. During 2.0.0 development, I really enjoyed the longer release cycle because there was a lot of major changes happening and the longer time was critical for thinking through architectural changes as well as API design. While I don't expect the same degree of drastic changes in a 2.x feature release, I do think it'd make sense to increase the length of release cycle so we can make better designs. My strawman proposal is to maintain a regular release cadence, as we did in Spark 1.x, and increase the cycle from 3 months to 4 months. This effectively gives us ~50% more time to develop (in reality it'd be slightly less than 50% since longer dev time also means longer QA time). As for maintenance releases, I think those should still be cut on-demand, similar to Spark 1.x, but more aggressively. To put this into perspective, 4-month cycle means we will release Spark 2.1.0 at the end of Nov or early Dec (and branch cut / code freeze at the end of Oct). I am curious what others think.
