Yesterday, the 2.4 branch was created. Based on the above discussion, I think we can bump the master branch to 3.0.0-SNAPSHOT. Any concern?
Thanks, Xiao vaquar khan <vaquar.k...@gmail.com> 于2018年6月16日周六 上午10:21写道： > +1 for 2.4 next, followed by 3.0. > > Where we can get Apache Spark road map for 2.4 and 2.5 .... 3.0 ? > is it possible we can share future release proposed specification same > like releases (https://spark.apache.org/releases/spark-release-2-3-0.html > ) > Regards, > Viquar khan > > On Sat, Jun 16, 2018 at 12:02 PM, vaquar khan <vaquar.k...@gmail.com> > wrote: > >> Plz ignore last email link (you tube )not sure how it added . >> Apologies not sure how to delete it. >> >> >> On Sat, Jun 16, 2018 at 11:58 AM, vaquar khan <vaquar.k...@gmail.com> >> wrote: >> >>> +1 >>> >>> https://www.youtube.com/watch?v=-ik7aJ5U6kg >>> >>> Regards, >>> Vaquar khan >>> >>> On Fri, Jun 15, 2018 at 4:55 PM, Reynold Xin <r...@databricks.com> >>> wrote: >>> >>>> Yes. At this rate I think it's better to do 2.4 next, followed by 3.0. >>>> >>>> >>>> On Fri, Jun 15, 2018 at 10:52 AM Mridul Muralidharan <mri...@gmail.com> >>>> wrote: >>>> >>>>> I agree, I dont see pressing need for major version bump as well. >>>>> >>>>> >>>>> Regards, >>>>> Mridul >>>>> On Fri, Jun 15, 2018 at 10:25 AM Mark Hamstra <m...@clearstorydata.com> >>>>> wrote: >>>>> > >>>>> > Changing major version numbers is not about new features or a vague >>>>> notion that it is time to do something that will be seen to be a >>>>> significant release. It is about breaking stable public APIs. >>>>> > >>>>> > I still remain unconvinced that the next version can't be 2.4.0. >>>>> > >>>>> > On Fri, Jun 15, 2018 at 1:34 AM Andy <andyye...@gmail.com> wrote: >>>>> >> >>>>> >> Dear all: >>>>> >> >>>>> >> It have been 2 months since this topic being proposed. Any progress >>>>> now? 2018 has been passed about 1/2. >>>>> >> >>>>> >> I agree with that the new version should be some exciting new >>>>> feature. How about this one: >>>>> >> >>>>> >> 6. ML/DL framework to be integrated as core component and feature. >>>>> (Such as Angel / BigDL / ……) >>>>> >> >>>>> >> 3.0 is a very important version for an good open source project. It >>>>> should be better to drift away the historical burden and focus in new >>>>> area. >>>>> Spark has been widely used all over the world as a successful big data >>>>> framework. And it can be better than that. >>>>> >> >>>>> >> Andy >>>>> >> >>>>> >> >>>>> >> On Thu, Apr 5, 2018 at 7:20 AM Reynold Xin <r...@databricks.com> >>>>> wrote: >>>>> >>> >>>>> >>> There was a discussion thread on scala-contributors about Apache >>>>> Spark not yet supporting Scala 2.12, and that got me to think perhaps it >>>>> is >>>>> about time for Spark to work towards the 3.0 release. By the time it comes >>>>> out, it will be more than 2 years since Spark 2.0. >>>>> >>> >>>>> >>> For contributors less familiar with Spark’s history, I want to >>>>> give more context on Spark releases: >>>>> >>> >>>>> >>> 1. Timeline: Spark 1.0 was released May 2014. Spark 2.0 was July >>>>> 2016. If we were to maintain the ~ 2 year cadence, it is time to work on >>>>> Spark 3.0 in 2018. >>>>> >>> >>>>> >>> 2. Spark’s versioning policy promises that Spark does not break >>>>> stable APIs in feature releases (e.g. 2.1, 2.2). API breaking changes are >>>>> sometimes a necessary evil, and can be done in major releases (e.g. 1.6 to >>>>> 2.0, 2.x to 3.0). >>>>> >>> >>>>> >>> 3. That said, a major version isn’t necessarily the playground for >>>>> disruptive API changes to make it painful for users to update. The main >>>>> purpose of a major release is an opportunity to fix things that are broken >>>>> in the current API and remove certain deprecated APIs. >>>>> >>> >>>>> >>> 4. Spark as a project has a culture of evolving architecture and >>>>> developing major new features incrementally, so major releases are not the >>>>> only time for exciting new features. For example, the bulk of the work in >>>>> the move towards the DataFrame API was done in Spark 1.3, and Continuous >>>>> Processing was introduced in Spark 2.3. Both were feature releases rather >>>>> than major releases. >>>>> >>> >>>>> >>> >>>>> >>> You can find more background in the thread discussing Spark 2.0: >>>>> http://apache-spark-developers-list.1001551.n3.nabble.com/A-proposal-for-Spark-2-0-td15122.html >>>>> >>> >>>>> >>> >>>>> >>> The primary motivating factor IMO for a major version bump is to >>>>> support Scala 2.12, which requires minor API breaking changes to Spark’s >>>>> APIs. Similar to Spark 2.0, I think there are also opportunities for other >>>>> changes that we know have been biting us for a long time but can’t be >>>>> changed in feature releases (to be clear, I’m actually not sure they are >>>>> all good ideas, but I’m writing them down as candidates for >>>>> consideration): >>>>> >>> >>>>> >>> 1. Support Scala 2.12. >>>>> >>> >>>>> >>> 2. Remove interfaces, configs, and modules (e.g. Bagel) deprecated >>>>> in Spark 2.x. >>>>> >>> >>>>> >>> 3. Shade all dependencies. >>>>> >>> >>>>> >>> 4. Change the reserved keywords in Spark SQL to be more ANSI-SQL >>>>> compliant, to prevent users from shooting themselves in the foot, e.g. >>>>> “SELECT 2 SECOND” -- is “SECOND” an interval unit or an alias? To make it >>>>> less painful for users to upgrade here, I’d suggest creating a flag for >>>>> backward compatibility mode. >>>>> >>> >>>>> >>> 5. Similar to 4, make our type coercion rule in DataFrame/SQL more >>>>> standard compliant, and have a flag for backward compatibility. >>>>> >>> >>>>> >>> 6. Miscellaneous other small changes documented in JIRA already >>>>> (e.g. “JavaPairRDD flatMapValues requires function returning Iterable, not >>>>> Iterator”, “Prevent column name duplication in temporary view”). >>>>> >>> >>>>> >>> >>>>> >>> Now the reality of a major version bump is that the world often >>>>> thinks in terms of what exciting features are coming. I do think there are >>>>> a number of major changes happening already that can be part of the 3.0 >>>>> release, if they make it in: >>>>> >>> >>>>> >>> 1. Scala 2.12 support (listing it twice) >>>>> >>> 2. Continuous Processing non-experimental >>>>> >>> 3. Kubernetes support non-experimental >>>>> >>> 4. A more flushed out version of data source API v2 (I don’t think >>>>> it is realistic to stabilize that in one release) >>>>> >>> 5. Hadoop 3.0 support >>>>> >>> 6. ... >>>>> >>> >>>>> >>> >>>>> >>> >>>>> >>> Similar to the 2.0 discussion, this thread should focus on the >>>>> framework and whether it’d make sense to create Spark 3.0 as the next >>>>> release, rather than the individual feature requests. Those are important >>>>> but are best done in their own separate threads. >>>>> >>> >>>>> >>> >>>>> >>> >>>>> >>> >>>>> >>>> >>> >>> >>> -- >>> Regards, >>> Vaquar Khan >>> +1 -224-436-0783 >>> Greater Chicago >>> >> >> >> >> -- >> Regards, >> Vaquar Khan >> +1 -224-436-0783 >> Greater Chicago >> > > > > -- > Regards, > Vaquar Khan > +1 -224-436-0783 > Greater Chicago >
