I'm also in favor of this. Thanks for your persistence Cody. My take on the specific issues Joseph mentioned:
1) voting vs. consensus -- I agree with the argument Ryan Blue made earlier for consensus: > Majority vs consensus: My rationale is that I don't think we want to consider a proposal approved if it had objections serious enough that committers down-voted (or PMC depending on who gets a vote). If these proposals are like PEPs, then they represent a significant amount of community effort and I wouldn't want to move forward if up to half of the community thinks it's an untenable idea. 2) Design doc template -- agree this would be useful, but also seems totally orthogonal to moving forward on the SIP proposal. 3) agree w/ Joseph's proposal for updating the template. One small addition: 4) Deciding on a name -- minor, but I think its wroth disambiguating from Scala's SIPs, and the best proposal I've heard is "SPIP". At least, no one has objected. (don't care enough that I'd object to anything else, though.) On Tue, Jan 3, 2017 at 3:30 PM, Joseph Bradley <jos...@databricks.com> wrote: > Hi Cody, > > Thanks for being persistent about this. I too would like to see this > happen. Reviewing the thread, it sounds like the main things remaining are: > * Decide about a few issues > * Finalize the doc(s) > * Vote on this proposal > > Issues & TODOs: > > (1) The main issue I see above is voting vs. consensus. I have little > preference here. It sounds like something which could be tailored based on > whether we see too many or too few SIPs being approved. > > (2) Design doc template (This would be great to have for Spark regardless > of this SIP discussion.) > * Reynold, are you still putting this together? > > (3) Template cleanups. Listing some items mentioned above + a new one > w.r.t. Reynold's draft > <https://docs.google.com/document/d/1-Zdi_W-wtuxS9hTK0P9qb2x-nRanvXmnZ7SUi4qMljg/edit#> > : > * Reinstate the "Where" section with links to current and past SIPs > * Add field for stating explicit deadlines for approval > * Add field for stating Author & Committer shepherd > > Thanks all! > Joseph > > On Mon, Jan 2, 2017 at 7:45 AM, Cody Koeninger <c...@koeninger.org> wrote: > >> I'm bumping this one more time for the new year, and then I'm giving up. >> >> Please, fix your process, even if it isn't exactly the way I suggested. >> >> On Tue, Nov 8, 2016 at 11:14 AM, Ryan Blue <rb...@netflix.com> wrote: >> > On lazy consensus as opposed to voting: >> > >> > First, why lazy consensus? The proposal was for consensus, which is at >> least >> > three +1 votes and no vetos. Consensus has no losing side, it requires >> > getting to a point where there is agreement. Isn't that agreement what >> we >> > want to achieve with these proposals? >> > >> > Second, lazy consensus only removes the requirement for three +1 votes. >> Why >> > would we not want at least three committers to think something is a good >> > idea before adopting the proposal? >> > >> > rb >> > >> > On Tue, Nov 8, 2016 at 8:13 AM, Cody Koeninger <c...@koeninger.org> >> wrote: >> >> >> >> So there are some minor things (the Where section heading appears to >> >> be dropped; wherever this document is posted it needs to actually link >> >> to a jira filter showing current / past SIPs) but it doesn't look like >> >> I can comment on the google doc. >> >> >> >> The major substantive issue that I have is that this version is >> >> significantly less clear as to the outcome of an SIP. >> >> >> >> The apache example of lazy consensus at >> >> http://apache.org/foundation/voting.html#LazyConsensus involves an >> >> explicit announcement of an explicit deadline, which I think are >> >> necessary for clarity. >> >> >> >> >> >> >> >> On Mon, Nov 7, 2016 at 1:55 PM, Reynold Xin <r...@databricks.com> >> wrote: >> >> > It turned out suggested edits (trackable) don't show up for >> non-owners, >> >> > so >> >> > I've just merged all the edits in place. It should be visible now. >> >> > >> >> > On Mon, Nov 7, 2016 at 10:10 AM, Reynold Xin <r...@databricks.com> >> >> > wrote: >> >> >> >> >> >> Oops. Let me try figure that out. >> >> >> >> >> >> >> >> >> On Monday, November 7, 2016, Cody Koeninger <c...@koeninger.org> >> wrote: >> >> >>> >> >> >>> Thanks for picking up on this. >> >> >>> >> >> >>> Maybe I fail at google docs, but I can't see any edits on the >> document >> >> >>> you linked. >> >> >>> >> >> >>> Regarding lazy consensus, if the board in general has less of an >> issue >> >> >>> with that, sure. As long as it is clearly announced, lasts at >> least >> >> >>> 72 hours, and has a clear outcome. >> >> >>> >> >> >>> The other points are hard to comment on without being able to see >> the >> >> >>> text in question. >> >> >>> >> >> >>> >> >> >>> On Mon, Nov 7, 2016 at 3:11 AM, Reynold Xin <r...@databricks.com> >> >> >>> wrote: >> >> >>> > I just looked through the entire thread again tonight - there >> are a >> >> >>> > lot >> >> >>> > of >> >> >>> > great ideas being discussed. Thanks Cody for taking the first >> crack >> >> >>> > at >> >> >>> > the >> >> >>> > proposal. >> >> >>> > >> >> >>> > I want to first comment on the context. Spark is one of the most >> >> >>> > innovative >> >> >>> > and important projects in (big) data -- overall technical >> decisions >> >> >>> > made in >> >> >>> > Apache Spark are sound. But of course, a project as large and >> active >> >> >>> > as >> >> >>> > Spark always have room for improvement, and we as a community >> should >> >> >>> > strive >> >> >>> > to take it to the next level. >> >> >>> > >> >> >>> > To that end, the two biggest areas for improvements in my opinion >> >> >>> > are: >> >> >>> > >> >> >>> > 1. Visibility: There are so much happening that it is difficult >> to >> >> >>> > know >> >> >>> > what >> >> >>> > really is going on. For people that don't follow closely, it is >> >> >>> > difficult to >> >> >>> > know what the important initiatives are. Even for people that do >> >> >>> > follow, it >> >> >>> > is difficult to know what specific things require their >> attention, >> >> >>> > since the >> >> >>> > number of pull requests and JIRA tickets are high and it's >> difficult >> >> >>> > to >> >> >>> > extract signal from noise. >> >> >>> > >> >> >>> > 2. Solicit user (broadly defined, including developers >> themselves) >> >> >>> > input >> >> >>> > more proactively: At the end of the day the project provides >> value >> >> >>> > because >> >> >>> > users use it. Users can't tell us exactly what to build, but it >> is >> >> >>> > important >> >> >>> > to get their inputs. >> >> >>> > >> >> >>> > >> >> >>> > I've taken Cody's doc and edited it: >> >> >>> > >> >> >>> > >> >> >>> > https://docs.google.com/document/d/1-Zdi_W-wtuxS9hTK0P9qb2x- >> nRanvXmnZ7SUi4qMljg/edit#heading=h.36ut37zh7w2b >> >> >>> > (I've made all my modifications trackable) >> >> >>> > >> >> >>> > There are couple high level changes I made: >> >> >>> > >> >> >>> > 1. I've consulted a board member and he recommended lazy >> consensus >> >> >>> > as >> >> >>> > opposed to voting. The reason being in voting there can easily >> be a >> >> >>> > "loser' >> >> >>> > that gets outvoted. >> >> >>> > >> >> >>> > 2. I made it lighter weight, and renamed "strategy" to "optional >> >> >>> > design >> >> >>> > sketch". Echoing one of the earlier email: "IMHO so far aside >> from >> >> >>> > tagging >> >> >>> > things and linking them elsewhere simply having design docs and >> >> >>> > prototypes >> >> >>> > implementations in PRs is not something that has not worked so >> far". >> >> >>> > >> >> >>> > 3. I made some the language tweaks to focus more on visibility. >> For >> >> >>> > example, >> >> >>> > "The purpose of an SIP is to inform and involve", rather than >> just >> >> >>> > "involve". SIPs should also have at least two emails that go to >> >> >>> > dev@. >> >> >>> > >> >> >>> > >> >> >>> > While I was editing this, I thought we really needed a suggested >> >> >>> > template >> >> >>> > for design doc too. I will get to that too ... >> >> >>> > >> >> >>> > >> >> >>> > On Tue, Nov 1, 2016 at 12:09 AM, Reynold Xin < >> r...@databricks.com> >> >> >>> > wrote: >> >> >>> >> >> >> >>> >> Most things looked OK to me too, although I do plan to take a >> >> >>> >> closer >> >> >>> >> look >> >> >>> >> after Nov 1st when we cut the release branch for 2.1. >> >> >>> >> >> >> >>> >> >> >> >>> >> On Mon, Oct 31, 2016 at 3:12 PM, Marcelo Vanzin >> >> >>> >> <van...@cloudera.com> >> >> >>> >> wrote: >> >> >>> >>> >> >> >>> >>> The proposal looks OK to me. I assume, even though it's not >> >> >>> >>> explicitly >> >> >>> >>> called, that voting would happen by e-mail? A template for the >> >> >>> >>> proposal document (instead of just a bullet nice) would also be >> >> >>> >>> nice, >> >> >>> >>> but that can be done at any time. >> >> >>> >>> >> >> >>> >>> BTW, shameless plug: I filed SPARK-18085 which I consider a >> >> >>> >>> candidate >> >> >>> >>> for a SIP, given the scope of the work. The document attached >> even >> >> >>> >>> somewhat matches the proposed format. So if anyone wants to try >> >> >>> >>> out >> >> >>> >>> the process... >> >> >>> >>> >> >> >>> >>> On Mon, Oct 31, 2016 at 10:34 AM, Cody Koeninger >> >> >>> >>> <c...@koeninger.org> >> >> >>> >>> wrote: >> >> >>> >>> > Now that spark summit europe is over, are any committers >> >> >>> >>> > interested >> >> >>> >>> > in >> >> >>> >>> > moving forward with this? >> >> >>> >>> > >> >> >>> >>> > >> >> >>> >>> > >> >> >>> >>> > >> >> >>> >>> > https://github.com/koeninger/spark-1/blob/SIP-0/docs/spark-i >> mprovement-proposals.md >> >> >>> >>> > >> >> >>> >>> > Or are we going to let this discussion die on the vine? >> >> >>> >>> > >> >> >>> >>> > On Mon, Oct 17, 2016 at 10:05 AM, Tomasz Gawęda >> >> >>> >>> > <tomasz.gaw...@outlook.com> wrote: >> >> >>> >>> >> Maybe my mail was not clear enough. >> >> >>> >>> >> >> >> >>> >>> >> >> >> >>> >>> >> I didn't want to write "lets focus on Flink" or any other >> >> >>> >>> >> framework. >> >> >>> >>> >> The >> >> >>> >>> >> idea with benchmarks was to show two things: >> >> >>> >>> >> >> >> >>> >>> >> - why some people are doing bad PR for Spark >> >> >>> >>> >> >> >> >>> >>> >> - how - in easy way - we can change it and show that Spark >> is >> >> >>> >>> >> still on >> >> >>> >>> >> the >> >> >>> >>> >> top >> >> >>> >>> >> >> >> >>> >>> >> >> >> >>> >>> >> No more, no less. Benchmarks will be helpful, but I don't >> think >> >> >>> >>> >> they're the >> >> >>> >>> >> most important thing in Spark :) On the Spark main page >> there >> >> >>> >>> >> is >> >> >>> >>> >> still >> >> >>> >>> >> chart >> >> >>> >>> >> "Spark vs Hadoop". It is important to show that framework is >> >> >>> >>> >> not >> >> >>> >>> >> the >> >> >>> >>> >> same >> >> >>> >>> >> Spark with other API, but much faster and optimized, >> comparable >> >> >>> >>> >> or >> >> >>> >>> >> even >> >> >>> >>> >> faster than other frameworks. >> >> >>> >>> >> >> >> >>> >>> >> >> >> >>> >>> >> About real-time streaming, I think it would be just good to >> see >> >> >>> >>> >> it >> >> >>> >>> >> in >> >> >>> >>> >> Spark. >> >> >>> >>> >> I very like current Spark model, but many voices that says >> "we >> >> >>> >>> >> need >> >> >>> >>> >> more" - >> >> >>> >>> >> community should listen also them and try to help them. With >> >> >>> >>> >> SIPs >> >> >>> >>> >> it >> >> >>> >>> >> would >> >> >>> >>> >> be easier, I've just posted this example as "thing that may >> be >> >> >>> >>> >> changed >> >> >>> >>> >> with >> >> >>> >>> >> SIP". >> >> >>> >>> >> >> >> >>> >>> >> >> >> >>> >>> >> I very like unification via Datasets, but there is a lot of >> >> >>> >>> >> algorithms >> >> >>> >>> >> inside - let's make easy API, but with strong background >> >> >>> >>> >> (articles, >> >> >>> >>> >> benchmarks, descriptions, etc) that shows that Spark is >> still >> >> >>> >>> >> modern >> >> >>> >>> >> framework. >> >> >>> >>> >> >> >> >>> >>> >> >> >> >>> >>> >> Maybe now my intention will be clearer :) As I said >> >> >>> >>> >> organizational >> >> >>> >>> >> ideas >> >> >>> >>> >> were already mentioned and I agree with them, my mail was >> just >> >> >>> >>> >> to >> >> >>> >>> >> show >> >> >>> >>> >> some >> >> >>> >>> >> aspects from my side, so from theside of developer and >> person >> >> >>> >>> >> who >> >> >>> >>> >> is >> >> >>> >>> >> trying >> >> >>> >>> >> to help others with Spark (via StackOverflow or other ways) >> >> >>> >>> >> >> >> >>> >>> >> >> >> >>> >>> >> Pozdrawiam / Best regards, >> >> >>> >>> >> >> >> >>> >>> >> Tomasz >> >> >>> >>> >> >> >> >>> >>> >> >> >> >>> >>> >> ________________________________ >> >> >>> >>> >> Od: Cody Koeninger <c...@koeninger.org> >> >> >>> >>> >> Wysłane: 17 października 2016 16:46 >> >> >>> >>> >> Do: Debasish Das >> >> >>> >>> >> DW: Tomasz Gawęda; dev@spark.apache.org >> >> >>> >>> >> Temat: Re: Spark Improvement Proposals >> >> >>> >>> >> >> >> >>> >>> >> I think narrowly focusing on Flink or benchmarks is missing >> my >> >> >>> >>> >> point. >> >> >>> >>> >> >> >> >>> >>> >> My point is evolve or die. Spark's governance and >> organization >> >> >>> >>> >> is >> >> >>> >>> >> hampering its ability to evolve technologically, and it >> needs >> >> >>> >>> >> to >> >> >>> >>> >> change. >> >> >>> >>> >> >> >> >>> >>> >> On Sun, Oct 16, 2016 at 9:21 PM, Debasish Das >> >> >>> >>> >> <debasish.da...@gmail.com> >> >> >>> >>> >> wrote: >> >> >>> >>> >>> Thanks Cody for bringing up a valid point...I picked up >> Spark >> >> >>> >>> >>> in >> >> >>> >>> >>> 2014 >> >> >>> >>> >>> as >> >> >>> >>> >>> soon as I looked into it since compared to writing Java >> >> >>> >>> >>> map-reduce >> >> >>> >>> >>> and >> >> >>> >>> >>> Cascading code, Spark made writing distributed code >> fun...But >> >> >>> >>> >>> now >> >> >>> >>> >>> as >> >> >>> >>> >>> we >> >> >>> >>> >>> went >> >> >>> >>> >>> deeper with Spark and real-time streaming use-case gets >> more >> >> >>> >>> >>> prominent, I >> >> >>> >>> >>> think it is time to bring a messaging model in conjunction >> >> >>> >>> >>> with >> >> >>> >>> >>> the >> >> >>> >>> >>> batch/micro-batch API that Spark is good at....akka-streams >> >> >>> >>> >>> close >> >> >>> >>> >>> integration with spark micro-batching APIs looks like a >> great >> >> >>> >>> >>> direction to >> >> >>> >>> >>> stay in the game with Apache Flink...Spark 2.0 integrated >> >> >>> >>> >>> streaming >> >> >>> >>> >>> with >> >> >>> >>> >>> batch with the assumption is that micro-batching is >> sufficient >> >> >>> >>> >>> to >> >> >>> >>> >>> run >> >> >>> >>> >>> SQL >> >> >>> >>> >>> commands on stream but do we really have time to do SQL >> >> >>> >>> >>> processing at >> >> >>> >>> >>> streaming data within 1-2 seconds ? >> >> >>> >>> >>> >> >> >>> >>> >>> After reading the email chain, I started to look into Flink >> >> >>> >>> >>> documentation >> >> >>> >>> >>> and if you compare it with Spark documentation, I think we >> >> >>> >>> >>> have >> >> >>> >>> >>> major >> >> >>> >>> >>> work >> >> >>> >>> >>> to do detailing out Spark internals so that more people >> from >> >> >>> >>> >>> community >> >> >>> >>> >>> start >> >> >>> >>> >>> to take active role in improving the issues so that Spark >> >> >>> >>> >>> stays >> >> >>> >>> >>> strong >> >> >>> >>> >>> compared to Flink. >> >> >>> >>> >>> >> >> >>> >>> >>> >> >> >>> >>> >>> https://cwiki.apache.org/confluence/display/SPARK/Spark+ >> Internals >> >> >>> >>> >>> >> >> >>> >>> >>> >> >> >>> >>> >>> https://cwiki.apache.org/confluence/display/FLINK/Flink+ >> Internals >> >> >>> >>> >>> >> >> >>> >>> >>> Spark is no longer an engine that works for micro-batch and >> >> >>> >>> >>> batch...We >> >> >>> >>> >>> (and >> >> >>> >>> >>> I am sure many others) are pushing spark as an engine for >> >> >>> >>> >>> stream >> >> >>> >>> >>> and >> >> >>> >>> >>> query >> >> >>> >>> >>> processing.....we need to make it a state-of-the-art engine >> >> >>> >>> >>> for >> >> >>> >>> >>> high >> >> >>> >>> >>> speed >> >> >>> >>> >>> streaming data and user queries as well ! >> >> >>> >>> >>> >> >> >>> >>> >>> On Sun, Oct 16, 2016 at 1:30 PM, Tomasz Gawęda >> >> >>> >>> >>> <tomasz.gaw...@outlook.com> >> >> >>> >>> >>> wrote: >> >> >>> >>> >>>> >> >> >>> >>> >>>> Hi everyone, >> >> >>> >>> >>>> >> >> >>> >>> >>>> I'm quite late with my answer, but I think my suggestions >> may >> >> >>> >>> >>>> help a >> >> >>> >>> >>>> little bit. :) Many technical and organizational topics >> were >> >> >>> >>> >>>> mentioned, >> >> >>> >>> >>>> but I want to focus on these negative posts about Spark >> and >> >> >>> >>> >>>> about >> >> >>> >>> >>>> "haters" >> >> >>> >>> >>>> >> >> >>> >>> >>>> I really like Spark. Easy of use, speed, very good >> community >> >> >>> >>> >>>> - >> >> >>> >>> >>>> it's >> >> >>> >>> >>>> everything here. But Every project has to "flight" on >> >> >>> >>> >>>> "framework >> >> >>> >>> >>>> market" >> >> >>> >>> >>>> to be still no 1. I'm following many Spark and Big Data >> >> >>> >>> >>>> communities, >> >> >>> >>> >>>> maybe my mail will inspire someone :) >> >> >>> >>> >>>> >> >> >>> >>> >>>> You (every Spark developer; so far I didn't have enough >> time >> >> >>> >>> >>>> to >> >> >>> >>> >>>> join >> >> >>> >>> >>>> contributing to Spark) has done excellent job. So why are >> >> >>> >>> >>>> some >> >> >>> >>> >>>> people >> >> >>> >>> >>>> saying that Flink (or other framework) is better, like it >> was >> >> >>> >>> >>>> posted >> >> >>> >>> >>>> in >> >> >>> >>> >>>> this mailing list? No, not because that framework is >> better >> >> >>> >>> >>>> in >> >> >>> >>> >>>> all >> >> >>> >>> >>>> cases.. In my opinion, many of these discussions where >> >> >>> >>> >>>> started >> >> >>> >>> >>>> after >> >> >>> >>> >>>> Flink marketing-like posts. Please look at StackOverflow >> >> >>> >>> >>>> "Flink >> >> >>> >>> >>>> vs >> >> >>> >>> >>>> ...." >> >> >>> >>> >>>> posts, almost every post in "winned" by Flink. Answers are >> >> >>> >>> >>>> sometimes >> >> >>> >>> >>>> saying nothing about other frameworks, Flink's users >> (often >> >> >>> >>> >>>> PMC's) >> >> >>> >>> >>>> are >> >> >>> >>> >>>> just posting same information about real-time streaming, >> >> >>> >>> >>>> about >> >> >>> >>> >>>> delta >> >> >>> >>> >>>> iterations, etc. It look smart and very often it is >> marked as >> >> >>> >>> >>>> an >> >> >>> >>> >>>> aswer, >> >> >>> >>> >>>> even if - in my opinion - there wasn't told all the truth. >> >> >>> >>> >>>> >> >> >>> >>> >>>> >> >> >>> >>> >>>> My suggestion: I don't have enough money and knowledgle to >> >> >>> >>> >>>> perform >> >> >>> >>> >>>> huge >> >> >>> >>> >>>> performance test. Maybe some company, that supports Spark >> >> >>> >>> >>>> (Databricks, >> >> >>> >>> >>>> Cloudera? - just saying you're most visible in community >> :) ) >> >> >>> >>> >>>> could >> >> >>> >>> >>>> perform performance test of: >> >> >>> >>> >>>> >> >> >>> >>> >>>> - streaming engine - probably Spark will loose because of >> >> >>> >>> >>>> mini-batch >> >> >>> >>> >>>> model, however currently the difference should be much >> lower >> >> >>> >>> >>>> that in >> >> >>> >>> >>>> previous versions >> >> >>> >>> >>>> >> >> >>> >>> >>>> - Machine Learning models >> >> >>> >>> >>>> >> >> >>> >>> >>>> - batch jobs >> >> >>> >>> >>>> >> >> >>> >>> >>>> - Graph jobs >> >> >>> >>> >>>> >> >> >>> >>> >>>> - SQL queries >> >> >>> >>> >>>> >> >> >>> >>> >>>> People will see that Spark is envolving and is also a >> modern >> >> >>> >>> >>>> framework, >> >> >>> >>> >>>> because after reading posts mentioned above people may >> think >> >> >>> >>> >>>> "it >> >> >>> >>> >>>> is >> >> >>> >>> >>>> outdated, future is in framework X". >> >> >>> >>> >>>> >> >> >>> >>> >>>> Matei Zaharia posted excellent blog post about how Spark >> >> >>> >>> >>>> Structured >> >> >>> >>> >>>> Streaming beats every other framework in terms of >> easy-of-use >> >> >>> >>> >>>> and >> >> >>> >>> >>>> reliability. Performance tests, done in various >> environments >> >> >>> >>> >>>> (in >> >> >>> >>> >>>> example: laptop, small 2 node cluster, 10-node cluster, >> >> >>> >>> >>>> 20-node >> >> >>> >>> >>>> cluster), could be also very good marketing stuff to say >> >> >>> >>> >>>> "hey, >> >> >>> >>> >>>> you're >> >> >>> >>> >>>> telling that you're better, but Spark is still faster and >> is >> >> >>> >>> >>>> still >> >> >>> >>> >>>> getting even more fast!". This would be based on facts >> (just >> >> >>> >>> >>>> numbers), >> >> >>> >>> >>>> not opinions. It would be good for companies, for >> marketing >> >> >>> >>> >>>> puproses >> >> >>> >>> >>>> and >> >> >>> >>> >>>> for every Spark developer >> >> >>> >>> >>>> >> >> >>> >>> >>>> >> >> >>> >>> >>>> Second: real-time streaming. I've written some time ago >> about >> >> >>> >>> >>>> real-time >> >> >>> >>> >>>> streaming support in Spark Structured Streaming. Some work >> >> >>> >>> >>>> should be >> >> >>> >>> >>>> done to make SSS more low-latency, but I think it's >> possible. >> >> >>> >>> >>>> Maybe >> >> >>> >>> >>>> Spark may look at Gearpump, which is also built on top of >> >> >>> >>> >>>> Akka? >> >> >>> >>> >>>> I >> >> >>> >>> >>>> don't >> >> >>> >>> >>>> know yet, it is good topic for SIP. However I think that >> >> >>> >>> >>>> Spark >> >> >>> >>> >>>> should >> >> >>> >>> >>>> have real-time streaming support. Currently I see many >> >> >>> >>> >>>> posts/comments >> >> >>> >>> >>>> that "Spark has too big latency". Spark Streaming is doing >> >> >>> >>> >>>> very >> >> >>> >>> >>>> good >> >> >>> >>> >>>> jobs with micro-batches, however I think it is possible to >> >> >>> >>> >>>> add >> >> >>> >>> >>>> also >> >> >>> >>> >>>> more >> >> >>> >>> >>>> real-time processing. >> >> >>> >>> >>>> >> >> >>> >>> >>>> Other people said much more and I agree with proposal of >> SIP. >> >> >>> >>> >>>> I'm >> >> >>> >>> >>>> also >> >> >>> >>> >>>> happy that PMC's are not saying that they will not listen >> to >> >> >>> >>> >>>> users, >> >> >>> >>> >>>> but >> >> >>> >>> >>>> they really want to make Spark better for every user. >> >> >>> >>> >>>> >> >> >>> >>> >>>> >> >> >>> >>> >>>> What do you think about these two topics? Especially I'm >> >> >>> >>> >>>> looking >> >> >>> >>> >>>> at >> >> >>> >>> >>>> Cody >> >> >>> >>> >>>> (who has started this topic) and PMCs :) >> >> >>> >>> >>>> >> >> >>> >>> >>>> Pozdrawiam / Best regards, >> >> >>> >>> >>>> >> >> >>> >>> >>>> Tomasz >> >> >>> >>> >>>> >> >> >>> >>> >>>> >> >> >>> >>> >> >> >>> >> >> >> >>> > >> >> >>> > >> >> > >> >> > >> >> >> >> --------------------------------------------------------------------- >> >> To unsubscribe e-mail: dev-unsubscr...@spark.apache.org >> >> >> > >> > >> > >> > -- >> > Ryan Blue >> > Software Engineer >> > Netflix >> >> --------------------------------------------------------------------- >> To unsubscribe e-mail: dev-unsubscr...@spark.apache.org >> >> > > > -- > > Joseph Bradley > > Software Engineer - Machine Learning > > Databricks, Inc. > > [image: http://databricks.com] <http://databricks.com/> >
