Metamorphosis...nice. :) This has been a great discussion. As a user of Samza who's recently integrated it into a relatively large organization, I just want to add support to a few points already made.
The biggest hurdles to adoption of Samza as it currently exists that I've experienced are: 1) YARN - YARN is overly complex in many environments where Puppet would do just fine but it was the only mechanism to get fault tolerance. 2) Configuration - I think I like the idea of configuring most of the job in code rather than config files. In general, I think the goal should be to make it harder to make mistakes, especially of the kind where the code expects something and the config doesn't match. The current config is quite intricate and error-prone. For example, the application logic may depend on bootstrapping a topic but rather than asserting that in the code, you have to rely on getting the config right. Likewise with serdes, the Java representations produced by various serdes (JSON, Avro, etc.) are not equivalent so you cannot just reconfigure a serde without changing the code. It would be nice for jobs to be able to assert what they expect from their input topics in terms of partitioning. This is getting a little off topic but I was even thinking about creating a "Samza config linter" that would sanity check a set of configs. Especially in organizations where config is managed by a different team than the application developer, it's very hard to get avoid config mistakes. 3) Java/Scala centric - for many teams (especially DevOps-type folks), the pain of the Java toolchain (maven, slow builds, weak command line support, configuration over convention) really inhibits productivity. As more and more high-quality clients become available for Kafka, I hope they'll follow Samza's model. Not sure how much it affects the proposals in this thread but please consider other languages in the ecosystem as well. From what I've heard, Spark has more Python users than Java/Scala. (FYI, we added a Jython wrapper for the Samza API https://github.com/Quantiply/rico/tree/master/jython/src/main/java/com/quantiply/samza and are working on a Yeoman generator https://github.com/Quantiply/generator-rico for Jython/Samza projects to alleviate some of the pain) I also want to underscore Jay's point about improving the user experience. That's a very important factor for adoption. I think the goal should be to make Samza as easy to get started with as something like Logstash. Logstash is vastly inferior in terms of capabilities to Samza but it's easy to get started and that makes a big difference. Cheers, Roger On Tue, Jul 7, 2015 at 3:29 AM, Gianmarco De Francisci Morales < g...@apache.org> wrote: > Forgot to add. On the naming issues, Kafka Metamorphosis is a clear winner > :) > > -- > Gianmarco > > On 7 July 2015 at 13:26, Gianmarco De Francisci Morales <g...@apache.org> > wrote: > > > Hi, > > > > @Martin, thanks for you comments. > > Maybe I'm missing some important point, but I think coupling the releases > > is actually a *good* thing. > > To make an example, would it be better if the MR and HDFS components of > > Hadoop had different release schedules? > > > > Actually, keeping the discussion in a single place would make agreeing on > > releases (and backwards compatibility) much easier, as everybody would be > > responsible for the whole codebase. > > > > That said, I like the idea of absorbing samza-core as a sub-project, and > > leave the fancy stuff separate. > > It probably gives 90% of the benefits we have been discussing here. > > > > Cheers, > > > > -- > > Gianmarco > > > > On 7 July 2015 at 02:30, Jay Kreps <jay.kr...@gmail.com> wrote: > > > >> Hey Martin, > >> > >> I agree coupling release schedules is a downside. > >> > >> Definitely we can try to solve some of the integration problems in > >> Confluent Platform or in other distributions. But I think this ends up > >> being really shallow. I guess I feel to really get a good user > experience > >> the two systems have to kind of feel like part of the same thing and you > >> can't really add that in later--you can put both in the same > downloadable > >> tar file but it doesn't really give a very cohesive feeling. I agree > that > >> ultimately any of the project stuff is as much social and naming as > >> anything else--theoretically two totally independent projects could work > >> to > >> tightly align. In practice this seems to be quite difficult though. > >> > >> For the frameworks--totally agree it would be good to maintain the > >> framework support with the project. In some cases there may not be too > >> much > >> there since the integration gets lighter but I think whatever stubs you > >> need should be included. So no I definitely wasn't trying to imply > >> dropping > >> support for these frameworks, just making the integration lighter by > >> separating process management from partition management. > >> > >> You raise two good points we would have to figure out if we went down > the > >> alignment path: > >> 1. With respect to the name, yeah I think the first question is whether > >> some "re-branding" would be worth it. If so then I think we can have a > big > >> thread on the name. I'm definitely not set on Kafka Streaming or Kafka > >> Streams I was just using them to be kind of illustrative. I agree with > >> your > >> critique of these names, though I think people would get the idea. > >> 2. Yeah you also raise a good point about how to "factor" it. Here are > the > >> options I see (I could get enthusiastic about any of them): > >> a. One repo for both Kafka and Samza > >> b. Two repos, retaining the current seperation > >> c. Two repos, the equivalent of samza-api and samza-core is absorbed > >> almost like a third client > >> > >> Cheers, > >> > >> -Jay > >> > >> On Mon, Jul 6, 2015 at 1:18 PM, Martin Kleppmann <mar...@kleppmann.com> > >> wrote: > >> > >> > Ok, thanks for the clarifications. Just a few follow-up comments. > >> > > >> > - I see the appeal of merging with Kafka or becoming a subproject: the > >> > reasons you mention are good. The risk I see is that release schedules > >> > become coupled to each other, which can slow everyone down, and large > >> > projects with many contributors are harder to manage. (Jakob, can you > >> speak > >> > from experience, having seen a wider range of Hadoop ecosystem > >> projects?) > >> > > >> > Some of the goals of a better unified developer experience could also > be > >> > solved by integrating Samza nicely into a Kafka distribution (such as > >> > Confluent's). I'm not against merging projects if we decide that's the > >> way > >> > to go, just pointing out the same goals can perhaps also be achieved > in > >> > other ways. > >> > > >> > - With regard to dropping the YARN dependency: are you proposing that > >> > Samza doesn't give any help to people wanting to run on > >> YARN/Mesos/AWS/etc? > >> > So the docs would basically have a link to Slider and nothing else? Or > >> > would we maintain integrations with a bunch of popular deployment > >> methods > >> > (e.g. the necessary glue and shell scripts to make Samza work with > >> Slider)? > >> > > >> > I absolutely think it's a good idea to have the "as a library" and > "as a > >> > process" (using Yi's taxonomy) options for people who want them, but I > >> > think there should also be a low-friction path for common "as a > service" > >> > deployment methods, for which we probably need to maintain > integrations. > >> > > >> > - Project naming: "Kafka Streams" seems odd to me, because Kafka is > all > >> > about streams already. Perhaps "Kafka Transformers" or "Kafka Filters" > >> > would be more apt? > >> > > >> > One suggestion: perhaps the core of Samza (stream transformation with > >> > state management -- i.e. the "Samza as a library" bit) could become > >> part of > >> > Kafka, while higher-level tools such as streaming SQL and integrations > >> with > >> > deployment frameworks remain in a separate project? In other words, > >> Kafka > >> > would absorb the proven, stable core of Samza, which would become the > >> > "third Kafka client" mentioned early in this thread. The Samza project > >> > would then target that third Kafka client as its base API, and the > >> project > >> > would be freed up to explore more experimental new horizons. > >> > > >> > Martin > >> > > >> > On 6 Jul 2015, at 18:51, Jay Kreps <jay.kr...@gmail.com> wrote: > >> > > >> > > Hey Martin, > >> > > > >> > > For the YARN/Mesos/etc decoupling I actually don't think it ties our > >> > hands > >> > > at all, all it does is refactor things. The division of > >> responsibility is > >> > > that Samza core is responsible for task lifecycle, state, and > >> partition > >> > > management (using the Kafka co-ordinator) but it is NOT responsible > >> for > >> > > packaging, configuration deployment or execution of processes. The > >> > problem > >> > > of packaging and starting these processes is > >> > > framework/environment-specific. This leaves individual frameworks to > >> be > >> > as > >> > > fancy or vanilla as they like. So you can get simple stateless > >> support in > >> > > YARN, Mesos, etc using their off-the-shelf app framework (Slider, > >> > Marathon, > >> > > etc). These are well known by people and have nice UIs and a lot of > >> > > flexibility. I don't think they have node affinity as a built in > >> option > >> > > (though I could be wrong). So if we want that we can either wait for > >> them > >> > > to add it or do a custom framework to add that feature (as now). > >> > Obviously > >> > > if you manage things with old-school ops tools (puppet/chef/etc) you > >> get > >> > > locality easily. The nice thing, though, is that all the samza > >> "business > >> > > logic" around partition management and fault tolerance is in Samza > >> core > >> > so > >> > > it is shared across frameworks and the framework specific bit is > just > >> > > whether it is smart enough to try to get the same host when a job is > >> > > restarted. > >> > > > >> > > With respect to the Kafka-alignment, yeah I think the goal would be > >> (a) > >> > > actually get better alignment in user experience, and (b) express > >> this in > >> > > the naming and project branding. Specifically: > >> > > 1. Website/docs, it would be nice for the "transformation" api to be > >> > > discoverable in the main Kafka docs--i.e. be able to explain when to > >> use > >> > > the consumer and when to use the stream processing functionality and > >> lead > >> > > people into that experience. > >> > > 2. Align releases so if you get Kafkza 1.4.2 (or whatever) that has > >> both > >> > > Kafka and the stream processing part and they actually work > together. > >> > > 3. Unify the programming experience so the client and Samza api > share > >> > > config/monitoring/naming/packaging/etc. > >> > > > >> > > I think sub-projects keep separate committers and can have a > separate > >> > repo, > >> > > but I'm actually not really sure (I can't find a definition of a > >> > subproject > >> > > in Apache). > >> > > > >> > > Basically at a high-level you want the experience to "feel" like a > >> single > >> > > system, not to relatively independent things that are kind of > >> awkwardly > >> > > glued together. > >> > > > >> > > I think if we did that they having naming or branding like "kafka > >> > > streaming" or "kafka streams" or something like that would actually > >> do a > >> > > good job of conveying what it is. I do that this would help adoption > >> > quite > >> > > a lot as it would correctly convey that using Kafka Streaming with > >> Kafka > >> > is > >> > > a fairly seamless experience and Kafka is pretty heavily adopted at > >> this > >> > > point. > >> > > > >> > > Fwiw we actually considered this model originally when open sourcing > >> > Samza, > >> > > however at that time Kafka was relatively unknown and we decided not > >> to > >> > do > >> > > it since we felt it would be limiting. From my point of view the > three > >> > > things have changed (1) Kafka is now really heavily used for stream > >> > > processing, (2) we learned that abstracting out the stream well is > >> > > basically impossible, (3) we learned it is really hard to keep the > two > >> > > things feeling like a single product. > >> > > > >> > > -Jay > >> > > > >> > > > >> > > On Mon, Jul 6, 2015 at 3:37 AM, Martin Kleppmann < > >> mar...@kleppmann.com> > >> > > wrote: > >> > > > >> > >> Hi all, > >> > >> > >> > >> Lots of good thoughts here. > >> > >> > >> > >> I agree with the general philosophy of tying Samza more firmly to > >> Kafka. > >> > >> After I spent a while looking at integrating other message brokers > >> (e.g. > >> > >> Kinesis) with SystemConsumer, I came to the conclusion that > >> > SystemConsumer > >> > >> tacitly assumes a model so much like Kafka's that pretty much > nobody > >> but > >> > >> Kafka actually implements it. (Databus is perhaps an exception, but > >> it > >> > >> isn't widely used outside of LinkedIn.) Thus, making Samza fully > >> > dependent > >> > >> on Kafka acknowledges that the system-independence was never as > real > >> as > >> > we > >> > >> perhaps made it out to be. The gains of code reuse are real. > >> > >> > >> > >> The idea of decoupling Samza from YARN has also always been > >> appealing to > >> > >> me, for various reasons already mentioned in this thread. Although > >> > making > >> > >> Samza jobs deployable on anything (YARN/Mesos/AWS/etc) seems > >> laudable, > >> > I am > >> > >> a little concerned that it will restrict us to a lowest common > >> > denominator. > >> > >> For example, would host affinity (SAMZA-617) still be possible? For > >> jobs > >> > >> with large amounts of state, I think SAMZA-617 would be a big boon, > >> > since > >> > >> restoring state off the changelog on every single restart is > painful, > >> > due > >> > >> to long recovery times. It would be a shame if the decoupling from > >> YARN > >> > >> made host affinity impossible. > >> > >> > >> > >> Jay, a question about the proposed API for instantiating a job in > >> code > >> > >> (rather than a properties file): when submitting a job to a > cluster, > >> is > >> > the > >> > >> idea that the instantiation code runs on a client somewhere, which > >> then > >> > >> pokes the necessary endpoints on YARN/Mesos/AWS/etc? Or does that > >> code > >> > run > >> > >> on each container that is part of the job (in which case, how does > >> the > >> > job > >> > >> submission to the cluster work)? > >> > >> > >> > >> I agree with Garry that it doesn't feel right to make a 1.0 release > >> > with a > >> > >> plan for it to be immediately obsolete. So if this is going to > >> happen, I > >> > >> think it would be more honest to stick with 0.* version numbers > until > >> > the > >> > >> library-ified Samza has been implemented, is stable and widely > used. > >> > >> > >> > >> Should the new Samza be a subproject of Kafka? There is precedent > for > >> > >> tight coupling between different Apache projects (e.g. Curator and > >> > >> Zookeeper, or Slider and YARN), so I think remaining separate would > >> be > >> > ok. > >> > >> Even if Samza is fully dependent on Kafka, there is enough > substance > >> in > >> > >> Samza that it warrants being a separate project. An argument in > >> favour > >> > of > >> > >> merging would be if we think Kafka has a much stronger "brand > >> presence" > >> > >> than Samza; I'm ambivalent on that one. If the Kafka project is > >> willing > >> > to > >> > >> endorse Samza as the "official" way of doing stateful stream > >> > >> transformations, that would probably have much the same effect as > >> > >> re-branding Samza as "Kafka Stream Processors" or suchlike. Close > >> > >> collaboration between the two projects will be needed in any case. > >> > >> > >> > >> From a project management perspective, I guess the "new Samza" > would > >> > have > >> > >> to be developed on a branch alongside ongoing maintenance of the > >> current > >> > >> line of development? I think it would be important to continue > >> > supporting > >> > >> existing users, and provide a graceful migration path to the new > >> > version. > >> > >> Leaving the current versions unsupported and forcing people to > >> rewrite > >> > >> their jobs would send a bad signal. > >> > >> > >> > >> Best, > >> > >> Martin > >> > >> > >> > >> On 2 Jul 2015, at 16:59, Jay Kreps <j...@confluent.io> wrote: > >> > >> > >> > >>> Hey Garry, > >> > >>> > >> > >>> Yeah that's super frustrating. I'd be happy to chat more about > this > >> if > >> > >>> you'd be interested. I think Chris and I started with the idea of > >> "what > >> > >>> would it take to make Samza a kick-ass ingestion tool" but > >> ultimately > >> > we > >> > >>> kind of came around to the idea that ingestion and transformation > >> had > >> > >>> pretty different needs and coupling the two made things hard. > >> > >>> > >> > >>> For what it's worth I think copycat (KIP-26) actually will do what > >> you > >> > >> are > >> > >>> looking for. > >> > >>> > >> > >>> With regard to your point about slider, I don't necessarily > >> disagree. > >> > >> But I > >> > >>> think getting good YARN support is quite doable and I think we can > >> make > >> > >>> that work well. I think the issue this proposal solves is that > >> > >> technically > >> > >>> it is pretty hard to support multiple cluster management systems > the > >> > way > >> > >>> things are now, you need to write an "app master" or "framework" > for > >> > each > >> > >>> and they are all a little different so testing is really hard. In > >> the > >> > >>> absence of this we have been stuck with just YARN which has > >> fantastic > >> > >>> penetration in the Hadoopy part of the org, but zero penetration > >> > >> elsewhere. > >> > >>> Given the huge amount of work being put in to slider, marathon, > aws > >> > >>> tooling, not to mention the umpteen related packaging technologies > >> > people > >> > >>> want to use (Docker, Kubernetes, various cloud-specific deploy > >> tools, > >> > >> etc) > >> > >>> I really think it is important to get this right. > >> > >>> > >> > >>> -Jay > >> > >>> > >> > >>> On Thu, Jul 2, 2015 at 4:17 AM, Garry Turkington < > >> > >>> g.turking...@improvedigital.com> wrote: > >> > >>> > >> > >>>> Hi all, > >> > >>>> > >> > >>>> I think the question below re does Samza become a sub-project of > >> Kafka > >> > >>>> highlights the broader point around migration. Chris mentions > >> Samza's > >> > >>>> maturity is heading towards a v1 release but I'm not sure it > feels > >> > >> right to > >> > >>>> launch a v1 then immediately plan to deprecate most of it. > >> > >>>> > >> > >>>> From a selfish perspective I have some guys who have started > >> working > >> > >> with > >> > >>>> Samza and building some new consumers/producers was next up. > Sounds > >> > like > >> > >>>> that is absolutely not the direction to go. I need to look into > the > >> > KIP > >> > >> in > >> > >>>> more detail but for me the attractiveness of adding new Samza > >> > >>>> consumer/producers -- even if yes all they were doing was really > >> > getting > >> > >>>> data into and out of Kafka -- was to avoid having to worry > about > >> the > >> > >>>> lifecycle management of external clients. If there is a generic > >> Kafka > >> > >>>> ingress/egress layer that I can plug a new connector into and > have > >> a > >> > >> lot of > >> > >>>> the heavy lifting re scale and reliability done for me then it > >> gives > >> > me > >> > >> all > >> > >>>> the pushing new consumers/producers would. If not then it > >> complicates > >> > my > >> > >>>> operational deployments. > >> > >>>> > >> > >>>> Which is similar to my other question with the proposal -- if we > >> > build a > >> > >>>> fully available/stand-alone Samza plus the requisite shims to > >> > integrate > >> > >>>> with Slider etc I suspect the former may be a lot more work than > we > >> > >> think. > >> > >>>> We may make it much easier for a newcomer to get something > running > >> but > >> > >>>> having them step up and get a reliable production deployment may > >> still > >> > >>>> dominate mailing list traffic, if for different reasons than > >> today. > >> > >>>> > >> > >>>> Don't get me wrong -- I'm comfortable with making the Samza > >> dependency > >> > >> on > >> > >>>> Kafka much more explicit and I absolutely see the benefits in > the > >> > >>>> reduction of duplication and clashing terminologies/abstractions > >> that > >> > >>>> Chris/Jay describe. Samza as a library would likely be a very > nice > >> > tool > >> > >> to > >> > >>>> add to the Kafka ecosystem. I just have the concerns above re the > >> > >>>> operational side. > >> > >>>> > >> > >>>> Garry > >> > >>>> > >> > >>>> -----Original Message----- > >> > >>>> From: Gianmarco De Francisci Morales [mailto:g...@apache.org] > >> > >>>> Sent: 02 July 2015 12:56 > >> > >>>> To: dev@samza.apache.org > >> > >>>> Subject: Re: Thoughts and obesrvations on Samza > >> > >>>> > >> > >>>> Very interesting thoughts. > >> > >>>> From outside, I have always perceived Samza as a computing layer > >> over > >> > >>>> Kafka. > >> > >>>> > >> > >>>> The question, maybe a bit provocative, is "should Samza be a > >> > sub-project > >> > >>>> of Kafka then?" > >> > >>>> Or does it make sense to keep it as a separate project with a > >> separate > >> > >>>> governance? > >> > >>>> > >> > >>>> Cheers, > >> > >>>> > >> > >>>> -- > >> > >>>> Gianmarco > >> > >>>> > >> > >>>> On 2 July 2015 at 08:59, Yan Fang <yanfang...@gmail.com> wrote: > >> > >>>> > >> > >>>>> Overall, I agree to couple with Kafka more tightly. Because > Samza > >> de > >> > >>>>> facto is based on Kafka, and it should leverage what Kafka has. > At > >> > the > >> > >>>>> same time, Kafka does not need to reinvent what Samza already > >> has. I > >> > >>>>> also like the idea of separating the ingestion and > transformation. > >> > >>>>> > >> > >>>>> But it is a little difficult for me to image how the Samza will > >> look > >> > >>>> like. > >> > >>>>> And I feel Chris and Jay have a little difference in terms of > how > >> > >>>>> Samza should look like. > >> > >>>>> > >> > >>>>> *** Will it look like what Jay's code shows (A client of Kakfa) > ? > >> And > >> > >>>>> user's application code calls this client? > >> > >>>>> > >> > >>>>> 1. If we make Samza be a library of Kafka (like what the code > >> shows), > >> > >>>>> how do we implement auto-balance and fault-tolerance? Are they > >> taken > >> > >>>>> care by the Kafka broker or other mechanism, such as "Samza > >> worker" > >> > >>>>> (just make up the name) ? > >> > >>>>> > >> > >>>>> 2. What about other features, such as auto-scaling, shared > state, > >> > >>>>> monitoring? > >> > >>>>> > >> > >>>>> > >> > >>>>> *** If we have Samza standalone, (is this what Chris suggests?) > >> > >>>>> > >> > >>>>> 1. we still need to ingest data from Kakfa and produce to it. > >> Then it > >> > >>>>> becomes the same as what Samza looks like now, except it does > not > >> > rely > >> > >>>>> on Yarn anymore. > >> > >>>>> > >> > >>>>> 2. if it is standalone, how can it leverage Kafka's metrics, > logs, > >> > >>>>> etc? Use Kafka code as the dependency? > >> > >>>>> > >> > >>>>> > >> > >>>>> Thanks, > >> > >>>>> > >> > >>>>> Fang, Yan > >> > >>>>> yanfang...@gmail.com > >> > >>>>> > >> > >>>>> On Wed, Jul 1, 2015 at 5:46 PM, Guozhang Wang < > wangg...@gmail.com > >> > > >> > >>>> wrote: > >> > >>>>> > >> > >>>>>> Read through the code example and it looks good to me. A few > >> > >>>>>> thoughts regarding deployment: > >> > >>>>>> > >> > >>>>>> Today Samza deploys as executable runnable like: > >> > >>>>>> > >> > >>>>>> deploy/samza/bin/run-job.sh --config-factory=... > >> > >>>> --config-path=file://... > >> > >>>>>> > >> > >>>>>> And this proposal advocate for deploying Samza more as embedded > >> > >>>>>> libraries in user application code (ignoring the terminology > >> since > >> > >>>>>> it is not the > >> > >>>>> same > >> > >>>>>> as the prototype code): > >> > >>>>>> > >> > >>>>>> StreamTask task = new MyStreamTask(configs); Thread thread = > new > >> > >>>>>> Thread(task); thread.start(); > >> > >>>>>> > >> > >>>>>> I think both of these deployment modes are important for > >> different > >> > >>>>>> types > >> > >>>>> of > >> > >>>>>> users. That said, I think making Samza purely standalone is > still > >> > >>>>>> sufficient for either runnable or library modes. > >> > >>>>>> > >> > >>>>>> Guozhang > >> > >>>>>> > >> > >>>>>> On Tue, Jun 30, 2015 at 11:33 PM, Jay Kreps <j...@confluent.io> > >> > wrote: > >> > >>>>>> > >> > >>>>>>> Looks like gmail mangled the code example, it was supposed to > >> look > >> > >>>>>>> like > >> > >>>>>>> this: > >> > >>>>>>> > >> > >>>>>>> Properties props = new Properties(); > >> > >>>>>>> props.put("bootstrap.servers", "localhost:4242"); > >> StreamingConfig > >> > >>>>>>> config = new StreamingConfig(props); > >> > >>>>>>> config.subscribe("test-topic-1", "test-topic-2"); > >> > >>>>>>> config.processor(ExampleStreamProcessor.class); > >> > >>>>>>> config.serialization(new StringSerializer(), new > >> > >>>>>>> StringDeserializer()); KafkaStreaming container = new > >> > >>>>>>> KafkaStreaming(config); container.run(); > >> > >>>>>>> > >> > >>>>>>> -Jay > >> > >>>>>>> > >> > >>>>>>> On Tue, Jun 30, 2015 at 11:32 PM, Jay Kreps <j...@confluent.io > > > >> > >>>> wrote: > >> > >>>>>>> > >> > >>>>>>>> Hey guys, > >> > >>>>>>>> > >> > >>>>>>>> This came out of some conversations Chris and I were having > >> > >>>>>>>> around > >> > >>>>>>> whether > >> > >>>>>>>> it would make sense to use Samza as a kind of data ingestion > >> > >>>>> framework > >> > >>>>>>> for > >> > >>>>>>>> Kafka (which ultimately lead to KIP-26 "copycat"). This kind > of > >> > >>>>>> combined > >> > >>>>>>>> with complaints around config and YARN and the discussion > >> around > >> > >>>>>>>> how > >> > >>>>> to > >> > >>>>>>>> best do a standalone mode. > >> > >>>>>>>> > >> > >>>>>>>> So the thought experiment was, given that Samza was basically > >> > >>>>>>>> already totally Kafka specific, what if you just embraced > that > >> > >>>>>>>> and turned it > >> > >>>>>> into > >> > >>>>>>>> something less like a heavyweight framework and more like a > >> > >>>>>>>> third > >> > >>>>> Kafka > >> > >>>>>>>> client--a kind of "producing consumer" with state management > >> > >>>>>> facilities. > >> > >>>>>>>> Basically a library. Instead of a complex stream processing > >> > >>>>>>>> framework > >> > >>>>>>> this > >> > >>>>>>>> would actually be a very simple thing, not much more > >> complicated > >> > >>>>>>>> to > >> > >>>>> use > >> > >>>>>>> or > >> > >>>>>>>> operate than a Kafka consumer. As Chris said we thought about > >> it > >> > >>>>>>>> a > >> > >>>>> lot > >> > >>>>>> of > >> > >>>>>>>> what Samza (and the other stream processing systems were > doing) > >> > >>>>> seemed > >> > >>>>>>> like > >> > >>>>>>>> kind of a hangover from MapReduce. > >> > >>>>>>>> > >> > >>>>>>>> Of course you need to ingest/output data to and from the > stream > >> > >>>>>>>> processing. But when we actually looked into how that would > >> > >>>>>>>> work, > >> > >>>>> Samza > >> > >>>>>>>> isn't really an ideal data ingestion framework for a bunch of > >> > >>>>> reasons. > >> > >>>>>> To > >> > >>>>>>>> really do that right you need a pretty different internal > data > >> > >>>>>>>> model > >> > >>>>>> and > >> > >>>>>>>> set of apis. So what if you split them and had an api for > Kafka > >> > >>>>>>>> ingress/egress (copycat AKA KIP-26) and a separate api for > >> Kafka > >> > >>>>>>>> transformation (Samza). > >> > >>>>>>>> > >> > >>>>>>>> This would also allow really embracing the same terminology > and > >> > >>>>>>>> conventions. One complaint about the current state is that > the > >> > >>>>>>>> two > >> > >>>>>>> systems > >> > >>>>>>>> kind of feel bolted on. Terminology like "stream" vs "topic" > >> and > >> > >>>>>>> different > >> > >>>>>>>> config and monitoring systems means you kind of have to learn > >> > >>>>>>>> Kafka's > >> > >>>>>>> way, > >> > >>>>>>>> then learn Samza's slightly different way, then kind of > >> > >>>>>>>> understand > >> > >>>>> how > >> > >>>>>>> they > >> > >>>>>>>> map to each other, which having walked a few people through > >> this > >> > >>>>>>>> is surprisingly tricky for folks to get. > >> > >>>>>>>> > >> > >>>>>>>> Since I have been spending a lot of time on airplanes I > hacked > >> > >>>>>>>> up an ernest but still somewhat incomplete prototype of what > >> > >>>>>>>> this would > >> > >>>>> look > >> > >>>>>>>> like. This is just unceremoniously dumped into Kafka as it > >> > >>>>>>>> required a > >> > >>>>>> few > >> > >>>>>>>> changes to the new consumer. Here is the code: > >> > >>>>>>>> > >> > >>>>>>>> > >> > >>>>>>> > >> > >>>>>> > >> > >>>>> > >> > > https://github.com/jkreps/kafka/tree/streams/clients/src/main/java/org > >> > >>>>> /apache/kafka/clients/streaming > >> > >>>>>>>> > >> > >>>>>>>> For the purpose of the prototype I just liberally renamed > >> > >>>>>>>> everything > >> > >>>>> to > >> > >>>>>>>> try to align it with Kafka with no regard for compatibility. > >> > >>>>>>>> > >> > >>>>>>>> To use this would be something like this: > >> > >>>>>>>> Properties props = new Properties(); > >> > >>>>>>>> props.put("bootstrap.servers", "localhost:4242"); > >> > >>>>>>>> StreamingConfig config = new > >> > >>>>> StreamingConfig(props); > >> > >>>>>>> config.subscribe("test-topic-1", > >> > >>>>>>>> "test-topic-2"); > >> config.processor(ExampleStreamProcessor.class); > >> > >>>>>>> config.serialization(new > >> > >>>>>>>> StringSerializer(), new StringDeserializer()); KafkaStreaming > >> > >>>>>> container = > >> > >>>>>>>> new KafkaStreaming(config); container.run(); > >> > >>>>>>>> > >> > >>>>>>>> KafkaStreaming is basically the SamzaContainer; > StreamProcessor > >> > >>>>>>>> is basically StreamTask. > >> > >>>>>>>> > >> > >>>>>>>> So rather than putting all the class names in a file and then > >> > >>>>>>>> having > >> > >>>>>> the > >> > >>>>>>>> job assembled by reflection, you just instantiate the > container > >> > >>>>>>>> programmatically. Work is balanced over however many > instances > >> > >>>>>>>> of > >> > >>>>> this > >> > >>>>>>> are > >> > >>>>>>>> alive at any time (i.e. if an instance dies, new tasks are > >> added > >> > >>>>>>>> to > >> > >>>>> the > >> > >>>>>>>> existing containers without shutting them down). > >> > >>>>>>>> > >> > >>>>>>>> We would provide some glue for running this stuff in YARN via > >> > >>>>>>>> Slider, Mesos via Marathon, and AWS using some of their tools > >> > >>>>>>>> but from the > >> > >>>>>> point > >> > >>>>>>> of > >> > >>>>>>>> view of these frameworks these stream processing jobs are > just > >> > >>>>>> stateless > >> > >>>>>>>> services that can come and go and expand and contract at > will. > >> > >>>>>>>> There > >> > >>>>> is > >> > >>>>>>> no > >> > >>>>>>>> more custom scheduler. > >> > >>>>>>>> > >> > >>>>>>>> Here are some relevant details: > >> > >>>>>>>> > >> > >>>>>>>> 1. It is only ~1300 lines of code, it would get larger if we > >> > >>>>>>>> productionized but not vastly larger. We really do get a ton > >> > >>>>>>>> of > >> > >>>>>>> leverage > >> > >>>>>>>> out of Kafka. > >> > >>>>>>>> 2. Partition management is fully delegated to the new > >> consumer. > >> > >>>>> This > >> > >>>>>>>> is nice since now any partition management strategy > available > >> > >>>>>>>> to > >> > >>>>>> Kafka > >> > >>>>>>>> consumer is also available to Samza (and vice versa) and > with > >> > >>>>>>>> the > >> > >>>>>>> exact > >> > >>>>>>>> same configs. > >> > >>>>>>>> 3. It supports state as well as state reuse > >> > >>>>>>>> > >> > >>>>>>>> Anyhow take a look, hopefully it is thought provoking. > >> > >>>>>>>> > >> > >>>>>>>> -Jay > >> > >>>>>>>> > >> > >>>>>>>> > >> > >>>>>>>> > >> > >>>>>>>> On Tue, Jun 30, 2015 at 6:55 PM, Chris Riccomini < > >> > >>>>>> criccom...@apache.org> > >> > >>>>>>>> wrote: > >> > >>>>>>>> > >> > >>>>>>>>> Hey all, > >> > >>>>>>>>> > >> > >>>>>>>>> I have had some discussions with Samza engineers at LinkedIn > >> > >>>>>>>>> and > >> > >>>>>>> Confluent > >> > >>>>>>>>> and we came up with a few observations and would like to > >> > >>>>>>>>> propose > >> > >>>>> some > >> > >>>>>>>>> changes. > >> > >>>>>>>>> > >> > >>>>>>>>> We've observed some things that I want to call out about > >> > >>>>>>>>> Samza's > >> > >>>>>> design, > >> > >>>>>>>>> and I'd like to propose some changes. > >> > >>>>>>>>> > >> > >>>>>>>>> * Samza is dependent upon a dynamic deployment system. > >> > >>>>>>>>> * Samza is too pluggable. > >> > >>>>>>>>> * Samza's SystemConsumer/SystemProducer and Kafka's consumer > >> > >>>>>>>>> APIs > >> > >>>>> are > >> > >>>>>>>>> trying to solve a lot of the same problems. > >> > >>>>>>>>> > >> > >>>>>>>>> All three of these issues are related, but I'll address them > >> in > >> > >>>>> order. > >> > >>>>>>>>> > >> > >>>>>>>>> Deployment > >> > >>>>>>>>> > >> > >>>>>>>>> Samza strongly depends on the use of a dynamic deployment > >> > >>>>>>>>> scheduler > >> > >>>>>> such > >> > >>>>>>>>> as > >> > >>>>>>>>> YARN, Mesos, etc. When we initially built Samza, we bet that > >> > >>>>>>>>> there > >> > >>>>>> would > >> > >>>>>>>>> be > >> > >>>>>>>>> one or two winners in this area, and we could support them, > >> and > >> > >>>>>>>>> the > >> > >>>>>> rest > >> > >>>>>>>>> would go away. In reality, there are many variations. > >> > >>>>>>>>> Furthermore, > >> > >>>>>> many > >> > >>>>>>>>> people still prefer to just start their processors like > normal > >> > >>>>>>>>> Java processes, and use traditional deployment scripts such > as > >> > >>>>>>>>> Fabric, > >> > >>>>>> Chef, > >> > >>>>>>>>> Ansible, etc. Forcing a deployment system on users makes the > >> > >>>>>>>>> Samza start-up process really painful for first time users. > >> > >>>>>>>>> > >> > >>>>>>>>> Dynamic deployment as a requirement was also a bit of a > >> > >>>>>>>>> mis-fire > >> > >>>>>> because > >> > >>>>>>>>> of > >> > >>>>>>>>> a fundamental misunderstanding between the nature of batch > >> jobs > >> > >>>>>>>>> and > >> > >>>>>>> stream > >> > >>>>>>>>> processing jobs. Early on, we made conscious effort to favor > >> > >>>>>>>>> the > >> > >>>>>> Hadoop > >> > >>>>>>>>> (Map/Reduce) way of doing things, since it worked and was > well > >> > >>>>>>> understood. > >> > >>>>>>>>> One thing that we missed was that batch jobs have a definite > >> > >>>>>> beginning, > >> > >>>>>>>>> and > >> > >>>>>>>>> end, and stream processing jobs don't (usually). This leads > to > >> > >>>>>>>>> a > >> > >>>>> much > >> > >>>>>>>>> simpler scheduling problem for stream processors. You > >> basically > >> > >>>>>>>>> just > >> > >>>>>>> need > >> > >>>>>>>>> to find a place to start the processor, and start it. The > way > >> > >>>>>>>>> we run grids, at LinkedIn, there's no concept of a cluster > >> > >>>>>>>>> being "full". We always > >> > >>>>>> add > >> > >>>>>>>>> more machines. The problem with coupling Samza with a > >> scheduler > >> > >>>>>>>>> is > >> > >>>>>> that > >> > >>>>>>>>> Samza (as a framework) now has to handle deployment. This > >> pulls > >> > >>>>>>>>> in a > >> > >>>>>>> bunch > >> > >>>>>>>>> of things such as configuration distribution (config > stream), > >> > >>>>>>>>> shell > >> > >>>>>>> scrips > >> > >>>>>>>>> (bin/run-job.sh, JobRunner), packaging (all the .tgz stuff), > >> etc. > >> > >>>>>>>>> > >> > >>>>>>>>> Another reason for requiring dynamic deployment was to > support > >> > >>>>>>>>> data locality. If you want to have locality, you need to put > >> > >>>>>>>>> your > >> > >>>>>> processors > >> > >>>>>>>>> close to the data they're processing. Upon further > >> > >>>>>>>>> investigation, > >> > >>>>>>> though, > >> > >>>>>>>>> this feature is not that beneficial. There is some good > >> > >>>>>>>>> discussion > >> > >>>>>> about > >> > >>>>>>>>> some problems with it on SAMZA-335. Again, we took the > >> > >>>>>>>>> Map/Reduce > >> > >>>>>> path, > >> > >>>>>>>>> but > >> > >>>>>>>>> there are some fundamental differences between HDFS and > Kafka. > >> > >>>>>>>>> HDFS > >> > >>>>>> has > >> > >>>>>>>>> blocks, while Kafka has partitions. This leads to less > >> > >>>>>>>>> optimization potential with stream processors on top of > Kafka. > >> > >>>>>>>>> > >> > >>>>>>>>> This feature is also used as a crutch. Samza doesn't have > any > >> > >>>>>>>>> built > >> > >>>>> in > >> > >>>>>>>>> fault-tolerance logic. Instead, it depends on the dynamic > >> > >>>>>>>>> deployment scheduling system to handle restarts when a > >> > >>>>>>>>> processor dies. This has > >> > >>>>>>> made > >> > >>>>>>>>> it very difficult to write a standalone Samza container > >> > >>>> (SAMZA-516). > >> > >>>>>>>>> > >> > >>>>>>>>> Pluggability > >> > >>>>>>>>> > >> > >>>>>>>>> In some cases pluggability is good, but I think that we've > >> gone > >> > >>>>>>>>> too > >> > >>>>>> far > >> > >>>>>>>>> with it. Currently, Samza has: > >> > >>>>>>>>> > >> > >>>>>>>>> * Pluggable config. > >> > >>>>>>>>> * Pluggable metrics. > >> > >>>>>>>>> * Pluggable deployment systems. > >> > >>>>>>>>> * Pluggable streaming systems (SystemConsumer, > SystemProducer, > >> > >>>> etc). > >> > >>>>>>>>> * Pluggable serdes. > >> > >>>>>>>>> * Pluggable storage engines. > >> > >>>>>>>>> * Pluggable strategies for just about every component > >> > >>>>> (MessageChooser, > >> > >>>>>>>>> SystemStreamPartitionGrouper, ConfigRewriter, etc). > >> > >>>>>>>>> > >> > >>>>>>>>> There's probably more that I've forgotten, as well. Some of > >> > >>>>>>>>> these > >> > >>>>> are > >> > >>>>>>>>> useful, but some have proven not to be. This all comes at a > >> cost: > >> > >>>>>>>>> complexity. This complexity is making it harder for our > users > >> > >>>>>>>>> to > >> > >>>>> pick > >> > >>>>>> up > >> > >>>>>>>>> and use Samza out of the box. It also makes it difficult for > >> > >>>>>>>>> Samza developers to reason about what the characteristics of > >> > >>>>>>>>> the container (since the characteristics change depending on > >> > >>>>>>>>> which plugins are use). > >> > >>>>>>>>> > >> > >>>>>>>>> The issues with pluggability are most visible in the System > >> APIs. > >> > >>>>> What > >> > >>>>>>>>> Samza really requires to be functional is Kafka as its > >> > >>>>>>>>> transport > >> > >>>>>> layer. > >> > >>>>>>>>> But > >> > >>>>>>>>> we've conflated two unrelated use cases into one API: > >> > >>>>>>>>> > >> > >>>>>>>>> 1. Get data into/out of Kafka. > >> > >>>>>>>>> 2. Process the data in Kafka. > >> > >>>>>>>>> > >> > >>>>>>>>> The current System API supports both of these use cases. The > >> > >>>>>>>>> problem > >> > >>>>>> is, > >> > >>>>>>>>> we > >> > >>>>>>>>> actually want different features for each use case. By > >> papering > >> > >>>>>>>>> over > >> > >>>>>>> these > >> > >>>>>>>>> two use cases, and providing a single API, we've introduced > a > >> > >>>>>>>>> ton of > >> > >>>>>>> leaky > >> > >>>>>>>>> abstractions. > >> > >>>>>>>>> > >> > >>>>>>>>> For example, what we'd really like in (2) is to have > >> > >>>>>>>>> monotonically increasing longs for offsets (like Kafka). > This > >> > >>>>>>>>> would be at odds > >> > >>>>> with > >> > >>>>>>> (1), > >> > >>>>>>>>> though, since different systems have different > >> > >>>>>>> SCNs/Offsets/UUIDs/vectors. > >> > >>>>>>>>> There was discussion both on the mailing list and the SQL > >> JIRAs > >> > >>>>> about > >> > >>>>>>> the > >> > >>>>>>>>> need for this. > >> > >>>>>>>>> > >> > >>>>>>>>> The same thing holds true for replayability. Kafka allows us > >> to > >> > >>>>> rewind > >> > >>>>>>>>> when > >> > >>>>>>>>> we have a failure. Many other systems don't. In some cases, > >> > >>>>>>>>> systems > >> > >>>>>>> return > >> > >>>>>>>>> null for their offsets (e.g. WikipediaSystemConsumer) > because > >> > >>>>>>>>> they > >> > >>>>>> have > >> > >>>>>>> no > >> > >>>>>>>>> offsets. > >> > >>>>>>>>> > >> > >>>>>>>>> Partitioning is another example. Kafka supports > partitioning, > >> > >>>>>>>>> but > >> > >>>>> many > >> > >>>>>>>>> systems don't. We model this by having a single partition > for > >> > >>>>>>>>> those systems. Still, other systems model partitioning > >> > >>>> differently (e.g. > >> > >>>>>>>>> Kinesis). > >> > >>>>>>>>> > >> > >>>>>>>>> The SystemAdmin interface is also a mess. Creating streams > in > >> a > >> > >>>>>>>>> system-agnostic way is almost impossible. As is modeling > >> > >>>>>>>>> metadata > >> > >>>>> for > >> > >>>>>>> the > >> > >>>>>>>>> system (replication factor, partitions, location, etc). The > >> > >>>>>>>>> list > >> > >>>>> goes > >> > >>>>>>> on. > >> > >>>>>>>>> > >> > >>>>>>>>> Duplicate work > >> > >>>>>>>>> > >> > >>>>>>>>> At the time that we began writing Samza, Kafka's consumer > and > >> > >>>>> producer > >> > >>>>>>>>> APIs > >> > >>>>>>>>> had a relatively weak feature set. On the consumer-side, you > >> > >>>>>>>>> had two > >> > >>>>>>>>> options: use the high level consumer, or the simple > consumer. > >> > >>>>>>>>> The > >> > >>>>>>> problem > >> > >>>>>>>>> with the high-level consumer was that it controlled your > >> > >>>>>>>>> offsets, partition assignments, and the order in which you > >> > >>>>>>>>> received messages. The > >> > >>>>> problem > >> > >>>>>>>>> with > >> > >>>>>>>>> the simple consumer is that it's not simple. It's basic. You > >> > >>>>>>>>> end up > >> > >>>>>>> having > >> > >>>>>>>>> to handle a lot of really low-level stuff that you > shouldn't. > >> > >>>>>>>>> We > >> > >>>>>> spent a > >> > >>>>>>>>> lot of time to make Samza's KafkaSystemConsumer very robust. > >> It > >> > >>>>>>>>> also allows us to support some cool features: > >> > >>>>>>>>> > >> > >>>>>>>>> * Per-partition message ordering and prioritization. > >> > >>>>>>>>> * Tight control over partition assignment to support joins, > >> > >>>>>>>>> global > >> > >>>>>> state > >> > >>>>>>>>> (if we want to implement it :)), etc. > >> > >>>>>>>>> * Tight control over offset checkpointing. > >> > >>>>>>>>> > >> > >>>>>>>>> What we didn't realize at the time is that these features > >> > >>>>>>>>> should > >> > >>>>>>> actually > >> > >>>>>>>>> be in Kafka. A lot of Kafka consumers (not just Samza stream > >> > >>>>>> processors) > >> > >>>>>>>>> end up wanting to do things like joins and partition > >> > >>>>>>>>> assignment. The > >> > >>>>>>> Kafka > >> > >>>>>>>>> community has come to the same conclusion. They're adding a > >> ton > >> > >>>>>>>>> of upgrades into their new Kafka consumer implementation. > To a > >> > >>>>>>>>> large extent, > >> > >>>>> it's > >> > >>>>>>>>> duplicate work to what we've already done in Samza. > >> > >>>>>>>>> > >> > >>>>>>>>> On top of this, Kafka ended up taking a very similar > approach > >> > >>>>>>>>> to > >> > >>>>>> Samza's > >> > >>>>>>>>> KafkaCheckpointManager implementation for handling offset > >> > >>>>>> checkpointing. > >> > >>>>>>>>> Like Samza, Kafka's new offset management feature stores > >> offset > >> > >>>>>>>>> checkpoints in a topic, and allows you to fetch them from > the > >> > >>>>>>>>> broker. > >> > >>>>>>>>> > >> > >>>>>>>>> A lot of this seems like a waste, since we could have shared > >> > >>>>>>>>> the > >> > >>>>> work > >> > >>>>>> if > >> > >>>>>>>>> it > >> > >>>>>>>>> had been done in Kafka from the get-go. > >> > >>>>>>>>> > >> > >>>>>>>>> Vision > >> > >>>>>>>>> > >> > >>>>>>>>> All of this leads me to a rather radical proposal. Samza is > >> > >>>>> relatively > >> > >>>>>>>>> stable at this point. I'd venture to say that we're near a > 1.0 > >> > >>>>>> release. > >> > >>>>>>>>> I'd > >> > >>>>>>>>> like to propose that we take what we've learned, and begin > >> > >>>>>>>>> thinking > >> > >>>>>>> about > >> > >>>>>>>>> Samza beyond 1.0. What would we change if we were starting > >> from > >> > >>>>>> scratch? > >> > >>>>>>>>> My > >> > >>>>>>>>> proposal is to: > >> > >>>>>>>>> > >> > >>>>>>>>> 1. Make Samza standalone the *only* way to run Samza > >> > >>>>>>>>> processors, and eliminate all direct dependences on YARN, > >> Mesos, > >> > >>>> etc. > >> > >>>>>>>>> 2. Make a definitive call to support only Kafka as the > stream > >> > >>>>>> processing > >> > >>>>>>>>> layer. > >> > >>>>>>>>> 3. Eliminate Samza's metrics, logging, serialization, and > >> > >>>>>>>>> config > >> > >>>>>>> systems, > >> > >>>>>>>>> and simply use Kafka's instead. > >> > >>>>>>>>> > >> > >>>>>>>>> This would fix all of the issues that I outlined above. It > >> > >>>>>>>>> should > >> > >>>>> also > >> > >>>>>>>>> shrink the Samza code base pretty dramatically. Supporting > >> only > >> > >>>>>>>>> a standalone container will allow Samza to be executed on > YARN > >> > >>>>>>>>> (using Slider), Mesos (using Marathon/Aurora), or most other > >> > >>>>>>>>> in-house > >> > >>>>>>> deployment > >> > >>>>>>>>> systems. This should make life a lot easier for new users. > >> > >>>>>>>>> Imagine > >> > >>>>>>> having > >> > >>>>>>>>> the hello-samza tutorial without YARN. The drop in mailing > >> list > >> > >>>>>> traffic > >> > >>>>>>>>> will be pretty dramatic. > >> > >>>>>>>>> > >> > >>>>>>>>> Coupling with Kafka seems long overdue to me. The reality > is, > >> > >>>>> everyone > >> > >>>>>>>>> that > >> > >>>>>>>>> I'm aware of is using Samza with Kafka. We basically require > >> it > >> > >>>>>> already > >> > >>>>>>> in > >> > >>>>>>>>> order for most features to work. Those that are using other > >> > >>>>>>>>> systems > >> > >>>>>> are > >> > >>>>>>>>> generally using it for ingest into Kafka (1), and then they > do > >> > >>>>>>>>> the processing on top. There is already discussion ( > >> > >>>>>>>>> > >> > >>>>>>> > >> > >>>>>> > >> > >>>>> > >> > > https://cwiki.apache.org/confluence/pages/viewpage.action?pageId=58851 > >> > >>>>> 767 > >> > >>>>>>>>> ) > >> > >>>>>>>>> in Kafka to make ingesting into Kafka extremely easy. > >> > >>>>>>>>> > >> > >>>>>>>>> Once we make the call to couple with Kafka, we can leverage > a > >> > >>>>>>>>> ton of > >> > >>>>>>> their > >> > >>>>>>>>> ecosystem. We no longer have to maintain our own config, > >> > >>>>>>>>> metrics, > >> > >>>>> etc. > >> > >>>>>>> We > >> > >>>>>>>>> can all share the same libraries, and make them better. This > >> > >>>>>>>>> will > >> > >>>>> also > >> > >>>>>>>>> allow us to share the consumer/producer APIs, and will let > us > >> > >>>>> leverage > >> > >>>>>>>>> their offset management and partition management, rather > than > >> > >>>>>>>>> having > >> > >>>>>> our > >> > >>>>>>>>> own. All of the coordinator stream code would go away, as > >> would > >> > >>>>>>>>> most > >> > >>>>>> of > >> > >>>>>>>>> the > >> > >>>>>>>>> YARN AppMaster code. We'd probably have to push some > partition > >> > >>>>>>> management > >> > >>>>>>>>> features into the Kafka broker, but they're already moving > in > >> > >>>>>>>>> that direction with the new consumer API. The features we > have > >> > >>>>>>>>> for > >> > >>>>>> partition > >> > >>>>>>>>> assignment aren't unique to Samza, and seem like they should > >> be > >> > >>>>>>>>> in > >> > >>>>>> Kafka > >> > >>>>>>>>> anyway. There will always be some niche usages which will > >> > >>>>>>>>> require > >> > >>>>>> extra > >> > >>>>>>>>> care and hence full control over partition assignments much > >> > >>>>>>>>> like the > >> > >>>>>>> Kafka > >> > >>>>>>>>> low level consumer api. These would continue to be > supported. > >> > >>>>>>>>> > >> > >>>>>>>>> These items will be good for the Samza community. They'll > make > >> > >>>>>>>>> Samza easier to use, and make it easier for developers to > add > >> > >>>>>>>>> new features. > >> > >>>>>>>>> > >> > >>>>>>>>> Obviously this is a fairly large (and somewhat backwards > >> > >>>>> incompatible > >> > >>>>>>>>> change). If we choose to go this route, it's important that > we > >> > >>>>> openly > >> > >>>>>>>>> communicate how we're going to provide a migration path from > >> > >>>>>>>>> the > >> > >>>>>>> existing > >> > >>>>>>>>> APIs to the new ones (if we make incompatible changes). I > >> think > >> > >>>>>>>>> at a minimum, we'd probably need to provide a wrapper to > allow > >> > >>>>>>>>> existing StreamTask implementations to continue running on > the > >> > >>>> new container. > >> > >>>>>>> It's > >> > >>>>>>>>> also important that we openly communicate about timing, and > >> > >>>>>>>>> stages > >> > >>>>> of > >> > >>>>>>> the > >> > >>>>>>>>> migration. > >> > >>>>>>>>> > >> > >>>>>>>>> If you made it this far, I'm sure you have opinions. :) > Please > >> > >>>>>>>>> send > >> > >>>>>> your > >> > >>>>>>>>> thoughts and feedback. > >> > >>>>>>>>> > >> > >>>>>>>>> Cheers, > >> > >>>>>>>>> Chris > >> > >>>>>>>>> > >> > >>>>>>>> > >> > >>>>>>>> > >> > >>>>>>> > >> > >>>>>> > >> > >>>>>> > >> > >>>>>> > >> > >>>>>> -- > >> > >>>>>> -- Guozhang > >> > >>>>>> > >> > >>>>> > >> > >>>> > >> > >> > >> > >> > >> > > >> > > >> > > >> > > > > >
