Good validation messages can't solve the broken user experience, especially that such update mode option will implicitly make half of current kafka options invalid or doesn't make sense.
Best, Kurt On Thu, Oct 22, 2020 at 10:31 PM Jark Wu <imj...@gmail.com> wrote: > Hi Timo, Seth, > > The default value "inserting" of "mode" might be not suitable, > because "debezium-json" emits changelog messages which include updates. > > On Thu, 22 Oct 2020 at 22:10, Seth Wiesman <s...@ververica.com> wrote: > > > +1 for supporting upsert results into Kafka. > > > > I have no comments on the implementation details. > > > > As far as configuration goes, I tend to favor Timo's option where we add > a > > "mode" property to the existing Kafka table with default value > "inserting". > > If the mode is set to "updating" then the validation changes to the new > > requirements. I personally find it more intuitive than a seperate > > connector, my fear is users won't understand its the same physical kafka > > sink under the hood and it will lead to other confusion like does it > offer > > the same persistence guarantees? I think we are capable of adding good > > valdiation messaging that solves Jark and Kurts concerns. > > > > > > On Thu, Oct 22, 2020 at 8:51 AM Timo Walther <twal...@apache.org> wrote: > > > > > Hi Jark, > > > > > > "calling it "kafka-compacted" can even remind users to enable log > > > compaction" > > > > > > But sometimes users like to store a lineage of changes in their topics. > > > Indepent of any ktable/kstream interpretation. > > > > > > I let the majority decide on this topic to not further block this > > > effort. But we might find a better name like: > > > > > > connector = kafka > > > mode = updating/inserting > > > > > > OR > > > > > > connector = kafka-updating > > > > > > ... > > > > > > Regards, > > > Timo > > > > > > > > > > > > > > > On 22.10.20 15:24, Jark Wu wrote: > > > > Hi Timo, > > > > > > > > Thanks for your opinions. > > > > > > > > 1) Implementation > > > > We will have an stateful operator to generate INSERT and > UPDATE_BEFORE. > > > > This operator is keyby-ed (primary key as the shuffle key) after the > > > source > > > > operator. > > > > The implementation of this operator is very similar to the existing > > > > `DeduplicateKeepLastRowFunction`. > > > > The operator will register a value state using the primary key fields > > as > > > > keys. > > > > When the value state is empty under current key, we will emit INSERT > > for > > > > the input row. > > > > When the value state is not empty under current key, we will emit > > > > UPDATE_BEFORE using the row in state, > > > > and emit UPDATE_AFTER using the input row. > > > > When the input row is DELETE, we will clear state and emit DELETE > row. > > > > > > > > 2) new option vs new connector > > > >> We recently simplified the table options to a minimum amount of > > > > characters to be as concise as possible in the DDL. > > > > I think this is the reason why we want to introduce a new connector, > > > > because we can simplify the options in DDL. > > > > For example, if using a new option, the DDL may look like this: > > > > > > > > CREATE TABLE users ( > > > > user_id BIGINT, > > > > user_name STRING, > > > > user_level STRING, > > > > region STRING, > > > > PRIMARY KEY (user_id) NOT ENFORCED > > > > ) WITH ( > > > > 'connector' = 'kafka', > > > > 'model' = 'table', > > > > 'topic' = 'pageviews_per_region', > > > > 'properties.bootstrap.servers' = '...', > > > > 'properties.group.id' = 'testGroup', > > > > 'scan.startup.mode' = 'earliest', > > > > 'key.format' = 'csv', > > > > 'key.fields' = 'user_id', > > > > 'value.format' = 'avro', > > > > 'sink.partitioner' = 'hash' > > > > ); > > > > > > > > If using a new connector, we can have a different default value for > the > > > > options and remove unnecessary options, > > > > the DDL can look like this which is much more concise: > > > > > > > > CREATE TABLE pageviews_per_region ( > > > > user_id BIGINT, > > > > user_name STRING, > > > > user_level STRING, > > > > region STRING, > > > > PRIMARY KEY (user_id) NOT ENFORCED > > > > ) WITH ( > > > > 'connector' = 'kafka-compacted', > > > > 'topic' = 'pageviews_per_region', > > > > 'properties.bootstrap.servers' = '...', > > > > 'key.format' = 'csv', > > > > 'value.format' = 'avro' > > > > ); > > > > > > > >> When people read `connector=kafka-compacted` they might not know > that > > it > > > >> has ktable semantics. You don't need to enable log compaction in > order > > > >> to use a KTable as far as I know. > > > > We don't need to let users know it has ktable semantics, as > Konstantin > > > > mentioned this may carry more implicit > > > > meaning than we want to imply here. I agree users don't need to > enable > > > log > > > > compaction, but from the production perspective, > > > > log compaction should always be enabled if it is used in this > purpose. > > > > Calling it "kafka-compacted" can even remind users to enable log > > > compaction. > > > > > > > > I don't agree to introduce "model = table/stream" option, or > > > > "connector=kafka-table", > > > > because this means we are introducing Table vs Stream concept from > > KSQL. > > > > However, we don't have such top-level concept in Flink SQL now, this > > will > > > > further confuse users. > > > > In Flink SQL, all the things are STREAM, the differences are whether > it > > > is > > > > bounded or unbounded, > > > > whether it is insert-only or changelog. > > > > > > > > > > > > Best, > > > > Jark > > > > > > > > > > > > On Thu, 22 Oct 2020 at 20:39, Timo Walther <twal...@apache.org> > wrote: > > > > > > > >> Hi Shengkai, Hi Jark, > > > >> > > > >> thanks for this great proposal. It is time to finally connect the > > > >> changelog processor with a compacted Kafka topic. > > > >> > > > >> "The operator will produce INSERT rows, or additionally generate > > > >> UPDATE_BEFORE rows for the previous image, or produce DELETE rows > with > > > >> all columns filled with values." > > > >> > > > >> Could you elaborate a bit on the implementation details in the FLIP? > > How > > > >> are UPDATE_BEFOREs are generated. How much state is required to > > perform > > > >> this operation. > > > >> > > > >> From a conceptual and semantical point of view, I'm fine with the > > > >> proposal. But I would like to share my opinion about how we expose > > this > > > >> feature: > > > >> > > > >> ktable vs kafka-compacted > > > >> > > > >> I'm against having an additional connector like `ktable` or > > > >> `kafka-compacted`. We recently simplified the table options to a > > minimum > > > >> amount of characters to be as concise as possible in the DDL. > > Therefore, > > > >> I would keep the `connector=kafka` and introduce an additional > option. > > > >> Because a user wants to read "from Kafka". And the "how" should be > > > >> determined in the lower options. > > > >> > > > >> When people read `connector=ktable` they might not know that this is > > > >> Kafka. Or they wonder where `kstream` is? > > > >> > > > >> When people read `connector=kafka-compacted` they might not know > that > > it > > > >> has ktable semantics. You don't need to enable log compaction in > order > > > >> to use a KTable as far as I know. Log compaction and table semantics > > are > > > >> orthogonal topics. > > > >> > > > >> In the end we will need 3 types of information when declaring a > Kafka > > > >> connector: > > > >> > > > >> CREATE TABLE ... WITH ( > > > >> connector=kafka -- Some information about the connector > > > >> end-offset = XXXX -- Some information about the boundedness > > > >> model = table/stream -- Some information about interpretation > > > >> ) > > > >> > > > >> > > > >> We can still apply all the constraints mentioned in the FLIP. When > > > >> `model` is set to `table`. > > > >> > > > >> What do you think? > > > >> > > > >> Regards, > > > >> Timo > > > >> > > > >> > > > >> On 21.10.20 14:19, Jark Wu wrote: > > > >>> Hi, > > > >>> > > > >>> IMO, if we are going to mix them in one connector, > > > >>> 1) either users need to set some options to a specific value > > > explicitly, > > > >>> e.g. "scan.startup.mode=earliest", "sink.partitioner=hash", etc.. > > > >>> This makes the connector awkward to use. Users may face to fix > > options > > > >> one > > > >>> by one according to the exception. > > > >>> Besides, in the future, it is still possible to use > > > >>> "sink.partitioner=fixed" (reduce network cost) if users are aware > of > > > >>> the partition routing, > > > >>> however, it's error-prone to have "fixed" as default for compacted > > > mode. > > > >>> > > > >>> 2) or make those options a different default value when > > > "compacted=true". > > > >>> This would be more confusing and unpredictable if the default value > > of > > > >>> options will change according to other options. > > > >>> What happens if we have a third mode in the future? > > > >>> > > > >>> In terms of usage and options, it's very different from the > > > >>> original "kafka" connector. > > > >>> It would be more handy to use and less fallible if separating them > > into > > > >> two > > > >>> connectors. > > > >>> In the implementation layer, we can reuse code as much as possible. > > > >>> > > > >>> Therefore, I'm still +1 to have a new connector. > > > >>> The "kafka-compacted" name sounds good to me. > > > >>> > > > >>> Best, > > > >>> Jark > > > >>> > > > >>> > > > >>> On Wed, 21 Oct 2020 at 17:58, Konstantin Knauf <kna...@apache.org> > > > >> wrote: > > > >>> > > > >>>> Hi Kurt, Hi Shengkai, > > > >>>> > > > >>>> thanks for answering my questions and the additional > > clarifications. I > > > >>>> don't have a strong opinion on whether to extend the "kafka" > > connector > > > >> or > > > >>>> to introduce a new connector. So, from my perspective feel free to > > go > > > >> with > > > >>>> a separate connector. If we do introduce a new connector I > wouldn't > > > >> call it > > > >>>> "ktable" for aforementioned reasons (In addition, we might suggest > > > that > > > >>>> there is also a "kstreams" connector for symmetry reasons). I > don't > > > >> have a > > > >>>> good alternative name, though, maybe "kafka-compacted" or > > > >>>> "compacted-kafka". > > > >>>> > > > >>>> Thanks, > > > >>>> > > > >>>> Konstantin > > > >>>> > > > >>>> > > > >>>> On Wed, Oct 21, 2020 at 4:43 AM Kurt Young <ykt...@gmail.com> > > wrote: > > > >>>> > > > >>>>> Hi all, > > > >>>>> > > > >>>>> I want to describe the discussion process which drove us to have > > such > > > >>>>> conclusion, this might make some of > > > >>>>> the design choices easier to understand and keep everyone on the > > same > > > >>>> page. > > > >>>>> > > > >>>>> Back to the motivation, what functionality do we want to provide > in > > > the > > > >>>>> first place? We got a lot of feedback and > > > >>>>> questions from mailing lists that people want to write > > > Not-Insert-Only > > > >>>>> messages into kafka. They might be > > > >>>>> intentional or by accident, e.g. wrote an non-windowed aggregate > > > query > > > >> or > > > >>>>> non-windowed left outer join. And > > > >>>>> some users from KSQL world also asked about why Flink didn't > > leverage > > > >> the > > > >>>>> Key concept of every kafka topic > > > >>>>> and make kafka as a dynamic changing keyed table. > > > >>>>> > > > >>>>> To work with kafka better, we were thinking to extend the > > > functionality > > > >>>> of > > > >>>>> the current kafka connector by letting it > > > >>>>> accept updates and deletions. But due to the limitation of kafka, > > the > > > >>>>> update has to be "update by key", aka a table > > > >>>>> with primary key. > > > >>>>> > > > >>>>> This introduces a couple of conflicts with current kafka table's > > > >> options: > > > >>>>> 1. key.fields: as said above, we need the kafka table to have the > > > >> primary > > > >>>>> key constraint. And users can also configure > > > >>>>> key.fields freely, this might cause friction. (Sure we can do > some > > > >> sanity > > > >>>>> check on this but it also creates friction.) > > > >>>>> 2. sink.partitioner: to make the semantics right, we need to make > > > sure > > > >>>> all > > > >>>>> the updates on the same key are written to > > > >>>>> the same kafka partition, such we should force to use a hash by > key > > > >>>>> partition inside such table. Again, this has conflicts > > > >>>>> and creates friction with current user options. > > > >>>>> > > > >>>>> The above things are solvable, though not perfect or most user > > > >> friendly. > > > >>>>> > > > >>>>> Let's take a look at the reading side. The keyed kafka table > > contains > > > >> two > > > >>>>> kinds of messages: upsert or deletion. What upsert > > > >>>>> means is "If the key doesn't exist yet, it's an insert record. > > > >> Otherwise > > > >>>>> it's an update record". For the sake of correctness or > > > >>>>> simplicity, the Flink SQL engine also needs such information. If > we > > > >>>>> interpret all messages to "update record", some queries or > > > >>>>> operators may not work properly. It's weird to see an update > record > > > but > > > >>>> you > > > >>>>> haven't seen the insert record before. > > > >>>>> > > > >>>>> So what Flink should do is after reading out the records from > such > > > >> table, > > > >>>>> it needs to create a state to record which messages have > > > >>>>> been seen and then generate the correct row type correspondingly. > > > This > > > >>>> kind > > > >>>>> of couples the state and the data of the message > > > >>>>> queue, and it also creates conflicts with current kafka > connector. > > > >>>>> > > > >>>>> Think about if users suspend a running job (which contains some > > > reading > > > >>>>> state now), and then change the start offset of the reader. > > > >>>>> By changing the reading offset, it actually change the whole > story > > of > > > >>>>> "which records should be insert messages and which records > > > >>>>> should be update messages). And it will also make Flink to deal > > with > > > >>>>> another weird situation that it might receive a deletion > > > >>>>> on a non existing message. > > > >>>>> > > > >>>>> We were unsatisfied with all the frictions and conflicts it will > > > create > > > >>>> if > > > >>>>> we enable the "upsert & deletion" support to the current kafka > > > >>>>> connector. And later we begin to realize that we shouldn't treat > it > > > as > > > >> a > > > >>>>> normal message queue, but should treat it as a changing keyed > > > >>>>> table. We should be able to always get the whole data of such > table > > > (by > > > >>>>> disabling the start offset option) and we can also read the > > > >>>>> changelog out of such table. It's like a HBase table with binlog > > > >> support > > > >>>>> but doesn't have random access capability (which can be fulfilled > > > >>>>> by Flink's state). > > > >>>>> > > > >>>>> So our intention was instead of telling and persuading users what > > > kind > > > >> of > > > >>>>> options they should or should not use by extending > > > >>>>> current kafka connector when enable upsert support, we are > actually > > > >>>> create > > > >>>>> a whole new and different connector that has total > > > >>>>> different abstractions in SQL layer, and should be treated > totally > > > >>>>> different with current kafka connector. > > > >>>>> > > > >>>>> Hope this can clarify some of the concerns. > > > >>>>> > > > >>>>> Best, > > > >>>>> Kurt > > > >>>>> > > > >>>>> > > > >>>>> On Tue, Oct 20, 2020 at 5:20 PM Shengkai Fang <fskm...@gmail.com > > > > > >> wrote: > > > >>>>> > > > >>>>>> Hi devs, > > > >>>>>> > > > >>>>>> As many people are still confused about the difference option > > > >>>> behaviours > > > >>>>>> between the Kafka connector and KTable connector, Jark and I > list > > > the > > > >>>>>> differences in the doc[1]. > > > >>>>>> > > > >>>>>> Best, > > > >>>>>> Shengkai > > > >>>>>> > > > >>>>>> [1] > > > >>>>>> > > > >>>>>> > > > >>>>> > > > >>>> > > > >> > > > > > > https://docs.google.com/document/d/13oAWAwQez0lZLsyfV21BfTEze1fc2cz4AZKiNOyBNPk/edit > > > >>>>>> > > > >>>>>> Shengkai Fang <fskm...@gmail.com> 于2020年10月20日周二 下午12:05写道： > > > >>>>>> > > > >>>>>>> Hi Konstantin, > > > >>>>>>> > > > >>>>>>> Thanks for your reply. > > > >>>>>>> > > > >>>>>>>> It uses the "kafka" connector and does not specify a primary > > key. > > > >>>>>>> The dimensional table `users` is a ktable connector and we can > > > >>>> specify > > > >>>>>> the > > > >>>>>>> pk on the KTable. > > > >>>>>>> > > > >>>>>>>> Will it possible to use a "ktable" as a dimensional table in > > > >>>> FLIP-132 > > > >>>>>>> Yes. We can specify the watermark on the KTable and it can be > > used > > > >>>> as a > > > >>>>>>> dimension table in temporal join. > > > >>>>>>> > > > >>>>>>>> Introduce a new connector vs introduce a new property > > > >>>>>>> The main reason behind is that the KTable connector almost has > no > > > >>>>> common > > > >>>>>>> options with the Kafka connector. The options that can be > reused > > by > > > >>>>>> KTable > > > >>>>>>> connectors are 'topic', 'properties.bootstrap.servers' and > > > >>>>>>> 'value.fields-include' . We can't set cdc format for > 'key.format' > > > and > > > >>>>>>> 'value.format' in KTable connector now, which is available in > > > Kafka > > > >>>>>>> connector. Considering the difference between the options we > can > > > use, > > > >>>>>> it's > > > >>>>>>> more suitable to introduce an another connector rather than a > > > >>>> property. > > > >>>>>>> > > > >>>>>>> We are also fine to use "compacted-kafka" as the name of the > new > > > >>>>>>> connector. What do you think? > > > >>>>>>> > > > >>>>>>> Best, > > > >>>>>>> Shengkai > > > >>>>>>> > > > >>>>>>> Konstantin Knauf <kna...@apache.org> 于2020年10月19日周一 下午10:15写道： > > > >>>>>>> > > > >>>>>>>> Hi Shengkai, > > > >>>>>>>> > > > >>>>>>>> Thank you for driving this effort. I believe this a very > > important > > > >>>>>> feature > > > >>>>>>>> for many users who use Kafka and Flink SQL together. A few > > > questions > > > >>>>> and > > > >>>>>>>> thoughts: > > > >>>>>>>> > > > >>>>>>>> * Is your example "Use KTable as a reference/dimension table" > > > >>>> correct? > > > >>>>>> It > > > >>>>>>>> uses the "kafka" connector and does not specify a primary key. > > > >>>>>>>> > > > >>>>>>>> * Will it be possible to use a "ktable" table directly as a > > > >>>>> dimensional > > > >>>>>>>> table in temporal join (*based on event time*) (FLIP-132)? > This > > is > > > >>>> not > > > >>>>>>>> completely clear to me from the FLIP. > > > >>>>>>>> > > > >>>>>>>> * I'd personally prefer not to introduce a new connector and > > > instead > > > >>>>> to > > > >>>>>>>> extend the Kafka connector. We could add an additional > property > > > >>>>>>>> "compacted" > > > >>>>>>>> = "true"|"false". If it is set to "true", we can add > additional > > > >>>>>> validation > > > >>>>>>>> logic (e.g. "scan.startup.mode" can not be set, primary key > > > >>>> required, > > > >>>>>>>> etc.). If we stick to a separate connector I'd not call it > > > "ktable", > > > >>>>> but > > > >>>>>>>> rather "compacted-kafka" or similar. KTable seems to carry > more > > > >>>>> implicit > > > >>>>>>>> meaning than we want to imply here. > > > >>>>>>>> > > > >>>>>>>> * I agree that this is not a bounded source. If we want to > > > support a > > > >>>>>>>> bounded mode, this is an orthogonal concern that also applies > to > > > >>>> other > > > >>>>>>>> unbounded sources. > > > >>>>>>>> > > > >>>>>>>> Best, > > > >>>>>>>> > > > >>>>>>>> Konstantin > > > >>>>>>>> > > > >>>>>>>> On Mon, Oct 19, 2020 at 3:26 PM Jark Wu <imj...@gmail.com> > > wrote: > > > >>>>>>>> > > > >>>>>>>>> Hi Danny, > > > >>>>>>>>> > > > >>>>>>>>> First of all, we didn't introduce any concepts from KSQL > (e.g. > > > >>>>> Stream > > > >>>>>> vs > > > >>>>>>>>> Table notion). > > > >>>>>>>>> This new connector will produce a changelog stream, so it's > > still > > > >>>> a > > > >>>>>>>> dynamic > > > >>>>>>>>> table and doesn't conflict with Flink core concepts. > > > >>>>>>>>> > > > >>>>>>>>> The "ktable" is just a connector name, we can also call it > > > >>>>>>>>> "compacted-kafka" or something else. > > > >>>>>>>>> Calling it "ktable" is just because KSQL users can migrate to > > > >>>> Flink > > > >>>>>> SQL > > > >>>>>>>>> easily. > > > >>>>>>>>> > > > >>>>>>>>> Regarding to why introducing a new connector vs a new > property > > in > > > >>>>>>>> existing > > > >>>>>>>>> kafka connector: > > > >>>>>>>>> > > > >>>>>>>>> I think the main reason is that we want to have a clear > > > separation > > > >>>>> for > > > >>>>>>>> such > > > >>>>>>>>> two use cases, because they are very different. > > > >>>>>>>>> We also listed reasons in the FLIP, including: > > > >>>>>>>>> > > > >>>>>>>>> 1) It's hard to explain what's the behavior when users > specify > > > the > > > >>>>>> start > > > >>>>>>>>> offset from a middle position (e.g. how to process non exist > > > >>>> delete > > > >>>>>>>>> events). > > > >>>>>>>>> It's dangerous if users do that. So we don't provide > the > > > >>>> offset > > > >>>>>>>> option > > > >>>>>>>>> in the new connector at the moment. > > > >>>>>>>>> 2) It's a different perspective/abstraction on the same kafka > > > >>>> topic > > > >>>>>>>> (append > > > >>>>>>>>> vs. upsert). It would be easier to understand if we can > > separate > > > >>>>> them > > > >>>>>>>>> instead of mixing them in one connector. The new > > connector > > > >>>>>> requires > > > >>>>>>>>> hash sink partitioner, primary key declared, regular format. > > > >>>>>>>>> If we mix them in one connector, it might be confusing > > how > > > to > > > >>>>> use > > > >>>>>>>> the > > > >>>>>>>>> options correctly. > > > >>>>>>>>> 3) The semantic of the KTable connector is just the same as > > > KTable > > > >>>>> in > > > >>>>>>>> Kafka > > > >>>>>>>>> Stream. So it's very handy for Kafka Stream and KSQL users. > > > >>>>>>>>> We have seen several questions in the mailing list > asking > > > how > > > >>>> to > > > >>>>>>>> model > > > >>>>>>>>> a KTable and how to join a KTable in Flink SQL. > > > >>>>>>>>> > > > >>>>>>>>> Best, > > > >>>>>>>>> Jark > > > >>>>>>>>> > > > >>>>>>>>> On Mon, 19 Oct 2020 at 19:53, Jark Wu <imj...@gmail.com> > > wrote: > > > >>>>>>>>> > > > >>>>>>>>>> Hi Jingsong, > > > >>>>>>>>>> > > > >>>>>>>>>> As the FLIP describes, "KTable connector produces a > changelog > > > >>>>>> stream, > > > >>>>>>>>>> where each data record represents an update or delete > event.". > > > >>>>>>>>>> Therefore, a ktable source is an unbounded stream source. > > > >>>>> Selecting > > > >>>>>> a > > > >>>>>>>>>> ktable source is similar to selecting a kafka source with > > > >>>>>>>> debezium-json > > > >>>>>>>>>> format > > > >>>>>>>>>> that it never ends and the results are continuously updated. > > > >>>>>>>>>> > > > >>>>>>>>>> It's possible to have a bounded ktable source in the future, > > for > > > >>>>>>>> example, > > > >>>>>>>>>> add an option 'bounded=true' or 'end-offset=xxx'. > > > >>>>>>>>>> In this way, the ktable will produce a bounded changelog > > stream. > > > >>>>>>>>>> So I think this can be a compatible feature in the future. > > > >>>>>>>>>> > > > >>>>>>>>>> I don't think we should associate with ksql related > concepts. > > > >>>>>>>> Actually, > > > >>>>>>>>> we > > > >>>>>>>>>> didn't introduce any concepts from KSQL (e.g. Stream vs > Table > > > >>>>>> notion). > > > >>>>>>>>>> The "ktable" is just a connector name, we can also call it > > > >>>>>>>>>> "compacted-kafka" or something else. > > > >>>>>>>>>> Calling it "ktable" is just because KSQL users can migrate > to > > > >>>>> Flink > > > >>>>>>>> SQL > > > >>>>>>>>>> easily. > > > >>>>>>>>>> > > > >>>>>>>>>> Regarding the "value.fields-include", this is an option > > > >>>> introduced > > > >>>>>> in > > > >>>>>>>>>> FLIP-107 for Kafka connector. > > > >>>>>>>>>> I think we should keep the same behavior with the Kafka > > > >>>> connector. > > > >>>>>> I'm > > > >>>>>>>>> not > > > >>>>>>>>>> sure what's the default behavior of KSQL. > > > >>>>>>>>>> But I guess it also stores the keys in value from this > example > > > >>>>> docs > > > >>>>>>>> (see > > > >>>>>>>>>> the "users_original" table) [1]. > > > >>>>>>>>>> > > > >>>>>>>>>> Best, > > > >>>>>>>>>> Jark > > > >>>>>>>>>> > > > >>>>>>>>>> [1]: > > > >>>>>>>>>> > > > >>>>>>>>> > > > >>>>>>>> > > > >>>>>> > > > >>>>> > > > >>>> > > > >> > > > > > > https://docs.confluent.io/current/ksqldb/tutorials/basics-local.html#create-a-stream-and-table > > > >>>>>>>>>> > > > >>>>>>>>>> > > > >>>>>>>>>> On Mon, 19 Oct 2020 at 18:17, Danny Chan < > > yuzhao....@gmail.com> > > > >>>>>>>> wrote: > > > >>>>>>>>>> > > > >>>>>>>>>>> The concept seems conflicts with the Flink abstraction > > “dynamic > > > >>>>>>>> table”, > > > >>>>>>>>>>> in Flink we see both “stream” and “table” as a dynamic > table, > > > >>>>>>>>>>> > > > >>>>>>>>>>> I think we should make clear first how to express stream > and > > > >>>>> table > > > >>>>>>>>>>> specific features on one “dynamic table”, > > > >>>>>>>>>>> it is more natural for KSQL because KSQL takes stream and > > table > > > >>>>> as > > > >>>>>>>>>>> different abstractions for representing collections. In > KSQL, > > > >>>>> only > > > >>>>>>>>> table is > > > >>>>>>>>>>> mutable and can have a primary key. > > > >>>>>>>>>>> > > > >>>>>>>>>>> Does this connector belongs to the “table” scope or > “stream” > > > >>>>> scope > > > >>>>>> ? > > > >>>>>>>>>>> > > > >>>>>>>>>>> Some of the concepts (such as the primary key on stream) > > should > > > >>>>> be > > > >>>>>>>>>>> suitable for all the connectors, not just Kafka, Shouldn’t > > this > > > >>>>> be > > > >>>>>> an > > > >>>>>>>>>>> extension of existing Kafka connector instead of a totally > > new > > > >>>>>>>>> connector ? > > > >>>>>>>>>>> What about the other connectors ? > > > >>>>>>>>>>> > > > >>>>>>>>>>> Because this touches the core abstraction of Flink, we > better > > > >>>>> have > > > >>>>>> a > > > >>>>>>>>>>> top-down overall design, following the KSQL directly is not > > the > > > >>>>>>>> answer. > > > >>>>>>>>>>> > > > >>>>>>>>>>> P.S. For the source > > > >>>>>>>>>>>> Shouldn’t this be an extension of existing Kafka connector > > > >>>>>> instead > > > >>>>>>>> of > > > >>>>>>>>> a > > > >>>>>>>>>>> totally new connector ? > > > >>>>>>>>>>> > > > >>>>>>>>>>> How could we achieve that (e.g. set up the parallelism > > > >>>>> correctly) ? > > > >>>>>>>>>>> > > > >>>>>>>>>>> Best, > > > >>>>>>>>>>> Danny Chan > > > >>>>>>>>>>> 在 2020年10月19日 +0800 PM5:17，Jingsong Li < > > jingsongl...@gmail.com > > > >>>>>>> ，写道： > > > >>>>>>>>>>>> Thanks Shengkai for your proposal. > > > >>>>>>>>>>>> > > > >>>>>>>>>>>> +1 for this feature. > > > >>>>>>>>>>>> > > > >>>>>>>>>>>>> Future Work: Support bounded KTable source > > > >>>>>>>>>>>> > > > >>>>>>>>>>>> I don't think it should be a future work, I think it is > one > > > >>>> of > > > >>>>>> the > > > >>>>>>>>>>>> important concepts of this FLIP. We need to understand it > > > >>>> now. > > > >>>>>>>>>>>> > > > >>>>>>>>>>>> Intuitively, a ktable in my opinion is a bounded table > > rather > > > >>>>>> than > > > >>>>>>>> a > > > >>>>>>>>>>>> stream, so select should produce a bounded table by > default. > > > >>>>>>>>>>>> > > > >>>>>>>>>>>> I think we can list Kafka related knowledge, because the > > word > > > >>>>>>>> `ktable` > > > >>>>>>>>>>> is > > > >>>>>>>>>>>> easy to associate with ksql related concepts. (If > possible, > > > >>>>> it's > > > >>>>>>>>> better > > > >>>>>>>>>>> to > > > >>>>>>>>>>>> unify with it) > > > >>>>>>>>>>>> > > > >>>>>>>>>>>> What do you think? > > > >>>>>>>>>>>> > > > >>>>>>>>>>>>> value.fields-include > > > >>>>>>>>>>>> > > > >>>>>>>>>>>> What about the default behavior of KSQL? > > > >>>>>>>>>>>> > > > >>>>>>>>>>>> Best, > > > >>>>>>>>>>>> Jingsong > > > >>>>>>>>>>>> > > > >>>>>>>>>>>> On Mon, Oct 19, 2020 at 4:33 PM Shengkai Fang < > > > >>>>> fskm...@gmail.com > > > >>>>>>> > > > >>>>>>>>>>> wrote: > > > >>>>>>>>>>>> > > > >>>>>>>>>>>>> Hi, devs. > > > >>>>>>>>>>>>> > > > >>>>>>>>>>>>> Jark and I want to start a new FLIP to introduce the > KTable > > > >>>>>>>>>>> connector. The > > > >>>>>>>>>>>>> KTable is a shortcut of "Kafka Table", it also has the > same > > > >>>>>>>>> semantics > > > >>>>>>>>>>> with > > > >>>>>>>>>>>>> the KTable notion in Kafka Stream. > > > >>>>>>>>>>>>> > > > >>>>>>>>>>>>> FLIP-149: > > > >>>>>>>>>>>>> > > > >>>>>>>>>>>>> > > > >>>>>>>>>>> > > > >>>>>>>>> > > > >>>>>>>> > > > >>>>>> > > > >>>>> > > > >>>> > > > >> > > > > > > https://cwiki.apache.org/confluence/display/FLINK/FLIP-149%3A+Introduce+the+KTable+Connector > > > >>>>>>>>>>>>> > > > >>>>>>>>>>>>> Currently many users have expressed their needs for the > > > >>>>> upsert > > > >>>>>>>> Kafka > > > >>>>>>>>>>> by > > > >>>>>>>>>>>>> mail lists and issues. The KTable connector has several > > > >>>>>> benefits > > > >>>>>>>> for > > > >>>>>>>>>>> users: > > > >>>>>>>>>>>>> > > > >>>>>>>>>>>>> 1. Users are able to interpret a compacted Kafka Topic as > > > >>>> an > > > >>>>>>>> upsert > > > >>>>>>>>>>> stream > > > >>>>>>>>>>>>> in Apache Flink. And also be able to write a changelog > > > >>>> stream > > > >>>>>> to > > > >>>>>>>>> Kafka > > > >>>>>>>>>>>>> (into a compacted topic). > > > >>>>>>>>>>>>> 2. As a part of the real time pipeline, store join or > > > >>>>> aggregate > > > >>>>>>>>>>> result (may > > > >>>>>>>>>>>>> contain updates) into a Kafka topic for further > > > >>>> calculation; > > > >>>>>>>>>>>>> 3. The semantic of the KTable connector is just the same > as > > > >>>>>>>> KTable > > > >>>>>>>>> in > > > >>>>>>>>>>> Kafka > > > >>>>>>>>>>>>> Stream. So it's very handy for Kafka Stream and KSQL > users. > > > >>>>> We > > > >>>>>>>> have > > > >>>>>>>>>>> seen > > > >>>>>>>>>>>>> several questions in the mailing list asking how to > model a > > > >>>>>>>> KTable > > > >>>>>>>>>>> and how > > > >>>>>>>>>>>>> to join a KTable in Flink SQL. > > > >>>>>>>>>>>>> > > > >>>>>>>>>>>>> We hope it can expand the usage of the Flink with Kafka. > > > >>>>>>>>>>>>> > > > >>>>>>>>>>>>> I'm looking forward to your feedback. > > > >>>>>>>>>>>>> > > > >>>>>>>>>>>>> Best, > > > >>>>>>>>>>>>> Shengkai > > > >>>>>>>>>>>>> > > > >>>>>>>>>>>> > > > >>>>>>>>>>>> > > > >>>>>>>>>>>> -- > > > >>>>>>>>>>>> Best, Jingsong Lee > > > >>>>>>>>>>> > > > >>>>>>>>>> > > > >>>>>>>>> > > > >>>>>>>> > > > >>>>>>>> > > > >>>>>>>> -- > > > >>>>>>>> > > > >>>>>>>> Konstantin Knauf > > > >>>>>>>> > > > >>>>>>>> https://twitter.com/snntrable > > > >>>>>>>> > > > >>>>>>>> https://github.com/knaufk > > > >>>>>>>> > > > >>>>>>> > > > >>>>>> > > > >>>>> > > > >>>> > > > >>>> > > > >>>> -- > > > >>>> > > > >>>> Konstantin Knauf > > > >>>> > > > >>>> https://twitter.com/snntrable > > > >>>> > > > >>>> https://github.com/knaufk > > > >>>> > > > >>> > > > >> > > > >> > > > > > > > > > > > > > > -- > > > > Seth Wiesman | Solutions Architect > > > > +1 314 387 1463 > > > > <https://www.ververica.com/> > > > > Follow us @VervericaData > > > > -- > > > > Join Flink Forward <https://flink-forward.org/> - The Apache Flink > > Conference > > > > Stream Processing | Event Driven | Real Time > > >
