Hi Jan,
I understand your concern. One implication of not passing any store name and
just getting an IQ handle is that all KTables would need to be materialised.
Currently the store name (or proposed .materialize() call) act as hints on
whether to materialise the KTable or not. Materialising every KTable can be
expensive, although there are some tricks one can play, e.g., have a virtual
store rather than one backed by a Kafka topic.
However, even with the above, after getting an IQ handle, the user would still
need to use IQ APIs to query the state. As such, we would still continue to be
outside the original DSL so this wouldn't address your original concern.
So I read this suggestion as simplifying the APIs by removing the store name,
at the cost of having to materialise every KTable. It's definitely an option
we'll consider as part of this KIP.
Thanks
Eno
> On 28 Jan 2017, at 06:49, Jan Filipiak <jan.filip...@trivago.com> wrote:
>
> Hi Exactly
>
> I know it works from the Processor API, but my suggestion would prevent DSL
> users dealing with storenames what so ever.
>
> In general I am pro switching between DSL and Processor API easily. (In my
> Stream applications I do this a lot with reflection and instanciating
> KTableImpl) Concerning this KIP all I say is that there should be a DSL
> concept of "I want to expose this __KTable__. This can be a Method like
> KTable::retrieveIQHandle():InteractiveQueryHandle, the table would know to
> materialize, and the user had a reference to the "store and the distributed
> query mechanism by the Interactive Query Handle" under the hood it can use
> the same mechanism as the PIP people again.
>
> I hope you see my point J
>
> Best Jan
>
>
> #DeathToIQMoreAndBetterConnectors :)
>
>
>
>
> On 27.01.2017 21:59, Matthias J. Sax wrote:
>> Jan,
>>
>> the IQ feature is not limited to Streams DSL but can also be used for
>> Stores used in PAPI. Thus, we need a mechanism that does work for PAPI
>> and DSL.
>>
>> Nevertheless I see your point and I think we could provide a better API
>> for KTable stores including the discovery of remote shards of the same
>> KTable.
>>
>> @Michael: Yes, right now we do have a lot of overloads and I am not a
>> big fan of those -- I would rather prefer a builder pattern. But that
>> might be a different discussion (nevertheless, if we would aim for a API
>> rework, we should get the changes with regard to stores right from the
>> beginning on, in order to avoid a redesign later on.)
>>
>> something like:
>>
>> stream.groupyByKey()
>> .window(TimeWindow.of(5000))
>> .aggregate(...)
>> .withAggValueSerde(new CustomTypeSerde())
>> .withStoreName("storeName);
>>
>>
>> (This would also reduce JavaDoc redundancy -- maybe a personal pain
>> point right now :))
>>
>>
>> -Matthias
>>
>> On 1/27/17 11:10 AM, Jan Filipiak wrote:
>>> Yeah,
>>>
>>> Maybe my bad that I refuse to look into IQ as i don't find them anywhere
>>> close to being interesting. The Problem IMO is that people need to know
>>> the Store name), so we are working on different levels to achieve a
>>> single goal.
>>>
>>> What is your peoples opinion on having a method on KTABLE that returns
>>> them something like a Keyvalue store. There is of course problems like
>>> "it cant be used before the streamthreads are going and groupmembership
>>> is established..." but the benefit would be that for the user there is a
>>> consistent way of saying "Hey I need it materialized as querries gonna
>>> be comming" + already get a Thing that he can execute the querries on in
>>> 1 step.
>>> What I think is unintuitive here is you need to say materialize on this
>>> Ktable and then you go somewhere else and find its store name and then
>>> you go to the kafkastreams instance and ask for the store with this name.
>>>
>>> So one could the user help to stay in DSL land and therefore maybe
>>> confuse him less.
>>>
>>> Best Jan
>>>
>>> #DeathToIQMoreAndBetterConnectors :)
>>>
>>>
>>>
>>> On 27.01.2017 16:51, Damian Guy wrote:
>>>> I think Jan is saying that they don't always need to be materialized,
>>>> i.e.,
>>>> filter just needs to apply the ValueGetter, it doesn't need yet another
>>>> physical state store.
>>>>
>>>> On Fri, 27 Jan 2017 at 15:49 Michael Noll <mich...@confluent.io> wrote:
>>>>
>>>>> Like Damian, and for the same reasons, I am more in favor of overloading
>>>>> methods rather than introducing `materialize()`.
>>>>> FWIW, we already have a similar API setup for e.g.
>>>>> `KTable#through(topicName, stateStoreName)`.
>>>>>
>>>>> A related but slightly different question is what e.g. Jan Filipiak
>>>>> mentioned earlier in this thread:
>>>>> I think we need to explain more clearly why KIP-114 doesn't propose the
>>>>> seemingly simpler solution of always materializing tables/state stores.
>>>>>
>>>>>
>>>>>
>>>>> On Fri, Jan 27, 2017 at 4:38 PM, Jan Filipiak <jan.filip...@trivago.com>
>>>>> wrote:
>>>>>
>>>>>> Hi,
>>>>>>
>>>>>> Yeah its confusing, Why shoudn't it be querable by IQ? If you uses the
>>>>>> ValueGetter of Filter it will apply the filter and should be completely
>>>>>> transparent as to if another processor or IQ is accessing it? How can
>>>>> this
>>>>>> new method help?
>>>>>>
>>>>>> I cannot see the reason for the additional materialize method being
>>>>>> required! Hence I suggest leave it alone.
>>>>>> regarding removing the others I dont have strong opinions and it
>>>>>> seems to
>>>>>> be unrelated.
>>>>>>
>>>>>> Best Jan
>>>>>>
>>>>>>
>>>>>>
>>>>>>
>>>>>> On 26.01.2017 20:48, Eno Thereska wrote:
>>>>>>
>>>>>>> Forwarding this thread to the users list too in case people would like
>>>>> to
>>>>>>> comment. It is also on the dev list.
>>>>>>>
>>>>>>> Thanks
>>>>>>> Eno
>>>>>>>
>>>>>>> Begin forwarded message:
>>>>>>>> From: "Matthias J. Sax" <matth...@confluent.io>
>>>>>>>> Subject: Re: [DISCUSS] KIP-114: KTable materialization and improved
>>>>>>>> semantics
>>>>>>>> Date: 24 January 2017 at 19:30:10 GMT
>>>>>>>> To: dev@kafka.apache.org
>>>>>>>> Reply-To: dev@kafka.apache.org
>>>>>>>>
>>>>>>>> That not what I meant by "huge impact".
>>>>>>>>
>>>>>>>> I refer to the actions related to materialize a KTable: creating a
>>>>>>>> RocksDB store and a changelog topic -- users should be aware about
>>>>>>>> runtime implication and this is better expressed by an explicit
>>>>>>>> method
>>>>>>>> call, rather than implicitly triggered by using a different
>>>>>>>> overload of
>>>>>>>> a method.
>>>>>>>>
>>>>>>>>
>>>>>>>> -Matthias
>>>>>>>>
>>>>>>>> On 1/24/17 1:35 AM, Damian Guy wrote:
>>>>>>>>
>>>>>>>>> I think your definition of a huge impact and mine are rather
>>>>>>>>> different
>>>>>>>>> ;-P
>>>>>>>>> Overloading a few methods is not really a huge impact IMO. It is
>>>>> also a
>>>>>>>>> sacrifice worth making for readability, usability of the API.
>>>>>>>>>
>>>>>>>>> On Mon, 23 Jan 2017 at 17:55 Matthias J. Sax <matth...@confluent.io>
>>>>>>>>> wrote:
>>>>>>>>>
>>>>>>>>> I understand your argument, but do not agree with it.
>>>>>>>>>> Your first version (even if the "flow" is not as nice) is more
>>>>> explicit
>>>>>>>>>> than the second version. Adding a stateStoreName parameter is quite
>>>>>>>>>> implicit but has a huge impact -- thus, I prefer the rather more
>>>>>>>>>> verbose
>>>>>>>>>> but explicit version.
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>> -Matthias
>>>>>>>>>>
>>>>>>>>>> On 1/23/17 1:39 AM, Damian Guy wrote:
>>>>>>>>>>
>>>>>>>>>>> I'm not a fan of materialize. I think it interrupts the flow, i.e,
>>>>>>>>>>>
>>>>>>>>>>> table.mapValue(..).materialize().join(..).materialize()
>>>>>>>>>>> compared to:
>>>>>>>>>>> table.mapValues(..).join(..)
>>>>>>>>>>>
>>>>>>>>>>> I know which one i prefer.
>>>>>>>>>>> My preference is stil to provide overloaded methods where
>>>>>>>>>>> people can
>>>>>>>>>>> specify the store names if they want, otherwise we just generate
>>>>> them.
>>>>>>>>>>> On Mon, 23 Jan 2017 at 05:30 Matthias J. Sax
>>>>>>>>>>> <matth...@confluent.io
>>>>>>>>>> wrote:
>>>>>>>>>>
>>>>>>>>>>> Hi,
>>>>>>>>>>>> thanks for the KIP Eno! Here are my 2 cents:
>>>>>>>>>>>>
>>>>>>>>>>>> 1) I like Guozhang's proposal about removing store name from all
>>>>>>>>>>>> KTable
>>>>>>>>>>>> methods and generate internal names (however, I would do this as
>>>>>>>>>>>> overloads). Furthermore, I would not force users to call
>>>>>>>>>>>> .materialize()
>>>>>>>>>>>> if they want to query a store, but add one more method
>>>>>>>>>>>> .stateStoreName()
>>>>>>>>>>>> that returns the store name if the KTable is materialized. Thus,
>>>>> also
>>>>>>>>>>>> .materialize() must not necessarily have a parameter storeName
>>>>>>>>>>>> (ie,
>>>>>>>>>>>> we
>>>>>>>>>>>> should have some overloads here).
>>>>>>>>>>>>
>>>>>>>>>>>> I would also not allow to provide a null store name (to
>>>>>>>>>>>> indicate no
>>>>>>>>>>>> materialization if not necessary) but throw an exception.
>>>>>>>>>>>>
>>>>>>>>>>>> This yields some simplification (see below).
>>>>>>>>>>>>
>>>>>>>>>>>>
>>>>>>>>>>>> 2) I also like Guozhang's proposal about KStream#toTable()
>>>>>>>>>>>>
>>>>>>>>>>>>
>>>>>>>>>>>> 3)
>>>>>>>>>>>>
>>>>>>>>>>>>> 3. What will happen when you call materialize on KTable
>>>>>>>>>>>>> that is
>>>>>>>>>>>>> already
>>>>>>>>>>>>> materialized? Will it create another StateStore (providing
>>>>>>>>>>>>> the
>>>>>>>>>>>>>> name
>>>>>>>>>>>>>>
>>>>>>>>>>>>> is
>>>>>>>>>>> different), throw an Exception?
>>>>>>>>>>>>> Currently an exception is thrown, but see below.
>>>>>>>>>>>>>
>>>>>>>>>>>>>
>>>>>>>>>>>>> If we follow approach (1) from Guozhang, there is no need to
>>>>>>>>>>>>> worry
>>>>>>>>>>>> about
>>>>>>>>>>>> a second materialization and also no exception must be throws. A
>>>>>>>>>>>> call to
>>>>>>>>>>>> .materialize() basically sets a "materialized flag" (ie,
>>>>>>>>>>>> idempotent
>>>>>>>>>>>> operation) and sets a new name.
>>>>>>>>>>>>
>>>>>>>>>>>>
>>>>>>>>>>>> 4)
>>>>>>>>>>>>
>>>>>>>>>>>>> Rename toStream() to toKStream() for consistency.
>>>>>>>>>>>>> Not sure whether that is really required. We also use
>>>>>>>>>>>>> `KStreamBuilder#stream()` and `KStreamBuilder#table()`, for
>>>>> example,
>>>>>>>>>>>> and
>>>>>>>>>>> don't care about the "K" prefix.
>>>>>>>>>>>> Eno's reply:
>>>>>>>>>>>>
>>>>>>>>>>>>> I think changing it to `toKStream` would make it absolutely
>>>>>>>>>>>>> clear
>>>>>>>>>>>>> what
>>>>>>>>>>>>>
>>>>>>>>>>>> we are converting it to.
>>>>>>>>>>>>
>>>>>>>>>>>>> I'd say we should probably change the KStreamBuilder methods
>>>>>>>>>>>>> (but
>>>>>>>>>>>>> not
>>>>>>>>>>>>>
>>>>>>>>>>>> in
>>>>>>>>>>> this KIP).
>>>>>>>>>>>> I would keep #toStream(). (see below)
>>>>>>>>>>>>
>>>>>>>>>>>>
>>>>>>>>>>>> 5) We should not remove any methods but only deprecate them.
>>>>>>>>>>>>
>>>>>>>>>>>>
>>>>>>>>>>>>
>>>>>>>>>>>> A general note:
>>>>>>>>>>>>
>>>>>>>>>>>> I do not understand your comments "Rejected Alternatives". You
>>>>>>>>>>>> say
>>>>>>>>>>>> "Have
>>>>>>>>>>>> the KTable be the materialized view" was rejected. But your KIP
>>>>>>>>>>>> actually
>>>>>>>>>>>> does exactly this -- the changelog abstraction of KTable is
>>>>> secondary
>>>>>>>>>>>> after those changes and the "view" abstraction is what a
>>>>>>>>>>>> KTable is.
>>>>>>>>>>>> And
>>>>>>>>>>>> just to be clear, I like this a lot:
>>>>>>>>>>>>
>>>>>>>>>>>> - it aligns with the name KTable
>>>>>>>>>>>> - is aligns with stream-table-duality
>>>>>>>>>>>> - it aligns with IQ
>>>>>>>>>>>>
>>>>>>>>>>>> I would say that a KTable is a "view abstraction" (as
>>>>>>>>>>>> materialization is
>>>>>>>>>>>> optional).
>>>>>>>>>>>>
>>>>>>>>>>>>
>>>>>>>>>>>>
>>>>>>>>>>>> -Matthias
>>>>>>>>>>>>
>>>>>>>>>>>>
>>>>>>>>>>>>
>>>>>>>>>>>>
>>>>>>>>>>>> On 1/22/17 5:05 PM, Guozhang Wang wrote:
>>>>>>>>>>>>
>>>>>>>>>>>>> Thanks for the KIP Eno, I have a few meta comments and a few
>>>>>>>>>>>>> detailed
>>>>>>>>>>>>> comments:
>>>>>>>>>>>>>
>>>>>>>>>>>>> 1. I like the materialize() function in general, but I would
>>>>>>>>>>>>> like
>>>>> to
>>>>>>>>>>>> see
>>>>>>>>>>> how other KTable functions should be updated accordingly. For
>>>>> example,
>>>>>>>>>>>> 1)
>>>>>>>>>>> KStreamBuilder.table(..) has a state store name parameter, and we
>>>>> will
>>>>>>>>>>>>> always materialize the KTable unless its state store name is set
>>>>> to
>>>>>>>>>>>> null;
>>>>>>>>>>> 2) KTable.agg requires the result KTable to be materialized, and
>>>>> hence
>>>>>>>>>>>> it
>>>>>>>>>>> also have a state store name; 3) KTable.join requires the joining
>>>>>>>>>>>>> table
>>>>>>>>>>>>>
>>>>>>>>>>>> to
>>>>>>>>>>>>
>>>>>>>>>>>>> be materialized. And today we do not actually have a
>>>>>>>>>>>>> mechanism to
>>>>>>>>>>>>>
>>>>>>>>>>>> enforce
>>>>>>>>>>> that, but will only throw an exception at runtime if it is not
>>>>>>>>>>> (e.g.
>>>>>>>>>>>>> if
>>>>>>>>>>>>>
>>>>>>>>>>>> you
>>>>>>>>>>>>
>>>>>>>>>>>>> have "builder.table("topic", null).join()" a RTE will be
>>>>>>>>>>>>> thrown).
>>>>>>>>>>>>>
>>>>>>>>>>>>> I'd make an extended proposal just to kick off the discussion
>>>>> here:
>>>>>>>>>>>> let's
>>>>>>>>>>> remove all the state store params in other KTable functions,
>>>>>>>>>>> and if
>>>>> in
>>>>>>>>>>>> some
>>>>>>>>>>>>
>>>>>>>>>>>>> cases KTable have to be materialized (e.g. KTable resulted from
>>>>>>>>>>>>>
>>>>>>>>>>>> KXX.agg)
>>>>>>>>>>> and users do not call materialize(), then we treat it as "users
>>>>>>>>>>> are
>>>>>>>>>>>>> not
>>>>>>>>>>>>> interested in querying it at all" and hence use an internal name
>>>>>>>>>>>>>
>>>>>>>>>>>> generated
>>>>>>>>>>>>
>>>>>>>>>>>>> for the materialized KTable; i.e. although it is materialized
>>>>>>>>>>>>> the
>>>>>>>>>>>>> state
>>>>>>>>>>>>> store is not exposed to users. And if users call materialize()
>>>>>>>>>>>>>
>>>>>>>>>>>> afterwards
>>>>>>>>>>> but we have already decided to materialize it, we can replace the
>>>>>>>>>>>> internal
>>>>>>>>>>>>
>>>>>>>>>>>>> name with the user's provided names. Then from a user's
>>>>> point-view,
>>>>>>>>>>>>> if
>>>>>>>>>>>>>
>>>>>>>>>>>> they
>>>>>>>>>>>>
>>>>>>>>>>>>> ever want to query a KTable, they have to call materialize()
>>>>>>>>>>>>> with
>>>>> a
>>>>>>>>>>>> given
>>>>>>>>>>> state store name. This approach has one awkwardness though, that
>>>>>>>>>>>>> serdes
>>>>>>>>>>>>>
>>>>>>>>>>>> and
>>>>>>>>>>>>
>>>>>>>>>>>>> state store names param are not separated and could be
>>>>>>>>>>>>> overlapped
>>>>>>>>>>>>> (see
>>>>>>>>>>>>> detailed comment #2 below).
>>>>>>>>>>>>>
>>>>>>>>>>>>>
>>>>>>>>>>>>> 2. This step does not need to be included in this KIP, but just
>>>>> as a
>>>>>>>>>>>>> reference / future work: as we have discussed before, we may
>>>>> enforce
>>>>>>>>>>>>> materialize KTable.join resulted KTables as well in the
>>>>>>>>>>>>> future. If
>>>>>>>>>>>>> we
>>>>>>>>>>>>>
>>>>>>>>>>>> do
>>>>>>>>>>> that, then:
>>>>>>>>>>>>> a) KXX.agg resulted KTables are always materialized;
>>>>>>>>>>>>> b) KTable.agg requires the aggregating KTable to always be
>>>>>>>>>>>>> materialized
>>>>>>>>>>>>> (otherwise we would not know the old value);
>>>>>>>>>>>>> c) KTable.join resulted KTables are always materialized, and so
>>>>> are
>>>>>>>>>>>>> the
>>>>>>>>>>>>> joining KTables to always be materialized.
>>>>>>>>>>>>> d) KTable.filter/mapValues resulted KTables materialization
>>>>>>>>>>>>> depend
>>>>>>>>>>>>> on
>>>>>>>>>>>>>
>>>>>>>>>>>> its
>>>>>>>>>>> parent's materialization;
>>>>>>>>>>>>> By recursive induction all KTables are actually always
>>>>> materialized,
>>>>>>>>>>>> and
>>>>>>>>>>> then the effect of the "materialize()" is just for specifying the
>>>>>>>>>>>>> state
>>>>>>>>>>>>> store names. In this scenario, we do not need to send
>>>>>>>>>>>>> Change<V> in
>>>>>>>>>>>>> repartition topics within joins any more, but only for
>>>>> repartitions
>>>>>>>>>>>> topics
>>>>>>>>>>>>
>>>>>>>>>>>>> within aggregations. Instead, we can just send a "tombstone"
>>>>> without
>>>>>>>>>>>> the
>>>>>>>>>>> old value and we do not need to calculate joins twice (one more
>>>>>>>>>>> time
>>>>>>>>>>>> when
>>>>>>>>>>> old value is received).
>>>>>>>>>>>>> 3. I'm wondering if it is worth-while to add a
>>>>>>>>>>>>> "KStream#toTable()"
>>>>>>>>>>>>>
>>>>>>>>>>>> function
>>>>>>>>>>>>
>>>>>>>>>>>>> which is interpreted as a dummy-aggregation where the new value
>>>>>>>>>>>>> always
>>>>>>>>>>>>> replaces the old value. I have seen a couple of use cases of
>>>>>>>>>>>>> this,
>>>>>>>>>>>>> for
>>>>>>>>>>>>> example, users want to read a changelog topic, apply some
>>>>>>>>>>>>> filters,
>>>>>>>>>>>>> and
>>>>>>>>>>>>>
>>>>>>>>>>>> then
>>>>>>>>>>>>
>>>>>>>>>>>>> materialize it into a KTable with state stores without creating
>>>>>>>>>>>>>
>>>>>>>>>>>> duplicated
>>>>>>>>>>>>
>>>>>>>>>>>>> changelog topics. With materialize() and toTable I'd imagine
>>>>>>>>>>>>> users
>>>>>>>>>>>>> can
>>>>>>>>>>>>> specify sth. like:
>>>>>>>>>>>>>
>>>>>>>>>>>>> "
>>>>>>>>>>>>> KStream stream = builder.stream("topic1").filter(..);
>>>>>>>>>>>>> KTable table = stream.toTable(..);
>>>>>>>>>>>>> table.materialize("state1");
>>>>>>>>>>>>> "
>>>>>>>>>>>>>
>>>>>>>>>>>>> And the library in this case could set store "state1" 's
>>>>>>>>>>>>> changelog
>>>>>>>>>>>>>
>>>>>>>>>>>> topic
>>>>>>>>>>> to
>>>>>>>>>>>>> be "topic1", and applying the filter on the fly while
>>>>>>>>>>>>> (re-)storing
>>>>>>>>>>>>> its
>>>>>>>>>>>>> state by reading from this topic, instead of creating a second
>>>>>>>>>>>>>
>>>>>>>>>>>> changelog
>>>>>>>>>>> topic like "appID-state1-changelog" which is a semi-duplicate of
>>>>>>>>>>>> "topic1".
>>>>>>>>>>>>
>>>>>>>>>>>>> Detailed:
>>>>>>>>>>>>>
>>>>>>>>>>>>> 1. I'm +1 with Michael regarding "#toStream"; actually I was
>>>>>>>>>>>>> thinking
>>>>>>>>>>>>>
>>>>>>>>>>>> about
>>>>>>>>>>>>
>>>>>>>>>>>>> renaming to "#toChangeLog" but after thinking a bit more I think
>>>>>>>>>>>>>
>>>>>>>>>>>> #toStream
>>>>>>>>>>>>
>>>>>>>>>>>>> is still better, and we can just mention in the javaDoc that
>>>>>>>>>>>>> it is
>>>>>>>>>>>>> transforming its underlying changelog stream to a normal stream.
>>>>>>>>>>>>> 2. As Damian mentioned, there are a few scenarios where the
>>>>>>>>>>>>> serdes
>>>>>>>>>>>>> are
>>>>>>>>>>>>> already specified in a previous operation whereas it is not
>>>>>>>>>>>>> known
>>>>>>>>>>>>>
>>>>>>>>>>>> before
>>>>>>>>>>> calling materialize, for example:
>>>>>>>>>>>>> stream.groupByKey.agg(serde).materialize(serde) v.s.
>>>>>>>>>>>>>
>>>>>>>>>>>> table.mapValues(/*no
>>>>>>>>>>> serde specified*/).materialize(serde). We need to specify what are
>>>>>>>>>>>>> the
>>>>>>>>>>>>> handling logic here.
>>>>>>>>>>>>> 3. We can remove "KTable#to" call as well, and enforce users to
>>>>>>>>>>>>> call "
>>>>>>>>>>>>> KTable.toStream.to" to be more clear.
>>>>>>>>>>>>>
>>>>>>>>>>>>>
>>>>>>>>>>>>> Guozhang
>>>>>>>>>>>>>
>>>>>>>>>>>>>
>>>>>>>>>>>>> On Wed, Jan 18, 2017 at 3:22 AM, Eno Thereska <
>>>>>>>>>>>>> eno.there...@gmail.com>
>>>>>>>>>>>>> wrote:
>>>>>>>>>>>>>
>>>>>>>>>>>>> I think changing it to `toKStream` would make it absolutely
>>>>>>>>>>>>> clear
>>>>>>>>>>>>>> what
>>>>>>>>>>>>>>
>>>>>>>>>>>>> we
>>>>>>>>>>>>> are converting it to.
>>>>>>>>>>>>>> I'd say we should probably change the KStreamBuilder methods
>>>>>>>>>>>>>> (but
>>>>>>>>>>>>>> not
>>>>>>>>>>>>>>
>>>>>>>>>>>>> in
>>>>>>>>>>> this KIP).
>>>>>>>>>>>>>> Thanks
>>>>>>>>>>>>>> Eno
>>>>>>>>>>>>>>
>>>>>>>>>>>>>> On 17 Jan 2017, at 13:59, Michael Noll <mich...@confluent.io>
>>>>>>>>>>>>>>> wrote:
>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>> Rename toStream() to toKStream() for consistency.
>>>>>>>>>>>>>>> Not sure whether that is really required. We also use
>>>>>>>>>>>>>>> `KStreamBuilder#stream()` and `KStreamBuilder#table()`, for
>>>>>>>>>>>>>>> example,
>>>>>>>>>>>>>>>
>>>>>>>>>>>>>> and
>>>>>>>>>>>>> don't care about the "K" prefix.
>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>> On Tue, Jan 17, 2017 at 10:55 AM, Eno Thereska <
>>>>>>>>>>>>>>>
>>>>>>>>>>>>>> eno.there...@gmail.com
>>>>>>>>>>> wrote:
>>>>>>>>>>>>>>> Thanks Damian, answers inline:
>>>>>>>>>>>>>>>> On 16 Jan 2017, at 17:17, Damian Guy <damian....@gmail.com>
>>>>>>>>>>>>>>>>> wrote:
>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>> Hi Eno,
>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>> Thanks for the KIP. Some comments:
>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>> 1. I'd probably rename materialized to materialize.
>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>> Ok.
>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>> 2. I don't think the addition of the new Log compaction
>>>>> mechanism
>>>>>>>>>>>>>>>> is
>>>>>>>>>>> necessary for this KIP, i.e, the KIP is useful without it. Maybe
>>>>>>>>>>>>>>>> that
>>>>>>>>>>>>> should be a different KIP?
>>>>>>>>>>>>>>>> Agreed, already removed. Will do a separate KIP for that.
>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>> 3. What will happen when you call materialize on KTable
>>>>>>>>>>>>>>>> that is
>>>>>>>>>>>>>>>> already
>>>>>>>>>>>>>>> materialized? Will it create another StateStore (providing the
>>>>>>>>>>>>>>>> name
>>>>>>>>>>> is
>>>>>>>>>>>>> different), throw an Exception?
>>>>>>>>>>>>>>>> Currently an exception is thrown, but see below.
>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>> 4. Have you considered overloading the existing KTable
>>>>> operations
>>>>>>>>>>>>>>>> to
>>>>>>>>>>> add
>>>>>>>>>>>>>>>>> a state store name? So if a state store name is provided,
>>>>>>>>>>>>>>>>> then
>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>> materialize
>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>> a state store? This would be my preferred approach as i
>>>>>>>>>>>>>>>>> don't
>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>> think
>>>>>>>>>>> materialize is always a valid operation.
>>>>>>>>>>>>>>>> Ok I can see your point. This will increase the KIP size
>>>>>>>>>>>>>>>> since
>>>>>>>>>>>>>>>> I'll
>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>> need
>>>>>>>>>>>>> to enumerate all overloaded methods, but it's not a problem.
>>>>>>>>>>>>>>>> 5. The materialize method will need ta value Serde as some
>>>>>>>>>>>>>>>> operations,
>>>>>>>>>>>>> i.e., mapValues, join etc can change the value types
>>>>>>>>>>>>>>>>> 6. https://issues.apache.org/jira/browse/KAFKA-4609 - might
>>>>>>>>>>>>>>>>> mean
>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>> that
>>>>>>>>>>>>> we
>>>>>>>>>>>>>>>>> always need to materialize the StateStore for KTable-KTable
>>>>>>>>>>>>>>>>> joins.
>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>> If
>>>>>>>>>>>>> that
>>>>>>>>>>>>>>>>> is the case, then the KTable Join operators will also need
>>>>> Serde
>>>>>>>>>>>>>>>>> information.
>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>> I'll update the KIP with the serdes.
>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>> Thanks
>>>>>>>>>>>>>>>> Eno
>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>> Cheers,
>>>>>>>>>>>>>>>>> Damian
>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>> On Mon, 16 Jan 2017 at 16:44 Eno Thereska <
>>>>>>>>>>>>>>>>> eno.there...@gmail.com>
>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>> wrote:
>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>> Hello,
>>>>>>>>>>>>>>>>>> We created "KIP-114: KTable materialization and improved
>>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>> semantics"
>>>>>>>>>>> to
>>>>>>>>>>>>> solidify the KTable semantics in Kafka Streams:
>>>>>>>>>>>>>>>>>> https://cwiki.apache.org/confluence/display/KAFKA/KIP-
>>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>> 114%3A+KTable+materialization+and+improved+semantics
>>>>>>>>>>>>>>>>> <
>>>>>>>>>>>>>>>>>> https://cwiki.apache.org/confluence/display/KAFKA/KIP-
>>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>> 114:+KTable+materialization+and+improved+semantics
>>>>>>>>>>>>>>>>> Your feedback is appreciated.
>>>>>>>>>>>>>>>>>> Thanks
>>>>>>>>>>>>>>>>>> Eno
>>>>>>>>>>>>>>>>>>
>
