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: d...@kafka.apache.org
Reply-To: d...@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
