Hi Guozhang,
thanks for the update.
On 15.12.2017 22:54, Guozhang Wang wrote:
Jan,
Thanks for the updated KIP, and the raised questions. Here are my thoughts
around the "back and forth mapper" approach on your wiki:
1) regarding the key-value types of KTableValueGetter, we do not
necessarily enforce its template K, V to be the same as its calling
Processor<K, V>, although today in all implementations we happen to do so.
So I think it is ok to extend this internal implementation to allow getter
and forwarding with different types.
I am not entirely sure how you mean this. The dependencies is only there
because
the downstream processor is going to invoke the ValueGetter with the
downstream key.
if this key is of different type we would run into a Runtime Exception.
We had to introduce
a fourth generic type. The "new key type" wich would also be the access
type of the
Value Getter. I like introducing this a lot but I don't think it works
w/o 4th generic type
and then we have
KTableProcessorSupplier<KEY_IN,K_OUT,VALUE_IN,VALUE_OUT> extends
ProcessorSupplier<KEY_IN,VALUE_IN>{
view ValueGetterSupplier<KEY_OUT,VALUE_OUT>()
processor ProcessorSupplier<KEY_IN,VALUE_IN>()
}
This would conveniently allow for some flatmap() on Ktable wich is a
neat thing IMO
2) regarding the KTableProcessorSupplier enforcing to return the same
key/value types of its "KTableValueGetterSupplier<K, T> view();" the key
observation to note is that "ProcessorSupplier<?, ?>" inside "KTableImpl<K,
V>" does not enforce to have the same key-value types of the KTable, i.e.
we can use a "ProcessorSupplier<K1, V1>" inside the impl of a `KTable<K,
V>`. I think that should help getting around the issue.
I think it has nothing really todo with places where the
ProccessorSupllier is referenced
but this is quircked inside KTableProccessorSuplier. regardless of the
scope of usage I cannot
come up with a KTableProccessorSupplier that changes keys while
maintaining all invariants (beeing querieable). One
can jump across with a ProcessorSupplier where its obvious that you
can't have a ValueGetterSupplier, but this is
rather a hack.
Why is it only inside KTableProcessorSupplier? We process key K, and
then we forward K1, but our ValueGetterSupplier
can only have K as Generic and therefore is will crash if we invoke the
ValueGetter.
3) About the alternative KTable::mapKeys(), I think the major issue is that
this mapKeys() cannot enforce users to always call it to get the
"non-combined" Key, and hence users may still need to consider the serde of
"CombinedKey" if they do not call mapKeys and then directly pipe it to the
output, while this approach enforce them to always "map" it before trying
to write it to anywhere externally exposable.
It cannot force them, but folks who want this can do it. People that are
fine with any Combinedkey type could just let it be forwarded as such.
A new aspect that I had not thought of as yet is that of course in an
to() call they could pass in a CombinedKeySerde on their own. I think
this flexibility is a plus rather than a minus. What do you think?
4) A very minor comment on the wiki page itself, about the "back and forth
mapper" section: the parameter names "customCombinedKey" and "combinedKey"
seems a bit hard to understand to normal users; should we consider renaming
them to something more understandable? For example, "outputKeyCombiner" and
"outputKeySpliter"?
yes your naming is superior.
Guozhang
On Thu, Dec 7, 2017 at 3:58 AM, Jan Filipiak <jan.filip...@trivago.com>
wrote:
On 05.12.2017 00:42, Matthias J. Sax wrote:
Jan,
The KTableValueGetter thing is a valid point. I think we would need a
backwards mapper (or merge both into one and sacrifices lambdas?).
Another alternative would be, to drop the optimization and materialize
the KTable.operator() result... (not a great solution either). I am
personally fine with a backwards mapper (we should call it KeySplitter).
2. I am not sure if we can pull it of w/o said forth generic type in
KTable (that I am in favour of btw)
Not sure if I can follow here. I am personally not worried about the
number of generic types -- it's just to have a clear definition what
each passed parameter does.
I need to double check this again. Its good that we are open to introduce
a new one
I think it will not work currently as a KTableProcessorSupplier when asked
for a
ValueGetterSupplier it can only return a ValueGetter Supplier that has the
same Keytype
as the key it receives in the process method. Even though it would forward
a different
key type and therefore KTables key Type can't change. I am thinking how to
pull this off but I see little chance
But I am always in big favour of introducing the forth type OutputKey, it
would become
straight forward then. I hope you can follow.
+ It won't solves peoples problem having CombinedKey on the wire and not
being able to inspect the topic with say there default tools.
I see your point, but do we not have this issue always? To make range
scan work, we need to serialize the prefix (K1) and suffix (K)
independently from each other. IMHO, it would be too much of a burden to
the user, to provide a single serialized for K0 that guaranteed the
ordering we need. Still, advanced user can provide custom Serde for the
changelog topic via `Joined` -- and they can serialize as they wish (ie,
get CombinedKey<K1,K>, convert internally to K0 and serialized -- but
this is an opt-in).
I think, this actually aligns with what you are saying. However, I think
the #prefix() call is not the best idea. We can just use Serde<K1> for
this (if users overwrite CombinedKey-Serde, it must overwrite Serde<K1>
too and can return the proper perfix (or do I miss something?).
I can't follow. For the stock implementation user would get
they wouldn't need prefix. Users had not to define it we can implement
that ourself by just getting K1 Serde.
But to Override with a custom Serde that prefix method is needed as an
indicator if only a prefix or the full thing is to be rendered.
- Id rather introduce KTable::mapKeys() or something (4th generic in
Ktable?) than overloading. It is better SOCs wise.
What overload are you talking about? From my understanding, we want to
add one single method (or maybe one for inner,left,outter each), but I
don't see any overloads atm?
The back and forth mapper would get an overload
Also, `KTable.mapKeys()` would have the issue, that one could create an
invalid KTable with key collisions. I would rather shield users to shoot
themselves in the foot.
This mapkeys would not be used to remove the actual values but to get rid
of the CombinedKey-type.
Users can shoot themself with the proposed back and forth mapper you
suggested.
Side remark:
In the KIP, in the Step-by-Step table (that I really like a lot!) I
think in line 5 (input A, with key A2 arrives, the columns "state B
materialized" and "state B other task" should not be empty but the same
as in line 4?
Will double check tonight. totally plausible i messed this up!
best Jan
-Matthias
On 11/25/17 8:56 PM, Jan Filipiak wrote:
Hi Matthias,
2 things that pop into my mind sunday morning. Can we provide an
KTableValueGetter when key in the store is different from the key
forwarded?
1. we would need a backwards mapper
2. I am not sure if we can pull it of w/o said forth generic type in
KTable (that I am in favour of btw)
+ It won't solves peoples problem having CombinedKey on the wire and not
beeing able to inspect the topic with say there default tools.
- Id rather introduce KTable::mapKeys() or something (4th generic in
Ktable?) than overloading. It is better SOCs wise.
I am thinking more into an overload where we replace the Comined key
Serde. So people can use a default CombinedKey Serde
but could provide an own implementation that would internally use K0 vor
serialisation and deserialisation. One could implement
a ##prefix() into this call to make explicit that we only want the
prefix rendered. This would take CombinedKey logic out of publicly
visible
data. A Stock CombinedKey Serde that would be used by default could also
handle the JSON users correctly.
Users would still get CombinedKey back. The downside of getting these
nested deeply is probably mitgated by users doing a group by
in the very next step to get rid of A's key again.
That is what I was able to come up with so far.
Let me know. what you think
On 22.11.2017 00:14, Matthias J. Sax wrote:
Jan,
Thanks for explaining the Serde issue! This makes a lot of sense.
I discussed with Guozhang about this issue and came up with the
following idea that bridges both APIs:
We still introduce CombinedKey as a public interface and exploit it to
manage the key in the store and the changelog topic. For this case we
can construct a suitable Serde internally based on the Serdes of both
keys that are combined.
However, the type of the result table is user defined and can be
anything. To bridge between the CombinedKey and the user defined result
type, users need to hand in a `ValueMapper<CombinedKey, KO>` that
convert the CombinedKey into the desired result type.
Thus, the method signature would be something like
<KO, VO, K1, V1> KTable<KO,VO> oneToManyJoin(> KTable<K1, V1> other,
ValueMapper<V1, K> keyExtractor,> ValueJoiner<V, V1, VO>
joiner,
ValueMapper<CombinedKey<K,K1>, KO> resultKeyMapper);
The interface parameters are still easy to understand and don't leak
implementation details IMHO.
WDYT about this idea?
-Matthias
On 11/19/17 11:28 AM, Guozhang Wang wrote:
Hello Jan,
I think I get your point about the cumbersome that CombinedKey would
introduce for serialization and tooling based on serdes. What I'm still
wondering is the underlying of joinPrefixFakers mapper: from your
latest
comment it seems this mapper will be a one-time mapper: we use this
to map
the original resulted KTable<combined<K1, K2>, V0> to KTable<K0, V0>
and
then that mapper can be thrown away and be forgotten. Is that true? My
original thought is that you propose to carry this mapper all the way
along
the rest of the topology to "abstract" the underlying combined keys.
If it is the other way (i.e. the former approach), then the diagram of
these two approaches would be different: for the less intrusive
approach we
would add one more step in this diagram to always do a mapping after
the
"task perform join" block.
Also another minor comment on the internal topic: I think many
readers may
not get the schema of this topic, so it is better to indicate that what
would be the key of this internal topic used for compaction, and what
would
be used as the partition-key.
Guozhang
On Sat, Nov 18, 2017 at 2:30 PM, Jan Filipiak<jan.filip...@trivago.com
wrote:
-> it think the relationships between the different used types,
K0,K1,KO
should be explains explicitly (all information is there implicitly,
but
one need to think hard to figure it out)
I'm probably blind for this. can you help me here? how would you
formulate
this?
Thanks,
Jan
On 16.11.2017 23:18, Matthias J. Sax wrote:
Hi,
I am just catching up on this discussion and did re-read the KIP and
discussion thread.
In contrast to you, I prefer the second approach with CombinedKey as
return type for the following reasons:
1) the oneToManyJoin() method had less parameter
2) those parameters are easy to understand
3) we hide implementation details (joinPrefixFaker,
leftKeyExtractor,
and the return type KO leaks internal implementation details from my
point of view)
4) user can get their own KO type by extending CombinedKey
interface
(this would also address the nesting issue Trevor pointed out)
That's unclear to me is, why you care about JSON serdes? What is the
problem with regard to prefix? It seems I am missing something here.
I also don't understand the argument about "the user can stick with
his
default serde or his standard way of serializing"? If we have
`CombinedKey` as output, the use just provide the serdes for both
input
combined-key types individually, and we can reuse both internally
to do
the rest. This seems to be a way simpler API. With the KO output type
approach, users need to write an entirely new serde for KO in
contrast.
Finally, @Jan, there are still some open comments you did not address
and the KIP wiki page needs some updates. Would be great if you
could do
this.
Can you also explicitly describe the data layout of the store that is
used to do the range scans?
Additionally:
-> some arrows in the algorithm diagram are missing
-> was are those XXX in the diagram
-> can you finish the "Step by Step" example
-> it think the relationships between the different used types,
K0,K1,KO
should be explains explicitly (all information is there implicitly,
but
one need to think hard to figure it out)
Last but not least:
But noone is really interested.
Don't understand this statement...
-Matthias
On 11/16/17 9:05 AM, Jan Filipiak wrote:
We are running this perfectly fine. for us the smaller table changes
rather infrequent say. only a few times per day. The performance
of the
flush is way lower than the computing power you need to bring to the
table to account for all the records beeing emmited after the one
single
update.
On 16.11.2017 18:02, Trevor Huey wrote:
Ah, I think I see the problem now. Thanks for the explanation.
That is
tricky. As you said, it seems the easiest solution would just be to
flush the cache. I wonder how big of a performance hit that'd be...
On Thu, Nov 16, 2017 at 9:07 AM Jan Filipiak
<jan.filip...@trivago.com
<mailto:jan.filip...@trivago.com>> wrote:
Hi Trevor,
I am leaning towards the less intrusive approach myself.
Infact
that is how we implemented our Internal API for this and
how we
run it in production.
getting more voices towards this solution makes me really
happy.
The reason its a problem for Prefix and not for Range is the
following. Imagine the intrusive approach. They key of the
RockDB
would be CombinedKey<A,B> and the prefix scan would take an
A, and
the range scan would take an CombinedKey<A,B> still. As you
can
see with the intrusive approach the keys are actually
different
types for different queries. With the less intrusive
apporach we
use the same type and rely on Serde Invariances. For us
this works
nice (protobuf) might bite some JSON users.
Hope it makes it clear
Best Jan
On 16.11.2017 16:39, Trevor Huey wrote:
1. Going over KIP-213, I am leaning toward the "less
intrusive"
approach. In my use case, I am planning on performing a
sequence
of several oneToMany joins, From my understanding, the more
intrusive approach would result in several nested levels of
CombinedKey's. For example, consider Tables A, B, C, D with
corresponding keys KA, KB, KC. Joining A and B would
produce
CombinedKey<KA, KB>. Then joining that result on C would
produce
CombinedKey<KC, CombinedKey<KA, KB>>. My "keyOtherSerde"
in this
case would need to be capable of deserializing
CombinedKey<KA,
KB>. This would just get worse the more tables I join. I
realize
that it's easier to shoot yourself in the foot with the
less
intrusive approach, but as you said, " the user can stick
with
his default serde or his standard way of serializing". In
the
simplest case where the keys are just strings, they can do
simple
string concatenation and Serdes.String(). It also allows
the user
to create and use their own version of CombinedKey if they
feel
so inclined.
2. Why is there a problem for prefix, but not for range?
https://github.com/apache/kafk
a/pull/3720/files#diff-8f863b7
4c3c5a0b989e89d00c149aef1L162
On Thu, Nov 16, 2017 at 2:57 AM Jan Filipiak
<jan.filip...@trivago.com <mailto:Jan.Filipiak@trivago.c
om>>
wrote:
Hi Trevor,
thank you very much for your interested. Too keep
discussion
mailing list focused and not Jira or Confluence I
decided to
reply here.
1. its tricky activity is indeed very low. In the
KIP-213
there are 2 proposals about the return type of the
join. I
would like to settle on one.
Unfortunatly its controversal and I don't want to have
the
discussion after I settled on one way and implemented
it. But
noone is really interested.
So discussing with YOU, what your preferred return
type would
look would be very helpfull already.
2.
The most difficult part is implementing
this
https://github.com/apache/kaf
ka/pull/3720/files#diff-ac41b4d
fb9fc6bb707d966477317783cR68
here
https://github.com/apache/kaf
ka/pull/3720/files#diff-8f863b7
4c3c5a0b989e89d00c149aef1R244
and here
https://github.com/apache/kaf
ka/pull/3720/files#diff-b1a1281
dce5219fd0cb5afad380d9438R207
One can get an easy shot by just flushing the
underlying
rocks and using Rocks for range scan.
But as you can see the implementation depends on the
API. For
wich way the API discussion goes
I would implement this differently.
3.
I only have so and so much time to work on this. I
filed the
KIP because I want to pull it through and I am pretty
confident that I can do it.
But I am still waiting for the full discussion to
happen on
this. To get the discussion forward it seems to be
that I
need to fill out the table in
the KIP entirly (the one describing the events, change
modifications and output). Feel free to continue the
discussion w/o the table. I want
to finish the table during next week.
Best Jan thank you for your interest!
_____ Jira Quote ______
Jan Filipiak
<https://issues.apache.org/ji
ra/secure/ViewProfile.jspa?name
=jfilipiak>
Please bear with me while I try to get caught up. I'm
not yet
familiar with the Kafka code base. I have a few
questions to
try to figure out how I can get involved:
1. It seems like we need to get buy-in on your
KIP-213? It
doesn't seem like there's been much activity on it
besides
yourself in a while. What's your current plan of
attack for
getting that approved?
2. I know you said that the most difficult part is yet
to be
done. Is there some code you can point me toward so I
can
start digging in and better understand why this is so
difficult?
3. This issue has been open since May '16. How far out
do you
think we are from getting this implemented?
