On 17.11.2017 06:59, Guozhang Wang wrote:
Thanks for the explanation Jan. On top of my head I'm leaning towards the
"more intrusive" approach to resolve the race condition issue we discussed
above. Matthias has some arguments for this approach already, so I would
not re-iterate them here. To me I find the "ValueMapper<K, KO>
joinPrefixFaker" is actually leaking the same amount of internal
implementation details information as the more intrusive approach, but in a
less clear way. So I'd rather just clarify to users than trying to abstract
in an awkward way.
As again. The benefits of __not__ introducing a new "Wrapper" type are huge!
We spend lot of effort to get rid of Changes<> in our Topics. We also
will not
want CombinedKeys.
I make one suggestion! Let's keep thinking how to make this more precise
w/o introducing new Kafka Streams only types?
As you can see currently the vote is 2 / 2. People that use kafka stream
like the less intrusive approach people that develop like the more
intrusive one.
The most pretty thing might not be the thing that gives the bang for the bug
out there.
Best Jan
Also I'm not clear what do you mean by "CombinedKey would require an
additional mapping to what the less intrusive method has". If you meant
that users are enforced to provide a new serde for this combo key, could
that be avoided with the library automatically generate a serde for it
until the user changed this key later in the topology (e.g. via a map()
function) in which they can "flatten" this combo key into a flat key.
*@Trevor: *for your case for concatenating multiple joins, I think a better
way is to call `oneToManyJoin().map().oneToManyJoin().map()...` than
specifying a sequence of joinPrefixFakers as they will also be chained up
together (remember we have to keep this object along the rest of the
topology) which will make serde even harder?
Hi,
that was the map I was talking about. Last time I checked KTable only
had 3 Generic Types.
For this I think it would require 4 Types, KeyIn,KeyOut,ValueIn,ValueOut
I am very much in favour to
add this since basically ever, maybe this opens up some discussion, but
without this Mapping keys of
KTable is not possible. I once again recommend peeking over to
Mapreduce/Tez guys wich have the
concept of these 4 Generics since basically ever.
Similar to Matthias's question, the "XXX" markers are a bit confusing to me.
Sorry!!!
Guozhang
On Thu, Nov 16, 2017 at 2:18 PM, Matthias J. Sax <matth...@confluent.io>
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/kafka/pull/3720/files#diff-
8f863b74c3c5a0b989e89d00c149aef1L162
On Thu, Nov 16, 2017 at 2:57 AM Jan Filipiak
<jan.filip...@trivago.com <mailto:jan.filip...@trivago.com>>
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/kafka/pull/3720/files#diff-
ac41b4dfb9fc6bb707d966477317783cR68
here
https://github.com/apache/kafka/pull/3720/files#diff-
8f863b74c3c5a0b989e89d00c149aef1R244
and here
https://github.com/apache/kafka/pull/3720/files#diff-
b1a1281dce5219fd0cb5afad380d9438R207
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/jira/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?
