Re: [DISCUSS] KIP-955: Add stream-table join on foreign key

[Matthias J. Sax]

Thanks for the details. And sorry for being a little bit picky. My goal 
is to really understand the use-case and the need for this KIP. It's a 
massive change and I just want to ensure we don't add (complex) things 
unnecessarily.

So you have a streams of "orderEvents" with key=orderId. You cannot 
represent them as a KTable, because `orderId` is not a PK, but just an 
identify that a message belongs to a certain order. This part I understand.

You also have a KTable "orderItems", with orderId as a value-field.



 Relationship between parent and child messages is 1:1

If I understand correctly, you want to join on orderId. If the join is 
1:1, it means that there is only a single table-record for each unique 
orderId. Thus, orderId could be the PK of the table. If that's correct, 
you could use orderId as the key of "orderItems" and do a regular 
stream-table join. -- Or do I miss something?



and to send it only once to the target system as one ‘complete order > message 
for each new ‘order event’ message.

This sound like an aggregation to me, not a join? It seems that an order 
consists of multiple "orderEvent" messages, and you would want to 
aggregate them based on orderId (plus add some more order detail 
information from the table)? Only after all "orderEvent" messages are 
received and the order is "completed" you want to send a result 
downstream (that is fine and would be a filter in the DSL to drop 
incomplete results).



Maybe there could be a flag to stream-table foreign key join that would
indicate if we want this join to aggregate children or not?

Wouldn't this mud the waters between a join and an aggregation and imply 
that it's a "weird" hybrid operator, and we would also need to change 
the `join()` method to accept an additional `Aggregator` function?



From what I understand so far (correct me if I am wrong), you could do 
what you want to do as follows:

// accumulate all orderEvents per `orderId`
// cf last step to avoid unbounded growth of the result KTable
KStream orderEventStream = builder.stream("orderEventTopic")
// you might want to disable caching in the next step
KTable orderEvents = orderEventStream.groupByKey().aggregate(...);

// rekey you orderItems to use `orderId` as PK for the table
KStream orderItemStream = builder.stream("orderItemTopic");
KTable orderItems = orderItemStream.map(/*put orderId as key */).toTable();

// do the join
KStream enrichedOrders = orderEvents.toStream().join(orderItems);

// drop incomplete orders
KStreame completedOrderds = enrichedOrders.filter(o -> o.isCompleted());

// publish result
completedOrderds.to("resultTopic");

// additional cleanup
completedOrderds.map(/*craft a special "delete order 
message"*/).to("orderEventTopic");


The last step is required to have a "cleanup" message to purge state 
from the `orderEvents` KTable that was computed via the aggregation. If 
such a cleanup message is processed by the `aggregate` step, you would 
return `null` as aggregation result to drop the record for the 
corresponding orderId that was completed, to avoid unbounded growth of 
the KTable. (There are other ways to do the same cleanup; it's just one 
example how it could be done.)


If I got it wrong, can you explain what part I messed up?



-Matthias




On 8/7/23 10:15 AM, Igor Fomenko wrote:
Hi Matthias,

Hi Matthias,



Thanks for your comments.



I would like to clarify the use case a little more to show why existing
table-table foreign key join will not work for the use case I am trying to
address.

Let’s consider the very simple use case with the parent messages in one
Kafka topic (‘order event’ messages that also contain some key order info)
and the child messages in another topic (‘order items’ messages with an
additional info for the order). Relationship between parent and child
messages is 1:1. Also ‘order items’ message has OrderID as one of its
fields (foreign key).



The requirement is to combine info of the parent ‘order event’ message with
child ‘order items’ message using foreign key and to send it only once to
the target system as one ‘complete order’ message for each new ‘order
event’ message.

Please note that the new messages which are related to order items (create,
update, delete) should not trigger the resulting ‘complete order’ message).



 From the above requirements we can state the following:

1.     Order events are unique and never updated or deleted; they can only
be replayed if we need to recover the event stream. For our order example I
would use OrderID as an event key but if we use the KTable to represent
events then events with the same OrderID will overwrite each other. This
may or may not cause some issues but using the stream to model seems to be
a more correct approach from at least performance point of view.

2.     We do not want updates from the “order items” table on the right
side of the join to generate an output since only events should be the
trigger for output messages in our scenario. This is aligned with the
stream-table join behavior rather than table-table join when updates are
coming from both sides

3.     Stream-table join will give us resulting stream which is more align
with our output requirements than the table that would be result of
table-table join



Requirement #2 above is the most important one and it can not be achieved
with existing table-table join on foreign key.



I also stated that the foreign key table in table-table join is on the
‘wrong’ side for our order management use case. By this I just meant that
in stream-table join I am proposing the foreign key table needs to be on
the right side and on the existing table-table join it is on the left. This
is however is irrelevant since we can not use table-table join anyway for
the reason #2 above.



You made a good point about aggregation of child messages for a more
complex use case of 1:n relation between parent and children. Initially I
was thinking that aggregation will be just a separate operation that could
be added after we performed a foreign key join. Now I realize that it will
not be possible to do it after.

Maybe there could be a flag to stream-table foreign key join that would
indicate if we want this join to aggregate children or not?



What do you think?

Regards,



Igor


On Fri, Aug 4, 2023 at 10:01 PM Matthias J. Sax <mj...@apache.org> wrote:

Thanks a lot for providing more background. It's getting much clear to
me now.

Couple of follow up questions:


It is not possible to use table-table join in this case because
triggering
events are supplied separately from the actual data entity that needs to
be
"assembled" and these events could only be presented as KStream due to
their nature.

Not sure if I understand this part? Why can't those events not
represented as a KTable. You say "could only be presented as KStream due
to their nature" -- what do you mean by this?

In the end, my understanding is the following (using the example for the
KIP):

For the shipments <-> orders and order-details <-> orders join, shipment
and order-details are the fact table, what is "reverse" to what you
want? Using existing FK join, it would mean you get two enriched tables,
that you cannot join to each other any further (because we don't support
n:m join): in the end, shipmentId+orderDetailId would be the PK of such
a n:m join?

If that's correct, (just for the purpose to make sure I understand
correctly), if we would add an n:m join, you could join shipment <->
order-details first, and use a FK join to enrich the result with orders.
-- In addition, you could also do a FK join to event if you represent
events as a table (this relates to my question from above, why events
cannot be represented as a KTable).


A the KIP itself, I am still wondering about details: if we get an event
in, and we do a lookup into the "FK table" and find multiple matches,
would we emit multiple results? This would kinda defeat the purpose to
re-assemble everything into a single entity? (And it might require an
additional aggregation downstream to put the entity together.) -- Or
would we join the singe event, with all found table rows, and emit a
single "enriched" event?


Thus, I am actually wondering, if you would not pre-process both
shipment and order-details table, via `groupBy(orderId)` and assemble a
list (or similar) of alls shipments (or order-details) per order? If you
do this pre-processing, you can do a PK-PK (1:1) join with the orders
table, and also do a stream-table join to enrich your events will the
full order information?



-Matthias

On 7/26/23 7:13 AM, Igor Fomenko wrote:
Hello Matthias,

Thank you for this response. It provides the context for a good
discussion
related to the need for this new interface.

The use case I have in mind is not really a stream enrichment which
usually
implies that the event has a primary key to some external info and that
external info could be just looked up in some other data source.

The pattern this KIP proposes is more akin to the data entity assembly
pattern from the persistence layer so it is not purely integration
pattern
but rather a pattern that enables an event stream from persistence layer
of
a data source application. The main driver here is the ability to stream
a
data entity of any complexity (complexity in terms of the relational
model)
from an application database to some data consumers. The technical
precondition here is of course that data is already extracted from the
relational database with something like Change Data Capture (CDC) and
placed to Kafka topics. Also due to CDC limitations, each database table
that is related to the entity relational data model is extracted to the
separate Kafka topic.

So to answer you first question the entity that needs to be "assembled"
from Kafka topics in the very common use case has 1:n relations where 1
corresponds to the triggering event enriched with the data from the main
(or parent) table of the data entity (for example completion of the
purchase order event + order data from the order table) and n corresponds
to the many children that needs to be joined with the order table to have
the full data entity (for example multiple line items of the purchase
order
needs to be added from the line items child table).

It is not possible to use table-table join in this case because
triggering
events are supplied separately from the actual data entity that needs to
be
"assembled" and these events could only be presented as KStream due to
their nature. Also currently the FK table in table-table join is on the
"wrong" side of the join.
It is possible to use existing stream-table join only to get data from
the
parent entity table (order table) because the event to order is 1:1.
After
that it is required to add "children" tables of the order to complete
entity assembly, these childered are related as 1:n with foreign key
fields
in each child table (which is order ID).

This use case is typically implemented with some sort of ESB (like
Mulesoft) where ESB receives an event and then uses JDBC adapter to issue
SQL query with left join on foreign key for child tables. ESB then loops
through the returned record set to assemble the full data entity. However
in many cases for various architecture reasons there is a desire to
remove
JDBC queries from the data source and replace it with CDC streaming data
to
Kafka. So in that case assembling data entities from Kafka topics instead
of JDBC would be beneficial.

Please let me know what you think.

Regards,

Igor

On Tue, Jul 25, 2023 at 5:53 PM Matthias J. Sax <mj...@apache.org>
wrote:

Igor,

thanks for the KIP. Interesting proposal. I am wondering a little bit
about the use-case and semantics, and if it's really required to add
what you propose? Please correct me if I am wrong.

In the end, a stream-table join is a "stream enrichment" (via a table
lookup). Thus, it's inherently a 1:1 join (in contrast to a FK
table-table join which is a n:1 join).

If this assumption is correct, and you have data for which the table
side join attribute is in the value, you could actually repartition the
table data using the join attribute as the PK of the table.

If my assumption is incorrect, and you say you want to have a 1:n join
(note that I intentionally reversed from n:1 to 1:n), I would rather
object, because it seems to violate the idea to "enrich" a stream, what
means that each input record produced an output record, not multiple?

Also note: for a FK table-table join, we use the forgeinKeyExtractor to
get the join attribute from the left input table (which corresponds to
the KStream in your KIP; ie, it's a n:1 join), while you propose to use
the foreignKeyExtractor to be applied to the KTable (which is the right
input, and thus it would be a 1:n join).

Maybe you can clarify the use case a little bit. For the current KIP
description I only see the 1:1 join case, what would mean we might not
need such a feature?


-Matthias


On 7/24/23 11:36 AM, Igor Fomenko wrote:
Hello developers of the Kafka Streams,

I would like to start discussion on KIP-955: Add stream-table join on
foreign key
<

https://cwiki.apache.org/confluence/display/KAFKA/KIP-955%3A+Add+stream-table+join+on+foreign+key

This KIP proposes the new API to join KStrem with KTable based on
foreign
key relation.
Ths KIP was inspired by one of my former projects to integrate RDBMS
databases with data consumers using Change Data Capture and Kafka.
If we had the capability in Kafka Stream to join KStream with KTable on
foreign key this would simplify our implementation significantly.

Looking forward to your feedback and discussion.

Regards,

Igor