Thanks for the link. I heave come across that at some point in the past, but I dont think it quite addresses the issue I'm looking at.
I think the custom partitioner strategy doesn't work either though. The number of groups we have changes over time, so we can't have a fixed strategy. We can use hashing and just create a large number of partitions so that "most of the time" there is only 1 group per partition, however, as far as I can tell, this is exactly the same as having 1 topic per group (but with more complexity). Am I wrong? I am under the impression that having 1000 topics with 1 partition incurs the same load/costs on the kafka brokers that 1 topic with 1000 partitions has. Shaun ________________________________________ From: Ben Stopford <b...@confluent.io> Sent: September 30, 2015 9:06 AM To: users@kafka.apache.org Subject: Re: number of topics given many consumers and groups within the data Hi Shaun You might consider using a custom partition assignment strategy to push your different “groups" to different partitions. This would allow you walk the middle ground between "all consumers consume everything” and “one topic per consumer” as you vary the number of partitions in the topic, albeit at the cost of a little extra complexity. Also, not sure if you’ve seen it but there is quite a good section in the FAQ here <https://cwiki.apache.org/confluence/display/KAFKA/FAQ#FAQ-HowmanytopicscanIhave?> on topic and partition sizing. B > On 29 Sep 2015, at 18:48, Shaun Senecal <shaun.sene...@lithium.com> wrote: > > Hi > > > I heave read Jay Kreps post regarding the number of topics that can be > handled by a broker > (https://www.quora.com/How-many-topics-can-be-created-in-Apache-Kafka), and > it has left me with more questions that I dont see answered anywhere else. > > > We have a data stream which will be consumed by many consumers (~400). We > also have many "groups" within our data. A group in the data corresponds 1:1 > with what the consumers would consume, so consumer A only ever see group A > messages, consumer B only consumes group B messages, etc. > > > The downstream consumers will be consuming via a websocket API, so the API > server will be the thing consuming from kafka. > > > If I use a single topic with, say, 20 partitions, the consumers in the API > server would need to re-read the same messages over and over for each > consumer, which seems like a waste of network and a potential bottleneck. > > > Alternatively, I could use a single topic with 20 partitions and have a > single consumer in the API put the messages into cassandra/redis (as > suggested by Jay), and serve out the downstream consumer streams that way. > However, that requires using a secondary sorted storage, which seems like a > waste (and added complexity) given that Kafka already has the data exactly as > I need it. Especially if cassandra/redis are required to maintain a long TTL > on the stream. > > > Finally, I could use 1 topic per group, each with a single partition. This > would result in 400 topics on the broker, but would allow the API server to > simply serve the stream for each consumer directly from kafka and wont > require additional machinery to serve out the requests. > > > The 400 topic solution makes the most sense to me (doesnt require extra > services, doesnt waste resources), but seem to conflict with best practices, > so I wanted to ask the community for input. Has anyone done this before? > What makes the most sense here? > > > > > Thanks > > > Shaun
