Using Kafka Streams, it seems reasonable to implement this using low-level Processor API with a custom state store.
Thus, you use the `StateStore` interface to implement you state store -- this allows you to spill to disk if you need to to handle state larger than main memory. If you want to browse some state store examples, you can check out RocksDBStore class that implement Kafka Streams' default `StateStore`. Within your custom `Processor` you can access the state accordingly to maintain the window etc. It's a quite special use case and thus, there is not much out-of-the-box support. You can check out some basic examples here: https://github.com/confluentinc/kafka-streams-examples One example implements a custom state store (but only in-memory): https://github.com/confluentinc/kafka-streams-examples/blob/3.3.0-post/src/test/scala/io/confluent/examples/streams/ProbabilisticCountingScalaIntegrationTest.scala Hope this helps. -Matthias On 11/21/17 5:53 PM, Ray Ruvinskiy wrote: > Thanks for your reply! I am quite inexperienced when it comes to Kafka and > Kafka Streams and so would appreciate a little more guidance. How would one > keep messages within a sliding window sorted by timestamp? Would the sort > operation be done all in memory? I would be dealing potentially with hundreds > of thousands of messages per partition within every 5 minute interval and so > was looking for solutions that were not necessary limited by the amount of > RAM. > > Ray > > On 2017-11-21, 5:57 PM, "Matthias J. Sax" <matth...@confluent.io> wrote: > > This is possible, but I think you don't need the time-based index for it > :) > > You will just buffer up all messages for a 5 minute sliding-window and > maintain all message sorted by timestamp in this window. Each time the > window "moves" you write the oldest records that "drop out" of the > window to the topic. If you get a record with an older timestamp that > allowed, you don't insert in into the window but drop it. > > The timestamp index is useful if you want to seek to a specific offset > base on timestamp. But I don't think you need this for your use case. > > > > -Matthias > > On 11/21/17 1:39 PM, Ray Ruvinskiy wrote: > > I’ve been reading > https://cwiki.apache.org/confluence/display/KAFKA/KIP-33+-+Add+a+time+based+log+index > and trying to determine whether I can use the time-based index as an > efficient way to sort a stream of messages into timestamp (CreateTime) order. > > > > I am dealing with a number of sources emitting messages that are then > processed in a distributed fashion and written to a Kafka topic. During this > processing, the original order of the messages is not strictly maintained. > Each message has an embedded timestamp. I’d like to be able to sort these > messages back into timestamp order, allowing for a certain lateness interval, > before processing them further. For example, supposing the lateness interval > is 5 minutes, at time T I’d like to consume from the topic all messages with > timestamp up to (T - 5 minutes), in timestamp order. The assumption is that a > message should be no more than 5 minutes late; if it is more than 5 minutes > late, it can be discarded. Is this something that can be done with the > time-based index? > > > > Thanks, > > > > Ray > > > > >
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