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https://issues.apache.org/jira/browse/KAFKA-4212?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16879569#comment-16879569
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Matthias J. Sax commented on KAFKA-4212:
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I agree about the application patterns and that it would be useful. :)
{quote}I very much could be wrong, but I think rocksDB and a topic setup with
`cleanup.policy=delete` & `delete.retention.ms` both work off wall-clock time
{quote}
It's not exactly the same: Each time a put() is done on RocksDB, the current
wall-clock time is used for the put(). However, for Kafka topics, the record
timestamp is used and the record timestamp can be set explicitly on send().
{quote}in particular, imagine the cache is configured with the same TTL as the
topic but that the cache is offline for a couple hours, when the cache comes
back online it will hold onto the values for an extra couple hours
{quote}
Yes, but this could also be the other way: assume your upstream pipeline
writing in your input topics is offline. Hence, you don't process any data, but
RocksDB would expire data even if your application is idle.
Last, I personally believe, that Kafka's retention time as it is design atm is
not perfect either, because it mixes wall-clock time and event-time. Also,
because it's a distributes system, relying on wall-clock time that could
diverge between brokers and the application it could be problematic (I and
don't think about some ms-scale time skew but potentially hours or days if
there is not proper time synchronization).
The only thing I am saying is, that we should come up with a good design and
not ship a "broken" feature. This includes the ability to keep RocksDB and the
corresponding changelog topic in-sync. And because how RocksDB and the brokers
work, I am not 100% sure atm how to achieve this. Maybe a similar mechanism as
we use for window-store would help. In fact, we might even want to improve how
window-stores expire data for the same reasons.
Thanks for the details [~savulchik]!
> Add a key-value store that is a TTL persistent cache
> ----------------------------------------------------
>
> Key: KAFKA-4212
> URL: https://issues.apache.org/jira/browse/KAFKA-4212
> Project: Kafka
> Issue Type: Improvement
> Components: streams
> Affects Versions: 0.10.0.1
> Reporter: Elias Levy
> Priority: Major
> Labels: api
>
> Some jobs needs to maintain as state a large set of key-values for some
> period of time. I.e. they need to maintain a TTL cache of values potentially
> larger than memory.
> Currently Kafka Streams provides non-windowed and windowed key-value stores.
> Neither is an exact fit to this use case.
> The {{RocksDBStore}}, a {{KeyValueStore}}, stores one value per key as
> required, but does not support expiration. The TTL option of RocksDB is
> explicitly not used.
> The {{RocksDBWindowsStore}}, a {{WindowsStore}}, can expire items via segment
> dropping, but it stores multiple items per key, based on their timestamp.
> But this store can be repurposed as a cache by fetching the items in reverse
> chronological order and returning the first item found.
> KAFKA-2594 introduced a fixed-capacity in-memory LRU caching store, but here
> we desire a variable-capacity memory-overflowing TTL caching store.
> Although {{RocksDBWindowsStore}} can be repurposed as a cache, it would be
> useful to have an official and proper TTL cache API and implementation.
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