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Elias Levy commented on KAFKA-4212: ----------------------------------- I am using the {{KStream.transform}} API, the {{Transform}} interface, and making use of state stores that I create. So very close to using the low level {{Processor}} API. But even so, the logic is essentially the same of the high level join, using a sliding window, except that one of the streams has a composite key. I don't see what hopping windows have to do with the use case. > 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 > Assignee: Guozhang Wang > > 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. -- This message was sent by Atlassian JIRA (v6.3.4#6332)