Hello, I observe throughput degradation when my pipeline reaches the maximum of the allocated block cache.
The pipeline is consuming from a few Kafka topics at a high rate (100k+ rec/s). Almost every processed message results in a (keyed) state read with an optional write. I've enabled native RocksDB metrics and noticed that everything stays stable until the block cache usage reaches maximum. If I understand correctly, this makes sense: this cache is used for all reads and cache misses could mean reading data on disk, which is much slower (I haven't switched to SSDs yet). Does it make sense? One thing I know about the messages I consume: I expect very few keys to be active simultaneously, most of them can be treated as cold. So I'd love RocksDB block cache to have a TTL option (say, 30 minutes), which, I imagine, could solve this issue by guaranteeing to only keep active keys in memory. I don't feel like LRU is doing a very good job here... I couldn't find any option like that, but I'm wondering if someone could recommend something similar. Thank you! -- Yaroslav Tkachenko sap1ens.com
