Good day,
I am using KStream on Java API (and springboot) to correlate (LEFT JOIN) two topics, lets say topic A and topic B
- A and B both have TPS around hundred thousands with event size approximately around 100GB per 3 hours
- Using Java 11 and KStream + Topology Processors Interface
- LEFT JOIN based on exact event KEY with windowed time 15 minutes
- A and B have retentions about 1 hour
The memory usage is ridiculously high (around 90-100GB) and only down after each windowed time
So, i tried to tweaked rocksdb like below
rocksdb.write.buffer.size=1073741824
rocksdb.max.write.buffer.number=2
rocksdb.block.cache.size=1073741824
rocksdb.increase.parallelism=2
rocksdb.level.compaction.style=true
rocksdb.min.write.buffer.number.to.merge=1
rocksdb.total.off.heap.memory=4294967296
rocksdb.total.memtable.size=2147483648Reduction on those numbers seems to no taking effects;
Any ideas? or that perhaps i was go wrong?
Thank you