Hi All, Does anyone have any suggestions about how to improve performance in the below use case?
I have a very simple table with a single Partition Key, and one Cluster key. My app is periodically writing new entries in the table and deleting old ones. There are a lot more reads than writes on this particular table. All of the queries are just for the partition key. Most of the queries are for partition keys that don't exists, more than 99% of the queries. I was looking at ways to tune the performance. At present there aren't that many records. So it would all fit in memory nicely. However presumably the key cache miss is likely to still require a read anyway? Below is a copy of cfstats: Read Count: 21795477 Read Latency: 0.009573296147636502 ms. Write Count: 11673 Write Latency: 0.03859205002998373 ms. Pending Tasks: 0 Table: inputs SSTable count: 1 Space used (live), bytes: 1655036 Space used (total), bytes: 1662004 SSTable Compression Ratio: 0.6104794381809562 Number of keys (estimate): 10240 Memtable cell count: 3058 Memtable data size, bytes: 1969808 Memtable switch count: 4 Local read count: 21795477 Local read latency: NaN ms Local write count: 11673 Local write latency: 0.040 ms Pending tasks: 0 Bloom filter false positives: 183 Bloom filter false ratio: 0.00000 Bloom filter space used, bytes: 13136 Compacted partition minimum bytes: 104 Compacted partition maximum bytes: 149 Compacted partition mean bytes: 149 Average live cells per slice (last five minutes): 0.0 Average tombstones per slice (last five minutes): 0.0 Thanks, Charlie M
