I saw some Cassandra benchmark reports mentioning read latency that is less than 50ms or even 30ms. But my benchmark with 0.5 doesn’t seem to support that. Here’s my settings:


Nodes: 2 machines. 2x2.5GHZ Xeon Quad Core (thus 8 cores), 8GB RAM

ReplicationFactor=2 Partitioner=Random

JVM Xmx: 4GB

Memory table size: 512MB (haven’t figured out how to enable binary memtable so I set both memtable number to 512mb)

Flushing threads: 2-4

Payload: ~1000 bytes, 3 columns in one CF.

Read/write time measure: get startTime right before each Java thrift call, transport objects are pre-created upon creation of each thread.


The result shows that total write throughput is around 2000/sec (for 2 nodes in the cluster) which is not bad, and read throughput is just around 750/sec. However for each thread the average read latency is more than 100ms. I’m running 100 threads for the testing and each thread randomly pick a node for thrift call. So the read/sec of each thread is just around 7.5, meaning duration of each thrift call is 1000/7.5=133ms. Without replication the cluster write throughput is around 3300/s, and read throughput is around 1400/s, so the read latency is still around 70ms without replication.


Is there anything wrong in my benchmark test? How can I achieve a reasonable read latency (< 30ms)?