Cassandra Stress test on a Raspberry Pi

So here are my initial results at using  a  Raspberry Pi to run Cassandra.  At the moment I’m running a single Pi with Cassandra 0.8.10 (compacting is not available and Snappy  will not run currently on the Pi) I’m using the  java stress tests that come with Cassandra source.  These tests where run with the stress test classes running on the same Pi as the Cassandra instance.  To be honest it’s not looking great,  but looking at ways of getting faster IO and tuning:

Pi with class 10 Sd card

total,interval_op_rate,interval_key_rate,avg_latency,elapsed_time
289,28,28,0.5914359861591696,11
1266,97,97,0.13869907881269192,22
2056,79,79,0.5817556962025316,32
3744,168,168,0.31356575829383887,43
5737,199,199,0.20355143000501758,54
7703,196,196,0.179558494404883,64
9514,181,181,0.2858961899503037,74
11305,179,179,0.1481675041876047,85

As you can see this ramps up to a interval op rate of nearly 200.  Using an external HD on the USB is actually slightly worse (extract from later in the run):

total,interval_op_rate,interval_key_rate,avg_latency,elapsed_time
889736,133,133,0.263335837716003,7116
890287,55,55,0.5460671506352087,7126
891445,115,115,0.37030224525043176,7136
892668,122,122,0.4226631234668847,7147
894149,148,148,0.23508845374746792,7159
895317,116,116,0.3649169520547945,7170
896475,115,115,0.23375302245250432,7180
897574,109,109,0.47590354868061874,7190
898558,98,98,0.41302845528455284,7201
899626,106,106,0.39788951310861426,7211
900910,128,128,0.21852570093457943,7221
902078,116,116,0.41339640410958906,7232

For comparison, here’s the results from my new Apple Mac Air with a SSD :

total,interval_op_rate,interval_key_rate,avg_latency,elapsed_time
30581,3058,3058,0.013996631895621465,10
137194,10661,10661,0.003453800193222215,20
277241,14004,14004,0.0024328332631188103,30
408411,13117,13117,0.0025887245559197986,40
535147,12673,12673,0.0027360339603585406,51
662768,12762,12762,0.0026654704163107954,61
792233,12946,12946,0.0026509326845093268,71
919061,12682,12682,0.002678690825369792,81
1000000,8093,8093,0.0026410383128034694,88
END