(Moving to users@ list.) Like any Java server, Cassandra will use as much memory in its heap as you allow it to. You can request a GC from jconsole to see what its approximate "real" working set it.
http://wiki.apache.org/cassandra/SSTableMemtable explains why reads are slower than writes. You can tune this by using the key cache, row cache, or by using range queries instead of requesting rows one at a time. contrib/py_stress is a better starting place for a benchmark than rolling your own, btw. we see about 8000 reads/s with that on a 4-core server. On Sun, Apr 18, 2010 at 8:40 PM, Bingbing Liu <rucb...@gmail.com> wrote: > Hi,all > > I have a cluster of 5 nodes, each node has a 4 cores cpu and 8 G Memory. > > I use the 0.6-beta3 cassandra for testting. > > First , i insert 6,000,000 rows each of which is 1k bytes, the speed of write > is so excited. > > But then ,when i read them each row at a time from two clients at the same > time ,one of the client is very slow and use so long a time, > > i find that on each node the process of Cassandra occupy 7 G memory or so > (use the "top" command), that puzzled me. > > Why read operation use so much of memory? May be i missed something? > > Thx. > > > 2010-04-18 > > > > Bingbing Liu >
