There are two scaling factors to consider here. In general the worst case growth of operations in Cassandra is kept near to O(log2(N)). Any worse growth would be considered a design problem, or at least a high priority target for improvement. This is important for considering the load generated by very large column families, as binary search is used when the bloom filter doesn't exclude rows from a query. O(log2(N)) is basically the best achievable growth for this type of data, but the bloom filter improves on it in some cases by paying a lower cost every time.
The other factor to be aware of is the reduction of binary search performance for datasets which can put disk seek times into high ranges. This is mostly a direct consideration for those installations which will be doing lots of cold reads (not cached data) against large sets. Disk seek times are much more limited (low) for adjacent or near tracks, and generally much higher when tracks are sufficiently far apart (as in a very large data set). This can compound with other factors when session times are longer, but that is to be expected with any system. Your storage system may have completely different characteristics depending on caching, etc. The read performance is still quite high relative to other systems for a similar data set size, but the drop-off in performance may be much worse than expected if you are wanting it to be linear. Again, this is not unique to Cassandra. It's just an important consideration when dealing with extremely large sets of data, when memory is not likely to be able to hold enough hot data for the specific application. As always, the real questions have lots more to do with your specific access patterns, storage system, etc. I would look at the benchmarking info available on the lists as a good starting point. On Fri, Jul 23, 2010 at 11:51 AM, Michael Widmann <michael.widm...@gmail.com> wrote: > Hi > > We plan to use cassandra as a data storage on at least 2 nodes with RF=2 > for about 1 billion small files. > We do have about 48TB discspace behind for each node. > > now my question is - is this possible with cassandra - reliable - means > (every blob is stored on 2 jbods).. > > we may grow up to nearly 40TB or more on cassandra "storage" data ... > > anyone out did something similar? > > for retrieval of the blobs we are going to index them with an hashvalue > (means hashes are used to store the blob) ... > so we can search fast for the entry in the database and combine the blobs to > a normal file again ... > > thanks for answer > > michael >
