har.... nah, think I'll give BT a miss for this purpose. Yeah, know it was a loaded question (no specifics), but was really only thinking out aloud.
The plans are: - Multiple copies of data on different machines (just thinking 2 copies of the data) - Load spread over multiple machines... anything between 2->lots (again, not being specific). - Data itself I'm expecting to be low.... a few Gb at tops (but ofcourse, as this extends I might want to increase the size) - Haven't thought a LOT about automatic handling of errors...... yet. - and its assumed to be on a trusted network. Apart from memcached, I haven't seen anything similar to what I'm after (plus to be perfectly honest..... I wouldn't mind coding it up anyway) ;) Was just "feeling about" to see if anything else is out there. KenF ps. btw, only part of it is theoretical, a lot of this I've already coded, but not targetted towards large scale (100's machines etc)... So am thinking what I'd need to consider to increase this to a larger scale. Roger Binns wrote: > <[EMAIL PROTECTED]> wrote in message news:[EMAIL PROTECTED] > > Does anyone know if a "distributed caching system" has been developed > > for use with Python? > > BitTorrent :-) > > > Yes, "distributed caching system" is a bit of a general term, but am > > really just talking about something as simple as key + value (arbitrary > > class) which can be split over a number of machines in an efficient > > manner. > > You'll need to define what the sweet spot is that you are aiming for. > Are we talking tens of thousands of keys or billions? How big is the > data (megabytes, gigabytes, terabytes?) Do you need transactional > integrity (eg when are updates seen by other readers)? Do you want > redundancy (data duplicated on multiple machines)? How many machines > are we talking about? Should failure be automatically detected? Is > there a need for security or treating the machines as untrusted? > > Roger -- http://mail.python.org/mailman/listinfo/python-list