If you have only one such objects, shared between all users than cache.ram may be a solution.
I am surprised cPickle fails since the data is not so large. Are you sure it is a file size problem? Is it possible that the object simply contains unpicklable references? try store it on the filesystem in the os.path.join(request.folder,'private') folder. > 937984 Bytes is the size of the file when I pickle a large object to a > file. This is protocol 0. When I attempted to use protocol 2, it > failed. > > I recently realized that the session itself is pickled, so I tried to > simply add the object to the session to see what would happen. Same > result. > > I'm dealing with large hierarchical data and would prefer to keep the > data in the session. However, it looks like this might not be > feasible for large amounts of data. What about increasing the memory > block for web2py? > > I'm thinking my other option would be to keep it in cache.ram and in > the database. What do you think? > > On Jul 22, 5:37 pm, mdipierro <mdipie...@cs.depaul.edu> wrote: > > > How big is the pickled file? > > > On Jul 22, 5:08 pm, "topher.baron" <topher.ba...@gmail.com> wrote: > > > > web2py community, > > > > I'm currently implementing a web application on localhost running OS > > > 10.6.4. When I cPickle.dump a large object to the /tmp directory, > > > web2py crashes. The same operations work with smaller objects. > > > > Does this mean I need to increase the heap? If so, how do I do this? > > > If not, any suggestions? > > > > Thanks in advance.
