Scalable python dict {'key_is_a_string': [count, some_val]}

Krishna K krishna.k.0001 at
Wed Mar 10 17:47:44 CET 2010

On Fri, Feb 19, 2010 at 11:27 PM, Jonathan Gardner <
jgardner at> wrote:

> On Fri, Feb 19, 2010 at 10:36 PM, krishna <krishna.k.0001 at>
> wrote:
> > I have to manage a couple of dicts with huge dataset (larger than
> > feasible with the memory on my system), it basically has a key which
> > is a string (actually a tuple converted to a string) and a two item
> > list as value, with one element in the list being a count related to
> > the key. I have to at the end sort this dictionary by the count.
> >
> > The platform is linux. I am planning to implement it by setting a
> > threshold beyond which I write the data into files (3 columns: 'key
> > count some_val' ) and later merge those files (I plan to sort the
> > individual files by the key column and walk through the files with one
> > pointer per file and merge them; I would add up the counts when
> > entries from two files match by key) and sorting using the 'sort'
> > command. Thus the bottleneck is the 'sort' command.
> >
> > Any suggestions, comments?
> >
> You should be using BDBs or even something like PostgreSQL. The
> indexes there will give you the scalability you need. I doubt you will
> be able to write anything that will select, update, insert or delete
> data better than what BDBs and PostgreSQL can give you.
> --
> Jonathan Gardner
> jgardner at

Thank you. I tried BDB, it seems to get very very slow as you scale.

Thank you,
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