On 18.08.13 17:09, Jim Fulton wrote:
On Fri, Aug 16, 2013 at 11:49 PM, Christian Tismer <tis...@stackless.com> wrote:
Explaining very concisely, now.
I don't think I/we understand your problem well enough to answer. If
data has a very low shelf life, then replacing it frequently might
make sense. If the schema changes that frequently, I'd as why. If this
is a data analysis application, you might be better served by tools
designed for that.
Is Python still the way to go, or should I stop this and use something like
PostgreSQL? (And I doubt that this would give a benefit, actually).
Would you implement a column store, and how would you do that?
Right now, everything gets too large, and I'm quite desperate. Therefore,
asking the master, which you definately are!
"large" can mean many things. The examples you give don't
seem very large in terms of storage, at least not for ZODB.
Beyond that there are lots of dimensions of scale that ZODB
doesn't handle well (e.g. large transaction rates, very
It's really hard to make specific recommendations without
knowing more about the problem. (And it's likely that someone
wouldn't be able to spend the time necessary to learn more
about the problem without a stake in it. IOW, don't assume I'll
read a much longer post getting into details. :)
Ok, just the sketch of it to make things clearer, don't waste time on
We get a medication prescription database in a certain serialized format
which is standard in Germany for all pharmacy support companies.
This database comes in ~25 files == tables in a zip file every two weeks.
The DB is actually a structured set of SQL tables with references et al.
I actually did not want to change the design and simply created the table
structure that they have, using ZODB, with tables as btrees that contain
tuples for the records, so this is basically the SQL model, mimicked in
What is boring is the fact, that the database gets incremental updates
all the time,
changed prices, packing info, etc.
We need to cope with millions of recipes that come from certain dates
and therefore need to inquire different versions of the database.
I just hate the huge redundancy that these database versions would have
and tried to find a way to put this all into a single Zodb with a way to
time-travel to every version.
The weird thing is that the DB also changes its structure over time:
- new fields are added, old fields dropped.
That's the reason why I thought to store the tables by column, and each
a BTree on itself. Is that feasible at all?
Of the 25 tables, there are 4 quite large, like
4 tables x 500,000 rows x 100 columns,
== 200,000,000 cells in one database.
With a btree bucket size of ~60, this gives ~ 3,333,333 buckets.
With multiple versions, this will be even more.
-- Can Zodb handle so many objects and still open the db fast?
-- Or will the huge index kill performance?
That's all I'm asking before doing another experiment ;-)
but don't waste time, just telling you the story -- chris
Christian Tismer :^) <mailto:tis...@stackless.com>
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