Can't help too much on the Valentina specifics as I'm evaluating it myself.
Suggest you take a look at the site http://www.paradigmasoft.com.
and ask the guys there (they've been very helpful). I know Scott endorses it
Post dated 3/9/2000
--snip-- Anyone building (or contemplating building) applications that
require managing more than a few MB of data or that require sophisticated
query support should download [valentina] --snip--
--snip-- This is a key technology for MetaCard developers to have in their
arsenal and we need to do what it takes to make sure that it works well.
Regards, Scott [Raney] --snip--
on 21/9/00 15:20, David Bovill at [EMAIL PROTECTED] wrote:
> Thanks Gary...
>> From: Gary Rathbone <[EMAIL PROTECTED]>
>> Reply-To: [EMAIL PROTECTED]
>> Date: Thu, 21 Sep 2000 14:23:55 +0100
>> To: [EMAIL PROTECTED]
>> Subject: Re: XML parsing (loads of data question)...
>> I'm looking towards Valentina (http://www.paradigmasoft.com) for a
>> relational database solution for MC.
> How implications does working with Valentina have for memory issues. I ask
> because one of the reasons for converting the project from Java is to get it
> working on Macs with under 50MB of RAM.
>> However you need to get the data from
>> the format its in, to the format suitable for Valentina import.
> What sort of format is required? Tab delimited?
>> A solution I've use in the past is to index the records into a file
>> structure depending on the key, or keys.
>> A converter would be written to split the data into directories and
>> subdirectories so that smaller files exist in defined locations.
>> eg to search on a surname "Davis" MC could look into C:/d/a/v/info.dat
>> which should contain a relatively small file with names such as Davis,
>> Davies, Davison, Davidson etc. and therefore much easier and quicker to
>> Other issues writing to this file structure 'database' and/or how often you
>> need to convert the original/updated data.
> Thanks for the tip.
>>> If I have large amounts of XML data (say 30-100MB), which I need to parse.
>>> The first thought was to load it into an array, at start-up and then get the
>>> keys, and loop through each key (using repeat for each line) - testing to
>>> see if there is a match and returning the value if there is.
>>> However I figure that this would nearly double the amount of memory that I
>>> would need and the full index of keys would be almost as large as the entire
>>> index. As there is no syntax for referring to elements in an associative
>>> array by numerical index (ie get the first, second etc), what would be the
>>> fastest, and most memory efficient technique? Should I use an external
>>> database like "Pandora" or whatever the name beginning with P I am searching
>>> for is? maybe i need my own relational database -:)
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Please send bug reports to <[EMAIL PROTECTED]>, not this list.