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I am concerned to hear this approach, and others here, discussed, without
comment as to scaling issues regarding very large datastores (in XML
documents or in relational dbms) that might be ten to several hundred
terabytes in size.
Specifically, in the following respects:
1- sheer size problems such as disk access time, out of memory conditions,
and processor time to parse very large XML documents (say, 1,000 documents
of 1 terabyte each) or a very large number of XML documents of smaller size
(say, 5,000,000 5MB docs).
2- maintenance issues driven by the smallest of interface changes or
presentation changes, that result in hundred of thousands if not millions
of manual static schema modifications, rippling across either a very large
number of smaller XML documents and their specific schemas or through as
many as a thousand or so documents of 1 terabyte each in size. Even if such
ripple effect maintenance can be automated, the processing time required to
update, say, 5,000,000 XML doc files of 5MB each cannot be said to be real
time, so perhaps weeks of processing time is required before the interface
mods can be subject to just one full test.
3- consistency across versions, releases, XML standards and tool sets (MS,
SQL Server, MySQL, Oracle, etc) considering that a very large scale project
will take some time to mature (possibly years), and that a lack of backward
compatibility could drive massive changes into the basic XML design
structure and overall document architecture.
4- transmission time across interchanges - whether lan, web or intranet
based, the time to transmit and parse result sets to XQuery are often very
large, and for very large XML documents this processing time is
unacceptably long. People want results in five to eleven seconds, not
minutes, not hours.
I have specific experience in very large paper based, and relational
database systems. From time to time, I see folks scale up systems that work
fine, up to a point, past which they are forced to redesign from scratch.
While I agree that broadly generalized discussions are the most common form
of technical exchange of information, having seen several of these pilot
efforts crash and burn, I feel a moral obligation to suggest that some
comment be made as to scaling issues, known propagation or ripple effects,
and sheer size problems that come into play when viable "average"
architectures are scaled beyond their design parameters.
In reference to this specific method, I submit that when dealing with a
very large repository of prose, that a very large number of "profile
documents" is possible, and that the number of possible "profile documents"
correlates to some index of the context and the subject matter and the
usage purposes (inquiry / result pairs), a result that to my mind increases
or scales up as the number of prose entities scales up. I will go further
and say that, for instance, for all articles ever published in the
scientific journal "Nature", or perhaps all items in the U.S. Library of
Congress or all pending applications and issued patent files in the U.S.
Patent Office, this number of possible "profile documents" becomes very
large indeed. Though it may be possible to satisfy as much as a majority if
inquiries with a small number of such structures, the rest of the
inquiries, it seems to me, will require an ever increasing number of
"profile documents" to satisfy so that satisfying the last 1 percent of
such inquiries might require several thousands of such "profile documents",
if not tens of thousands or hundreds of thousands.
So, I am interested to hear about practical applications using XML only
implementation (XQuery, XML, XSLT, XPath, etc) that deal with wide ranging
subject matter, such as is found in the scientific journal "Nature", or
perhaps all items in the U.S. Library of Congress or all pending
applications and issued patent files in the U.S. Patent Office, to a very
broad audience, across scientific disciplines and cultures (and possibly
languages), for a very large data repository of mixed content (prose,
graphics, slides, photos, video, sound, other streaming data sources or
media) measured in tens or hundreds of terabytes.
While XML is superb at document mark up, in my experience almost as good as
TeX, it does not strike me as the best tool for the job when dealing with
very large scale data repositories. Still, I have an open mind and perhaps
someone here can enlighten me.
Thank you.
At 10:28 PM 8/18/2003 -0400, you wrote:
>One of the difficulties in considering factoring out functionally
>dependent entities from prose, is that the block of prose may itself not
>be worth reusing. That is, the prose may be a one-shot document whose
>original intent is simply to present information, not to act as a reliable
>container for access by clients with a variety of intents.
>One thing I've done is to try to identify those concepts which are best
>understood, are most firmly established, and which serve as the focus of
>the stakeholders' activities and communications. Then design a profile
>document for each of these high-level concepts, which provide context for
>making pointers and for generating identifiers. The profiles are designed
>to provide some elements which are rigidly structured, and other elements
>which are prose with mixed content. In one case at least, this allowed me
>(with a stylesheet) to resolve most cross references internal to the
>document itself, minimizing calls to scan external documents. Also,
>depending upon the nature of your data and your validation techniques, you
>may be able to use the mixed content prose as the source of the definitive
>information, rather than just as glue.
>It is certainly something a good CMS can help with, but I've also used
>DSSSL and XSLT/XPath for doing just this sort of thing with reasonable
>results. You might also want to check out DITA by Michael Priestley et al.
>of IBM, which I think intends to facilitate topical reuse.
>
>Roger L. Costello wrote:
>
>>Hi Folks,
>>I am working with some people who wish to migrate from an
>>all-prose format to a prose-plus-reusable-XML-fragments
>>format.
>>They have some data in prose that is useable in many contexts. They
>>want to break out that reusable data into XML fragments. However,
>>they want to continue to provide the prose style.
>>For example, consider this prose data:
>><para>The city of Miami, Florida (pop. 1, 234,000) is a sprawling city
>>with many attractions. Miami Beach is a popular attraction. The
>>spring tide is ... The neap tide is ... </para>
>>Examining this prose we can extract reusable info about the city of
>>Miami:
>><City id="Miami">
>> <state>Florida</state>
>> <population>1,234,000</population>
>></City>
>>We can also extract reusable info about tide data on Miami Beach:
>><TideData id="MiamiBeachTides">
>> <springTide>...</springTide>
>> <neapTide>...</neapTide>
>></TideData>
>>The problem now is to create a framework which allows the prose
>>to bring-together the independent, reusable XML components.
>>Conceptually, what is desired is a "glue framework" like this:
>><para>The <ref href="Miami.xml"> is a sprawling city with
>>many attractions. Miami Beach is a popular attraction. The
>>tides are <ref href="MiamiBeachTides.xml"><para>
>>Thus, the prose is "glueing" together the XML fragments.
>>Is this a problem that you have experience with? What "glue
>>framework" have you used? What strategy did you use to merge
>>the XML fragments with the prose? Is there is a standard way
>>of combining semi-structured data with structured data?
>>/Roger
>>
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>
>
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