Hi Lyle,
Your email gave me flashbacks to when I gave tutorials on distributed
databases at the University of Technology, Sydney (UTS). At the time Oracle
were very happy to provide free copies of their DDBMS software for the uni
labs. We had an "east" and "west" cluster set up and there were all sorts of
tricky update/locking/concurrency/partitioning problems with interesting
schema design decisions as a result. No doubt your lecturer has got some
interesting exam/assignment questions lined up ... ;-)
Lately, I've been appreciating more and more the need to consider 'time'
in schema design as it applies to the dimensions of interest in your
database. Most of the extra features in a DDBMS are trying to overcome the
hassles caused by latency between database nodes and queries across physical
partitions. A DDBMS tries to hide this complexity under the carpet but
sometimes I think it's better to deal with it head on.
In my opinion Ralph Kimball's data warehouse methodology is currently a
good approach to remodelling distributed databases[1]. It does not rely on a
DDBMS doing its magic but deals directly with the temporal aspects of
relational data modelling by forcing you to look at the granularity of data
your system actually requires, who needs it, and what are the dimensions of
interest? Once you know the answers to these questions the transaction
processing can be distributed but the actual reporting data can be
consolidated into data warehouses close to their respective users with no
inherent need for a DDBMS.
DBMSs traditionally managed 'the tyranny of disk seek times but thanks to
the march of Moore's law - we're free - to go and dive into deep endless RAM
pools! ;-) ... err ... maybe not quite yet. But it's interesting to watch
the NoSQL movement develop and other non-relational ways of dealing with
large distributed data sets [2].
The Sun is shining - time for a beer!
NIge
[1] http://en.wikipedia.org/wiki/Ralph_Kimball
[2] http://en.wikipedia.org/wiki/NoSQL
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