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ASIA
Tokyo
EUROPE
ARCTIC
OCEAN
A
F
U.K.
GREENLAND
(DEN.)
Paris
B
D
E
AFRICA
CANADA
NORTH AMERICA
A
B
F
PACIFIC
OCEAN
ATLANTIC
OCEAN
C
D
New York
UNITED STATES
Los Angeles
D
E
Memphis
Gulf of
Mexico
MEXICO
Caribbean
Sea
SOUTH AMERICA
F I G U R E 12.9
Distributed database with targeted data
replication
In Figure 12.9, if one person updates a particular value in a record of Table B in
New York at the same time that someone else updates the very same value in the
very same record of Table B in Paris, clearly the results are going to be wrong. Or if
one person updates a particular record of Table B in New York and then right after
that a second person reads the same record of Table B in Paris, that second person
is not going to get the latest, most up-to-date data. The protections discussed earlier
that can be set up to handle the problem of concurrent update in a single table are
not adequate to handle the new, expanded problem.
If the nature of the data and of the applications that use it can tolerate retrieved
data not necessarily being up-to-the-minute accurate, then several ''asynchronous''
approaches to updating replicated data can be used. For example, the site at which
the data was updated, New York in the above example involving Table B, can
simply send a message to the other sites that contain a copy of the same table
(in this case Paris) in the hope that the update will reach Paris reasonably quickly
and that the computer in Paris will update that record in Table B right away. In
another asynchronous scheme, one of the sites can be chosen to accumulate all of
the updates to all of the tables. That site can then regularly transmit the changes
to all of the other sites. Or each table can have one of the sites be declared the
''dominant'' site for that table. All of the updates for a particular table can be sent
to the copy of the table at its dominant site, which can then transmit the updates to
the other copies of the table on some timed or other basis.
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