I am looking for possible ways to model a distributed table(s) and provide local exceptions to that table. Consider a situation where head office publishes a list of products/prices that is distributed to branches and they load this price list into their local database. Now sometimes these branches want to change the head office price to a local price. Clearly we can simply update the price in the local database, but then it gets lost when the next head office update is applied. We also only want to block that single column(s), not changes to other fields in the row.
EG. Head office send
| Name | Price |
| ABC | $5 |
| DEF | $8 |
In one database (out of say 100) we want ABC to have a price of $3. And this $3 should continue to apply even as future updates from head office are received. Head office are not aware of this local exeception.
In the past we’ve done this in two ways. The first was to maintain a second LocalProducts table with the changes to be applied – then when the head office version was applied, any local changes would then be read from LocalProducts and replace the distributed value.
This works OK, but suffers as the table sizes go up.
The second method we tried was to duplicate the column and use coalesce
eg rather than
select price where name='abc' we would use
select coalesce(localprice,price) where name='abc' This works ok, but had the overhead that we had to change every SQL and remember to do it on future development too.
Are there any other better methods? I am looking for a database agnostic solution, the target databases are ODBC (90% sql/server), SQL-Lite or MS-Access. Access can be ignored if it helps, it is being actively phased out. Engine specific solutions are ok, we can detect the engine and use a different technique, but would prefer not to have a different technique for each engine.
- The data is distributed by the application, not built in replication. This means we can have code/logic during the loading phase
- Multiple tables are require this feature, not just one as the example above
- Some of the tables have a reasonable number of columns that could be involved, but typically not.
- Most of the tables aren’t large, perhaps 50M rows in the biggest, and only 7 rows in the smallest case.
(please feel free to retag this question – not exactly sure which tags are relevant. And yes I have spent many hours over the years investigating this)