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Consistent Distributed Data Set (CDDS)
A Consistent Distributed Data Set is a set of data that is kept consistent (identical) across two or more databases. A CDDS provides a method of defining and grouping data so that an entire database or parts of databases can be replicated to different target sites.
The CDDS gives the distributed DBA the ability to replicate information according to the needs of the business. Data can be replicated precisely when, where, and how the company requires. Changes to data in a CDDS must only be permitted to take place in full peer targets. This is not strictly enforced by Ingres Replicator, but if not adhered to, can result in collisions or inconsistencies.
A CDDS can consist of:
Whole database
The whole database is replicated. For example, where two databases are geographically remote, each office accesses the local replicated database and propagates changes to the other database.
Subset of tables
Only certain tables in the database are replicated. For example, branch offices do not need all the information that the head office has. For a detailed example, see CDDS Example: Subset of Tables.
Subset of columns (vertical partitioning)
Only selected columns in selected tables are replicated. For a detailed example, see CDDS Example: Vertical Partitioning.
Subset of rows based on values (horizontal partitioning)
Only certain rows from selected tables are replicated based on the values of one or more columns. For example, the branch office in London only gets those rows with London in the location column. Horizontal partitioning can only be done for specific values; data ranges are not allowed. For a detailed example, see CDDS Example: Horizontal Partitioning. For information about setting up horizontal replication, see How You Set Up Horizontal Partitioning.
When assigning tables to a CDDS, be sure to consider logical groupings of data. Keep in mind that if a user transaction crosses two or more CDDSs, for example, update a table in one CDDS and insert into a table in another CDDS, the Replicator Server(s) processes it as two or more separate transactions. For more information, see How Errors Are Handled.
Last modified date: 06/10/2024