The following terms are used in the discussion of Change Data Capture:
Change Data Capture (CDC) – Industry term used to describe the duplication of subsets of OLTP data in an external data source with a relatively up to date version of relational data. Implementations of CDC can involve an extraction/transformation/load (ETL) application that captures individual data changes per table. Instead of dealing with the entire table, the ETL application can selectively choose which fields from an individual table to capture and to populate to an external data source.
Change Field Policy – Describes a table used to select fields from an identified Source Table for CDC activity. A policy represents only one field. A Change Table policy can have several of these related policies reporting to it. The maximum number of field policies per Change Table policy is the number of fields in the Source Table.
Change Record Sets (also referred to as chained Change records) – Describes the splitting of change data (which represents one change) into a chained grouping of records. The chaining of these records is indicated by the use of the continuation position field.
Change Table – Describes a user defined data capture table. The construction of this table begins when a CDC policy on the table level is created.
Change Table Policy – Describes a table used to select a Source table for CDC activity. The policy designer through the OpenEdge Management Policy Tool creates table policies as a first step in designing what data will be captured from a Source table.
Change Tracking Table – Describes a table used by the CDC process to insure transactional sequence. The construction of this table occurs when CDC is enabled. The table represents transactional information for all tables that participate in the Change Capture process. Their participation begins when a source table is enabled for CDC through the OpenEdge Management Policy Tool.
Identifying fields – Describes the fields the CDC policy designer uses to potentially build an index in the external data source table being constructed from the Change table data. The CDC policy designer must select from the source data file, the fields that best identify each particular change.
Identifying index –Describes an index containing identifying field values used in identifying/locating records in the external data store. Once the CDC designer has created the identifying fields, the CDC capture process will create the record and related index using those values from each source data record.
Meta data - Describes the columns in the Change Table Header. Meta data means data which describes data. The initial columns in the Change Table are meta data columns containing information describing data in the Change Table that is necessary for understanding source fields changed and whether record/field splits are present.
Source Table – Describes a table that contains original data to be captured by the CDC process. The table can be of any user defined schema table. Virtual, System, View, and non-user defined schema tables are not eligible to participate in the CDC process. Each source table must be enabled individually through the OpenEdge Management Policy Tool.
Table Policy Record Sets – Describes the grouping of a Table policy record with its related Field policy records by use of a foreign key. This grouping implies that they are considered a unit and need to be managed as a unit.
Change Data Capture (CDC) – Industry term used to describe the duplication of subsets of OLTP data in an external data source with a relatively up to date version of relational data. Implementations of CDC can involve an extraction/transformation/load (ETL) application that captures individual data changes per table. Instead of dealing with the entire table, the ETL application can selectively choose which fields from an individual table to capture and to populate to an external data source.