Incremental Load DW by using CDC in SSIS
To load data from OLTP system to DW, we have to face a problem: how to balance time and cost. Since data raises faster and faster, we need to increase our hardware ability to match the time requirement. So, incremental load coming out to reduce the data transmission significantly. There are three way to achieve it: 1. use datetime column 2. Changed data capture 3. changed data tracking. For a long time, I use the first way to capture the changed data manual, it is good, but too many works in development and testing. Here I want to introduce the CDC. Basically, CDC just a feature to utilize LSN(Log Sequence Number) and log tables to capture changed data, while SSIS itself provide native components to easy work with this new feature.
Let’s build a CDC workflow in SSIS for example:
Enable CDC feature
- enable CDC by executing
sp_cdc_disable_db). Then check it with
select name from sys.databaseswhere is_cdc_enabled=1
- enable CDC for spec table with
sp_cdc_enable_tablethen we can find the CDC table in systemtable folder or using
select namefrom sys.tables tabwhere is_tracked_by_cdc=1to check.
@source_schema = N'Person'
, @source_name = N'Address'
, @role_name = N'cdc_Admin'
, @capture_column_list = N'column1, column2'; //can track spec columns, rather than the whole table
Control flow setting
CDC control task
- set CDC control operation to
mark cdc startand set the cdc states for saving cdc states
- run this control task, it will create a record in table
- create two
CDC control tasks, one set operation to
Get Processing Range, another for
Mark process range, they will get changed data and update CDC states respectively.
- put a dataflow which is response for ETL operation, between two CDC control tasks.
Data flow setting into staging table
CDC sourcewhich points to the table enabled CDC and choose the correct cdc_states table as well.
NetCDC processing mode in CDC source.
CDC splinterafter CDC source, create three
Derived Column transformationfor insert(0), update(2) and delete(1) data.
- create a
Union All transformationto union all data and export to stage database.
- if necessary, we need to add a
truncatescript before all control flow to delete everything in stage database.
Update fact table through staging tables
- create a oledb source to connect to stage database
- use conditional split to split
insert, we directly export; for
update+deletewe need to delete from fact table by identifier by
OLE DB Command transformation, and use conditional split to export update data.
- if necessary, use lookup to replace some dimensional columns
- export to fact database.