Logo DWBI.org Login / Sign Up
Sign Up
Have Login?
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
New Account?
Go to Login
By continuing you indicate that you agree to Terms of Service and Privacy Policy of the site.

Implementing Informatica Incremental Aggregation

Updated on Sep 30, 2020

Using incremental aggregation, we apply captured changes in the source data (CDC part) to aggregate calculations in a session. If the source changes incrementally and we can capture the changes, then we can configure the session to process those changes. This allows the Integration Service to update the target incrementally, rather than forcing it to delete previous loads data, process the entire source data and recalculate the same data each time you run the session.

Incremental Aggregation

When the session runs with incremental aggregation enabled for the first time say 1st week of Jan, we will use the entire source. This allows the Integration Service to read and store the necessary aggregate data information. On 2nd week of Jan, when we run the session again, we will filter out the CDC records from the source i.e the records loaded after the initial load. The Integration Service then processes these new data and updates the target accordingly.

Use incremental aggregation when the changes do not significantly change the target. If processing the incrementally changed source alters more than half the existing target, the session may not benefit from using incremental aggregation. In this case, drop the table and recreate the target with entire source data and recalculate the same aggregation formula .

INCREMENTAL AGGREGATION, may be helpful in cases when we need to load data in monthly facts in a weekly basis.

Sample Mapping

Let us see a sample mapping to implement incremental aggregation:

Incremental Aggregation Mapping
Incremental Aggregation Mapping

Look at the Source Qualifier query to fetch the CDC part using a BATCH_LOAD_CONTROL table that saves the last successful load date for the particular mapping.

Incremental Aggregation Source Qualifier
Incremental Aggregation Source Qualifier

Look at the ports tab of Expression transformation.

Incremental Aggregation Expression
Incremental Aggregation Expression

Look at the ports tab of Aggregator Transformation.

Incremental Aggregation Aggregator
Incremental Aggregation Aggregator

Now the most important session properties configuration to implement incremental Aggregation.

Incremental Aggregation Session property
Incremental Aggregation Session property

If we want to reinitialize the aggregate cache suppose during first week of every month we will configure the same session in a new workflow at workflow level with the Reinitialize aggregate cache property checked in.

Incremental Aggregation Session property
Incremental Aggregation Session property

Example with Data

Now have a look at the source table data:


After the first Load on 1st week of Jan 2010, the data in the target is as follows:


Now during the 2nd week load it will process only the incremental data in the source i.e those records having load date greater than the last session run date. After the 2nd weeks load after incremental aggregation of the incremental source data with the aggregate cache file data will update the target table with the following dataset:

11116008201001450The cache file updated after aggretation
22226009201001500The cache file updated after aggretation
33335003201001300The cache file remains the same as before
44441234201001350New group row inserted in cache file
55556157201001500New group row inserted in cache file

Understanding Incremental Aggregation Process

The first time we run an incremental aggregation session, the Integration Service processes the entire source. At the end of the session, the Integration Service stores aggregate data for that session run in two files, the index file and the data file. The Integration Service creates the files in the cache directory specified in the Aggregator transformation properties.

Each subsequent time we run the session with incremental aggregation, we use the incremental source changes in the session. For each input record, the Integration Service checks historical information in the index file for a corresponding group. If it finds a corresponding group, the Integration Service performs the aggregate operation incrementally, using the aggregate data for that group, and saves the incremental change. If it does not find a corresponding group, the Integration Service creates a new group and saves the record data.

When writing to the target, the Integration Service applies the changes to the existing target. It saves modified aggregate data in the index and data files to be used as historical data the next time you run the session.

Each subsequent time we run a session with incremental aggregation, the Integration Service creates a backup of the incremental aggregation files. The cache directory for the Aggregator transformation must contain enough disk space for two sets of the files.

The Integration Service creates new aggregate data, instead of using historical data, when we configure the session to reinitialize the aggregate cache, Delete cache files etc.

When the Integration Service rebuilds incremental aggregation files, the data in the previous files is lost.

Note: To protect the incremental aggregation files from file corruption or disk failure, periodically back up the files.

Top 10 Articles