What is Pushdown Optimization?

In this blog, I would like to share or republish a article about "Pushdown Optimization"  which is a new terminology in ETL. I found that the following article gives much more clear explanation about Pushdown Optimization.

Pushdown Optimization which is a new concept in Informatica PowerCentre, allows developers to balance data transformation load among servers. This article describes pushdown techniques.

What is Pushdown Optimization?

Pushdown optimization is a way of load-balancing among servers in order to achieve optimal performance. Veteran ETL developers often come across issues when they need to determine the appropriate place to perform ETL logic. Suppose an ETL logic needs to filter out data based on some condition. One can either do it in database by using WHERE condition in the SQL query or inside Informatica by using Informatica Filter transformation.

Sometimes, we can even "push" some transformation logic to the target database instead of doing it in the source side (Especially in the case of EL-T rather than ETL). Such optimization is crucial for overall ETL performance.

How does Push-Down Optimization work?

One can push transformation logic to the source or target database using pushdown optimization. The Integration Service translates the transformation logic into SQL queries and sends the SQL queries to the source or the target database which executes the SQL queries to process the transformations. The amount of transformation logic one can push to the database depends on the database, transformation logic, and mapping and session configuration. The Integration Service analyzes the transformation logic it can push to the database and executes the SQL statement generated against the source or target tables, and it processes any transformation logic that it cannot push to the database.

Using Pushdown Optimization

Use the Pushdown Optimization Viewer to preview the SQL statements and mapping logic that the Integration Service can push to the source or target database. You can also use the Pushdown Optimization Viewer to view the messages related to pushdown optimization.

Let us take an example:

Filter Condition used in this mapping is: DEPTNO>40

Suppose a mapping contains a Filter transformation that filters out all employees except those with a DEPTNO greater than 40. The Integration Service can push the transformation logic to the database. It generates the following SQL statement to process the transformation logic:

INSERT INTO EMP_TGT(EMPNO, ENAME, SAL, COMM, DEPTNO)     

SELECT

EMP_SRC.EMPNO,

EMP_SRC.ENAME,

EMP_SRC.SAL,

EMP_SRC.COMM,

EMP_SRC.DEPTNO

FROM EMP_SRC

WHERE (EMP_SRC.DEPTNO >40)

The Integration Service generates an INSERT SELECT statement and it filters the data using a WHERE clause. The Integration Service does not extract data from the database at this time.

We can configure pushdown optimization in the following ways:

Using source-side pushdown optimization:

The Integration Service pushes as much transformation logic as possible to the source database. The Integration Service analyzes the mapping from the source to the target or until it reaches a downstream transformation it cannot push to the source database and executes the corresponding SELECT statement.

Using target-side pushdown optimization:

The Integration Service pushes as much transformation logic as possible to the target database. The Integration Service analyzes the mapping from the target to the source or until it reaches an upstream transformation it cannot push to the target database. It generates an INSERT, DELETE, or UPDATE statement based on the transformation logic for each transformation it can push to the database and executes the DML.

Using full pushdown optimization:

The Integration Service pushes as much transformation logic as possible to both source and target databases. If you configure a session for full pushdown optimization, and the Integration Service cannot push all the transformation logic to the database, it performs source-side or target-side pushdown optimization instead. Also the source and target must be on the same database. The Integration Service analyzes the mapping starting with the source and analyzes each transformation in the pipeline until it analyzes the target.

When it can push all transformation logic to the database, it generates an INSERT SELECT statement to run on the database. The statement incorporates transformation logic from all the transformations in the mapping. If the Integration Service can push only part of the transformation logic to the database, it does not fail the session, it pushes as much transformation logic to the source and target database as possible and then processes the remaining transformation logic.

Please read the full article in the below link:

http://dwbi.org/etl/informatica/162-pushdown-optimization-in-informatica