The document discusses a new pushdown optimization option available in Informatica PowerCenter 8 that can improve data integration performance and scalability. It works by generating database-specific logic to represent the overall data flow and pushing the execution of that logic into the database to perform data transformations. This allows taking advantage of database processing power and avoids extracting large amounts of data. The option provides flexibility in controlling where processing takes place and leverages a single design environment. Pushing logic to the database can significantly increase performance by avoiding extracting and reloading large amounts of data.

1. WHITE PAPER
How to Obtain Flexible, Cost-effective Scalability and
Performance through Pushdown Processing
Under the Hood of the Pushdown Optimization Option
Now Available Through Informatica PowerCenter 8

2. This document contains Confidential, Proprietary and Trade Secret Information (“Confidential Information”) of
Informatica Corporation and may not be copied, distributed, duplicated, or otherwise reproduced in any manner
without the prior written consent of Informatica.
While every attempt has been made to ensure that the information in this document is accurate and complete,
some typographical errors or technical inaccuracies may exist. Informatica does not accept responsibility for any
kind of loss resulting from the use of information contained in this document. The information contained in this
document is subject to change without notice.
The incorporation of the product attributes discussed in these materials into any release or upgrade of any
Informatica software product—as well as the timing of any such release or upgrade—is at the sole discretion of
Informatica.
Protected by one or more of the following U.S. Patents: 6,032,158; 5,794,246; 6,014,670; 6,339,775;
6,044,374; 6,208,990; 6,208,990; 6,850,947; 6,895,471; or by the following pending U.S. Patents:
09/644,280; 10/966,046; 10/727,700.
This edition published April 2006

3. White Paper
Table of Contents
Executive Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .2
Historical Approaches to Data Integration . . . . . . . . . . . . . . . . . . . . . . . . .4
The Combined Engine- and RDBMS-based Approach to Data Integration . .5
How Pushdown Optimization Works . . . . . . . . . . . . . . . . . . . . . . . . . . . . .5
Overview of Pushdown Processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .6
Two-Pass Pushdown Processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .7
Partial Pushdown Processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .8
Full Pushdown Processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .8
Platform-specific Pushdown Optimization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .9
Limitations on the Types of Transformations that Can Be Pushed to the Database . . . . . .9
Benefits of Pushdown Optimization . . . . . . . . . . . . . . . . . . . . . . . . . . . . .10
Increased Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .10
Increased IT Team Productivity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .11
Reduced Risk and Enhanced Flexibility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .12
Conclusion and Next Steps . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .12
Pushdown Optimization 1

4. Executive Summary
Over the next five to 10 years and beyond, the two dominant variables in the enterprise data
integration equation are painfully clear—more data and less time. Given these, what’s the right
data integration strategy to effectively manage terabytes or even hundreds of terabytes of data
with enough flexibility and adaptability to cope with future growth?
Historically, data integration was performed by developing hand-coded programs that extract
data from source systems, apply business/transformation logic and then populate the appropriate
downstream system, be it a staging area, data warehouse or other application interface.
Hand-coding has been replaced, in many instances, by data integration software that performs
“Helping to overcome the challenges the access, discovery, integration, and delivery of data using an “engine” or “data integration
of implementing data integration as an server” and visual tools to map and execute the desired process. Driven by accelerated
enterprise-wide function, PowerCenter 8 productivity gains and ever-increasing performance, “state of the art” data integration platforms,
offers key new features that can enable such as Informatica® PowerCenter®, handle the vast majority of today’s scenarios quite effectively.
near-universal data access, deliver greater PowerCenter has enjoyed wide acceptance and use by high-volume customers representing
performance and scalability, and signifi- companies and government organizations of all sizes. Based on this use, Informatica has
cantly increase developer productivity. identified performance scenarios where processing data in a source or target database—instead
The push-down logic will allow us to of within the data integration server—can lead to significant performance gains. These scenarios
take further advantage of our database are primarily where data is “co-located” within a common database instance, such as when
processing power.” staging and production reside in a single Oracle relational database management system
(RDBMS) or where a large investment has been made in database hardware and software that
Mark Cothron can provide additional processing power.
Data Integration Architect,
Ace Hardware With these scenarios in mind, Informatica Corporation set out to deliver a solution that
delivers the best of both worlds without incurring undo configuration and management burden;
a solution that best leverages the performance capabilities of its data integration server
and/or the processing power of a relational database interchangeably to optimize the use
of available resources.
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5. White Paper
Informatica has developed a solution that offers IT architects flexibility and ease of performance
optimization through “push down” processing into a relational database using the same
metadata-driven mapping and execution architecture: the PowerCenter Pushdown Optimization
Option now available through Informatica PowerCenter 8. PowerCenter 8 is the latest release of
Informatica’s single, unified enterprise data integration platform for accessing and integrating
data from virtually any business system, in any format, and delivering that data throughout the
enterprise at any speed.
This white paper describes the flexibility, performance optimization, and leverage provided by the
PowerCenter 8 Pushdown Optimization Option. It examines the historical approaches to data
integration and describes how a combined engine- and RDBMS-based approach to data
integration can help the enterprise:
• Cost-effectively scale by using a flexible, adaptable data integration architecture
• Increase developer and team productivity
• Save costs through greater leverage of RDBMS and hardware investments
• Eliminate the need to write custom-coded solutions
• Easily adapt to changes in underlying RDBMS architecture
• Maintain visibility and control of data integration processes
After reading this paper, you will understand how pushdown processing works, the option’s
technical capabilities, and how these capabilities will benefit your environment.
Pushdown Optimization 3

6. Historical Approaches to Data Integration
Historically, there have been four approaches to data integration:
1. Hand-coding. Since the early days of data processing, IT has attempted to solve integration
problems through development of hand-coded programs. These efforts still proliferate in many
mainframe environments, data migration projects, and other scenarios where manual labor is
applied to extract, transform, and move data for the purposes of integration. The high risks,
escalating costs, and lack of compliance associated with hand-coded efforts are well
documented, especially in today’s environment of heightened regulatory oversight and the
THE POWERCENTER PUSHDOWN need for data transparency. Early on, solutions for automation emerged to replace hand-
coding as an alternative cost effective solution.
OPTIMIZATION OPTION
2. Code generators. The first early attempts at increasing IT efficiency led to the development of
Automatically generates and “pushes down” code generation frameworks that leveraged visual tools to map out processes and data flow
but then generated and compiled code as the resultant run-time solution. Code generators
mapping logic were a step-up from hand-coding for developers, but this approach did not gain widespread
adoption as solution requirements and IT architecture complexity arose and the issues around
• Generates database-specific logic that code maintenance, lack of visibility through metadata, and inaccuracies in the generation
represents overall data flow process led to higher rather than lower costs.
3. RDBMS-centric SQL Code generators. An offspring of early generation code generators
• Pushes the execution of the logic into the
emerged from the database vendors themselves. Using the database as an “engine” and SQL
database to perform data transformation as a language, RDBMS vendors delivered offerings that centered on their “flavor” of database
processing programming. Unfortunately, these products exposed the lack of capability of the SQL
language and the database-specific extensions (e.g., PL/SQL, stored procedures) to handle
Provides a single design environment with cross-platform data issues; XML data; the full range of functions such as data quality,
an easy-to-use GUI profiling, and conditional aggregation; and the rest of the complete range of business
logic needed for enterprise data integration. What these products did prove was that for
certain scenarios, the horsepower of the relational database can be effectively used for
• Decouples data transformation logic
data integration.
from the physical execution plan
4. Metadata-driven engines. Informatica pioneered a data integration approach that leveraged
• Controls where processing takes place a data server, or “engine,” powered by open, interpreted metadata as the workhorse for
transformation processing. This approach addressed complexity and met the needs for
• Dynamically creates and executes performance. It also provided the added benefit of re-use and openness due to its meta
database specific transformation language data-centricity. Others have since copied this approach through other types of engines
and languages, but it wasn’t until this metadata-driven, engine-based approach was widely
• Allows you to preview the processing adopted by the market as the preferred method for saving costs and rapidly delivering
on data integration requirements that extraction, transformation, and loading (ETL) was established
you can push to the database as a proven technology. Figure 1 shows this engine-based data integration approach.
Leverages a single, unified data
integration platform
• Applies pushdown optimization to all data
integration processing available on the Data
Integration
PowerCenter platform, including data Server
cleansing, data profiling, and unstructured
Data
and semi-structured data processing Target
Metadata
Data Repository
Sources
Figure 1: Informatica Pioneered the Metadata-driven Engine Approach to Data Integration
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7. White Paper
The Combined Engine- and RDBMS-based
Approach to Data Integration
Using an engine-based approach, Informatica PowerCenter has become the industry performance
leader for enterprise data integration. This leadership has been demonstrated in industry
benchmarks, with continued success in complex, high-volume customer environments and in
head-to-head evaluations with other competitive offerings. Performance capabilities, such as
source-specific partitioning, 64-bit support, threaded architecture, and continued testing
and refinement of the data server, led to organizations to choose PowerCenter to meet their
most strenuous requirements.
In reviewing requirements for the latest version of the product, PowerCenter 8, Informatica
evaluated certain scenarios in which it made sense, while processing transformations in a A SQL code generator-only approach to data
relational database, to limit the movement of data out and subsequent back in the database integration hampers IT’s ability to deliver on
during “data co-resident” periods. It is with these scenarios in mind that Informatica developed the various needs of the enterprise due to
the pushdown optimization capabilities to round out the optimal performance architecture of the limitations of SQL as a comprehensive
its enterprise data integration platform. language for data integration efforts.
Pushdown optimization is enabled through PowerCenter’s metadata-driven architecture, which
decouples the data transformation logic from the physical execution plan. This unique
architecture allows processing to be “pushed down” inside an RDBMS when possible.
PowerCenter 8 is the only software on the market that offers engine-based and RDBMS-based
integration technology in a single, unified platform. This approach ensures a broad spectrum of
data integration initiatives and enables IT to save costs through intelligent use of existing
computing resources. Both approaches are required for organizations looking to develop an
Integration Competency Center where all integration efforts are developed and/or managed by
an expert team faced with varying solution requirements.
Although processing is spread between the data integration engine and the database engine,
with Power Center 8 developers use a single design environment and the same standard set of
PowerCenter tools. For example, a developer can design the data flow using the PowerCenter
Designer, and can design job workflow using the PowerCenter Workflow Manager. Metadata
continues to be generated and managed within PowerCenter. By simply selecting pushdown
optimization in the PowerCenter graphical user interface (GUI), developers can control where
processing takes place, and database-specific transformation language will be dynamically
created and executed as appropriate. Pushdown optimization ensures that existing IT assets
are fully utilized, helping organizations maximize their investment in RDBMS horsepower.
How Pushdown Optimization Works
The Pushdown Optimization Option increases systems performance by providing the flexibility
to push data transformation processing to the most appropriate processing resource, whether
within a source or target database or through the PowerCenter server. This section explains how
pushdown processing works, including two-pass, partial, and full pushdown processing. It
describes platform-specific pushdown processing and outlines the limitations on the types of
transformations that can be pushed to the database.
Pushdown Optimization 5

8. Overview of Pushdown Processing
Separating logical business logic from physical run-time execution, the Pushdown Optimization
Option is coupled with the creation and management of workflows. Workflows tie the execution
of a metadata-based mapping to an actual physical environment. This environment spans not
only the PowerCenter Data Integration Services that may reside on multiple hardware systems,
but also the relational databases where pushdown processing will occur. As shown in Figure 2,
data integration solution architects can configure the pushdown strategy through a simple drop-
down menu in the PowerCenter 8 Workflow Manager.
Figure 2: Data Integration Solution Architects Can Configure the Pushdown Strategy through a Simple Drop-Down
Menu in the Powercenter 8 Workflow Manager
Pushdown optimization can be used to push data transformation logic to the source or target
database. The amount of work data integration solution architects can push to the database
depends on the pushdown optimization configuration, the data transformation logic, and the
mapping configuration.
When pushdown optimization is used, PowerCenter writes one or more SQL statements to the
source or target database based on the data transformation logic. PowerCenter analyzes the
data transformation logic and mapping configuration to determine the data transformation logic
it can push to the database. At run time, PowerCenter executes any SQL statement generated
against the source or target tables, and it processes any data transformation logic within
PowerCenter that it cannot push to the database.
Using pushdown processing can improve performance and optimize available resources. For
example, PowerCenter can push the data transformation logic for the mapping seen in Figure 2
to the source database.
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9. White Paper
Figure 3 shows a mapping that can be pushed to the source database.
Figure 3: Sample Mapping Pushed to Source Database
The mapping contains a filter transformation that filters out all items except for those with an ID
greater than 1005. PowerCenter can push the data transformation logic to the database, and it
generates the following SQL statement to process the data transformation logic:
INSERT INTO ITEMS(ITEM_ID, ITEM_NAME, ITEM_DESC, n_PRICE) SELECT ITEMS.ITEM_ID,
ITEMS.ITEM_NAME, ITEMS.ITEM_DESC, CAST(ITEMS.PRICE AS INTEGER) FROM ITEMS WHERE
(ITEMS.ITEM_ID >1005)
PowerCenter generates an INSERT SELECT statement to obtain and insert the ID, NAME, and
DESCRIPTION columns from the source table, and it filters the data using a WHERE clause.
PowerCenter does not extract any data from the database during this process. Because
PowerCenter does not need to extract and load data, performance improves and resources
are maximized.
Two-Pass Pushdown Processing
Pushdown processing is based on a two-pass scan of the mapping metadata. In the first pass,
PowerCenter starts scanning the mapping objects starting with source definition object, moving
towards the target definition object. When the scan encounters an object containing data
transformation logic that cannot be represented in SQL, the scanning process stops, and all
transformation upstream of this transformation are grouped together with equivalent SQL for
execution inside the source system.
In the second pass, PowerCenter scans in the opposite direction (i.e., from the target definitions
towards the source definitions). When the scan encounters an object containing data
transformation logic that cannot be represented in SQL, the scanning process stops, and all
transformation objects downstream of this transformation are grouped together with equivalent
SQL for execution inside the target system. PowerCenter executes any remaining data
transformation logic.
When you configure PowerCenter to use pushdown optimization, it can process the data
transformation logic using full or partial pushdown optimization.
Pushdown Optimization 7

10. Partial Pushdown Processing
Partial pushdown processing occurs when either the source and target systems are in different
database instances, or only some of the data transformation logic can be represented in SQL.
In such cases, some processing may be pushed into source database, some processing occurs
inside PowerCenter, and some processing may be pushed to the target database.
In Figure 4, all transformations up to and including the aggregate transformation are pushed into
the source database. The Update Strategy transformation is executed within PowerCenter, and
the Expression transformation is executed inside the target database.
Figure 4 shows an example of partial pushdown processing.
Figure 4: Mapping for Partial Pushdown Processing
Full Pushdown Processing
Full pushdown processing occurs when the source and target relational database management
systems are the same instance, and data transformation logic can be completely represented
in SQL. In this case, PowerCenter pushes down the entire mapping processing inside the
database system.
Figure 5 shows example mapping that is fully processed inside the database system.
Figure 5: Mapping for Full Pushdown Processing
In Figure 5, the sources and targets are the same instance, and the data transformation logic
can be pushed to the database. The work of the filtering, joining, and sorting the data is
performed by the database, freeing PowerCenter resources to perform other tasks. However, the
transformation logic is represented in PowerCenter, so it is platform independent and easy to
modify. The visual representation makes it simple to review the flow of logic, and the Pushdown
Optimizer Viewer allows you to preview the SQL statements PowerCenter will execute at run time.
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11. White Paper
Platform-specific Pushdown Optimization
When pushdown optimization is applied to specific database type, the PowerCenter Data
Integration Services generate SQL statements using native database SQL. Standards-based
generation for ODBC is also supported, and PowerCenter generates SQL statements using ANSI
SQL. PowerCenter can generate a greater variety of transformation functions when a specific
database type is used and ensures optimal generation of the fastest execution plan.
Limitations on the Types of Transformations that Can Be
Pushed to the Database
PowerCenter includes a number of transformations that perform functions that cannot be
performed within a database. Figure 6 summarizes the transformation types that can be pushed
to the database.
Transformation Source-side Target-side
Aggregator x
Application Source Qualifier
Custom
Expression x x
External Procedure
Filter x
Java
Joiner x
Lookup x x
Normalizer
Rank
Router
Sequence Generator
Sorter x
Source Qualifier x
Stored Procedure
Target x
Transaction Control
Union x
Update Strategy
XML Generator
XML Parser
XML Source Qualifier
Figure 6: Transformation Types that Can Be Pushed to The Database Using PowerCenter
With the PowerCenter Pushdown Optimization Option, data integration solution architects
canleverage both the database and PowerCenter’s capabilities by pushing some transformation
logic to the database and processing other data transformation logic using PowerCenter.
Pushdown Optimization 9

12. For example, users might have a mapping that filters and sorts data and then outputs the data
to an XML target. To utilize database and PowerCenter capabilities to their fullest potential, data
integration solution architects might push the transformation logic for the Source Qualifier, Filter,
and Sorter transformations to the source database, and then the extract the data to output it to
the XML target.
Figure 7 shows a mapping that uses database capabilities and PowerCenter’s XML capabilities.
Figure 7: Mapping Pushes Transformation Logic to the Source and Writes to an XML Target
Benefits of Pushdown Optimization
The PowerCenter Pushdown Optimization Option offers many benefits, including:
• Increased performance by using optimal resources
• Increased ease-of-use with a metadata-driven architecture that provides metadata lineage
• Increased IT team productivity with simplified debugging and performance tuning
• Reduced risk and enhanced flexibility through database neutrality
Increased Performance
The PowerCenter Pushdown Optimization Option increases systems performance by providing
the flexibility to push data transformation processing to the most appropriate processing
resource, whether within a source or target database or through the PowerCenter server. With
this option, PowerCenter is the only enterprise data integration software on the market that
allows data integration solution architects to choose when pushing down processing offers
a performance advantage.
With the PowerCenter Pushdown Optimization Option, data integration solution architects can
choose to push all or part of the data transformation logic to the source or target database.
Data integration solution architects can select the database they want to push transformation
logic to, and they can choose to push some sessions to the database, while allowing
PowerCenter to process other sessions.
For example, let’s say an IT organization has an Oracle source database with very low user
activity. This organization may choose to push transformation logic for all sessions that run on
this database. In contrast, let’s say an IT organization has a Teradata® source database with
heavy user activity. This organization may choose to allow PowerCenter to process the
transformation logic for sessions that run on this database. In this way, the sessions can
be tuned to work with the load on each database, optimizing performance.
With the PowerCenter Pushdown Optimization Option, data integration solution architects can
also use variables to choose to push different volumes of transformation logic to the source or
target database at different times during the day. For example, partial pushdown optimization
may be used during the peak hours of the day, but full pushdown optimization is used from
midnight until 2 a.m. when activity is low.
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13. White Paper
Increased IT Team Productivity
With its unique metadata-driven architecture, the PowerCenter Pushdown Optimization Option
increases IT team productivity in several ways:
• Ease-of-use on different platforms. PowerCenter’s metadata-driven architecture allows
transformation logic to be easily ported to different platforms. The same transformation logic
can easily be performed on different databases. The same session can be assigned different
database connections, and the same data transformation can be performed without rewriting
code or using different SQL syntax.
• Ease of maintenance. PowerCenter’s metadata-driven architecture makes it easy to track data
for the purposes of error-logging, data cleansing, or data profiling. In addition, metadata for
repository objects is also maintained in the PowerCenter repository. Modifications to repository
objects, import and export metadata can be tracked and a history of changes to repository
objects can be maintained.
• Simplified debugging and performance tuning. When data transformation logic is configured
in PowerCenter, the data transformation logic is represented in a mapping, which provides a
visual representation of the data flow, making it simple to debug and edit the transformation
logic. Because PowerCenter is a single, unified platform, different functions can be applied
to the same metadata without exiting the PowerCenter GUI. For example, a developer might
create a mapping to represent data transformation, and then launch the Data Profiling tool
to assess the status of the data. Later, the developer can open the Workflow Manager to
perform the transformation and launch the Workflow Monitor to track the data as it moves
from the source to the target.
A tool called the Pushdown Optimization Viewer lets data integration solution architects preview
the flow of data to the source or target database. This tool allows data integration solution
architects to preview the data flow, the amount of transformation logic that can be pushed to
the source or target database, and the SQL statements that will be generated at run time as well
as any messages related to pushdown optimization. Figure 8 shows the mapping from Figure 6
displayed in the Pushdown Optimization Viewer.
Figure 8: Pushdown Optimization Viewer
Pushdown Optimization 11

14. Reduced Risk and Enhanced Flexibility
IT organizations typically support several different relational databases. Even when they are
able to standardize on a single RDBMS, changing business conditions—resulting from mergers
and acquisitions, cost cutting, etc.—dictate that they need to be prepared to support multiple
relational databases architectures. IT organizations need to be able to fully leverage the
capabilities of each type of database, and yet stay agile enough to rapidly integrate other
types of databases as the need arises. New regulatory and governance requirements also
dictate increased visibility and control into the business rules applied to data as it moves
throughout the enterprise.
PowerCenter reduce the risk of changing database architectures and enhances flexibility by being
database-neutral. PowerCenter’s metadata-driven architecture extends to mappings that leverage
the Pushdown Optimization Option. The appropriate database-specific logic can be easily
regenerated post-database change, providing flexibility of choice and ease of change. Leveraging
metadata analysis and reporting, rather than having business logic tied to vendor-specific hand-
coded logic, enables effective data governance and transparency.
Conclusion and Next Steps
Today’s challenges to save costs and also drive revenue are pushing organizations to examine
their current data integration infrastructure needs and choose solutions that provide flexibility
and maximum leverage of current assets.
Informatica PowerCenter provides IT organizations with the flexibility to optimize performance
in response to changing runtime demands, peak processing needs, or other dynamic aspects
of the production environment, helping IT organizations achieve cost-effective scalability and
performance. By delivering a combined engine-centric and RDBMS-centric approach to data
integration in a single, unified platform, PowerCenter 8, with its Pushdown Optimization Option,
ensures optimal performance for the broad spectrum of data integration projects and helps IT
save costs through the intelligent use of existing computing resources.
With the Pushdown Optimization Option, PowerCenter 8 can help the enterprise:
• Cost-effectively scale through a flexible, adaptable data integration architecture
• Increase developer and team productivity
• Save costs through greater leverage of RDBMS and hardware investments
• Eliminate the need to write custom coded solutions
• Easily adapt to changes in underlying RDBMS architecture
• Maintain visibility and control of data integration processes
To find out how using a combined engine- and RDBMS-centric approach can benefit your
data integration initiatives, or to find out more about PowerCenter 8, please visit us at
www.informatica.com or call us at (800) 653-3871.
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15. White Paper
Pushdown Optimization 13

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