Preface
Introduction to Informatica Connector Toolkit
- Supported features
- Informatica Connector perspective
  - Connector Navigator
  - Connector Progress
Before you begin
- Download the welcome kit
- Download and install Eclipse IDE
- Download and install the Informatica Connector Toolkit
- Download OpenJDK and configure environment variables
- Log in to Informatica Intelligent Data Management Cloud
Develop a connector for Cloud Data Integration
- Create a new connector project
- Phase 1: Establish a connection
  - Create a connection
  - Test a connection
- Phase 2: Define the metadata
- Phase 3: Configure the runtime behavior
- Phase 4: Generate the connector package
  - Naming Convention
- Phase 5: Generate and run the test scenarios
  - Generate the test scenarios
    - Configure parameters in test suite file
    - Regenerate a test case
  - Run the test scenarios
    - Unit tests and sanity tests
    - Integration tests
Develop a connector for Data Loader
- Create a new connector project
- Phase 1: Establish a connection
  - Create a connection
  - Test a connection
- Phase 2: Define the metadata
- Phase 3: Configure the runtime behavior
- Phase 4: Generate the connector package
  - Naming Convention-DLT
- Phase 5: Generate and run the test scenarios
  - Generate the test scenarios
    - Configure parameters in test suite file
    - Regenerate a test case
  - Run the test scenarios
    - Unit tests and sanity tests
    - Integration tests
Import a connector
Connection attributes
- Connection attribute properties
Type system
- Native types and semantic categories
  - Native Type Properties
- Cloud Data Integration types
Connector metadata
- Metadata components
- Import dialog box settings
Partitioning capability
- Automatic partitioning
- Static partitioning
Pushdown capability
- Pushdown optimization execution flow
- Classes and methods for pushdown capabilities
Mappings in advanced mode
- Project, classes, and methods
Manual changes to Informatica Connector Toolkit source code
- Code changes for connection pooling
  - Connection Pooling through API
- Code changes for custom query
- Code changes for object path override
- Code changes for pushdown capability
- Code changes for SQL transformation
- Code changes for stored procedures
Runtime behavior
- Runtime Java functions
Connector example: MySQL_Cloud
- MySQL_Cloud Connector requirements
- Building the sample connector
- MySQL_Cloud Connector components
Version control integration
- Git version control integration
  - Prerequisites
  - Build a connector in Git repository
- Perforce version control integration
Appendix A: Metadata models
- Metadata model components
- Metadata patterns
- Features of type A metadata template
Appendix B: ASO model
- ASO model components
- ASO projections
Appendix C: Connector project migration
- Migrate connector project from Windows platform to other platforms
Appendix D: Frequently used generic APIs in Informatica Connector Toolkit
Appendix E: Frequently asked questions

Cloud Data Integration Connector Toolkit Developer Guide

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Pushdown optimization execution flow

You can use the Informatica Connector Toolkit to configure full pushdown using the native database connection to push the entire mapping logic to target databases for execution.

The Informatica Connector Toolkit performs pushdown optimization with the following execution flow:

During runtime, the source and the target connectors are invoked to validate if the current transformation is supported. You must declare the support for pushdown to the source in

adapter.contribution.plugin.xml

file.

When source pushdown support is enabled, the transformation might get pushed to the source database instead of the target database. An additional flag is marked in the intermediate result to indicate that source handles the transformations.

Additional validation callback configured in the target connector checks if the target database can support the current transformation. If the target connector returns true, the flag in the intermediate result is updated to indicate that target performs full pushdown provided the forward data flow reaches the target.

If the data flow does not reach the target and the additional flag is marked in the intermediate result in Step 2, the source database will handle the transformations.

You cannot push partial mapping logic to the target database using source pushdown.

If the forward data flow reaches the target, the mapping is updated to replace the source with a placeholder source and the target transformation contains a new data object with a reference to the source object. If the data flow does not reach target, the mapping runs without pushdown. You cannot partially push down transformation logic with full pushdown.

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Cloud Data Integration Connector Toolkit Developer Guide

Cloud Data Integration Connector Toolkit Developer Guide

Pushdown optimization execution flow

Pushdown optimization execution flow