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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ASO projections

An ASO projection is a sequence of operations that you perform on data when you read data from a data source or write data to a data source.

Use the Informatica Connector Toolkit to define a basic ASO projection model or an advanced projection model according to your requirements. The basic ASO projection model provides a simple view of the advanced projection model. The Informatica Connector Toolkit uses the BasicProjectionView interface to provide a simple and basic model to the connector developer. Use the get methods in the BasicProjectionView interface to get information on native metadata object, platform types, scale, precision, and conditions like filter and join.

To define the advanced ASO projection model, define the following projection operation interfaces as required.

Sink operation: There are two types of sink operations: native sink operation and platform sink operation. The native sink operation gets data from the platform operation when you write to a data source. The platform sink operation gets data from the native source operation when you read from a data source.
Source operation: There are two types of source operations: native source operation and platform source operation. The native source operation inputs the native data to the platform sink operation in a read projection operation. The platform source operation inputs the platform data to the native sink operation in a write projection operation.
Join operation: Use the join operation to join data from two related sources or from the same source.
Filter operation: Use the filter operation to filter data based on one or more conditions.
Projection operation: Use the projection operation to select a subset of attributes to rename or to drop fields.

For more information about interfaces that define the ASO projection model, see the

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Cloud Data Integration Connector Toolkit Developer Guide

Cloud Data Integration Connector Toolkit Developer Guide

ASO projections

ASO projections