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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Metadata components

The metadata model contains components that represent the metadata of the data source.

The metadata model consists of the following components:

Flat Record: A flat record represents a structure that contains columns, unique keys, and primary keys. The structure of a flat record is similar to a database table that contains columns and keys.
A flat record contains attributes that store the following information:

Name of the endpoint metadata object
Type of endpoint metadata object
Related records for the flat record
Primary key for the flat record
Unique keys for the flat record
Indexes for the flat record
Any additional record attributes specific to the data source
Field: A field is a data structure for a single unit of data in a data source.
A field contains attributes that store the following information:

Name of the field
Default value of the field
Precision of the field
Scale of the field
Boolean value that indicates whether the field can contain a null value
Any additional field attributes specific to the data source
Constraints: Constraints represent the primary key and unique keys for a flat record.
The primary key and unique key contain attributes that store the following information:

Name of the key
Native name of the key defined in the native metadata
List of fields that form the key
Index: Index represents a native index that orders the flat records or uniquely identifies a row in the flat record.
An index contains attributes that store the following information:

Name of the index
Native name of the index
Boolean value that indicates whether the index is unique
List of index fields
Index order to retrieve the data

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Cloud Data Integration Connector Toolkit Developer Guide

Cloud Data Integration Connector Toolkit Developer Guide

Metadata components

Metadata components