Understanding the Kafka Connect Connector API

Kafka Connect is a framework for streaming data between Apache Kafka and other systems. At its core, Kafka Connect relies on Connectors, which are reusable components that define how data flows into or out of Kafka. Understanding the Connector API is crucial for building custom integrations or customizing existing ones in real-time data engineering pipelines.

What is a Connector?

A Connector is the fundamental building block of Kafka Connect. It manages the overall lifecycle of data movement between Kafka and another system. Connectors are responsible for creating and managing Tasks, which perform the actual data transfer.

Connectors are the high-level orchestrators of data flow.

Connectors define the source or sink for data, manage configuration, and delegate the actual data transfer to Tasks. They are responsible for creating and managing these Tasks.

A Connector is an interface that defines the overall data flow. It acts as a manager, responsible for creating and managing one or more Tasks. Each Task is designed to handle a specific partition of data. The Connector itself doesn't move data; it orchestrates the work of the Tasks. This separation allows for scalability and fault tolerance, as Tasks can be distributed and restarted independently.

Types of Connectors

There are two primary types of Connectors:

Connector Type	Purpose	Key Responsibilities
Source Connector	Ingests data from external systems into Kafka.	Reads data from a source (e.g., database, file system, API), converts it into Kafka records, and publishes it to Kafka topics.
Sink Connector	Exports data from Kafka to external systems.	Consumes data from Kafka topics, transforms it if necessary, and writes it to a destination (e.g., database, data warehouse, search index).

The Connector API: Key Interfaces

The Kafka Connect API provides a set of Java interfaces that developers implement to create custom connectors. The most important interfaces are:

Implement `Connector` and `Task` interfaces to build custom connectors.

The Connector interface defines the high-level behavior, while the Task interface handles the actual data transfer. You'll also interact with SourceRecord or SinkRecord for data representation.

To build a custom connector, you typically implement the org.apache.kafka.connect.connector.Connector interface. This interface requires methods like version(), start(Map<String, String> props), taskClass(), taskConfigs(int maxTasks), stop(), and config(). For the actual data processing, you'll implement either org.apache.kafka.connect.source.SourceTask (for source connectors) or org.apache.kafka.connect.sink.SinkTask (for sink connectors). These task implementations will use SourceRecord or SinkRecord objects to represent the data being moved.

Connector Configuration

Connectors are configured through a set of key-value pairs. These configurations define how the connector operates, including connection details to external systems, Kafka topic names, data transformation logic, and error handling strategies. The

code

ConfigDef

class is used to define the schema and validation rules for these configurations.

Well-defined configurations are key to robust and reusable Kafka Connectors.

Tasks and Parallelism

Connectors can create multiple Tasks to achieve parallelism. For source connectors, each task might read from a different partition of the source system. For sink connectors, tasks consume from different partitions of Kafka topics. This allows Kafka Connect to scale data ingestion and egress efficiently.

Loading diagram...

Key Concepts for API Implementation

When developing custom connectors, pay close attention to:

code
ConfigDef
: Defining and validating connector configurations.
code
Connector
interface: Managing the lifecycle and task creation.
code
SourceTask
/
code
SinkTask
: Implementing the core data processing logic.
code
SourceRecord
/
code
SinkRecord
: Representing data records with Kafka topic and partition information.
Error Handling: Strategies for dealing with data processing failures.

What are the two main types of Kafka Connectors?

Source Connectors (ingest data into Kafka) and Sink Connectors (export data from Kafka).

Which interface is responsible for creating and managing Tasks?

The Connector interface.

What Java objects represent data records for source and sink connectors, respectively?

SourceRecord for source connectors and SinkRecord for sink connectors.

Learning Resources

Kafka Connect API Documentation(documentation)

The official Apache Kafka documentation for Kafka Connect, covering its architecture and APIs.

Kafka Connect: The Missing Piece of Your Data Pipeline(blog)

An introductory blog post explaining the purpose and benefits of Kafka Connect for data integration.

Building Custom Kafka Connectors(blog)

A detailed guide on the process and considerations for developing your own Kafka Connectors.

Kafka Connect Source Connector Tutorial(tutorial)

A step-by-step tutorial on creating a simple Kafka Connect source connector.

Kafka Connect Sink Connector Tutorial(tutorial)

A step-by-step tutorial on creating a simple Kafka Connect sink connector.

Kafka Connect: A Deep Dive into the Connector API(video)

A video presentation that delves into the Kafka Connect API and its practical application.

Kafka Connect: Architecture and Design(video)

Explains the underlying architecture of Kafka Connect, including the roles of Connectors and Tasks.

Kafka Connect Configuration API(documentation)

Javadoc for the Kafka Connect API, focusing on configuration interfaces like `ConfigDef`.

Understanding Kafka Connect Data Transformation(blog)

Discusses how to use transformations within Kafka Connect to modify data as it flows.

Kafka Connect Best Practices(blog)

Provides practical advice and best practices for deploying and managing Kafka Connect connectors.