Posts Tagged ‘KafkaConnect’
[DevoxxUK2024] Processing XML with Kafka Connect by Dale Lane
Dale Lane, a seasoned developer at IBM with a deep focus on event-driven architectures, delivered a compelling session at DevoxxUK2024, unveiling a powerful Kafka Connect plugin designed to streamline XML data processing. With extensive experience in Apache Kafka and Flink, Dale addressed the challenges of integrating XML data into Kafka pipelines, a task often fraught with complexity due to the format’s incompatibility with Kafka’s native data structures like Avro or JSON. His presentation offers practical solutions for developers seeking to bridge external systems with Kafka, transforming XML into more manageable formats or generating XML outputs for legacy systems. Through clear examples, Dale illustrates how this open-source plugin enhances flexibility and efficiency in Kafka Connect pipelines, empowering developers to handle diverse data integration scenarios with ease.
Understanding Kafka Connect Pipelines
Dale begins by demystifying Kafka Connect, a robust framework for moving data between Kafka and external systems. He outlines two primary pipeline types: source pipelines, which import data from external systems into Kafka, and sink pipelines, which export Kafka data to external destinations. A source pipeline typically involves a connector to fetch data, optional transformations to modify or filter it, and a converter to serialize the data into formats like Avro or JSON for Kafka topics. Conversely, a sink pipeline starts with a converter to deserialize Kafka data, followed by transformations and a connector to deliver it to an external system. This foundational explanation sets the stage for understanding where and how XML processing fits into these workflows, ensuring developers grasp the pipeline’s modular structure before diving into specific use cases.
Converting XML for Kafka Integration
A common challenge Dale addresses is integrating XML data from external systems, such as IBM MQ or XML-based web services, into Kafka’s ecosystem, which favors structured formats. He introduces the Kafka Connect plugin, available on GitHub under an Apache license, as a solution to parse XML into structured records early in the pipeline. For instance, using an IBM MQ source connector, the plugin can transform XML documents from a message queue into a generic structured format, allowing subsequent transformations and serialization into JSON or Avro. Dale demonstrates this with a weather API that returns XML strings, showing how the plugin converts these into structured objects for further processing, making them compatible with Kafka tools that struggle with raw XML. This approach significantly enhances the usability of external data within Kafka’s ecosystem.
Generating XML Outputs from Kafka
For scenarios where external systems require XML, Dale showcases the plugin’s ability to convert Kafka’s JSON or Avro messages into XML strings within a sink pipeline. He provides an example using a Kafka topic with JSON messages destined for an IBM MQ system, where the plugin, integrated as part of the sink connector, transforms structured data into XML before delivery. Another case involves an HTTP sink connector posting to an XML-based web service, such as an XML-RPC API. Here, the pipeline deserializes JSON, applies transformations to align with the API’s payload requirements, and uses the plugin to produce an XML string. This flexibility ensures seamless communication with legacy systems, bridging modern Kafka workflows with traditional XML-based infrastructure.
Enhancing Pipelines with Schema Support
Dale emphasizes the plugin’s schema handling capabilities, which add robustness to XML processing. In source pipelines, the plugin can reference an external XSD schema to validate and structure XML data, which is then paired with an Avro converter to submit schemas to a registry, ensuring compatibility with Kafka’s schema-driven ecosystem. In sink pipelines, enabling schema inclusion generates an XSD alongside the XML output, providing a clear description of the data’s structure. Dale illustrates this with a stock price connector, where enabling schema support produces XML events with accompanying XSDs, enhancing interoperability. This feature is particularly valuable for maintaining data integrity across systems, making the plugin a versatile tool for complex integration tasks.