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Amazon’s Managed Service for Apache Flink has recently embraced Apache Flink version 1.18, bringing a host of new features and enhancements for users. This fully managed, serverless platform facilitates the operation of Apache Flink applications, ensuring developers can focus on building without worrying about infrastructure management.
Apache Flink is renowned as an open-source distributed processing engine, excelling in both stream and batch processing. It offers robust support for stateful processing and event time semantics, accommodating multiple programming languages including Java, Python, Scala, and SQL, and allowing seamless integration of various APIs within the same application.
New Features in Apache Flink 1.18.1
The latest version, 1.18.1, introduces a range of new capabilities, especially through several new open-source connectors. For instance, a dedicated OpenSearch connector is now available, enabling applications to write data directly into OpenSearch without needing to rely on Elasticsearch compatibility mode. This connector supports both SQL and Table APIs and works with the DataStream API, providing at-least-once guarantees and the option for exactly-once semantics through deterministic IDs.
Another exciting addition is the Amazon DynamoDB connector, which allows developers to efficiently write data into DynamoDB using a non-blocking approach via the Flink AsyncSink. Supporting both SQL and Table APIs, as well as the DataStream API for Java, it features batch writing to optimize throughput and a PARTITIONED BY clause for improved client-side deduplication.
The MongoDB connector is also noteworthy, offering both source and sink capabilities for SQL, Table APIs, and the DataStream API. This new connector has replaced the older version provided by MongoDB, enhancing compatibility and functionality with the latest Flink infrastructure.
Moreover, with the introduction of connector versioning starting from Flink 1.17, developers need to ensure they specify the correct artifact version for their dependencies. For example, the Kafka connector version 3.1.0 is compatible with Apache Flink 1.18 and can be included in projects accordingly.
SQL Enhancements
As for SQL enhancements, users can now provide hints to join queries, optimizing query plans in streaming applications. The improvements in lookup joins allow for better performance through features like in-memory caching and asynchronous lookups, which facilitate non-blocking database requests.
Additional Resources
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In summary, the updates in Apache Flink 1.18 provide substantial advancements for developers using Amazon’s Managed Service for Apache Flink, enhancing the overall experience and capabilities of the platform.
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