This topic describes the release notes for Realtime Compute for Apache Flink and provides links to relevant references. The release notes provide the major updates and bug fixes in Realtime Compute for Apache Flink in the version that was released on December 7, 2023.
A canary release will be gradually complete on the entire network for the upgrade. To learn about the upgrade plan, view the most recent announcement on the right side of the homepage of the Realtime Compute for Apache Flink console. If you cannot use new features in Realtime Compute for Apache Flink, the new version is still unavailable for your account. If you want to perform an upgrade at the earliest opportunity, submit a ticket to apply for an upgrade. To learn about the upgrade plan, view the most recent announcement on the right side of the homepage of the Realtime Compute for Apache Flink console.
Overview
Realtime Compute for Apache Flink was upgraded on December 7, 2023. This version includes new features, such as queue management, Workflows (public preview), and scripts. You can build a complete streaming lakehouse to perform batch and streaming storage and computing based on the capabilities of the Apache Paimon connector.
Features
Feature | Description | References |
Queue management | The queue management feature helps you allocate and manage resources. You can configure tasks that have different workloads to different queues to isolate and manage the resources. This improves the resource utilization during task running and ensures sufficient resources for deployments that have high priorities. | |
Workflows (public preview) | The Workflows feature helps schedule batch deployments on a graphical user interface (GUI) in an efficient manner. You can use the Workflows feature to build a data warehouse and implement integration of development, scheduling, deployment, and O&M in the Realtime Compute for Apache Flink console. | |
Scripts | A script can contain the DDL, DQL, and DML statements. You can use scripts to create and manage catalogs and tables, perform data queries, manage data, and manage Apache Paimon tables. | None |