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    Realtime Compute for Apache Flink:May 6, 2024

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    Realtime Compute for Apache Flink:May 6, 2024

    Last Updated:Dec 03, 2024

    This topic describes the major updates and bug fixes of the Realtime Compute for Apache Flink version released on May 6, 2024.

    Important

    The version upgrade will be incrementally rolled out across the network by using a canary release strategy. For information about the upgrade schedule, see the latest announcement on the right side of the management console of Realtime Compute for Apache Flink. You can use the new features in this version only after the upgrade is complete for your account. To apply for the upgrade at the earliest opportunity, submit a ticket.

    Overview

    This release includes updates that improve user experience in Realtime Compute for Apache Flink.

    • More efficient development: You can use the code search feature to quickly find SQL drafts that contain a specific table, user-defined function (UDF), or other information in string format, thereby achieving cross-draft management and improving management efficiency. You can also use variables in SQL drafts and update variable values during O&M. This significantly improves efficiency when you run a batch deployment at different times and manage streaming deployments that have the same processing logic.

    • Enhanced O&M: You can configure alert rules in batch. You can also use alert levels and alert scheduling to facilitate O&M in various scenarios.

    Features

    Feature

    Description

    References

    Code search in SQL drafts

    The code search feature is introduced. You can search for and locate a string across all SQL drafts.

    image

    N/A

    Deployment-level variables

    Variables can be configured within a deployment. SQL users can add variables in Data Definition Language (DDL). Java and Python users can add variables in the arguments of the main function.

    Manage keys

    Monitoring and alerting optimization for Application Real-Time Monitoring Service (ARMS)

    • The name and ID of the corresponding Realtime Compute for Apache Flink workspace are displayed on the Prometheus instance details page. image

    • The following operations are supported when you configure alert rules in the ARMS console:

      • Configure alert rules for a group of namespaces and deployments that match specific filtering conditions.

      • Use custom PromQL to create alerts for metrics that are not supported by Realtime Compute for Apache Flink.

      • Configure advanced features, such as alert levels and alert scheduling.

    Limit optimization

    • The limit on the number of UDFs and JAR packages that can be uploaded to a namespace is removed.

    • The maximum number of files and subfolders within a folder is increased to 10,000.

    Limits

    Creation of Simple Log Service and StarRocks catalogs by using GUI

    N/A