The Realtime Compute for Apache Flink development platform provides multiple features for Realtime Compute Flink SQL jobs, including data storage management, job development, job debugging, job administration, monitoring and alerting, and job optimization.

Flink SQL Developer Guide consists of the following topics:
  • Data storage

    You can manage upstream and downstream data storage systems, such as ApsaraDB RDS, DataHub, and Tablestore, for jobs on the Realtime Compute for Apache Flink development platform. After you register resources from these systems with Realtime Compute for Apache Flink, you can preview or sample their related data, or obtain the data definition language (DDL) statements that are automatically generated to reference these resources. For more information about data storage, see Overview.

    Note For more information about how to add the IP addresses of Realtime Compute for Apache Flink to a whitelist of an upstream or downstream storage system, see Configure a whitelist for accessing storage resources.
  • Job development

    This topic describes how to develop, publish, and start a Flink SQL job. For more information, see Develop a job, Publish a job, and Start a job.

  • Job debugging

    This topic describes how to debug Flink SQL jobs. Online debugging and local debugging are supported. For more information, see Online debugging.

  • Job administration

    This topic describes how to view the administration information of a Realtime Compute for Apache Flink job, such as the running information, curve charts, and failover. For more information, see Running information, Curve charts, and Failover.

  • Monitoring and alerting

    This topic describes how to create and activate alert rules. For more information, see Monitoring and alerts.

  • Job optimization

    This topic describes how to optimize Flink SQL jobs, such as skills for optimizing Flink SQL code, automatic configuration optimization, performance optimization by auto scaling, and performance optimization by manual configuration. For more information, see Skills for optimizing the Flink SQL code,Performance optimization by using auto scaling, and Performance optimization by manual configuration.

  • Flink SQL

    This topic describes the syntax of Flink SQL. For more information, see Flink SQL overview.