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离线开发平台-HTTP数据同步到Doris数仓能力演示
Sou Hu Cai Jing· 2025-08-26 11:44
Group 1 - AllData big data product serves as a defined data middle platform, providing a full-link digital solution with a data platform as the foundation, a data middle platform as a bridge, a machine learning platform as the middle framework, and large model applications as upstream products [1] Group 2 - The offline development platform is built on the open-source project DolphinScheduler, which is a powerful distributed task scheduling platform suitable for offline data processing scenarios [2] - It supports complex workflow orchestration, task monitoring, and alerting [2] Group 3 - The platform offers a visual interface that allows users to create complex workflow tasks easily through drag-and-drop operations, reducing the coding requirement and improving work efficiency [3] - It supports various task types such as Shell, SQL, and Python, catering to different data processing needs [4] - Users can flexibly set dependencies between tasks to ensure they execute in the desired order, effectively managing complex data processing workflows [5] Group 4 - The platform provides unified management and allocation of computing resources, optimizing resource utilization and preventing waste [6] - Real-time monitoring of task execution status, including progress, runtime, and resource usage, is available [7] - The system can issue alerts when tasks encounter exceptions, enabling quick responses from operations personnel to maintain stability and reliability in data processing [8] Group 5 - The platform supports multi-tenant mode, allowing different tenants to independently develop and manage tasks on the same platform, ensuring resource isolation and permission control [9] Group 6 - Key features of the offline development platform include distributed scalable architecture, visual DAG workflow orchestration, multi-tenant and permission management, diverse task types, high reliability, fault tolerance mechanisms, flexible scheduling strategies, task status monitoring, data source integration capabilities, version control, and ecosystem compatibility [12] Group 7 - The environment preparation requires a Linux or macOS operating system, installation of Java (JDK 1.8 or higher), Maven (3.6 or higher), and a supported database like MySQL or PostgreSQL [13][14]