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所在平台: Udemy |
课程主页: https://www.udemy.com/course/learn-databricks-asset-bundles/
课程评论：没有评论
**课程名称：Databricks Asset Bundles 101** **课程概述：** 本课程旨在帮助学员掌握Databricks Asset Bundles，一种现代化的、结构化的部署方法，可用于自动化开发、预生产和生产环境的部署。通过动手实践，学员将学会使用Databricks CLI和bundle框架来构建、验证、部署、运行和清理Databricks资源。Asset Bundles允许学员在一个声明式的、基于YML的项目中定义所有的job、notebook、配置和权限，从而使部署过程可重复、可扩展且受版本控制。 **核心内容：** 1. **创建Bundle项目与配置：** 学员将学习如何创建Bundle项目，并通过`databricks.yml`文件配置多个部署目标。 2. **验证部署：** 利用`databricks bundle validate`命令，学员可以及早发现语法错误和配置缺失，避免部署问题。 3. **部署资源：** 使用`Databricks bundle deploy`命令，学员可以将资源自信地部署到目标工作空间环境。 4. **触发与管理：** 学员将学习如何使用`Databricks bundle run`触发job，并使用`Databricks bundle destroy`安全地清理已部署的资源，以保持环境的整洁。 **适用人群：** 本课程特别适合数据工程师、DevOps工程师和平台团队，他们希望简化和自动化Databricks工作流程。 **学习成果：** 完成本课程后，学员将具备管理Databricks项目完整生命周期（在本地和跨环境）的实用技能。
Unlock the full power of your Databricks workspace by mastering Databricks Asset Bundles-a modern, structured approach for automating deployments across development, staging, and production environments.In this hands-on course, you'll learn how to build, validate, deploy, run, and clean up Databricks resources using the Databricks CLI and bundle framework. Asset Bundles let you define all your jobs, notebooks, configurations, and permissions in one declarative YML-based project, making your deployment process repeatable, scalable, and version-controlled.We begin by creating a bundle project and configuring multiple deployment targets using the databricks.yml file. You'll then use the powerful databricks bundle validate command to catch syntax errors and missing configurations early-before anything is deployed. Once validated, you'll use Databricks bundle deploy to push your resources to the desired workspace environment with confidence.You'll also learn how to trigger jobs using Databricks bundle run and, when needed, how to clean up safely with Databricks bundle destroy to remove deployed resources and keep your environments organized.This course is ideal for data engineers, DevOps engineers, and platform teams looking to streamline and automate their Databricks workflows. By the end, you'll be equipped with practical, real-world skills to manage the full lifecycle of Databricks projects-locally and across environments.
