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所在平台: Udemy |
课程主页: https://www.udemy.com/course/microsoft-azure-databricks-administration-etl-workflow/
课程评论：没有评论
课程名称：Microsoft Azure Databricks Administration - ETL Workflow 课程概述：本课程将带您学习基于Spark的Azure Databricks。随着数据每天的迅猛增长，无论是CSV、文本、JSON或其他格式的数据，通过各种物联网系统、手机、互联网和其他设备，数据消费变得极为便捷。Azure Databricks提供最新版本的Apache Spark，并允许您与开源库无缝集成。在一个完全托管的Apache Spark环境中快速启动集群，享受Azure的全球规模和可用性。本课程为期望在数据领域（尤其是Azure Databricks管理方面）开始职业生涯的学员量身定制，即使您没有Databricks和Azure的先前知识，也可以轻松参与。 课程内容亮点： 1. 了解什么是Databricks； 2. Databricks的组成部分： a. 笔记本 b. 集群 c. 池 d. 密钥 e. Databricks CLI f. 集群策略 3. 通过Terraform自动化整个管理活动； 4. 将Azure Blob Storage与Databricks挂载； 5. 自动化Azure Blob Storage的挂载； 6. 在Azure Blob存储中加载CSV数据； 7. 使用Scala和SQL查询转换数据； 8. 将转换后的数据加载到Azure Blob存储； 9. 了解Databricks表和文件系统； 10. 通过Log4j和Spark监听库配置Azure Databricks日志； 11. 使用Azure DevOps配置CI/CD； 12. 进行Git提供者集成； 13. 通过Databricks Jobs配置笔记本部署。 课程目的：本课程旨在帮助学员准备Azure Databricks认证助理平台管理员考试，以及通过课程结束时的测验来为面试和认证做准备。
In this Course, you will learn about spark based Azure Databricks, with more and more data growing daily take it any source be it in csv, text , JSON or any other format the consumption of data has been really easy via different IoT system. mobile phones internet and many other devices.Azure Databricks provides the latest versions of Apache Spark and allows you to seamlessly integrate with open source libraries. Spin up clusters and build quickly in a fully managed Apache Spark environment with the global scale and availability of Azure.Here is the 30,000 ft. overview of the agenda of the course, what will you learn and how you can utilise the learning into a real world data engineering scenario, this course is tailor made for some one who is coming from a background with no prior knowledge of Databricks and Azure and would like to start off their career in data world, specially around administering Azure Databricks.Prepare for Azure Databricks Certified Associate Platform Administrator by solving practise questions.Prepare for interviews and certification by solving quizzes at the end of sessions.1. What is Databricks?2. Databricks Components:a. Notebookb. Clustersc. Poold. Secretse. Databricks CLIf. Cluster Policy3. Automate the entire administration activity via Terraform.4. Mount Azure Blob Storage with Databricks.5. Automate mount Azure Blob Storage with Databricks.6. Load CSV data in Azure blob storage7. Transform data using Scala and SQL queries.8. Load the transform data into Azure blob storage.9. Understand about Databricks tables and filessystem.10. Configure Azure Databricks logging via Log4j and spark listener library via log analytics workspace.11. Configure CI CD using Azure DevOps.12. Git provider intergration.13. Configure notebook deployment via Databricks Jobs.
