学完这些课程后，我对创建专业的可视化图表和仪表板充满信心
Shoebur Rahman采购专员，Giz Bangladesh
课程简介
Data lakes promised cheap, flexible storage at scale, but they left engineers fighting broken queries, painful schema changes, and no reliable way to update data. Apache Iceberg fixes that by bringing database-grade reliability to the data lake. In this course, you'll build production-ready Iceberg lakehouses from the ground up: model and partition data for fast queries, migrate existing tables without downtime, evolve schemas and partitions safely with Git-like workflows, and keep everything performant through compaction, snapshot management, and smart write strategies. By the end, you'll be ready to design and operate a modern lakehouse with confidence.
先修要求
课程体系
课程大纲
1
Apache Iceberg Fundamentals
In this chapter, learn how to set up an Apache Iceberg lakehouse and model data with hidden partitioning so your queries skip the files they don't need.
- Course Introduction50 XP
- What does it mean that Apache Iceberg is an Open Table Format?50 XP
- The Open Lakehouse50 XP
- Getting Started: Setting Up Your Apache Iceberg Learning Environment50 XP
- Modeling Data into an Apache Iceberg Table50 XP
- Hidden Partitioning in Apache Iceberg Tables50 XP
- Introduction to Data Modeling Exercise50 XP
- Chapter 1 Summary50 XP
- Chapter 1 review - Question 150 XP
- Chapter 1 review - Question 250 XP
- Chapter 1 review - Question 350 XP
- Chapter 1 review - Question 450 XP
- Chapter 1 review - Question 550 XP
2
Taking Advantage of Apache Iceberg Tables
In this chapter, learn how to migrate existing data into Iceberg and safely evolve schemas and partitions using Git-like workflows such as Write-Audit-Publish, branching, and tagging.
3
Operating and Optimizing Apache Iceberg
In this final chapter, learn how to keep production Iceberg tables fast at scale through smart write strategies, safe concurrency, and maintenance operations like compaction and snapshot expiration.
R
Apache Iceberg: From Zero to Production Data Lakehouse
课程已完成
