Delta Lake Masterclass | Azure Databricks | PySpark | From Zero-To-Expert
Afaque Ahmad
0:00 / 0:00
Delta Lake Masterclass | Azure Databricks | PySpark | From Zero-To-Expert
96 044 просмотра · 1 год назад
Afaque Ahmad
35,7 тыс. подписчиков
96 044 просмотра · 1 год назад
Welcome to this ~6 hour Masterclass on Delta Lake. We'll be covering deep-dive concepts with extensive hands-on labs on Azure Databricks using PySpark. This video will set a very strong base / foundation for Lakehouse concepts or if you're preparing for Data Engineering roles
In this video, you will master:
The Fundamentals: Problems with Data Lake and how Delta Lake solves those problems?
Core Internals: A deep dive into the _delta_log to understand how the magic happens, Optimistic Concurrency Control, Pessimistic Concurrency Control
Key Features: Time Travel, Schema Evolution, and Schema Enforcement / Validation, Shallow Cloning, Deep Cloning, Deletion Vectors, Managed & External Tables
Performance Tuning: Solving the "Small File Problem"
Advanced Optimization: OPTIMIZE, VACUUM, ZORDER, Liquid Clustering
Codes (Delta Lake Masterclass): https://github.com/afaqueahmad7117/da...
Chapters
00:00:00 Introduction & Course Outline
00:02:28 Challenges with Data Lakes
00:04:07 Lack of ACID Support (ACID Explained)
00:04:59 Atomicity
00:08:10 Consistency
00:13:27 Isolation
00:15:28 Durability
00:20:15 Lack of UPDATE, MERGE, DELETE Operations
00:21:59 Data Reliability & Quality Issues
00:24:12 Lab Architecture on Azure
00:27:49 Lab Setup on Azure
00:35:57 DML Operations on Delta Tables (Lab)
00:44:31 Uncovering the Delta Log (_delta_log)
01:06:07 How Delta Lake Computes the Latest State
01:13:47 How Delta Lake's Transaction Log Scales
01:21:48 Pessimistic Concurrency Control
01:27:57 Optimistic Concurrency Control
01:35:32 Time Travel & Versioning
01:48:26 Schema Validation
02:16:40 Schema Evolution
02:47:54 Converting Parquet to Delta
02:52:13 Managed & External Tables
02:58:46 Deletion Vectors (Copy on Write vs. Merge on Read)
03:22:15 Cloning Delta Tables
03:22:37 Shallow Clone Explained
03:25:53 Deep Clone Explained
03:28:09 Shallow Clone Lab
03:48:25 Deep Clone Lab
03:54:28 CTAS (CREATE TABLE AS SELECT) vs. Deep Clone
03:57:43 The Small File Problem
04:01:20 Optimization Techniques
04:01:27 OPTIMIZE Command & Bin Packing Algorithm
04:07:47 OPTIMIZE Lab
04:21:34 Root Causes of the Small File Problem
04:26:03 Manual OPTIMIZE
04:26:40 Optimize Write Explained
04:29:30 Optimize Write Lab
04:33:40 Auto Compaction
04:39:06 VACUUM Command
04:43:05 VACUUM Lab
04:52:17 ZOrdering
05:06:47 ZOrdering Lab
05:20:17 Liquid Clustering
05:33:46 Liquid Clustering Lab
05:40:06 How to Choose Liquid Clustering Columns
05:44:26 Conclusion
My Social Media Handles:
LinkedIn: / afaque-ahmad-5a5847129
YouTube Channel: / @afaqueahmad7117
Playlists:
Interview Preparation: • Data Engineering Interview Preparation
Spark Performance Tuning: • Ultimate Guide To Apache Spark Performance...
Data Engineering Roadmap: • The $500k+ Data Engineering Roadmap: Exact...
How I Mastered Data Modeling: • How I Mastered Data Modeling Interviews
Cracking Interviews @ Apple, Uber, Atlassian, Databricks: • This Is How You Can Crack Data Engineering...
Github: https://github.com/afaqueahmad7117
Spark Performance Tuning Codes: https://github.com/afaqueahmad7117/sp...
#databricks #databrickstutorial #deltalake #dataengineering #bigdata