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Databricks Streaming and Delta Live Tables

This course provides a comprehensive understanding of Spark Structured Streaming and Delta Lake, including computation models, configuration for streaming read, and maintaining data quality in a streaming environment.

Note: This course is part of the 'Advanced Data Engineering with Databricks' course series.


Languages Available: English | 日本語 | Português BR | 한국어

Skill Level
Professional
Duration
4h
Prerequisites

The content was developed for participants with these skills/knowledge/abilities:  

  • Ability to perform basic code development tasks using the Databricks Data Engineering and Data Science workspace (create clusters, run code in notebooks, use basic notebook operations, import repos from git, etc.)
  • Intermediate programming experience with PySpark
  • Extract data from a variety of file formats and data sources
  • Apply a number of common transformations to clean data
  • Reshape and manipulate complex data using advanced built-in functions
  • Intermediate programming experience with Delta Lake (create tables, perform complete and incremental updates, compact files, restore previous versions, etc.)
  • Beginner experience configuring and scheduling data pipelines using the Delta Live Tables (DLT) UI 
  • Beginner experience defining Delta Live Tables pipelines using PySpark
  • Ingest and process data using Auto Loader and PySpark syntax
  • Process Change Data Capture feeds with APPLY CHANGES INTO syntax
  • Review pipeline event logs and results to troubleshoot DLT syntax

Outline

Introduction to Streaming

* Streaming Data Concepts

* Introduction to Structured Streaming

* Reading from a Streaming Query

* Streaming from Delta Lake

* Streaming Query Lab


Aggregations, Time Windows, Watermarks

* Aggregations, Time Windows, Watermarks

* Event Time + Aggregatios over Time Windows

* Stream Aggregation Lab

* Windowed Aggregation with Watermark


Streaming ETL Patterns with DLT

* Data Ingestion Patterns

* Auto Load to Bronze

* Stream from Multiplex Bronze

* Quality Enforcement Patterns

* Quality Enforcement

* Streaming ETL Lab

Upcoming Public Classes

Date
Time
Language
Price
Jun 02
09 AM - 01 PM (Europe/London)
English
$750.00
Jun 03
09 AM - 01 PM (Asia/Kolkata)
English
$750.00
Jun 06
09 AM - 01 PM (America/New_York)
English
$750.00

Public Class Registration

If your company has purchased success credits or has a learning subscription, please fill out the Training Request form. Otherwise, you can register below.

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Upcoming Public Classes

Data Engineer

Automated Deployment with Databricks Asset Bundles

This course provides a comprehensive review of DevOps principles and their application to Databricks projects. It begins with an overview of core DevOps, DataOps, continuous integration (CI), continuous deployment (CD), and testing, and explores how these principles can be applied to data engineering pipelines.

The course then focuses on continuous deployment within the CI/CD process, examining tools like the Databricks REST API, SDK, and CLI for project deployment. You will learn about Databricks Asset Bundles (DABs) and how they fit into the CI/CD process. You’ll dive into their key components, folder structure, and how they streamline deployment across various target environments in Databricks. You will also learn how to add variables, modify, validate, deploy, and execute Databricks Asset Bundles for multiple environments with different configurations using the Databricks CLI.

Finally, the course introduces Visual Studio Code as an Interactive Development Environment (IDE) for building, testing, and deploying Databricks Asset Bundles locally, optimizing your development process. The course concludes with an introduction to automating deployment pipelines using GitHub Actions to enhance the CI/CD workflow with Databricks Asset Bundles.

By the end of this course, you will be equipped to automate Databricks project deployments with Databricks Asset Bundles, improving efficiency through DevOps practices.

Languages Available: English | 日本語 | Português BR | 한국어

Paid
4h
Lab
instructor-led
Professional

Questions?

If you have any questions, please refer to our Frequently Asked Questions page.