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Data Engineering with Apache Spark, Delta Lake, and Lakehouse

You're reading from Data Engineering with Apache Spark, Delta Lake, and Lakehouse

Product type Book

Published in Oct 2021

Publisher Packt

ISBN-13 9781801077743

Pages 480 pages

Edition 1st Edition

Languages

Concepts

Data Processing

Author (1):

Manoj Kukreja

Table of Contents (17) Chapters

Preface

1. Section 1: Modern Data Engineering and Tools

2. Chapter 1: The Story of Data Engineering and Analytics

3. Chapter 2: Discovering Storage and Compute Data Lakes

4. Chapter 3: Data Engineering on Microsoft Azure

5. Section 2: Data Pipelines and Stages of Data Engineering

6. Chapter 4: Understanding Data Pipelines

7. Chapter 5: Data Collection Stage – The Bronze Layer

8. Chapter 6: Understanding Delta Lake

9. Chapter 7: Data Curation Stage – The Silver Layer

10. Chapter 8: Data Aggregation Stage – The Gold Layer

11. Section 3: Data Engineering Challenges and Effective Deployment Strategies

12. Chapter 9: Deploying and Monitoring Pipelines in Production

13. Chapter 10: Solving Data Engineering Challenges

14. Chapter 11: Infrastructure Provisioning

15. Chapter 12: Continuous Integration and Deployment (CI/CD) of Data Pipelines

16. Other Books You May Enjoy

Developing CI/CD pipelines

In this section, we will learn how to create and deploy the two CI/CD pipelines we mentioned previously. We will create these CI/CD pipelines using Azure DevOps. Azure DevOps is a collection of developer services for planning, collaborating, developing, and deploying code. Although Azure DevOps supports a variety of developer services, for this exercise, we will primarily focus on Azure Repos and Azure Pipelines.

I know we are eager to proceed with creating the pipelines, but there is a fair bit of preparation required before we can get started. The process starts with creating the Azure DevOps organization, which can be done in a few simple steps. However, to use the free tier of Azure Pipelines, you need to fill in a free parallelism request form for your newly created Azure DevOps organization. The approval process may take 2-3 days to complete.

Creating an Azure DevOps organization

Follow these steps to create an Azure DevOps organization:

...

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Authors (1)

Manoj Kukreja

Manoj Kukreja is a Principal Architect at Northbay Solutions who specializes in creating complex Data Lakes and Data Analytics Pipelines for large-scale organizations such as banks, insurance companies, universities, and US/Canadian government agencies. Previously, he worked for Pythian, a large managed service provider where he was leading the MySQL and MongoDB DBA group and supporting large-scale data infrastructure for enterprises across the globe. With over 25 years of IT experience, he has delivered Data Lake solutions using all major cloud providers including AWS, Azure, GCP, and Alibaba Cloud. On weekends, he trains groups of aspiring Data Engineers and Data Scientists on Hadoop, Spark, Kafka and Data Analytics on AWS and Azure Cloud.

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