BIBLIO is the largest independent book marketplace in the world, with over 100 million books.

Skip to content

Data Engineering with Databricks Cookbook: Build effective data and AI solutions using Apache Spark, Databricks, and Delta Lake

Data Engineering with Databricks Cookbook: Build effective data and AI solutions using Apache Spark, Databricks, and Delta Lake

Data Engineering with Databricks Cookbook: Build effective data and AI solutions
Stock photo: cover may vary

Data Engineering with Databricks Cookbook: Build effective data and AI solutions using Apache Spark, Databricks, and Delta Lake Papeback -

by Pulkit Chadha

Add to wish list
  • New
New

Description

. Papeback. New.
Ask the seller a question Add to wish list
A$150.00
A$5.87 Delivery within USA
Standard delivery: 9 to 14 days
More delivery options
Ships from Cold Books (New York, United States)
The BIBLIO Guarantee

Details

  • Title Data Engineering with Databricks Cookbook: Build effective data and AI solutions using Apache Spark, Databricks, and Delta Lake
  • Author Pulkit Chadha
  • Binding Papeback
  • Condition New
  • Pages 438
  • Volumes 1
  • Language ENG
  • Publisher Packt Publishing
  • Publication date
  • Bookseller's Inventory # 6400848237
  • ISBN 9781837633357 / 1837633355
  • Weight 1.65 lbs (0.75 kg)
  • Dimensions 9.25 x 7.5 x 0.89 in (23.50 x 19.05 x 2.26 cm)
  • Category Computers - Data Base Management
  • Quantity available 4

About Cold Books New York, United States

Biblio member since 2012

Terms of Sale: 30 day return guarantee, with full refund including shipping costs for up to 30 days after delivery if an item arrives misdescribed or damaged.

Browse books from Cold Books

Reader reviews for Data Engineering with Databricks Cookbook: Build effective data and AI solutions using Apache Spark, Databricks, and Delta Lake

Write a review for this book

There are no reviews for this book yet. Be the first to write a review!

Your review will be anonymous unless you login or create an account first.

Overall rating
Remember: You’re rating the book as a work, not the seller or the condition of the specific copy you purchased!

Important Terms and Guidelines

  • Please focus on the book’s content and context. Also, add any personal comments as to how you enjoyed the book. Substantiate your likes and dislikes. You may make comparisons to other books.
  • Reviews must be at least 140 characters in length.
  • Please do not reveal critical plot elements.
  • This is not a help line. Contact customer support if you need help.
Your review must not include:
  • Obscenities, discriminatory language, or other insulting language not suitable for public domain
  • Advertisements, “spam” content, or references to other products, offers or websites.
  • Email addresses, URLs, phone numbers, physical addresses or other contact information.
  • Overly critical comments about other reviews or reviewers
  • Time-sensitive material (i.e. promotional tours, seminars, lectures, etc.)
  • Availability, price, or alternative ordering/shipping information

From the publisher

Work through 70 recipes for implementing reliable data pipelines with Apache Spark, optimally store and process structured and unstructured data in Delta Lake, and use Databricks to orchestrate and govern your data

Key Features:

- Learn data ingestion, data transformation, and data management techniques using Apache Spark and Delta Lake

- Gain practical guidance on using Delta Lake tables and orchestrating data pipelines

- Implement reliable DataOps and DevOps practices, and enforce data governance policies on Databricks

- Purchase of the print or Kindle book includes a free PDF eBook

Book Description:

Written by a Senior Solutions Architect at Databricks, Data Engineering with Databricks Cookbook will show you how to effectively use Apache Spark, Delta Lake, and Databricks for data engineering, starting with comprehensive introduction to data ingestion and loading with Apache Spark.

What makes this book unique is its recipe-based approach, which will help you put your knowledge to use straight away and tackle common problems. You'll be introduced to various data manipulation and data transformation solutions that can be applied to data, find out how to manage and optimize Delta tables, and get to grips with ingesting and processing streaming data. The book will also show you how to improve the performance problems of Apache Spark apps and Delta Lake. Advanced recipes later in the book will teach you how to use Databricks to implement DataOps and DevOps practices, as well as how to orchestrate and schedule data pipelines using Databricks Workflows. You'll also go through the full process of setup and configuration of the Unity Catalog for data governance.

By the end of this book, you'll be well-versed in building reliable and scalable data pipelines using modern data engineering technologies.

What You Will Learn:

- Perform data loading, ingestion, and processing with Apache Spark

- Discover data transformation techniques and custom user-defined functions (UDFs) in Apache Spark

- Manage and optimize Delta tables with Apache Spark and Delta Lake APIs

- Use Spark Structured Streaming for real-time data processing

- Optimize Apache Spark application and Delta table query performance

- Implement DataOps and DevOps practices on Databricks

- Orchestrate data pipelines with Delta Live Tables and Databricks Workflows

- Implement data governance policies with Unity Catalog

Who this book is for:

This book is for data engineers, data scientists, and data practitioners who want to learn how to build efficient and scalable data pipelines using Apache Spark, Delta Lake, and Databricks. To get the most out of this book, you should have basic knowledge of data architecture, SQL, and Python programming.

Table of Contents

- Data Ingestion and Data Extraction with Apache Spark

- Data Transformation and Data Manipulation with Apache Spark

- Data Management with Delta Lake

- Ingesting Streaming Data

- Processing Streaming Data

- Performance Tuning with Apache Spark

- Performance Tuning in Delta Lake

- Orchestration and Scheduling Data Pipeline with Databricks Workflows

- Building Data Pipelines with Delta Live Tables

- Data Governance with Unity Catalog

- Implementing DataOps and DevOps on Databricks

Please wait a moment while we load the requested page.

tracking-