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Optimizing Databricks Workloads

You're reading from Optimizing Databricks Workloads

Product type Book

Published in Dec 2021

Publisher Packt

ISBN-13 9781801819077

Pages 230 pages

Edition 1st Edition

Languages

Concepts

Data Processing

Authors (3):

Anirudh Kala

Anshul Bhatnagar

Sarthak Sarbahi

View More author details

Table of Contents (13) Chapters

Preface

Section 1: Introduction to Azure Databricks

Chapter 1: Discovering Databricks

Chapter 2: Batch and Real-Time Processing in Databricks

Chapter 3: Learning about Machine Learning and Graph Processing in Databricks

Section 2: Optimization Techniques

Chapter 4: Managing Spark Clusters

Chapter 5: Big Data Analytics

Chapter 6: Databricks Delta Lake

Chapter 7: Spark Core

Section 3: Real-World Scenarios

Chapter 8: Case Studies

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Technical requirements

To follow the hands-on tutorials in the chapter, the following is required:

An Azure subscription
Azure Databricks
Azure Databricks notebooks and a Spark cluster
Access to this book's GitHub repository at https://github.com/PacktPublishing/Optimizing-Databricks-Workload/tree/main/Chapter06

To start, let's spin up a Spark cluster with the following configurations:

Cluster Name: packt-cluster
Cluster Mode: Standard
Databricks Runtime Version: 8.3 (includes Apache Spark 3.1.1, Scala 2.12)
Autoscaling: Disabled
Automatic Termination: After 30 minutes of inactivity
Worker Type: Standard_DS3_v2
Number of workers: 1
Spot instances: Disabled
Driver Type: Same as the worker

Now, create a new notebook and attach it to the newly created cluster to get started!

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Authors (3)

Anirudh Kala

Anirudh Kala is an expert in machine learning techniques, artificial intelligence, and natural language processing. He has helped multiple organizations to run their large-scale data warehouses with quantitative research, natural language generation, data science exploration, and big data implementation. He has worked in every aspect of data analytics using the Azure data platform. Currently, he works as the director of Celebal Technologies, a data science boutique firm dedicated to large-scale analytics. Anirudh holds a computer engineering degree from the University of Rajasthan and his work history features the likes of IBM and ZS Associates.

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Anshul Bhatnagar

Anshul Bhatnagar is an experienced, hands-on data architect involved in the architecture, design, and implementation of data platform architectures, and distributed systems. He has worked in the IT industry since 2015 in a range of roles such as Hadoop/Spark developer, data engineer, and data architect. He has also worked in many other sectors including energy, media, telecoms, and e-commerce. He is currently working for a data and AI boutique company, Celebal Technologies, in India. He is always keen to hear about new ideas and technologies in the areas of big data and AI, so look him up on LinkedIn to ask questions or just to say hi.

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Sarthak Sarbahi

Sarthak Sarbahi is a certified data engineer and analyst with a wide technical breadth and a deep understanding of Databricks. His background has led him to a variety of cloud data services with an eye toward data warehousing, big data analytics, robust data engineering, data science, and business intelligence. Sarthak graduated with a degree in mechanical engineering.

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