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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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Learning to differentiate Pandas and Koalas

The Pandas project is a very popular data transformation library in Python that is widely used for data analytics and data science purposes. Put simply, it's the bread and butter of data science for the majority of data scientists. But there are some limitations with the Pandas project. It is not really built for working with big data and distributed datasets. Pandas code, when executed in Databricks, only runs on the driver. This creates a performance bottleneck when the data size increases.

On the other hand, when data analysts and data scientists start working with Spark, they need to be using PySpark as an alternative. Due to this challenge, the creators of Databricks came up with another project and named it Koalas. This project has been built to allow data scientists working with Pandas to become productive with Apache Spark. It is nothing but a Pandas DataFrame API built on top of Apache Spark. Therefore, it leverages very...

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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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