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Distributed Data Systems with Azure Databricks

You're reading from   Distributed Data Systems with Azure Databricks Create, deploy, and manage enterprise data pipelines

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Product type Paperback
Published in May 2021
Publisher Packt
ISBN-13 9781838647216
Length 414 pages
Edition 1st Edition
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Author (1):
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Alan Bernardo Palacio Alan Bernardo Palacio
Author Profile Icon Alan Bernardo Palacio
Alan Bernardo Palacio
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Table of Contents (17) Chapters Close

Preface 1. Section 1: Introducing Databricks
2. Chapter 1: Introduction to Azure Databricks FREE CHAPTER 3. Chapter 2: Creating an Azure Databricks Workspace 4. Section 2: Data Pipelines with Databricks
5. Chapter 3: Creating ETL Operations with Azure Databricks 6. Chapter 4: Delta Lake with Azure Databricks 7. Chapter 5: Introducing Delta Engine 8. Chapter 6: Introducing Structured Streaming 9. Section 3: Machine and Deep Learning with Databricks
10. Chapter 7: Using Python Libraries in Azure Databricks 11. Chapter 8: Databricks Runtime for Machine Learning 12. Chapter 9: Databricks Runtime for Deep Learning 13. Chapter 10: Model Tracking and Tuning in Azure Databricks 14. Chapter 11: Managing and Serving Models with MLflow and MLeap 15. Chapter 12: Distributed Deep Learning in Azure Databricks 16. Other Books You May Enjoy

pandas DataFrame API (Koalas)

Data scientists and data engineers that are Python users are very familiar with working with pandas DataFrames when manipulating data. pandas is a Python library for data manipulation and analysis but that lacks the capability to work with big data, therefore it is only suitable when working with small datasets. When we need to work with more data, the most common option is PySpark, as we have demonstrated in the previous section, which is a library with a very different syntax than pandas.

Koalas is a library that eases the learning curve from transitioning from pandas to working with big data in Azure Databricks. Koalas has a syntax that is very similar to the pandas API but with the functionality of PySpark.

Not all the pandas methods have been implemented and there are many small differences or subtleties that must be considered and might not be obvious. We cannot understand Koalas without understanding PySpark.

Koalas, functionality is built...

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