Azure Databricks allows you to work with big data processing and queries using the Apache Spark unified analytics engine. Azure Databricks allows to work with a variety of batch sources and makes it seamless to analyze, visualize, and process data on the Azure Cloud Platform. In this course, Handling Batch Data with Apache Spark on Databricks, you will learn how to perform transformations and aggregations on batch data with selection, filtering, grouping, and ordering queries that use the DataFrame API. You will understand the difference between narrow transformations and wide transformations in Spark which will help you figure out why certain transformations are more efficient than others. You will also see how you can execute these same transformations by executing SQL queries on your data. Next, you will learn how you can implement your own custom user-defined functions to process your data. You will write code on Azure Databricks notebooks to define and register your UDFs and use them to transform your data. You will also understand how to define and use different flavors of vectorized UDFs for data processing and learn how vectorized UDFs are often more efficient than regular UDFs. Along the way, you will also see how you can read from Azure Cosmos DB as a source for your batch data. Finally, you will see how you can repartition your data in memory to improve processing performance, you will use window functions to compute statistics on your data and you will combine data frames using union and join operations. When you’re finished with this course you will have the skills and ability to perform advanced transformations and aggregations on batch data, including defining and using user-defined functions for processing.
Author Name: Janani Ravi
Author Description:
Janani has a Masters degree from Stanford and worked for 7+ years at Google. She was one of the original engineers on Google Docs and holds 4 patents for its real-time collaborative editing framework. After spending years working in tech in the Bay Area, New York, and Singapore at companies such as Microsoft, Google, and Flipkart, Janani finally decided to combine her love for technology with her passion for teaching. She is now the co-founder of Loonycorn, a content studio focused on providing … more

Table of Contents

• Course Overview
  2mins
• Transforming Data Using DataFrames
  40mins
• Transforming Data Using Spark SQL
  31mins
• Applying User-defined Functions to Transform Data
  31mins
• Processing Data Using Joins and Window Functions
  37mins