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Getting Started with Apache Spark on Databricks

Janani Ravi

This course will introduce you to analytical queries and big data processing using Apache Spark on Azure Databricks. You will learn how to work with Spark transformations, actions, visualizations, and functions using the Databricks Runtime.

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This course will introduce you to analytical queries and big data processing using Apache Spark on Azure Databricks. You will learn how to work with Spark transformations, actions, visualizations, and functions using the Databricks Runtime.

Azure Databricks allows you to work with big data processing and queries using the Apache Spark unified analytics engine. With Azure Databricks you can set up your Apache Spark environment in minutes, autoscale your processing, and collaborate and share projects in an interactive workspace.

In this course, Getting Started with Apache Spark on Databricks, you will learn the components of the Apache Spark analytics engine which allows you to process batch as well as streaming data using a unified API. First, you will learn how the Spark architecture is configured for big data processing, you will then learn how the Databricks Runtime on Azure makes it very easy to work with Apache Spark on the Azure Cloud Platform and will explore the basic concepts and terminology for the technologies used in Azure Databricks.

Next, you will learn the workings and nuances of Resilient Distributed Datasets also known as RDDs which is the core data structure used for big data processing in Apache Spark. You will see that RDDs are the data structures on top of which Spark Data frames are built. You will study the two types of operations that can be performed on Data frames - namely transformations and actions and understand the difference between them. You’ll also learn how Databricks allows you to explore and visualize your data using the display() function that leverages native Python libraries for visualizations.

Finally, you will get hands-on experience with big data processing operations such as projection, filtering, and aggregation operations. Along the way, you will learn how you can read data from an external source such as Azure Cloud Storage and how you can use built-in functions in Apache Spark to transform your data.

When you are finished with this course you will have the skills and ability to work with basic transformations, visualizations, and aggregations using Apache Spark on Azure Databricks.

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What's inside

Syllabus

Course Overview
Overview of Apache Spark on Databricks
Transformations, Actions, and Visualizations
Modify Data Using Spark Functions
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Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Develops foundational skills and understanding for beginners in big data processing
Taught by instructors Janani Ravi who are recognized for their expertise in Apache Spark and big data processing
Explores Apache Spark on Azure Databricks, which is highly relevant to industry
Teaches basic transformations, actions, and visualizations which are core skills for big data processing
Hands-on labs and interactive materials enhance learning experience

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Career center

Learners who complete Getting Started with Apache Spark on Databricks will develop knowledge and skills that may be useful to these careers:
Data Scientist
Data Scientists use their skills in statistics, mathematics, and computer science to extract insights from data. They work with data analysts and data engineers to help organizations to understand their data and make better decisions about their products, services, and operations. Getting Started with Apache Spark on Databricks may be useful for those who want to become data scientists because it can help them to develop the skills needed to work with big data, including data analysis, data mining, and data visualization.
Machine Learning Engineer
Machine Learning Engineers design, build, and deploy machine learning models. They work with data scientists and other IT professionals to help organizations to automate tasks and make better decisions about their products, services, and operations. Getting Started with Apache Spark on Databricks may be useful for those who want to become machine learning engineers because it can help them to develop the skills needed to work with big data, including data engineering, data processing, and data visualization.
Business Analyst
Business Analysts use their skills in business and technology to identify and solve problems for organizations. They work with stakeholders to understand their needs and develop solutions that improve business processes and performance. Getting Started with Apache Spark on Databricks may be useful for those who want to become business analysts because it can help them to develop the skills needed to work with big data, including data analysis, data interpretation, and data communication.
Operations Research Analyst
Operations Research Analysts use their skills in mathematics, statistics, and computer science to solve problems in a variety of industries. They work with operations managers and other stakeholders to develop and implement solutions that improve operational efficiency and performance. Getting Started with Apache Spark on Databricks may be useful for those who want to become operations research analysts because it can help them to develop the skills needed to work with big data, including data analysis, data interpretation, and data communication.
Data Architect
Data Architects design and build the data infrastructure that supports an organization's data needs. They work with data engineers, data scientists, and other IT professionals to develop and implement data storage, processing, and analysis solutions. Getting Started with Apache Spark on Databricks may be useful for those who want to become data architects because it can help them to develop the skills needed to work with big data, including data engineering, data processing, and data visualization.
Software Engineer
Software Engineers design, build, and maintain software applications. They work with other IT professionals to develop and implement software solutions for a variety of industries. Getting Started with Apache Spark on Databricks may be useful for those who want to become software engineers because it can help them to develop the skills needed to work with big data, including data engineering, data processing, and data visualization.
Data Analyst
Data Analysts use their expertise in data to examine data sets, identify trends, and make predictions about the future. They help organizations to understand their data and make better decisions about their products, services, and operations. Getting Started with Apache Spark on Databricks may be useful for those who want to become data analysts because it can help them to develop the skills needed to work with big data, including data cleaning, data analysis, and data visualization.
Database Administrator
Database Administrators are responsible for the maintenance and performance of databases. They work with database developers and other IT professionals to ensure that databases are available and performant. Getting Started with Apache Spark on Databricks may be useful for those who want to become database administrators because it can help them to develop the skills needed to work with big data, including data engineering, data processing, and data visualization.
Financial Analyst
Financial Analysts use their skills in finance and analytics to evaluate the financial performance of companies and make recommendations about investments. They work with investors, portfolio managers, and other stakeholders to provide insights into the financial markets and help them to make informed decisions. Getting Started with Apache Spark on Databricks may be useful for those who want to become financial analysts because it can help them to develop the skills needed to work with big data, including data analysis, data interpretation, and data communication.
Marketing Analyst
Marketing Analysts use their skills in marketing and analytics to measure the effectiveness of marketing campaigns and develop new strategies. They work with marketers and other stakeholders to identify and target customer segments, develop marketing campaigns, and measure the results. Getting Started with Apache Spark on Databricks may be useful for those who want to become marketing analysts because it can help them to develop the skills needed to work with big data, including data analysis, data interpretation, and data communication.
Risk Analyst
Risk Analysts use their skills in risk management and analytics to identify and assess risks for organizations. They work with risk managers and other stakeholders to develop and implement risk management strategies. Getting Started with Apache Spark on Databricks may be useful for those who want to become risk analysts because it can help them to develop the skills needed to work with big data, including data analysis, data interpretation, and data communication.
Product Manager
Product Managers are responsible for the development and launch of new products. They work with engineers, designers, and other stakeholders to bring new products to market. Getting Started with Apache Spark on Databricks may be useful for those who want to become product managers because it can help them to develop the skills needed to work with big data, including data analysis, data interpretation, and data communication.
Data Engineer
Data Engineers design, build, and maintain the infrastructure and processes that allow organizations to collect, store, and analyze data. They work with data scientists, data analysts, and other IT professionals to ensure that data is available and accessible to those who need it. Getting Started with Apache Spark on Databricks may be useful for those who want to become data engineers because it can help them to develop the skills needed to work with big data, including data engineering, data processing, and data visualization.
Data Visualization Specialist
Data Visualization Specialists use their skills in design and technology to create visualizations that communicate data insights to a wide audience. They work with data analysts, data scientists, and other IT professionals to help organizations to understand their data and make better decisions about their products, services, and operations. Getting Started with Apache Spark on Databricks may be useful for those who want to become data visualization specialists because it can help them to develop the skills needed to work with big data, including data visualization and data communication.
Big Data Engineer
Big Data Engineers design, build, and maintain big data systems. They work with data engineers, data scientists, and other IT professionals to develop and implement solutions for storing, processing, and analyzing large volumes of data. Getting Started with Apache Spark on Databricks may be useful for those who want to become big data engineers because it can help them to develop the skills needed to work with big data, including data engineering, data processing, and data visualization.

Reading list

We've selected seven books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Getting Started with Apache Spark on Databricks.
Is essential reading for anyone interested in learning about Apache Spark.
Provides a comprehensive guide to using Apache Spark with Python. It covers a wide range of topics, from basic concepts to advanced techniques, and good choice for anyone who wants to learn more about Spark.
"Python for Data Science Handbook" comprehensive book that covers a wide range of Python topics that are useful for data science, including data manipulation, machine learning, and data visualization. It helpful resource for anyone who wants to learn more about Python for data science.
"Big Data Analytics with Spark" book that covers the basics of big data analytics using Apache Spark. It teaches you how to use Spark to process and analyze big data.
Save
"Spark: The Definitive Guide: Big Data Processing Made Simple, Second Edition" book that covers the basics of Apache Spark. It teaches you how to use Spark for data processing and analysis.

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