We may earn an affiliate commission when you visit our partners.
Justin Pihony

This course will teach you how to use Apache Spark to analyze your big data at lightning-fast speeds; leaving Hadoop in the dust! For a deep dive on SQL and Streaming check out the sequel, Handling Fast Data with Apache Spark SQL and Streaming.

Read more

This course will teach you how to use Apache Spark to analyze your big data at lightning-fast speeds; leaving Hadoop in the dust! For a deep dive on SQL and Streaming check out the sequel, Handling Fast Data with Apache Spark SQL and Streaming.

Our ever-connected world is creating data faster than Moore's law can keep up, making it so that we have to be smarter in our decisions on how to analyze it. Previously, we had Hadoop's MapReduce framework for batch processing, but modern big data processing demands have outgrown this framework. That's where Apache Spark steps in, boasting speeds 10-100x faster than Hadoop and setting the world record in large scale sorting. Spark's general abstraction means it can expand beyond simple batch processing, making it capable of such things as blazing-fast, iterative algorithms and exactly once streaming semantics. In this course, you'll learn Spark from the ground up, starting with its history before creating a Wikipedia analysis application as one of the means for learning a wide scope of its core API. That core knowledge will make it easier to look into Spark's other libraries, such as the streaming and SQL APIs. Finally, you'll learn how to avoid a few commonly encountered rough edges of Spark. You will leave this course with a tool belt capable of creating your own performance-maximized Spark application.

Enroll now

Here's a deal for you

We found an offer that may be relevant to this course.
Save money when you learn. All coupon codes, vouchers, and discounts are applied automatically unless otherwise noted.

What's inside

Syllabus

Getting Started
Spark Core: Part 1
Spark Core: Part 2
Distribution and Instrumentation
Read more
Spark Libraries
Optimizations and the Future

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Examines the use of Apache Spark for big data analysis, which is highly relevant in industry
Introduces learners to Apache Spark Core, which is the foundation for understanding the tool
Presents use cases for Spark Streaming and SQL APIs, expanding learners' knowledge of the tool
Emphasizes optimizations and future developments in Spark, ensuring learners are up-to-date with industry trends
Taught by Justin Pihony, who is recognized for their work in Apache Spark
Requires learners to have some prior knowledge of big data processing, which may be a barrier for beginners

Save this course

Save Apache Spark Fundamentals to your list so you can find it easily later:
Save

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Apache Spark Fundamentals with these activities:
Organize and Review Course Materials
Maximize your learning by organizing and reviewing course notes, assignments, and other materials regularly.
Show steps
  • Create a dedicated folder or notebook for course materials.
  • Organize materials by topic, module, or week.
  • Review materials at regular intervals to reinforce learning and identify areas for improvement.
Review Python Basics
Strengthen your Python programming skills, which are essential for working with Apache Spark.
Browse courses on Python
Show steps
  • Review Python tutorials or documentation to refresh your understanding of basic syntax and concepts.
  • Attempt Python coding exercises or challenges to test your skills.
  • Practice writing Python scripts that perform simple data manipulation tasks.
Read 'Learning Spark' by Holden Karau, Andy Konwinski, Patrick Wendell, and Matei Zaharia
Gain a comprehensive understanding of Apache Spark by reading a foundational book written by experts in the field.
Show steps
  • Acquire a copy of the book, either physically or digitally.
  • Set aside dedicated time each day or week for reading and comprehension.
  • Take notes and highlight important sections for future reference.
Three other activities
Expand to see all activities and additional details
Show all six activities
Join a Study Group or Discussion Forum
Engage with other learners in study groups or online forums to share knowledge, ask questions, and deepen your understanding of Apache Spark.
Browse courses on Apache Spark
Show steps
  • Identify Apache Spark study groups or discussion forums on platforms like Reddit, LinkedIn, or Meetup.
  • Join the group and actively participate in discussions and Q&A sessions.
  • Share your own experiences, insights, and questions related to Apache Spark.
  • Collaborate with others on projects or learning challenges.
Explore Apache Spark Tutorials and Courses
Supplement your learning by exploring online tutorials and courses that delve deeper into specific aspects of Apache Spark.
Browse courses on Apache Spark
Show steps
  • Identify areas where you want to enhance your knowledge or skills related to Apache Spark.
  • Search for reputable online courses or tutorials on platforms like Udemy, Coursera, or YouTube.
  • Review the course outlines, instructor profiles, and student reviews to select the most suitable option.
  • Dedicate time to complete the tutorial or course, taking notes and practicing along the way.
Complete the Apache Spark Code Challenges
Sharpen your Apache Spark skills by solving code challenges and exercises to solidify your understanding of core concepts.
Browse courses on Apache Spark
Show steps
  • Visit the Apache Spark website or other online resources for code challenges.
  • Select an appropriate challenge that aligns with your current level of expertise.
  • Attempt to solve the challenge using the concepts learned in the course.
  • Compare your solution with provided answers or online forums to identify areas for improvement.

Career center

Learners who complete Apache Spark Fundamentals will develop knowledge and skills that may be useful to these careers:
Quantitative Analyst
Quantitative Analysts are those who blend mathematical and statistical modeling together with data analysis to solve complex problems. For those that want to pursue this career role, Apache Spark is a beneficial tool to have under your belt. The concepts that you will learn about data analytics and fast data processing, like SQL and streaming, can prove to be quite useful.
Software Architect
Software Architects are those that get to play an influential role within the designing and building of enterprise applications, infrastructures, and software solutions. If you are interested in such a career role, this Apache Spark course may be useful to you. It will teach you about core APIs like Spark Core, as well as how to optimize future applications.
Data Architect
Data Architects, much like Software Architects, also plan out the design and implementation of applications. However, they focus primarily on data management. If this sounds like a career role that you would enjoy, you may find use in the content that this course teaches. It will help you to understand how to design and maintain structured data.
Data Engineer
Data Engineers are responsible for overseeing data acquisition, storage, cleansing, and analysis. If you would like to go into this career role, the Apache Spark course will help you to build a foundation for analyzing structured and unstructured data.
Data Scientist
Data Scientists use their knowledge of data to solve business challenges by utilizing scientific methods. For an aspiring Data Scientist, the Apache Spark course will be useful. A foundational understanding of how to analyze data quickly and efficiently will be extremely beneficial.
Statistician
Statisticians use data to study and solve real-world problems. The Apache Spark course can be useful for those who want to enter this field. Through learning how to analyze large quantities of data, this course can help to build your foundation in statistics.
Operations Research Analyst
Operations Research Analysts use advanced analytical methods to solve complex business problems. This course can be a valuable tool to add to your skill set. With Apache Spark and its ability to process large amounts of data quickly, you will be able to deliver data-driven solutions more efficiently.
Business Analyst
Business Analysts are responsible for analyzing and interpreting data to help businesses make better decisions. The Apache Spark course may be useful to those interested in becoming a Business Analyst. It can teach you how to analyze large and complex data sets to extract insights that can help businesses grow.
Financial Analyst
Financial Analysts use data to make investment recommendations. If you want to pursue a career as a Financial Analyst, taking the Apache Spark course would be beneficial. It will teach you how to analyze large and complex data sets, which is a skill that is in high demand in the financial industry.
Market Researcher
Market Researchers use data to understand consumer behavior and trends. This course may be useful for those interested in becoming a Market Researcher. It will teach you how to analyze large and complex data sets, which is a skill that is essential in this field.
Data Analyst
Data Analysts use data to solve business problems. If you want to become a Data Analyst, the Apache Spark course will be useful. It will teach you how to analyze large and complex data sets, which is a skill that is in high demand in the tech industry.
Database Administrator
Database Administrators are responsible for managing and maintaining databases. This course can be useful for aspiring Database Administrators as it teaches the fundamentals of data storage and management. With this course, you will be more prepared to ensure that data is secure and accessible to users.
Software Developer
Software Developers design, develop, and maintain software applications. This course can provide value to those seeking a career as a Software Developer. Its lessons on data analysis and API usage can contribute to your ability to create robust and efficient software.
Data Visualization Analyst
Data Visualization Analysts use data visualization tools to communicate data insights to stakeholders. This course may be useful for those interested in becoming a Data Visualization Analyst. It will teach you how to analyze and visualize data in a way that is easy to understand.
Data Journalist
Data Journalists use data to tell stories. If you want to become a Data Journalist, taking the Apache Spark course will be helpful. It will teach you how to analyze large and complex data sets, which is a skill that is essential in this field.

Reading list

We've selected 11 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 Apache Spark Fundamentals.
Is the official guide to Apache Spark, written by its creators. It provides a comprehensive overview of Spark's architecture, APIs, and use cases, and valuable reference for anyone working with Spark.
Is the definitive guide to Apache Spark, written by its creators. It provides a deep dive into Spark's architecture, internals, and best practices.
Provides a comprehensive overview of Apache Spark, covering its core concepts, APIs, and use cases. It valuable resource for anyone looking to learn more about Spark and its applications in big data analysis.
Provides a deep dive into the advanced features of Apache Spark, including machine learning, graph processing, and streaming. It valuable resource for experienced Spark users who want to learn more about its capabilities.
Provides a comprehensive guide to using Apache Spark for machine learning. It covers a wide range of topics, from basic concepts to advanced techniques, and includes numerous code examples and case studies.
Provides a comprehensive overview of Apache Hadoop, the open-source framework for distributed data processing. It valuable resource for anyone who wants to learn more about Hadoop and its applications in big data processing.
Provides a hands-on guide to using Spark for data analytics. It covers topics such as data loading, transformations, and visualizations.
Provides a collection of recipes for using Spark Streaming. It covers topics such as data ingestion, transformations, and queries.

Share

Help others find this course page by sharing it with your friends and followers:

Similar courses

Here are nine courses similar to Apache Spark Fundamentals.
Handling Fast Data with Apache Spark SQL and Streaming
Most relevant
Apache Spark 3 Fundamentals
Most relevant
Structured Streaming in Apache Spark 2
Most relevant
Conceptualizing the Processing Model for Apache Spark...
Most relevant
Applying the Lambda Architecture with Spark, Kafka, and...
Most relevant
Developing Spark Applications Using Scala & Cloudera
Most relevant
Windowing and Join Operations on Streaming Data with...
Most relevant
Apache Spark for Data Engineering and Machine Learning
Most relevant
Processing Streaming Data Using Apache Spark Structured...
Most relevant
Our mission

OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.

Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.

Find this site helpful? Tell a friend about us.

Affiliate disclosure

We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.

Your purchases help us maintain our catalog and keep our servers humming without ads.

Thank you for supporting OpenCourser.

© 2016 - 2024 OpenCourser