In this hands-on, 1-hour project-based course, you will master real-time data processing using Apache Spark Structured Streaming. This course is designed for data engineers and developers who want to gain practical experience in building streaming data pipelines. You will begin by setting up the Spark environment and learn how to configure micro-batches and fault tolerance mechanisms through checkpointing. Next, you’ll dive into transforming streaming data by applying filters, maps, and aggregations to extract meaningful insights. You'll also handle out-of-order data with watermarks, ensuring the accuracy of your real-time analytics. The course will introduce you to querying streaming data using SQL, allowing you to perform transformations and aggregations on live data. Finally, you will learn to deploy your streaming pipeline to production by writing results to an external sink like Parquet files. This is an intermediate level project and in order to succeed in this course it is recommended to have basic understanding of Apache Spark and API PySpark, proficiency in programming and big data as well and some basic knowledge on writing SQL queries. This is the perfect opportunity for anyone looking to dive into real-time data processing and Spark Structured Streaming!
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Recommended experience
What you'll learn
Set up and configure a real-time data processing pipeline
Perform transformations, aggregations, and SQL queries on streaming data
Implement fault-tolerance mechanisms and ensure the pipeline remains resilient under high workloads and data inconsistencies
Skills you'll practice
Details to know
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January 2025
Only available on desktop
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About this Guided Project
Learn step-by-step
In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:
Task 1: Setting Up the Environment for Real-Time Data Streaming
Task 2: Managing Triggers and Checkpoints
Task 3: Transforming Streaming Data
Practice Activity
Task 4: Performing Transformations, Aggregations, and Advanced SQL Queries
Task 5: Writing and Deploying the Pipeline
Cumulative Challenge
Recommended experience
Experience with Apache Spark and API Pyspark. Python coding skills. SQL query proficiency. Big Data concepts. Kafka basics.
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Instructor
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How you'll learn
Skill-based, hands-on learning
Practice new skills by completing job-related tasks.
Expert guidance
Follow along with pre-recorded videos from experts using a unique side-by-side interface.
No downloads or installation required
Access the tools and resources you need in a pre-configured cloud workspace.
Available only on desktop
This Guided Project is designed for laptops or desktop computers with a reliable Internet connection, not mobile devices.
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Frequently asked questions
By purchasing a Guided Project, you'll get everything you need to complete the Guided Project including access to a cloud desktop workspace through your web browser that contains the files and software you need to get started, plus step-by-step video instruction from a subject matter expert.
Because your workspace contains a cloud desktop that is sized for a laptop or desktop computer, Guided Projects are not available on your mobile device.
Guided Project instructors are subject matter experts who have experience in the skill, tool or domain of their project and are passionate about sharing their knowledge to impact millions of learners around the world.