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Modeling Streaming Data for Processing with Apache Spark Structured Streaming

Eugene Meidinger

Streaming analytics can be difficult to implement. This course will teach you to model real-time data processing with Spark Structured Streaming.

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Streaming analytics can be difficult to implement. This course will teach you to model real-time data processing with Spark Structured Streaming.

Streaming analytics can be a difficult to set up, especially when working with late data arrivals and other variables. In this course, Modeling Streaming Data for Processing with Apache Spark Structured Streaming, you’ll learn to model your data for real-time analysis. First, you’ll explore applying batch processing to streaming data. Next, you’ll discover aggregating and outputting data. Finally, you’ll learn how to late arrivals and job failures. When you’re finished with this course, you’ll have the skills and knowledge of Spark Structured Streaming needed to combine your batch and streaming analytics jobs.

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What's inside

Syllabus

Course Overview
Comparing Batch and Stream Processing
Understanding Structured Streaming
Grouping and Aggregating Data
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Handling Late Arrivals and Failures

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Develops essential skills for real-time data analysis
Covers industry-standard Apache Spark Structured Streaming
Experienced instructors recognized for their work in data engineering
May require prior knowledge in data processing fundamentals

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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 Modeling Streaming Data for Processing with Apache Spark Structured Streaming with these activities:
Review Concepts of Real-time and Batch Processing
Refresh your understanding of the differences and similarities between real-time and batch processing.
Browse courses on Batch Processing
Show steps
  • Review course materials or online resources.
  • Create a comparison table of key concepts.
  • Discuss the advantages and disadvantages of each approach.
Review 'Learning Spark: Lightning-Fast Data Analytics'
Enhance your theoretical knowledge of Spark Streaming concepts by reviewing a comprehensive book on the topic.
View Learning Spark: Lightning-Fast Big Data Analysis on Amazon
Show steps
  • Identify chapters relevant to streaming analytics.
  • Read and understand the core concepts of streaming.
  • Review code samples and examples.
Follow Along with Hands-on Spark Streaming Tutorials
Enhance your hands-on experience by working through guided tutorials on Spark Structured Streaming.
Browse courses on Apache Spark
Show steps
  • Find online tutorials or resources.
  • Set up your development environment.
  • Follow the tutorial steps and implement the code.
Four other activities
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Show all seven activities
Build a Spark Streaming Application
Develop a real streaming analytics project to solidify your understanding of Spark Structured Streaming.
Browse courses on Real-Time Data Processing
Show steps
  • Define your data source and schema.
  • Implement streaming transformations and aggregations.
  • Handle late data arrivals and job failures.
Practice Data Aggregation and Outputting Techniques
Reinforce your understanding of data aggregation and output in Spark Streaming through targeted exercises.
Browse courses on Aggregation Functions
Show steps
  • Create a dataset for practice.
  • Write code to aggregate data using Spark SQL or DataFrames.
  • Explore different output options, such as writing to files or databases.
Practice Spark Structured Streaming exercises
Practicing these exercises will help you solidify your knowledge of the concepts taught in the 'Modeling Streaming Data for Processing with Apache Spark Structured Streaming' course.
Browse courses on Spark Structured Streaming
Show steps
  • Download and install the Apache Spark distribution.
  • Create a Spark Session object.
  • Read data from a streaming source (e.g., a Kafka topic).
  • Transform the data using Spark Structured Streaming operations.
  • Output the transformed data to a sink (e.g., a database or a file system).
Build a real-time data processing application using Spark Structured Streaming
This project will allow you to apply the skills you have learned in the course to a practical scenario, reinforcing your understanding of how to use Spark Structured Streaming for real-time data processing.
Browse courses on Spark Structured Streaming
Show steps
  • Identify a real-world problem that can be solved using Spark Structured Streaming.
  • Design and implement the data processing pipeline using Spark Structured Streaming.
  • Deploy the application to a cloud platform or on-premises infrastructure.
  • Monitor the application and make necessary adjustments to ensure optimal performance.

Career center

Learners who complete Modeling Streaming Data for Processing with Apache Spark Structured Streaming will develop knowledge and skills that may be useful to these careers:
Data Scientist
Data Scientists use scientific methods to extract insights from data. The course, Modeling Streaming Data for Processing with Apache Spark Structured Streaming, may be useful for aspiring Data Scientists by providing them with the skills needed to work with streaming data and leverage it for insights.
See salaries and explore the career path for Data Scientist
Machine Learning Engineer
Machine Learning Engineers design, develop, and deploy machine learning models. The course, Modeling Streaming Data for Processing with Apache Spark Structured Streaming, may be useful for aspiring Machine Learning Engineers by providing them with the skills needed to work with streaming data and leverage it for insights.
See salaries and explore the career path for Machine Learning Engineer
Business Analyst
Business Analysts identify and solve business problems using data. The course, Modeling Streaming Data for Processing with Apache Spark Structured Streaming, may be useful for aspiring Business Analysts by providing them with the skills needed to work with streaming data and leverage it for insights.
See salaries and explore the career path for Business Analyst
Operations Research Analyst
Operations Research Analysts use mathematical and analytical methods to solve business problems. The course, Modeling Streaming Data for Processing with Apache Spark Structured Streaming, may be useful for aspiring Operations Research Analysts by providing them with the skills needed to work with streaming data and leverage it for insights.
See salaries and explore the career path for Operations Research Analyst
Statistician
Statisticians collect, analyze, and interpret data. The course, Modeling Streaming Data for Processing with Apache Spark Structured Streaming, may be useful for aspiring Statisticians by providing them with the skills needed to work with streaming data and leverage it for insights.
See salaries and explore the career path for Statistician
Data Architect
Data Architects design and manage data systems. The course, Modeling Streaming Data for Processing with Apache Spark Structured Streaming, may be useful for aspiring Data Architects by providing them with the skills needed to work with streaming data and leverage it for insights.
See salaries and explore the career path for Data Architect
Software Engineer
Software Engineers design, develop, and test software applications. The course, Modeling Streaming Data for Processing with Apache Spark Structured Streaming, may be useful for aspiring Software Engineers by providing them with the skills needed to work with streaming data and leverage it for insights.
See salaries and explore the career path for Software Engineer
Data Analyst
Data Analysts collect, clean, and analyze data to help businesses make informed decisions. The course, Modeling Streaming Data for Processing with Apache Spark Structured Streaming, may be useful for aspiring Data Analysts by providing them with the skills needed to work with streaming data and leverage it for insights.
See salaries and explore the career path for Data Analyst
Database Administrator
Database Administrators manage and maintain databases. The course, Modeling Streaming Data for Processing with Apache Spark Structured Streaming, may be useful for aspiring Database Administrators by providing them with the skills needed to work with streaming data and leverage it for insights.
See salaries and explore the career path for Database Administrator
Data Engineer
Data Engineers design, build, and maintain data pipelines and systems. The course, Modeling Streaming Data for Processing with Apache Spark Structured Streaming, may be useful for aspiring Data Engineers by providing them with the skills needed to work with streaming data and leverage it for insights.
See salaries and explore the career path for Data Engineer
Cloud Architect
Cloud Architects design and manage cloud computing systems. The course, Modeling Streaming Data for Processing with Apache Spark Structured Streaming, may be useful for aspiring Cloud Architects by providing them with the skills needed to work with streaming data and leverage it for insights.
See salaries and explore the career path for Cloud Architect
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze data and make predictions. The course, Modeling Streaming Data for Processing with Apache Spark Structured Streaming, may be useful for aspiring Quantitative Analysts by providing them with the skills needed to work with streaming data and leverage it for insights.
See salaries and explore the career path for Quantitative Analyst
Actuary
Actuaries use mathematical and statistical models to assess risk and uncertainty. The course, Modeling Streaming Data for Processing with Apache Spark Structured Streaming, may be useful for aspiring Actuaries by providing them with the skills needed to work with streaming data and leverage it for insights.
See salaries and explore the career path for Actuary
DevOps Engineer
DevOps Engineers manage the software development lifecycle. The course, Modeling Streaming Data for Processing with Apache Spark Structured Streaming, may be useful for aspiring DevOps Engineers by providing them with the skills needed to work with streaming data and leverage it for insights.
See salaries and explore the career path for DevOps Engineer
Big Data Engineer
Big Data Engineers design and manage big data systems. The course, Modeling Streaming Data for Processing with Apache Spark Structured Streaming, may be useful for aspiring Big Data Engineers by providing them with the skills needed to work with streaming data and leverage it for insights.
See salaries and explore the career path for Big Data Engineer

Reading list

We've selected six 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 Modeling Streaming Data for Processing with Apache Spark Structured Streaming.
Cover image
Spark: The Definitive Guide
Save
Provides a comprehensive guide to leveraging Spark Structured Streaming for real-time data processing. It offers practical examples and techniques to optimize performance and handle complex streaming scenarios.
Spark: The Definitive Guide
Paperback
Check
Spark: The Definitive Guide
Kindle Edition
Check
Cover image
Learning Spark
Save
This comprehensive book serves as an introduction to Apache Spark, covering both batch and streaming data processing. It provides a solid foundation for understanding the concepts and techniques used in Spark Structured Streaming, making it a valuable resource for beginners and intermediate users.
Learning Spark: Lightning-Fast Big Data Analysis
Paperback
$$
Cover image
Learning Spark
Save
Provides a fast-paced introduction to Spark, including how to use Spark for streaming data processing.
Learning Spark: Lightning-Fast Data Analytics
Paperback
$$
Learning Spark: Lightning-Fast Data Analytics
Kindle Edition
$$
Cover image
Python Data Science Handbook
Save
Provides a practical introduction to data science algorithms and techniques using Python. It covers topics such as data exploration, machine learning, and deep learning, offering valuable insights into the fundamentals of data science that can be applied to streaming data analysis.
Python Data Science Handbook: Essential Tools for...
Paperback
$$$
Cover image
Spark: The Definitive Guide
Save
Provides a comprehensive overview of Spark, including how to use Spark for streaming data processing.
Spark: The Definitive Guide: Big Data Processing...
Paperback
$$
Spark: The Definitive Guide: Big Data Processing...
Kindle Edition
$$
Cover image
Advanced Analytics with PySpark
Save
Provides a comprehensive overview of advanced analytics with Spark, including how to use Spark for streaming data processing.
Advanced Analytics with PySpark: Patterns for...
Paperback
$$
Advanced Analytics with PySpark
Kindle Edition
$$

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Course image
Time
79 hours
Level
Introductory
Via
Pluralsight
Instructor
Eugene Meidinger
Language
English
Good to know
Develops essential skills for real-time data analysis
Covers industry-standard Apache Spark Structured Streaming
Experienced instructors recognized for their work in data engineering
May require prior knowledge in data processing fundamentals
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