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David Dalsveen
By the end of this project, you will use the Apache Spark Structured Streaming API with Python to stream data from two different sources, store a dataset in the MongoDB database, and join two datasets. The Apache Spark Structured Streaming API is used to continuously stream data from various sources including the file system or a TCP/IP socket. One application is to continuously capture data from weather stations for historical purposes.
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Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Extends skills with core tools and technologies for data streaming analysis
Well-suited for learners who want to enhance their data engineering skills
Introduces the Apache Spark Structured Streaming API for real-time data processing
Uses Python, a popular programming language for data analysis

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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 Use the Apache Spark Structured Streaming API with MongoDB with these activities:
Follow Spark Streaming Tutorials
Expand your knowledge of Spark Streaming by following guided tutorials.
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  • Find Spark Streaming tutorials online.
  • Follow the steps in the tutorials to learn how to use Spark Streaming.
  • Complete the exercises and quizzes in the tutorials.
Read 'Learning Apache Spark'
Get an overview of Apache Spark and the Structured Streaming API to prepare for the course.
Show steps
  • Read Chapters 1-3 to understand the basics of Apache Spark.
  • Read Chapter 6 to learn about the Structured Streaming API.
Join a Spark Streaming Study Group
Collaborate with peers and discuss Apache Spark and Structured Streaming to enhance your learning experience.
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  • Find a study group or create your own.
  • Meet regularly with your study group to discuss the course material.
  • Work together on projects and assignments.
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Write a Summary of the Course Concepts
Reinforce your understanding of the course material by summarizing the key concepts.
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  • Identify the main concepts covered in the course.
  • Write a summary for each concept, explaining it in your own words.
  • Review your summary and make any necessary revisions.
Solve Spark Streaming Coding Challenges
Master the practical aspects of Spark Streaming by solving coding challenges.
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  • Find Spark Streaming coding challenges online or create your own.
  • Solve the challenges and test your solutions.
  • Review your solutions and identify areas for improvement.
Build a Spark Streaming Application
Apply the concepts learned in the course by creating a project that uses Spark Streaming to process data in real-time and store it in MongoDB.
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  • Set up a Spark Streaming environment.
  • Create a data source and a sink.
  • Write a Spark Streaming program to process the data and store it in MongoDB.
  • Test the application.
Create a Slide Presentation on Apache Spark Structured Streaming API
Solidify your understanding of the API by creating a presentation that explains its features and capabilities.
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  • Gather information about the Apache Spark Structured Streaming API.
  • Create a slide presentation that covers the key features and capabilities of the API.
  • Present your slide presentation to a group of peers.
Contribute to Open Source Spark Streaming Projects
Gain practical experience and contribute to the community by working on open source Spark Streaming projects.
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  • Find open source Spark Streaming projects that interest you.
  • Contact the project maintainers and offer your help.
  • Work on the project and contribute your code.

Career center

Learners who complete Use the Apache Spark Structured Streaming API with MongoDB will develop knowledge and skills that may be useful to these careers:
Data Engineer
Data Engineers design, develop, and maintain pipelines for data collection, storage, and processing. They ensure that data is reliable, accurate, and accessible for analysis. The Apache Spark Structured Streaming API is a critical tool for Data Engineers who build systems to process streaming data in real time. This course provides a deep dive into the concepts and techniques of the Structured Streaming API, enabling Data Engineers to build robust and efficient data pipelines.
Data Analyst
The Data Analyst helps business leaders develop and maintain processes and strategies to turn raw data into valuable insights, often assisting in identifying market trends, understanding customer buying habits, and monitoring competition. As a Data Analyst, you may use the skills learned in this course to develop and implement data collection systems, maintain and manage databases, and analyze and visualize data. The Apache Spark Structured Streaming API is essential for Data Analysts to effectively analyze and interpret streaming data in real-time, making this course an ideal choice for those seeking a career as a Data Analyst.
Data Scientist
As a Data Scientist, you use data, mathematical or statistical models, and algorithms to extract knowledge and insights that can be used by organizations to make informed decisions. The Apache Spark Structured Streaming API is a key tool for Data Scientists as it enables real-time data processing and analysis, allowing for rapid decision-making and predictive modeling. This course provides a solid foundation in the principles and applications of the Structured Streaming API, making it beneficial for aspiring Data Scientists.
Database Administrator
The Database Administrator maintains and manages an organization's databases, ensuring that data is secure, reliable, and accessible. The Apache Spark Structured Streaming API can be utilized by Database Administrators to create and manage streaming data pipelines, enabling them to process and store data in real-time. This course offers valuable knowledge on the design and implementation of the Structured Streaming API, empowering Database Administrators to build and maintain robust database systems.
Data Architect
Data Architects design and manage an organization's data infrastructure, ensuring that data is available, secure, and reliable. The Apache Spark Structured Streaming API is becoming increasingly important for Data Architects who need to build systems for real-time data processing and analysis. This course offers a deep dive into the concepts and techniques of the Structured Streaming API, enabling Data Architects to design and implement robust data infrastructure.
Business Analyst
The Business Analyst helps organizations understand their business needs and goals, and then uses data to identify opportunities for improvement. The Apache Spark Structured Streaming API can be a valuable tool for Business Analysts who want to analyze real-time data to gain insights into customer behavior, market trends, and operational efficiency. This course provides a thorough understanding of the Structured Streaming API and its applications, enabling Business Analysts to make data-driven recommendations for business improvement.
Software Engineer
Responsible for designing, developing, and maintaining software systems, Software Engineers often work with streaming data to develop real-time applications. The Apache Spark Structured Streaming API is a key tool for Software Engineers who build systems to process and analyze streaming data. This course provides a comprehensive understanding of the Structured Streaming API, enabling Software Engineers to create scalable and efficient software solutions.
Big Data Engineer
Big Data Engineers design and manage systems for processing and analyzing large volumes of data. The Apache Spark Structured Streaming API is a key tool for Big Data Engineers who work with streaming data. This course provides a deep dive into the principles and applications of the Structured Streaming API, enabling Big Data Engineers to build and manage robust data processing systems.
Machine Learning Engineer
The Machine Learning Engineer builds and deploys machine learning models to solve business problems. The Apache Spark Structured Streaming API can be leveraged by Machine Learning Engineers to develop models that process and analyze streaming data in real-time. This course provides a solid foundation in the concepts and applications of the Structured Streaming API, enabling Machine Learning Engineers to build and deploy real-time machine learning solutions.
Data Warehouse Manager
Data Warehouse Managers oversee the design, implementation, and maintenance of data warehouses. The Apache Spark Structured Streaming API can be utilized by Data Warehouse Managers to create and manage streaming data pipelines, enabling them to store and analyze real-time data. This course provides valuable knowledge on the design and implementation of the Structured Streaming API, empowering Data Warehouse Managers to build and maintain efficient data warehouses.
Database Developer
Database Developers design and develop database systems to meet the needs of an organization. The Apache Spark Structured Streaming API can be utilized by Database Developers to create and manage streaming data pipelines, enabling them to process and store data in real-time. This course offers valuable knowledge on the design and implementation of the Structured Streaming API, empowering Database Developers to build and maintain robust database systems.
Data Visualization Analyst
Data Visualization Analysts create visual representations of data to help organizations understand complex information. The Apache Spark Structured Streaming API can be leveraged by Data Visualization Analysts to visualize streaming data in real-time, enabling them to identify trends and patterns. This course provides a solid foundation in the concepts and applications of the Structured Streaming API, empowering Data Visualization Analysts to build interactive and insightful data visualizations.
Network Engineer
Network Engineers design, build, and maintain computer networks. The Apache Spark Structured Streaming API can be leveraged by Network Engineers to analyze streaming data in real-time, enabling them to identify and resolve network issues. This course provides a solid foundation in the concepts and applications of the Structured Streaming API, empowering Network Engineers to build and manage efficient and reliable networks.
Information Security Analyst
Information Security Analysts protect an organization's computer systems and networks from unauthorized access, use, disclosure, disruption, modification, or destruction. The Apache Spark Structured Streaming API can be used by Information Security Analysts to monitor and analyze streaming data in real-time, enabling them to identify and respond to security threats. This course provides a solid foundation in the concepts and applications of the Structured Streaming API, empowering Information Security Analysts to build and deploy robust security systems.
Product Manager
Product Managers are responsible for the development and launch of new products. The Apache Spark Structured Streaming API can be utilized by Product Managers to analyze streaming data in real-time, enabling them to track customer usage and make informed decisions about product development. This course provides a solid foundation in the concepts and applications of the Structured Streaming API, empowering Product Managers to build and launch successful products.

Reading list

We've selected eight 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 Use the Apache Spark Structured Streaming API with MongoDB.
Provides a practical guide to using Apache Spark for real-world data analysis tasks. It covers a wide range of topics, including data ingestion, transformation, and machine learning. It good choice for beginners who want to learn how to use Spark effectively.
Provides a comprehensive guide to Apache Spark, covering its architecture, APIs, and advanced topics such as machine learning and graph processing. It valuable reference for developers who want to learn more about the technical details of Spark.
Combines MongoDB and Spark, providing a comprehensive guide to building data analytics applications. It covers data ingestion, transformation, analysis, and visualization using both technologies.
Provides a deep dive into MongoDB, covering its internal architecture, performance optimization techniques, and advanced features. It is intended for experienced MongoDB users who want to gain a deeper understanding of the database and its capabilities.
Provides a comprehensive guide to MongoDB, covering its architecture, data modeling, and administration. It valuable reference for developers who want to learn more about the technical details of MongoDB.
Provides a comprehensive overview of the Python programming language and its libraries for data analysis. It valuable reference for anyone who wants to learn more about Python and how to use it for data analysis.
Provides a gentle introduction to data science, covering topics such as data cleaning, data exploration, and machine learning. It good starting point for anyone who is new to data science.
Provides a gentle introduction to the Python programming language. It good starting point for anyone who is new to Python.

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