Building Event-Driven Real-Time Data Processor with Spark Structured Streaming and API Integration

[MichTalebzadeh]

I recently saw an article from Databricks titled "Scalable Spark Structured Streaming for REST API Destinations". A great article focusing on continuous Spark Structured Streaming (SSS). About a year old. I then decided, given customer demands to work on "Building an Event-Driven Real-Time Data Processor with Spark Structured Streaming and API Integratio...". In the fast-paced realm of data processing, the ability to derive actionable insights in real-time is essential for organizations across various domains. My article tries to construct a robust, event-driven, real-time data processor, seamlessly integrating APIs using Apache Spark, REST API, and Flask. The focus is on empowering data engineers and developers to efficiently process streaming data while staying responsive to external events. This article introduces a distinctive approach centred around handling simulated market data. In contrast to conventional scenarios like Databricks article, our architecture comprises two key components: a well-established Bash script, serving as a robust historical financial data generator for various tickers (IBM, MRW, MSFT, among others), and a Python application designed for seamless data transmission to a REST API. The diagram below shows the components. The full article is available from the linkedlin above including the accompanying GitHub code

[Kaniz]

Hi @MichTalebzadeh, Thank you for sharing your insightful article, "Building an Event-Driven Real-Time Data Processor with Spark Structured Streaming and API Integration."

Your approach to integrating Apache Spark™, REST API, and Flask to create a robust, event-driven data processor is innovative and practical.

Your article demonstrates a deep understanding of real-time data processing challenges and provides a unique solution that can benefit data engineers and developers in various domains. We are delighted to have you as a community member and appreciate your valuable contributions.

We believe that your expertise and insights would be highly beneficial to our community. We invite you to consider writing technical blogs for our platform to share your knowledge and experiences with our community members. Your contributions could inspire and educate others, further enriching our community's knowledge base.

Please let us know if you are interested in contributing, and we can discuss the details further. Once again, thank you for sharing your article with us, and we look forward to potentially collaborating with you in the future.

[MichTalebzadeh]

Hi @Kaniz 

Thank you for your kind words. Of course I will be delighted to contribute to your technical blogs. Let me know how.

Regards,

Mich

[Kaniz · Accepted solution]

Hi @MichTalebzadeh, Thank you for expressing your interest in contributing to our technical blogs! We're thrilled to have you on board.

To get started, you can explore our technical blogs section on our community platform under the Resources node. This section contains examples of previous blog posts. You can use these resources to help you craft your own articles.

Once you have written an article, you can submit it for review through our platform. Our editorial team will review your article and work with you to make any necessary revisions before publishing it on our community blog.

If you have any questions or need assistance at any point during the process, please don't hesitate to reach out. We're here to help and support you as you contribute to our community's knowledge base.

Thank you once again for your willingness to contribute. We look forward to reading your articles!