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Data stream development with Apache Spark, Kafka, and Spring Boot

Author: Anghel Leonard
Publisher: [Place of publication not identified] : Packt Publishing, 2018.
Edition/Format:   eVideo : Clipart/images/graphics : English
Summary:
"Today, organizations have a difficult time working with huge numbers of datasets. In addition, data processing and analyzing need to be done in real time to gain insights. This is where data streaming comes in. As big data is no longer a niche topic, having the skill set to architect and develop robust data streaming pipelines is a must for all developers. In addition, they also need to think of the entire  Read more...
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Details

Material Type: Clipart/images/graphics, Internet resource, Videorecording
Document Type: Internet Resource, Computer File, Visual material
All Authors / Contributors: Anghel Leonard
OCLC Number: 1084292725
Notes: Title from resource description page (Safari, viewed February 4, 2019).
Performer(s): Presenter, Anghel Leonard.
Description: 1 online resource (1 streaming video file (7 hr., 51 min., 20 sec.)) : digital, sound, color
Responsibility: Anghel Leonard.

Abstract:

"Today, organizations have a difficult time working with huge numbers of datasets. In addition, data processing and analyzing need to be done in real time to gain insights. This is where data streaming comes in. As big data is no longer a niche topic, having the skill set to architect and develop robust data streaming pipelines is a must for all developers. In addition, they also need to think of the entire pipeline, including the trade-offs for every tier. This course starts by explaining the blueprint architecture for developing a completely functional data streaming pipeline and installing the technologies used. With the help of live coding sessions, you will get hands-on with architecting every tier of the pipeline. You will also handle specific issues encountered working with streaming data. You will input a live data stream of Meetup RSVPs that will be analyzed and displayed via Google Maps. By the end of the course, you will have built an efficient data streaming pipeline and will be able to analyze its various tiers, ensuring a continuous flow of data."--Resource description page.

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Primary Entity

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