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Updated in [February 21st, 2023]

What does this course tell?
(Please note that the following overview content is from the original platform)

This "Spark Streaming Tutorial" will help you to master all the concepts of Spark Streaming. Spark Streaming is an extension of the core Spark API that allows data engineers and data scientists to process real-time data from various sources including (but not limited to) Kafka, Flume, and Amazon Kinesis. This processed data can be pushed out to file systems, databases, and live dashboards.

Through this Spark Streaming tutorial, you will learn the basics of Spark Streaming that includes why there is a need for streaming in Spark, How it can be used in real-time analysis, and much more. At the end of the video, you will have a better hold over the Spark streaming sources and various Streaming Operations.

Apache Spark Streaming is a scalable fault-tolerant streaming processing system that natively supports both batch and streaming workloads. This video will help you to understand every aspect of Spark Streaming along with the examples and visuals for better understanding.
What can you get from this course?
We consider the value of this course from multiple aspects, and finally summarize it for you from three aspects: personal skills, career development, and further study:
(Kindly be aware that our content is optimized by AI tools while also undergoing moderation carefully from our editorial staff.)
What skills and knowledge will you acquire during this course?
This Spark Streaming Tutorial will provide learners with the skills and knowledge to understand the basics of Spark Streaming, including why there is a need for streaming in Spark, how it can be used in real-time analysis, and more. Learners will gain an understanding of Spark Streaming sources and various streaming operations, as well as a better grasp of Apache Spark Streaming, a scalable fault-tolerant streaming processing system that natively supports both batch and streaming workloads. Additionally, learners will gain an understanding of how to process real-time data from various sources, including (but not limited to) Kafka, Flume, and Amazon Kinesis, and how to push out the processed data to file systems, databases, and live dashboards.

How does this course contribute to professional growth?
This course contributes to professional growth by providing an in-depth understanding of Spark Streaming, an extension of the core Spark API. Through this course, learners will gain knowledge of the basics of Spark Streaming, including why there is a need for streaming in Spark, how it can be used in real-time analysis, and more. Learners will also gain an understanding of Spark Streaming sources and various streaming operations.

Is this course suitable for preparing further education?
This Spark Streaming Tutorial is suitable for those looking to prepare for further education in the field of data engineering and data science. It covers the basics of Spark Streaming, including why there is a need for streaming in Spark, how it can be used in real-time analysis, and more. It also provides examples and visuals to help with understanding.