Real-Time Stream Processing Using Apache Spark 3 for Scala Developers

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Scholar Nest

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01.01-about_the_course.mp4

02:54

01.02-course_prerequisites.mp4

01:09

02.01-spark_development_environment.mp4

01:40

02.02-spark_installation_prerequisites.mp4

05:25

02.03-installing_apache_spark.mp4

08:21

02.04-set_up_and_test_your_ide.mp4

06:39

02.05-install_and_run_apache_kafka.mp4

10:20

03.01-introduction_to_stream_processing.mp4

09:12

03.02-spark_streaming_apis-dstream_versus_structured_streaming.mp4

03:46

03.03-creating_your_first_stream_processing_application.mp4

17:35

03.04-stream_processing_model_in_spark.mp4

08:29

03.05-working_with_files_and_directories.mp4

11:38

03.06-streaming_sources_sinks_and_output_mode.mp4

13:00

03.07-fault_tolerance_and_restarts.mp4

06:26

04.01-streaming_from_kafka_source.mp4

16:14

04.02-working_with_kafka_sinks.mp4

10:26

04.03-multi-query_streams_application.mp4

04:08

04.04-kafka_serialization_and_deserialization_for_spark.mp4

04:57

04.05-creating_kafka_avro_sinks.mp4

03:56

04.06-working_with_kafka_avro_source.mp4

04:47

05.01-stateless_versus_stateful_transformations.mp4

10:14

05.02-event_time_and_windowing.mp4

07:09

05.03-tumbling_window_aggregate.mp4

14:00

05.04-watermarking_your_windows.mp4

12:32

05.05-watermark_and_output_modes.mp4

09:49

05.06-sliding_windows.mp4

07:34

06.01-joining_stream_to_static_source.mp4

13:54

06.02-joining_stream_to_another_stream.mp4

09:53

06.03-streaming_watermark.mp4

07:12

06.04-streaming_outer_joins.mp4

11:12

9781803242040_Code.zip

Description

Since its inception, Apache Spark has seen rapid adoption by enterprises across a wide range of industries. So, mastering Apache Spark opens a wide range of professional opportunities. If you are a software engineer or architect and want to design or build your own projects, then this is the right course for you.

This is a hands-on, example-driven, advanced course with demonstrations and coding sessions. This course will help you understand real-time stream processing using Apache Spark and later, you will be able to apply that knowledge to build real-time stream processing solutions.

This course covers everything from scratch, which involves installing Apache Spark and seeing how to set up and run Apache Kafka. Furthermore, it introduces stream processing and how to work with files and directories. You will also explore Kafka serialization and deserialization for Spark and how to work with Kafka AVRO Source. And finally, the course wraps up with streaming Watermark and outer joints.

By the end of this course, you will be able to design and develop big data engineering projects. You will be able to create real-time stream processing applications with Apache Spark. This course will also help you further your growth in real-time stream processing.

All resources and code files are placed here: https://github.com/PacktPublishing/Spark-Streaming-In-Scala

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Apache Spark

Scholar Nest

Instructor's Courses

ScholarNest is a small team of people passionate about helping others learn and grow in their careers by bridging the gap between their existing and required skills. Together, they have over 40+ years of experience in IT as a developer, architect, consultant, trainer, and mentor. They have worked with international software services organizations on various data-centric and Big Data projects. It is a team of firm believers in lifelong continuous learning and skill development. To popularize the importance of continuous learning, they started publishing free training videos on their YouTube channel. They conceptualized the notion of continuous learning, creating a journal of our learning under the Learning Journal banner.

PacktPub

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Packt is a publishing company founded in 2003 headquartered in Birmingham, UK, with offices in Mumbai, India. Packt primarily publishes print and electronic books and videos relating to information technology, including programming, web design, data analysis and hardware.