Building Structured Streaming Jobs in Spark
Lecture
Opsgility Gil
Intermediate
0 h 0 m
2018-07-30
Lecture Overview
In this course, you will be introduced to Spark Structured Streaming. You will learn about data sources and data sinks and working with the Structured Streaming APIs. You will look at stream processing techniques such as windowing and aggregation functions, checkpointing and watermarking and their use in stream processing jobs. Finally, you will investigate fault tolerance in stream processing jobs.
Objectives
  • Understand how to use data sources and data sinks and working with the Structured Streaming APIs
  • Understand stream processing techniques such as windowing and aggregation functions, checkpointing and watermarking and their use in stream processing jobs
  • Understand fault tolerance in stream processing jobs.
Pre-Requisites
  • Familiarity with cloud computing concepts
  • Familiarity with Spark
Lecture Modules
In this course, you will be introduced to Spark Structured Streaming. You will learn about data sources and data sinks and working with the Structured Streaming APIs. You will look at stream processing techniques such as windowing and aggregation functions, checkpointing and watermarking and their use in stream processing jobs. Finally, you will investigate fault tolerance in stream processing jobs.
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