Structured Streaming: Philosophy behind it

Knoldus Blogs

In our previous blogs:

  1. Structured Streaming: What is it? &
  2. Structured Streaming: How it works?

We got to know 2 major points about Structured Streaming –

  1. It is a fast, scalable, fault-tolerant, end-to-end, exactly-once stream processing API that helps users in building streaming applications.
  2. It treats the live data stream as a table that is being continuously appended/updated which allows us to express our streaming computation as a standard batch-like query as on a static table, whereas Spark runs it as an incremental query on the unbounded input table.

In this blog post, we will talk about the philosophy or the programming model of the Structured Streaming. So, let’s get started with the example that we saw in the previous blog post.

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About Himanshu Gupta

Himanshu Gupta is a lead consultant having more than 4 years of experience. He is always keen to learn new technologies. He not only likes programming languages but Data Analytics too. He has sound knowledge of "Machine Learning" and "Pattern Recognition".He believes that best result comes when everyone works as a team. He likes listening to Coding ,music, watch movies, and read science fiction books in his free time.
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