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Apache Spark 2.x for Java Developers

You're reading from   Apache Spark 2.x for Java Developers Explore big data at scale using Apache Spark 2.x Java APIs

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Product type Paperback
Published in Jul 2017
Publisher Packt
ISBN-13 9781787126497
Length 350 pages
Edition 1st Edition
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Authors (2):
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Sourav Gulati Sourav Gulati
Author Profile Icon Sourav Gulati
Sourav Gulati
Sumit Kumar Sumit Kumar
Author Profile Icon Sumit Kumar
Sumit Kumar
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Table of Contents (12) Chapters Close

Preface 1. Introduction to Spark FREE CHAPTER 2. Revisiting Java 3. Let Us Spark 4. Understanding the Spark Programming Model 5. Working with Data and Storage 6. Spark on Cluster 7. Spark Programming Model - Advanced 8. Working with Spark SQL 9. Near Real-Time Processing with Spark Streaming 10. Machine Learning Analytics with Spark MLlib 11. Learning Spark GraphX

Structured Streaming


Structured is a brand new edition in Apache Spark's streaming processing vertical. It is a stream processing engine built on top of the Spark SQL engine. With the introduction of structured streaming, a unification bond of batch processing and stream processing as it allows us to develop a stream processing is enabled application similar to the batch processing application. At the same time, it is scalable and fault tolerant as well.

As per Apache Spark's documentation,

Structured Streaming provides fast, scalable, fault-tolerant, end-to-end exactly-once stream processing without the user having to reason about streaming

.

Instead of using DStream in structured streaming, the dataset API can be used and it is the responsibility of the Spark SQL engine to keep the dataset updated as new streaming data arrives. As the dataset API is used, all the Spark SQL operations are available. Therefore, users can use SQL queries on the stream data using the optimized Spark SQL engine...

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