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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

Streaming transformations


As in the previous word count example, we saw that words from each line were being counted once and for the next set of records the counter was reset again. But what if we want to add the previous state count to the new set of words in the following batch to come? Can we do that and how? The answer to the first part of the question is, in Spark Streaming there are two kinds of transformation, stateful and stateless transformation, so if we want to preserve the previous state then one will have to opt for stateful transformation rather than the stateless transformation that we achieved in the previous example.

Stream processing can be stateless or stateful based on the requirement. Some stream processing problems may require maintaining a state over a period of time, others may not.

Consider that an airline company wants to process data consistiting of the temperature reading of all active a flights at real time. If the airline wants to just print or store the reading...

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