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Mastering Apache Spark 2.x

You're reading from Mastering Apache Spark 2.x Advanced techniques in complex Big Data processing, streaming analytics and machine learning

Product type Paperback

Published in Jul 2017

Publisher Packt

ISBN-13 9781786462749

Length 354 pages

Edition 2nd Edition

Languages

Scala

Tools

Apache Spark

Concepts

Big Data

Author (1):

Romeo Kienzler

View More author details

Table of Contents (15) Chapters

Preface

1. A First Taste and What’s New in Apache Spark V2 FREE CHAPTER

2. Apache Spark SQL

3. The Catalyst Optimizer

4. Project Tungsten

5. Apache Spark Streaming

6. Structured Streaming

7. Apache Spark MLlib

8. Apache SparkML

9. Apache SystemML

10. Deep Learning on Apache Spark with DeepLearning4j and H2O

11. Apache Spark GraphX

12. Apache Spark GraphFrames

13. Apache Spark with Jupyter Notebooks on IBM DataScience Experience

14. Apache Spark on Kubernetes

Windowing

Open source and commercial streaming engines such as IBM Streams, Apache Storm, or Apache Flink are using the concept of windows.

Windows specify the granularity or number of subsequent records, which are taken into account when executing aggregation functions on streams.

How streaming engines use windowing

There exist five different properties in two dimensions, which is how windows can be defined, where each window definition needs to use one property of each dimension.

The first property is the mode in which subsequent windows of a continuous stream of tuples can be created: sliding and tumbling.

The second is that the number of tuples that fall into a window has to be specified: either count-based, time-based or session...

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Authors (1)

Romeo Kienzler

Romeo Kienzler

Romeo Kienzler works as the chief data scientist in the IBM Watson IoT worldwide team, helping clients to apply advanced machine learning at scale on their IoT sensor data. He holds a Master's degree in computer science from the Swiss Federal Institute of Technology, Zurich, with a specialization in information systems, bioinformatics, and applied statistics.

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