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Mastering Hadoop

You're reading from Mastering Hadoop Go beyond the basics and master the next generation of Hadoop data processing platforms

Product type Paperback

Published in Dec 2014

Publisher

ISBN-13 9781783983643

Length 374 pages

Edition 1st Edition

Tools

Hadoop

Concepts

Data Processing

Author (1):

Sandeep Karanth

View More author details

Table of Contents (15) Chapters

Preface

1. Hadoop 2.X FREE CHAPTER

2. Advanced MapReduce

3. Advanced Pig

4. Advanced Hive

5. Serialization and Hadoop I/O

6. YARN – Bringing Other Paradigms to Hadoop

7. Storm on YARN – Low Latency Processing in Hadoop

8. Hadoop on the Cloud

9. HDFS Replacements

10. HDFS Federation

11. Hadoop Security

12. Analytics Using Hadoop

A. Hadoop for Microsoft Windows

Index

Summary

The number one goal of the streaming paradigm is to cater to low-latency applications. The Storm-on-YARN project has brought this paradigm to Hadoop. Stakeholders can now multiplex streaming and batch processing on a single Hadoop cluster and cater to different kinds of applications.

There are a number of streaming frameworks available, such as Microsoft SQL Server StreamInsight, S4, and Apache Storm, among others. Apache Storm is open source, part of the Apache Software Foundation, Hadoop integrated, and has a large community behind it, making it attractive for distributed stream processing.

Some key takeaways from this chapter are as follows:

The basic data model in Apache Storm is an unbounded sequence of tuples called Streams.
Long-standing queries are modeled as computational topologies. The data stream flows through these topologies.
Apache Storm provides the following primitives:
- Spouts: They convert input data into streams
- Bolts: They take an input stream, do some processing on...

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Authors (1)

Karanth

Karanth

Sandeep Karanth is a technical architect who specializes in building and operationalizing software systems. He has more than 14 years of experience in the software industry, working on a gamut of products ranging from enterprise data applications to newer-generation mobile applications. He has primarily worked at Microsoft Corporation in Redmond, Microsoft Research in India, and is currently a cofounder at Scibler, architecting data intelligence products.

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