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Mastering Apache Storm

You're reading from   Mastering Apache Storm Real-time big data streaming using Kafka, Hbase and Redis

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Product type Paperback
Published in Aug 2017
Publisher
ISBN-13 9781787125636
Length 284 pages
Edition 1st Edition
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Author (1):
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Ankit Jain Ankit Jain
Author Profile Icon Ankit Jain
Ankit Jain
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Toc

Table of Contents (13) Chapters Close

Preface 1. Real-Time Processing and Storm Introduction FREE CHAPTER 2. Storm Deployment, Topology Development, and Topology Options 3. Storm Parallelism and Data Partitioning 4. Trident Introduction 5. Trident Topology and Uses 6. Storm Scheduler 7. Monitoring of Storm Cluster 8. Integration of Storm and Kafka 9. Storm and Hadoop Integration 10. Storm Integration with Redis, Elasticsearch, and HBase 11. Apache Log Processing with Storm 12. Twitter Tweet Collection and Machine Learning

Programming languages

Storm was designed from the ground up to be usable with any programming language. At the core of Storm is a thrift definition for defining and submitting topologies. Since thrift can be used in any language, topologies can be defined and submitted in any language.

Similarly, spouts and bolts can be defined in any language. Non-JVM spouts and bolts communicate with Storm over a JSON-based protocol over stdin/stdout. Adapters that implement this protocol exist for Ruby, Python, JavaScript, and Perl. You can refer to https://github.com/apache/storm/tree/master/storm-multilang to find out about the implementation of these adapters.

Storm-starter has an example topology, https://github.com/apache/storm/tree/master/examples/storm-starter/multilang/resources, which implements one of the bolts in Python.

You have been reading a chapter from
Mastering Apache Storm
Published in: Aug 2017
Publisher:
ISBN-13: 9781787125636
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