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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

Trident state

Trident provides an abstraction for reading from and writing results to stateful sources. We can maintain the state either internally to the topology (memory), or we can store it in external sources (Memcached or Cassandra).

Let's consider that we are maintaining the output of the preceding hello world Trident topology in a database. Every time you process the tuple, the count of country present in a tuple is increased in the database. We can't achieve exactly-once processing by only maintaining a count in the database. The reason is that if any tuple failed during processing, then the failed tuple is retried. This gives us a problem while updating the state, because we are not sure whether the state of this tuple was updated previously or not. If the tuple has failed before updating the state, then retrying the tuple will increase the count in the database...

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