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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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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 aggregator

The Trident aggregator is used to perform the aggregation operation on the input batch, partition, or input stream. For example, if a user wants to count the number of tuples present in each batch, then we can use the count aggregator to count the number of tuples in each batch. The output of the aggregator completely replaces the value of the input tuple. There are three types of aggregator available in Trident:

  • partitionAggregate
  • aggregate
  • persistenceAggregate

Let's understand each type of aggregator in detail.

partitionAggregate

As the name suggests, the partitionAggregate works on each partition instead of the whole batch. The output of partitionAggregate completely replaces the input tuple. Also...

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