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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

Write Storm topology to persist data into HDFS

In this section, we are going to cover how we can write the HDFS bolt to persist data into HDFS. In this section, we are focusing on the following points:

  • Consuming data from Kafka
  • The logic to store the data into HDFS
  • Rotating file into HDFS after a predefined time or size

Perform the following steps to create the topology to store the data into the HDFS:

  1. Create a new maven project with groupId com.stormadvance and artifactId storm-hadoop.
  2. Add the following dependencies in the pom.xml file. We are adding the Kafka Maven dependency in pom.xml to support Kafka Consumer. Please refer the previous chapter to produce data in Kafka as here we are going to consume data from Kafka and store in HDFS:
         <dependency> 
               <groupId>org.codehaus.jackson</groupId> 
               <artifactId>jackson...
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