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Practical Real-time Data Processing and Analytics

You're reading from   Practical Real-time Data Processing and Analytics Distributed Computing and Event Processing using Apache Spark, Flink, Storm, and Kafka

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Product type Paperback
Published in Sep 2017
Publisher Packt
ISBN-13 9781787281202
Length 360 pages
Edition 1st Edition
Languages
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Authors (2):
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Shilpi Saxena Shilpi Saxena
Author Profile Icon Shilpi Saxena
Shilpi Saxena
Saurabh Gupta Saurabh Gupta
Author Profile Icon Saurabh Gupta
Saurabh Gupta
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Table of Contents (14) Chapters Close

Preface 1. Introducing Real-Time Analytics FREE CHAPTER 2. Real Time Applications – The Basic Ingredients 3. Understanding and Tailing Data Streams 4. Setting up the Infrastructure for Storm 5. Configuring Apache Spark and Flink 6. Integrating Storm with a Data Source 7. From Storm to Sink 8. Storm Trident 9. Working with Spark 10. Working with Spark Operations 11. Spark Streaming 12. Working with Apache Flink 13. Case Study

Setting up and configuring Cassandra


Before moving towards setting up and configuring Cassandra, let's explain what Cassandra is and why it is so popular. Cassandra is a NoSQL columnar database. If you need high scalability with high availability then Cassandra is the best choice. It has high read and write performance but with eventual consistency.

Eventual consistency is when you insert a row in a database and at same time another user reads the same table, making it possible that the newly added row would be visible to the user or not. Keyspace in Cassandra is the same as a database in RDMS. The rest of the terminology is the same as RDMS. Cassandra is an open source tool but if you need to manage clusters with designed a UI, then go for DataStax. DataStax provides paid premium services and includes full-time support. Now, let's see how to set up Cassandra.

Setting up Cassandra

Download the latest version 3.10 from http://cassandra.apache.org/download/and the older version can be downloaded...

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