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  • Book Overview & Buying Mastering Apache Cassandra - Second Edition
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Mastering Apache Cassandra - Second Edition

Mastering Apache Cassandra - Second Edition

By : Nishant Neeraj
4.6 (10)
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Mastering Apache Cassandra - Second Edition

Mastering Apache Cassandra - Second Edition

4.6 (10)
By: Nishant Neeraj

Overview of this book

The book is aimed at intermediate developers with an understanding of core database concepts who want to become a master at implementing Cassandra for their application.
Table of Contents (10 chapters)
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Preface
Preface
What this book covers
What you need for this book
Who this book is for
Conventions
Reader feedback
Customer support
Free Chapter
1
1. Quick Start
1. Quick Start
Introduction to Cassandra
A brief introduction to a data model
Installing Cassandra locally
Cassandra in action
Summary
2
2. Cassandra Architecture
2. Cassandra Architecture
Problems in the RDBMS world
Enter NoSQL
Cassandra
Understanding the architecture of Cassandra
Summary
3
3. Effective CQL
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3. Effective CQL
The Cassandra data model
CQL shell commands
Summary
4
4. Deploying a Cluster
4. Deploying a Cluster
Evaluating requirements
System configurations
The required software
Installing Cassandra
Configuring a Cassandra cluster
Authorization and authentication
Summary
5
5. Performance Tuning
5. Performance Tuning
Stress testing
Performance tuning
Summary
6
6. Managing a Cluster – Scaling, Node Repair, and Backup
6. Managing a Cluster – Scaling, Node Repair, and Backup
Scaling
Replacing a node
Backup and restoration
Load balancing
DataStax OpsCenter – managing large clusters
Summary
7
7. Monitoring
7. Monitoring
Cassandra's JMX interface
Cassandra's nodetool utility
DataStax OpsCenter
Nagios – monitoring and notification
Cassandra log
Troubleshooting
Summary
8
8. Integration with Hadoop
8. Integration with Hadoop
Using Hadoop
Hadoop and Cassandra
Cassandra with Hadoop MapReduce
Cassandra and Hadoop in action
Hadoop in a Cassandra cluster
Integration with Pig
Summary
9
Index
Index

Chapter 3. Effective CQL

This chapter will introduce you to the underlying data structure of tables in Cassandra. Let's set some development rules of thumb before we dive into CQL. With CQL 3, Cassandra development team has done a commendable job of almost entirely eliminating any chance of using an antipattern, and at the same time bringing an interface that is SQL people friendly.

If you are a developer, this is probably the most important chapter for you. You will get a sense of things that are possible and not possible when working with Cassandra. You may also want to refer Chapter 8, Integration with Hadoop, to understand how to use Cassandra with various big data technologies such as the Hadoop ecosystem and Spark/Shark.

When dealing with Cassandra, keep the following things in mind:

  • Denormalize, denormalize, and denormalize: Forget about old school 3NF in Cassandra; the fewer the network trips, the better the performance. Denormalize wherever you can for quicker retrieval...

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