Book Image

Mastering Apache Cassandra 3.x - Third Edition

By : Aaron Ploetz, Tejaswi Malepati, Nishant Neeraj
Book Image

Mastering Apache Cassandra 3.x - Third Edition

By: Aaron Ploetz, Tejaswi Malepati, Nishant Neeraj

Overview of this book

With ever-increasing rates of data creation, the demand for storing data fast and reliably becomes a need. Apache Cassandra is the perfect choice for building fault-tolerant and scalable databases. Mastering Apache Cassandra 3.x teaches you how to build and architect your clusters, configure and work with your nodes, and program in a high-throughput environment, helping you understand the power of Cassandra as per the new features. Once you’ve covered a brief recap of the basics, you’ll move on to deploying and monitoring a production setup and optimizing and integrating it with other software. You’ll work with the advanced features of CQL and the new storage engine in order to understand how they function on the server-side. You’ll explore the integration and interaction of Cassandra components, followed by discovering features such as token allocation algorithm, CQL3, vnodes, lightweight transactions, and data modelling in detail. Last but not least you will get to grips with Apache Spark. By the end of this book, you’ll be able to analyse big data, and build and manage high-performance databases for your application.
Table of Contents (12 chapters)

Summary

Apache Cassandra is based on a peer-to-peer architecture, which makes it difficult to manage and monitor when we have more nodes. This chapter provides a wide variety of options available for monitoring and logging for Apache Cassandra, which will help in identifying issues proactively. We started with a single-node GUI-based monitoring with JConsole, followed by a CLI utility, JMXTerm, which can easily be integrated to jobs/scripts for any kind of operation. These two are really handy for monitoring or managing in the current state, but neither of them would help historical data-analysis when there is an outage. Inbuilt tools from Cassandra also would not solve this, because nodetool would just be a wrapper to JMXTerm.

The introduction of a metric stack is important. It would contain a metrics publisher, Telegraf for system metrics, and JMXTrans for JVM-related metrics...