|Title||Learning Cassandra for Administrators|
|Sub Title||Optimize high-scale data by tuning and troubleshooting using Cassandra|
|Category||Computer & Programming|
|Tags||Data Mining Processing|
|File Size||2.1 MB|
Apache Cassandra is a massively scalable open source NoSQL database. Cassandra is perfect for managing large amounts of structured, semi-structured, and unstructured data across multiple data centers and the cloud. Cassandra delivers linear scalability and performance across many commodity servers with no single point of failure. This book starts by explaining how to derive the solution, basic concepts, and CAP theorem. You will learn how to install and configure a Cassandra cluster as well as tune the cluster for performance. After reading the book, you should be able to understand why the system works in a particular way, and you will also be able to find patterns (and/or use cases) and anti-patterns which would potentially cause performance degradation. Furthermore, the book explains how to configure Hadoop, vnodes, multi-DC clusters, enabling trace, enabling various security features, and querying data from Cassandra. Starting with explaining about the trade-offs, we gradually learn about setting up and configuring high performance clusters. This book will help the administrators understand the system better by understanding various components in Cassandra’s architecture and hence be more productive in operating the cluster. This book talks about the use cases and problems, anti-patterns, and potential practical solutions as opposed to raw techniques. You will learn about kernel and JVM tuning parameters that can be adjusted to get the maximum use out of system resources.