Cassandra High Performance Cookbook Second Edition
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Cassandra High Performance Cookbook - Second Edition
Easily analyze big data with frameworks such as Hadoop, Hive, Presto, and SparkAbout This Book* Over 200 hands-on recipes to help you efficiently administer, design, and optimize large-scale Apache Cassandra Clusters* From a seasoned author, learn how to set up, use, and troubleshoot globally distributed large-scale databases* This book will help you create efficient data models and access patternsWho This Book Is ForThis book is for those who want to know how to set up, administer, and optimize large-scale Cassandra clusters. If you have never used a Cassandra before, then this book will bring you up to speed with the use cases of No SQL and eventual consistency model. For more experienced users, the book provides that will show to better design your existing applications and tune the Cassandra cluster to get the best performance and availability.What you will learn* Design and set up a Cassandra cluster in single and multiple data center environments* Interact with Cassandra using the versatile and powerful command line CQLSH* Write programs to access data in Cassandra* Tune a Cassandra cluster and your programs to get the best performance* Get to know how to model data to optimize storage and access* Perform big data analytics using Cassandra with Hadoop, Spark, and PrestoIn DetailApache Cassandra is a fault-tolerant, distributed data store, which offers linear scalability allowing it to be a storage platform for large high volume websites. It's master less and symmetric architecture provides easy scalability and high availability. Using the tuneable consistency the same Cassandra cluster can satisfy a variety of application requirements, for example very high availability and guaranteed consistency. This book provides detailed recipes starting from how to set up a single node Cassandra cluster to more complex installations involving multiple nodes and multiple datacentres. The recipes provide a detailed and hands-on introduction to the CQL language through the CQL shell and introduces the Java and Python drivers for API access.The book provides detailed coverage on how to tune Cassandra to get the best performance and explains the tuneable consistency, availability, and partition tolerance through working example code snippets.The recipes demonstrate how to design a data model and schema to solve a variety of application requirements. This book introduces how to use Cassandra with big data analytics frameworks such as Hadoop and Spark.A significant portion of the book deals with recipes on administering, monitoring, and automating operations tasks to run a large-scale multi datacentre Cassandra cluster.
Mastering Apache Cassandra - Second Edition
Author: Nishant Neeraj
language: en
Publisher: Packt Publishing Ltd
Release Date: 2015-03-26
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.
Cassandra: The Definitive Guide
Author: Jeff Carpenter
language: en
Publisher: "O'Reilly Media, Inc."
Release Date: 2016-06-29
Imagine what you could do if scalability wasn't a problem. With this hands-on guide, you’ll learn how the Cassandra database management system handles hundreds of terabytes of data while remaining highly available across multiple data centers. This expanded second edition—updated for Cassandra 3.0—provides the technical details and practical examples you need to put this database to work in a production environment. Authors Jeff Carpenter and Eben Hewitt demonstrate the advantages of Cassandra’s non-relational design, with special attention to data modeling. If you’re a developer, DBA, or application architect looking to solve a database scaling issue or future-proof your application, this guide helps you harness Cassandra’s speed and flexibility. Understand Cassandra’s distributed and decentralized structure Use the Cassandra Query Language (CQL) and cqlsh—the CQL shell Create a working data model and compare it with an equivalent relational model Develop sample applications using client drivers for languages including Java, Python, and Node.js Explore cluster topology and learn how nodes exchange data Maintain a high level of performance in your cluster Deploy Cassandra on site, in the Cloud, or with Docker Integrate Cassandra with Spark, Hadoop, Elasticsearch, Solr, and Lucene