Mastering Apache Cassandra 3.x Third Edition

An expert guide to improving database scalability and availability without compromising performance

Aaron Ploetz , Tejaswi Malepati , Nishant Neeraj 지음

Packt(GCO Science) 2018년 10월 31일 출간

작품소개

책소개

▶Book Description
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.

▶What You Will Learn
？ Write programs more efficiently using Cassandra's features more efficiently
？ Exploit the given infrastructure, improve performance, and tweak the Java Virtual Machine (JVM)
？ Use CQL3 in your application in order to simplify working with Cassandra
？ Configure Cassandra and fine-tune its parameters depending on your needs
？ Set up a cluster and learn how to scale it
？ Monitor a Cassandra cluster in different ways
？ Use Apache Spark and other big data processing tools

▶Key Features
？ Write programs more efficiently using Cassandra's features with the help of examples
？ Configure Cassandra and fine-tune its parameters depending on your needs
？ Integrate Cassandra database with Apache Spark and build strong data analytics pipeline

▶Who This Book Is For
This book is intended for a DBA who is responsible for supporting Apache Cassandra clusters. It may also benefit full-stack engineers at smaller companies. While these individuals primarily build applications, they may also have to maintain and support their Cassandra cluster out of necessity.

목차

▶TABLE of CONTENTS
1: QUICK START
2: CASSANDRA ARCHITECTURE
3: EFFECTIVE CQL
4: CONFIGURING A CLUSTER
5: PERFORMANCE TUNING
6: MANAGING A CLUSTER
7: MONITORING
8: APPLICATION DEVELOPMENT
9: INTEGRATION WITH APACHE SPARK
10: Appendix A

책 속으로

▶What this book covers
？ Chapter 1, Quick Start, walks the reader through getting started with Apache Cassandra. As the title suggests, explanations will be brief in favor of guiding the reader toward quickly standing up an Apache Cassandra single-node cluster.

？ Chapter 2, Cassandra Architecture, covers the ideas and theories behind how Apache Cassandra works. These concepts will be useful going forward, as an understanding of Cassandra's inner workings can help in building high-performing data models.

？ Chapter 3, Effective CQL, introduces the reader to the CQL. It describes building appropriate data models and how to leverage CQL to get the most out of your cluster.

？ Chapter 4, Configuring a Cluster, details the configuration files and settings that go into building an Apache Cassandra Cluster. In addition, this chapter also describes the effects that some of the settings have, and how they can be used to keep your cluster running well.

？ Chapter 5, Performance Tuning, discusses the extra settings, configurations, and design considerations that can help to improve performance or mitigate issues.

？ Chapter 6, Managing a Cluster, goes into detail when describing the nodetool utility, and how it can be used for operations on an Apache Cassandra cluster. Adding and removing nodes is covered, as well as taking and restoring from backups.

？ Chapter 7, Monitoring, describes how to integrate a technology stack that provides a window into an Apache Cassandra cluster's history and performance metrics.

？ Chapter 8, Application Development, takes the reader through design considerations around coding Java applications to work with an Apache Cassandra cluster.

？ Chapter 9, Integration with Apache Spark, talks about installing and using Apache Spark in order to analyze and discover value in your data.

？ Appendix A, References, In this chapter you will find links present for various references present throughout the book.

출판사 서평

▶ Preface
This book is intended to help you understand the Apache Cassandra NoSQL database. It will describe procedures and methods for configuring, installing, and maintaining a highperforming Cassandra cluster. This book can serve as a reference for some of the more obscure configuration parameters and commands that may be needed to operate and maintain a cluster. Also, tools and methods will be suggested for integrating Cassandra with Apache Spark, as well as practices for building Java applications that use Cassandra.

인물정보

저자(글) Aaron Ploetz

Aaron Ploetz is the NoSQL Engineering Lead for Target, where his DevOps team supports Cassandra, MongoDB, and Neo4j. He has been named a DataStax MVP for Apache Cassandra three times and has presented at multiple events, including the DataStax Summit and Data Day Texas. Aaron earned a BS in Management/Computer Systems from the University of Wisconsin-Whitewater, and an MS in Software Engineering from Regis University. He and his wife, Coriene, live with their three children in the Twin Cities area.

저자(글) Tejaswi Malepati

Tejaswi Malepati is the Cassandra Tech Lead for Target. He has been instrumental in designing and building custom Cassandra integrations, including web-based SQL interface and data validation frameworks between Oracle and Cassandra. Tejaswi earned a master's degree in computer science from the University of New Mexico, and a bachelor's degree in Electronics and Communication from Jawaharlal Nehru Technological University in India. He is passionate about identifying and analyzing data patterns in datasets using R, Python, Spark, and Cassandra and MySQL.

저자(글) Nishant Neeraj

Nishant Neeraj is an independent software developer with experience in developing and planning out architectures for massively scalable data storage and data processing systems. Over the years, he has helped to design and implement a wide variety of products and systems for companies, ranging from small start-ups to large multinational companies. Currently, he helps drive WealthEngine's core product to the next level by leveraging a variety of big data technologies.