Follow this handbook to build, configure, tune, and secure Apache Cassandra databases. Start with the installation of Cassandra and move on to the creation of a single instance, and then a cluster of Cassandra databases. Cassandra is increasingly a key player in many big data environments, and this book shows you how to use Cassandra with Apache Spark, a popular big data processing framework. Also covered are day-to-day topics of importance such as the backup and recovery of Cassandra databases, using the right compression and compaction strategies, and loading and unloading data. Expert Apache Cassandra Administration provides numerous step-by-step examples starting with the basics of a Cassandra database, and going all the way through backup and recovery, performance optimization, and monitoring and securing the data. The book serves as an authoritative and comprehensive guide to the building and management of simple to complex Cassandra databases. The book: Takes you through building a Cassandra database from installation of the software and creation of a single database, through to complex clusters and data centers Provides numerous examples of actual commands in a real-life Cassandra environment that show how to confidently configure, manage, troubleshoot, and tune Cassandra databases Shows how to use the Cassandra configuration properties to build a highly stable, available, and secure Cassandra database that always operates at peak efficiency What You'll Learn Install the Cassandra software and create your first database Understand the Cassandra data model, and the internal architecture of a Cassandra database Create your own Cassandra cluster, step-by-step Run a Cassandra cluster on Docker Work with Apache Spark by connecting to a Cassandra database Deploy Cassandra clusters in your data center, or on Amazon EC2 instances Back up and restore mission-critical Cassandra databases Monitor, troubleshoot, and tune production Cassandra databases, and cut your spending on resources such as memory, servers, and storage Who This Book Is For Database administrators, developers, and architects who are looking for an authoritative and comprehensive single volume for all their Cassandra administration needs. Also for administrators who are tasked with setting up and maintaining highly reliable and high-performing Cassandra databases. An excellent choice for big data administrators, database administrators, architects, and developers who use Cassandra as their key data store, to support high volume online transactions, or as a decentralized, elastic data store.

Follow this handbook to build, configure, tune, and secure Apache Cassandra databases. Start with the installation of Cassandra and move on to the creation of a single instance, and then a cluster of Cassandra databases. Cassandra is increasingly a key player in many big data environments, and this book shows you how to use Cassandra with Apache Spark, a popular big data processing framework. Also covered are day-to-day topics of importance such as the backup and recovery of Cassandra databases, using the right compression and compaction strategies, and loading and unloading data. Expert Apache Cassandra Administration provides numerous step-by-step examples starting with the basics of a Cassandra database, and going all the way through backup and recovery, performance optimization, and monitoring and securing the data. The book serves as an authoritative and comprehensive guide to the building and management of simple to complex Cassandra databases. The book: Takes you through building a Cassandra database from installation of the software and creation of a single database, through to complex clusters and data centers Provides numerous examples of actual commands in a real-life Cassandra environment that show how to confidently configure, manage, troubleshoot, and tune Cassandra databases Shows how to use the Cassandra configuration properties to build a highly stable, available, and secure Cassandra database that always operates at peak efficiency What You'll Learn: Install the Cassandra software and create your first database Understand the Cassandra data model, and the internal architecture of a Cassandra database Create your own Cassandra cluster, step-by-step Run a Cassandra cluster on Docker Work with Apache Spark by connecting to a Cassandra database Deploy Cassandra clusters in your data center, or on Amazon EC2 instances Back up and restore mission-critical Cassandra databases Monitor, troubleshoot, and tune production Cassandra databases, and cut your spending on resources such as memory, servers, and storage.

Build, manage, and configure high-performing, reliable NoSQL database for your applications with Cassandra Key FeaturesWrite programs more efficiently using Cassandra's features with the help of examplesConfigure Cassandra and fine-tune its parameters depending on your needsIntegrate Cassandra database with Apache Spark and build strong data analytics pipelineBook 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 learnWrite programs more efficiently using Cassandra's features more efficientlyExploit the given infrastructure, improve performance, and tweak the Java Virtual Machine (JVM)Use CQL3 in your application in order to simplify working with CassandraConfigure Cassandra and fine-tune its parameters depending on your needsSet up a cluster and learn how to scale itMonitor a Cassandra cluster in different waysUse Apache Spark and other big data processing toolsWho this book is for Mastering Apache Cassandra 3.x is for you if you are a big data administrator, database administrator, architect, or developer who wants to build a high-performing, scalable, and fault-tolerant database. Prior knowledge of core concepts of databases is required.

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

Beginning Apache Cassandra Development introduces you to one of the most robust and best-performing NoSQL database platforms on the planet. Apache Cassandra is a document database following the JSON document model. It is specifically designed to manage large amounts of data across many commodity servers without there being any single point of failure. This design approach makes Apache Cassandra a robust and easy-to-implement platform when high availability is needed. Apache Cassandra can be used by developers in Java, PHP, Python, and JavaScript—the primary and most commonly used languages. In Beginning Apache Cassandra Development, author and Cassandra expert Vivek Mishra takes you through using Apache Cassandra from each of these primary languages. Mishra also covers the Cassandra Query Language (CQL), the Apache Cassandra analog to SQL. You'll learn to develop applications sourcing data from Cassandra, query that data, and deliver it at speed to your application's users. Cassandra is one of the leading NoSQL databases, meaning you get unparalleled throughput and performance without the sort of processing overhead that comes with traditional proprietary databases. Beginning Apache Cassandra Development will therefore help you create applications that generate search results quickly, stand up to high levels of demand, scale as your user base grows, ensure operational simplicity, and—not least—provide delightful user experiences.

This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book. The Comprehensive, Up-to-Date Apache Hadoop Administration Handbook and Reference “Sam Alapati has worked with production Hadoop clusters for six years. His unique depth of experience has enabled him to write the go-to resource for all administrators looking to spec, size, expand, and secure production Hadoop clusters of any size.” —Paul Dix, Series Editor In Expert Hadoop® Administration, leading Hadoop administrator Sam R. Alapati brings together authoritative knowledge for creating, configuring, securing, managing, and optimizing production Hadoop clusters in any environment. Drawing on his experience with large-scale Hadoop administration, Alapati integrates action-oriented advice with carefully researched explanations of both problems and solutions. He covers an unmatched range of topics and offers an unparalleled collection of realistic examples. Alapati demystifies complex Hadoop environments, helping you understand exactly what happens behind the scenes when you administer your cluster. You’ll gain unprecedented insight as you walk through building clusters from scratch and configuring high availability, performance, security, encryption, and other key attributes. The high-value administration skills you learn here will be indispensable no matter what Hadoop distribution you use or what Hadoop applications you run. Understand Hadoop’s architecture from an administrator’s standpoint Create simple and fully distributed clusters Run MapReduce and Spark applications in a Hadoop cluster Manage and protect Hadoop data and high availability Work with HDFS commands, file permissions, and storage management Move data, and use YARN to allocate resources and schedule jobs Manage job workflows with Oozie and Hue Secure, monitor, log, and optimize Hadoop Benchmark and troubleshoot Hadoop

This graduate-level textbook is ideally suited for lecturing the most relevant topics of Edge Computing and its ties to Artificial Intelligence (AI) and Machine Learning (ML) approaches. It starts from basics and gradually advances, step-by-step, to ways AI/ML concepts can help or benefit from Edge Computing platforms. The book is structured into seven chapters; each comes with its own dedicated set of teaching materials (practical skills, demonstration videos, questions, lab assignments, etc.). Chapter 1 opens the book and comprehensively introduces the concept of distributed computing continuum systems that led to the creation of Edge Computing. Chapter 2 motivates the use of container technologies and how they are used to implement programmable edge computing platforms. Chapter 3 introduces ways to employ AI/ML approaches to optimize service lifecycles at the edge. Chapter 4 goes deeper in the use of AI/ML and introduces ways to optimize spreading computational tasks along edge computing platforms. Chapter 5 introduces AI/ML pipelines to efficiently process generated data on the edge. Chapter 6 introduces ways to implement AI/ML systems on the edge and ways to deal with their training and inferencing procedures considering the limited resources available at the edge-nodes. Chapter 7 motivates the creation of a new orchestrator independent object model to descriptive objects (nodes, applications, etc.) and requirements (SLAs) for underlying edge platforms. To provide hands-on experience to students and step-by-step improve their technical capabilities, seven sets of Tutorials-and-Labs (TaLs) are also designed. Codes and Instructions for each TaL is provided on the book website, and accompanied by videos to facilitate their learning process.