Create Cassandra Service
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CASSANDRA
Author: Jeff Carpenter (Systems architect)
language: en
Publisher: "O'Reilly Media, Inc."
Release Date: 2022
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 revised third edition--updated for Cassandra 4.0 and new developments in the Cassandra ecosystem, including deployments in Kubernetes with K8ssandra--provides technical details and practical examples to help you put this database to work in a production environment. Authors Jeff Carpenter and Eben Hewitt demonstrate the advantages of Cassandra's nonrelational design, with special attention to data modeling. Developers, DBAs, and application architects looking to solve a database scaling issue or future-proof an application will learn how to 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 Design and develop applications using client drivers Explore cluster topology and learn how nodes exchange data Maintain a high level of performance in your cluster Deploy Cassandra onsite, in the cloud, or with Docker and Kubernetes Integrate Cassandra with Spark, Kafka, Elasticsearch, Solr, and Lucene.
Kubernetes Microservices with Docker
Start using Kubernetes in complex big data and enterprise applications, including Docker containers. Starting with installing Kubernetes on a single node, the book introduces Kubernetes with a simple Hello example and discusses using environment variables in Kubernetes. Next, Kubernetes Microservices with Docker discusses using Kubernetes with all major groups of technologies such as relational databases, NoSQL databases, and in the Apache Hadoop ecosystem. The book concludes with using multi container pods and installing Kubernetes on a multi node cluster. /div "a concise but clear introduction to containers, Docker and Kubernetes, using simple real-world examples to pass on the core concepts, via repetition, and is a very useful enabler." 10/10 Dave Hay MBCS CITP: review for BCS, The Chartered Institute for IT (http://www.bcs.org/content/conWebDoc/58512) What You Will Learn Install Kubernetes on a single node Set environment variables Create multi-container pods using Docker Use volumes Use Kubernetes with the Apache Hadoop ecosystem, NoSQL databases, and RDBMSs Install Kubernetes on a multi-node cluster Who This Book Is For Application developers including Apache Hadoop developers, database developers and NoSQL developers.
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