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Ralph Kimball, Margy Ross
Ralph Kimball invented a data warehousing technique called ?dimensional modelling? and popularised it in his first Wiley bestseller The Data Warehouse Toolkit. Since then dimensional modelling has become the most widely accepted technique for data warehouse design. Since the first edition, Kimball has improved on his earlier techniques and created many new ones. In this second edition, he provides a comprehensive collection of all of them, from basic to advanced, and strategies for optimising data warehouse design for common business applications. He includes examples for retail sales, inventory management, procurement, orders and invoices, customer relationship management, accounting, financial services, telecommunication and utilities, health care, insurance and more. He also presents unique modelling techniques for e-commerce and shows strategies for optimising performance. A companion Web site provides updates on dimensional modelling techniques, links to related sites and source code where appropriate.
Counsels programmers and administrators for big and small organizations on how to work with large-scale application datasets using Apache Hadoop, discussing its capacity for storing and processing large amounts of data while demonstrating best practices for building reliable and scalable distributed systems.
Michael James Hernandez, John Viescas
"Master every business SQL skill you need! Grouping, totaling, summaries, modifying databases, integrating data from multiple tables, and much more! Includes video introduction, 2+ hours of expert audio commentary, 200+ animated figures, 100+ self review questions, 100+ exercises, searching, hyperlinking, and more."--Container.
Whether you're building the newest and hottest social media web site or developing an internal-use-only enterprise business intelligence application, scaling your data model has never been more important. Traditional relational databases, while familiar, present significant challenges and complications when trying to scale up to such "big data" needs. Into this world steps MongoDB, a leading NoSQL database, to address these scaling challenges while also simplifying the process of development. However, in all the hype surrounding big data, many sites have launched their business on NoSQL databases without an understanding of the techniques necessary to effectively use the features of their chosen database. MongoDB Applied Design Patterns provides the much-needed connection between the features of MongoDB and the business problems that it is suited to solve. The book's focus on the practical aspects of the MongoDB implementation makes it an ideal purchase for developers charged with bringing MongoDB's scalability to bear on the particular problem you've been tasked to solve.
Create a MongoDB cluster that will to grow to meet the needs of your application. With this short and concise book, you'll get guidelines for setting up and using clusters to store a large volume of data, and learn how to access the data efficiently. In the process, you'll understand how to make your application work with a distributed database system. Scaling MongoDB will help you: Set up a MongoDB cluster through sharding Work with a cluster to query and update data Operate, monitor, and backup your cluster Plan your application to deal with outages By following the advice in this book, you'll be well on your way to building and running an efficient, predictable distributed system using MongoDB.
Russell Bradberry, Eric Lubow
”Eric and Russell were early adopters of Cassandra at SimpleReach. In Practical Cassandra, you benefit from their experience in the trenches administering Cassandra, developing against it, and building one of the first CQL drivers. If you are deploying Cassandra soon, or you inherited a Cassandra cluster to tend, spend some time with the deployment, performance tuning, and maintenance chapters… If you are new to Cassandra, I highly recommend the chapters on data modeling and CQL.” –From the Foreword by Jonathon Ellis, Apache Cassandra Chair Build and Deploy Massively Scalable, Super-fast Data Management Applications with Apache Cassandra Practical Cassandra is the first hands-on developer's guide to building Cassandra systems and applications that deliver breakthrough speed, scalability, reliability, and performance. Fully up to date, it reflects the latest versions of Cassandra–including Cassandra Query Language (CQL), which dramatically lowers the learning curve for Cassandra developers. Pioneering Cassandra developers and Datastax MVPs Russell Bradberry and Eric Lubow walk you through every step of building a real production application that can store enormous amounts of structured, semi-structured, and unstructured data. Drawing on their exceptional expertise, Bradberry and Lubow share practical insights into issues ranging from querying to deployment, management, maintenance, monitoring, and troubleshooting. The authors cover key issues, from architecture to migration, and guide you through crucial decisions about configuration and data modeling. They provide tested sample code, detailed explanations of how Cassandra works ”under the covers,” and new case studies from three cutting-edge users: Ooyala, Hailo, and eBay. Coverage includes Understanding Cassandra's approach, architecture, key concepts, and primary use cases– and why it's so blazingly fast Getting Cassandra up and running on single nodes and large clusters Applying the new design patterns, philosophies, and features that make Cassandra such a powerful data store Leveraging CQL to simplify your transition from SQL-based RDBMSes Deploying and provisioning through the cloud or on bare-metal hardware Choosing the right configuration options for each type of workload Tweaking Cassandra to get maximum performance from your hardware, OS, and JVM Mastering Cassandra's essential tools for maintenance and monitoring Efficiently solving the most common problems with Cassandra deployment, operation, and application development