Apress.Beginning.Database.Design.From.Novice.to.Professional.Jan.2007.pdf

Energy Efficient Servers: Blueprints for Data Center Optimization

Learn various commercial and open source products that perform SQL on Big Data platforms. You will understand the architectures of the various SQL engines being used and how the tools work internally in terms of execution, data movement, latency, scalability, performance, and system requirements. This book consolidates in one place solutions to the challenges associated with the requirements of speed, scalability, and the variety of operations needed for data integration and SQL operations. After discussing the history of the how and why of SQL on Big Data, the book provides in-depth insight into the products, architectures, and innovations happening in this rapidly evolving space. SQL on Big Data discusses in detail the innovations happening, the capabilities on the horizon, and how they solve the issues of performance and scalability and the ability to handle different data types. The book covers how SQL on Big Data engines are permeating the OLTP, OLAP, and Operational analytics space and the rapidly evolving HTAP systems. You will learn the details of: Batch Architectures ―an understanding of the internals and how the existing Hive engine is built and how it is evolving continually to support new features and provide lower latency on queries Interactive Architectures―an understanding of how SQL engines are architected to support low latency on large data sets Streaming Architectures ―an understanding of how SQL engines are architected to support queries on data in motion using in-memory and lock-free data structures Operational Architectures―an understanding of how SQL engines are architected for transactional and operational systems to support transactions on Big Data platforms Innovative Architectures―an exploration of the rapidly evolving newer SQL engines on Big Data with innovative ideas and concepts

Apress.Pro.Spring.4th.Edition

This book is an introduction to the well-known Spring Framework that offers an inversion of control container for the Java platform. The Spring Framework is an open source application framework that can be used with any Java application. After reading this book, you will know how to do the following: • Use the Spring Framework efficiently. • Add persistence through JDBC and NoSQL databases. • Do unit and integration testing. • Apply AOP (aspect-oriented programming) to separate concerns. • Create web applications and expose RESTful APIs. • Send messages via JMS and AMQP by using ActiveMQ and RabbitMQ. • Use dynamic languages like Groovy, Ruby, and Bean Shell. • Use Groovy with Spring. • Use the new Spring Boot and Spring XD technologies.

Pro Spring MVC_With Web Flow-Apress(2012) Pro Spring MVC_With Web Flow-Apress(2012)

使用此深度指南正确设计基准，测量. NET 应用程序的关键性能度量，并分析结果.. 这本书提供了几十个案例研究，以帮助您理解复杂的基准主题。 您将避免常见的陷阱，控制测量的准确性，并提高您的软件的性能。 作者 AndreyAkinshin 已经维护了 Benchmark DotNet (最受欢迎的. NET 基准库) 五年，并涵盖了开发人员通常在基准中犯下的常见错误。 这本书不仅包括. NET 特定的内容，而且还包括关于性能测量的基本知识，这些知识可以应用于任何语言或平台（ 通用的基准方法、统计和现代硬件的低级特性）。

了解Libvirt开发的基本概念，并了解如何与Linux虚拟化环境进行接口，如QEMU/KVM、Xen、Virtuozzo、VMWare ESX、LXC、Bhyve等。本书将为您设置和维护虚拟机环境做准备。首先回顾虚拟化，然后使用Python介绍特定于libvirt的概念，包括虚拟化操作系统和网络、连接、存储池以及事件和错误处理。本文最后全面介绍了域、网络、设备、网络过滤、存储、节点设备等XML模式定义。libvirtAPI涵盖了虚拟对象的整个生命周期，从创建到销毁。它包含了在这个生命周期内管理虚拟对象所需的一切。虽然libvirt有支持多种语言的API，但是Libvirt开发的基础只关注Python，以及如何使用API控制QEMU/KVM系统下的虚拟机。还有更多。

Learn from state-of-the-art examples in robotics, motors, detection filters, chemical processes, aircraft, and spacecraft. MATLAB Recipes: A Problem-Solution Approach is a practical reference for industry engineers using MATLAB to solve everyday problems. With this book you will review contemporary MATLAB coding including the latest language features and use MATLAB as a software development environment including code organization, GUI development, and algorithm design and testing. This book provides practical guidance for using MATLAB to build a body of code you can turn to time and again for solving technical problems in your line of work. Develop algorithms, test them, visualize the results, and pass the code along to others to create a functional code base for your firm.

Practical Scala DSLs Real-World Applications Using Domain Speci c Languages