Download multi tenancy for cloud based in memory column databases workload management and data placement in memory data management research in pdf or read multi tenancy for cloud based in memory column databases workload management and data placement in memory data management research in pdf online books in PDF, EPUB and Mobi Format. Click Download or Read Online button to get multi tenancy for cloud based in memory column databases workload management and data placement in memory data management research in pdf book now. This site is like a library, Use search box in the widget to get ebook that you want.



Multi Tenancy For Cloud Based In Memory Column Databases

Author: Jan Schaffner
Publisher: Springer Science & Business Media
ISBN: 3319004972
Size: 79.74 MB
Format: PDF
View: 900
Download and Read
With the proliferation of Software-as-a-Service (SaaS) offerings, it is becoming increasingly important for individual SaaS providers to operate their services at a low cost. This book investigates SaaS from the perspective of the provider and shows how operational costs can be reduced by using “multi tenancy,” a technique for consolidating a large number of customers onto a small number of servers. Specifically, the book addresses multi tenancy on the database level, focusing on in-memory column databases, which are the backbone of many important new enterprise applications. For efficiently implementing multi tenancy in a farm of databases, two fundamental challenges must be addressed, (i) workload modeling and (ii) data placement. The first involves estimating the (shared) resource consumption for multi tenancy on a single in-memory database server. The second consists in assigning tenants to servers in a way that minimizes the number of required servers (and thus costs) based on the assumed workload model. This step also entails replicating tenants for performance and high availability. This book presents novel solutions to both problems.

Main Memory Database Systems

Author: Frans Faerber
Publisher: Foundations and Trends(r) in D
ISBN: 9781680833249
Size: 25.36 MB
Format: PDF, Mobi
View: 4829
Download and Read
With growing memory sizes and memory prices dropping by a factor of 10 every 5 years, data having a "primary home" in memory is now a reality. Main-memory databases eschew many of the traditional architectural pillars of relational database systems that optimized for disk-resident data. The result of these memory-optimized designs are systems that feature several innovative approaches to fundamental issues (e.g., concurrency control, query processing) that achieve orders of magnitude performance improvements over traditional designs. This monograph provides an overview of recent developments in main-memory database systems. It covers five main issues and architectural choices that need to be made when building a high performance main-memory optimized database: data organization and storage, indexing, concurrency control, durability and recovery techniques, and query processing and compilation. The monograph focuses on four commercial and research systems: H-Store/VoltDB, Hekaton, HyPer, and SAPHANA. These systems are diverse in their design choices and form a representative sample of the state of the art in main-memory database systems. It also covers other commercial and academic systems, along with current and future research trends.

Ibm Technical Computing Clouds

Author: Dino Quintero
Publisher: IBM Redbooks
ISBN: 0738438782
Size: 29.81 MB
Format: PDF, ePub, Mobi
View: 7408
Download and Read
This IBM® Redbooks® publication highlights IBM Technical Computing as a flexible infrastructure for clients looking to reduce capital and operational expenditures, optimize energy usage, or re-use the infrastructure. This book strengthens IBM SmartCloud® solutions, in particular IBM Technical Computing clouds, with a well-defined and documented deployment model within an IBM System x® or an IBM Flex SystemTM. This provides clients with a cost-effective, highly scalable, robust solution with a planned foundation for scaling, capacity, resilience, optimization, automation, and monitoring. This book is targeted toward technical professionals (consultants, technical support staff, IT Architects, and IT Specialists) responsible for providing cloud-computing solutions and support.

A Course In In Memory Data Management

Author: Hasso Plattner
Publisher: Springer
ISBN: 3642552706
Size: 58.83 MB
Format: PDF, Kindle
View: 4093
Download and Read
Recent achievements in hardware and software development, such as multi-core CPUs and DRAM capacities of multiple terabytes per server, enabled the introduction of a revolutionary technology: in-memory data management. This technology supports the flexible and extremely fast analysis of massive amounts of enterprise data. Professor Hasso Plattner and his research group at the Hasso Plattner Institute in Potsdam, Germany, have been investigating and teaching the corresponding concepts and their adoption in the software industry for years. This book is based on an online course that was first launched in autumn 2012 with more than 13,000 enrolled students and marked the successful starting point of the openHPI e-learning platform. The course is mainly designed for students of computer science, software engineering, and IT related subjects, but addresses business experts, software developers, technology experts, and IT analysts alike. Plattner and his group focus on exploring the inner mechanics of a column-oriented dictionary-encoded in-memory database. Covered topics include - amongst others - physical data storage and access, basic database operators, compression mechanisms, and parallel join algorithms. Beyond that, implications for future enterprise applications and their development are discussed. Step by step, readers will understand the radical differences and advantages of the new technology over traditional row-oriented, disk-based databases. In this completely revised 2nd edition, we incorporate the feedback of thousands of course participants on openHPI and take into account latest advancements in hard- and software. Improved figures, explanations, and examples further ease the understanding of the concepts presented. We introduce advanced data management techniques such as transparent aggregate caches and provide new showcases that demonstrate the potential of in-memory databases for two diverse industries: retail and life sciences.

High Performance In Memory Genome Data Analysis

Author: Hasso Plattner
Publisher: Springer Science & Business Media
ISBN: 3319030353
Size: 68.49 MB
Format: PDF, ePub
View: 3019
Download and Read
Recent achievements in hardware and software developments have enabled the introduction of a revolutionary technology: in-memory data management. This technology supports the flexible and extremely fast analysis of massive amounts of data, such as diagnoses, therapies, and human genome data. This book shares the latest research results of applying in-memory data management to personalized medicine, changing it from computational possibility to clinical reality. The authors provide details on innovative approaches to enabling the processing, combination, and analysis of relevant data in real-time. The book bridges the gap between medical experts, such as physicians, clinicians, and biological researchers, and technology experts, such as software developers, database specialists, and statisticians. Topics covered in this book include - amongst others - modeling of genome data processing and analysis pipelines, high-throughput data processing, exchange of sensitive data and protection of intellectual property. Beyond that, it shares insights on research prototypes for the analysis of patient cohorts, topology analysis of biological pathways, and combined search in structured and unstructured medical data, and outlines completely new processes that have now become possible due to interactive data analyses.

Hybrid Cloud For Dummies

Author: Judith Hurwitz
Publisher: John Wiley & Sons
ISBN: 1118235002
Size: 58.64 MB
Format: PDF
View: 2117
Download and Read
Choose the right combination of public, private, and data center resources to empower your business Hybrid clouds are transforming the way that organizations do business. This handy guide helps you find out what this new cloud deployment model is all about. You'll get down- to-earth information about cloud technology, questions to consider, and how to plan and deliver your move to a hybrid environment. Constructing the cloud — learn the basic concepts of the hybrid cloud from both a technical and business perspective Delivering cloud services — dive deeper into the actual foundational elements of the hybrid cloud Identifying business value — determine your hybrid cloud needs based on your business objectives Unified hybrid environments — find out what it means to create a computing environment that brings elements of the data center together with public and private cloud services Making it work — examine the steps you need to take to make this new architectural approach work — including security, governance, data, integration, monitoring, and more Get your ticket to the cloud — tips on how to talk to cloud providers and plan for the service you choose Open the book and find: Different cloud deployment models and what differentiates a hybrid cloud from other cloud models The impact of the hybrid cloud on cloud delivery models Why service orientation matters in a hybrid cloud Ways to develop and deploy applications in a hybrid world Guidance in finding the right hybrid cloud service providers Security and governance in a hybrid model The role of workload optimization in hybrid environments Learn to: Recognize the benefits and challenges of a hybrid cloud Efficiently deliver and manage cloud services Understand the impact of emerging cloud standards Protect customer data with sound security practices

Ibm Data Engine For Hadoop And Spark

Author: Dino Quintero
Publisher: IBM Redbooks
ISBN: 0738441937
Size: 55.18 MB
Format: PDF, ePub
View: 6844
Download and Read
This IBM® Redbooks® publication provides topics to help the technical community take advantage of the resilience, scalability, and performance of the IBM Power SystemsTM platform to implement or integrate an IBM Data Engine for Hadoop and Spark solution for analytics solutions to access, manage, and analyze data sets to improve business outcomes. This book documents topics to demonstrate and take advantage of the analytics strengths of the IBM POWER8® platform, the IBM analytics software portfolio, and selected third-party tools to help solve customer's data analytic workload requirements. This book describes how to plan, prepare, install, integrate, manage, and show how to use the IBM Data Engine for Hadoop and Spark solution to run analytic workloads on IBM POWER8. In addition, this publication delivers documentation to complement available IBM analytics solutions to help your data analytic needs. This publication strengthens the position of IBM analytics and big data solutions with a well-defined and documented deployment model within an IBM POWER8 virtualized environment so that customers have a planned foundation for security, scaling, capacity, resilience, and optimization for analytics workloads. This book is targeted at technical professionals (analytics consultants, technical support staff, IT Architects, and IT Specialists) that are responsible for delivering analytics solutions and support on IBM Power Systems.

Building Big Data And Analytics Solutions In The Cloud

Author: Wei-Dong Zhu
Publisher: IBM Redbooks
ISBN: 0738453994
Size: 71.97 MB
Format: PDF
View: 3732
Download and Read
Big data is currently one of the most critical emerging technologies. Organizations around the world are looking to exploit the explosive growth of data to unlock previously hidden insights in the hope of creating new revenue streams, gaining operational efficiencies, and obtaining greater understanding of customer needs. It is important to think of big data and analytics together. Big data is the term used to describe the recent explosion of different types of data from disparate sources. Analytics is about examining data to derive interesting and relevant trends and patterns, which can be used to inform decisions, optimize processes, and even drive new business models. With today's deluge of data comes the problems of processing that data, obtaining the correct skills to manage and analyze that data, and establishing rules to govern the data's use and distribution. The big data technology stack is ever growing and sometimes confusing, even more so when we add the complexities of setting up big data environments with large up-front investments. Cloud computing seems to be a perfect vehicle for hosting big data workloads. However, working on big data in the cloud brings its own challenge of reconciling two contradictory design principles. Cloud computing is based on the concepts of consolidation and resource pooling, but big data systems (such as Hadoop) are built on the shared nothing principle, where each node is independent and self-sufficient. A solution architecture that can allow these mutually exclusive principles to coexist is required to truly exploit the elasticity and ease-of-use of cloud computing for big data environments. This IBM® RedpaperTM publication is aimed at chief architects, line-of-business executives, and CIOs to provide an understanding of the cloud-related challenges they face and give prescriptive guidance for how to realize the benefits of big data solutions quickly and cost-effectively.

The Sybase Iq Survival Guide

Author: Trevor Moore
Publisher: Lulu.com
ISBN: 1446657582
Size: 37.83 MB
Format: PDF, ePub, Docs
View: 1964
Download and Read
The Sybase IQ Survival Guide is a clear and concise roadmap through the wealth of information out there, presented in logical steps and enhanced with the authors considerable hands on experience. All you need to get going with this book is a basic knowledge of SQL and databases. This guide has hundreds of tested methods for executing day to day tasks as well as hints, tips and guidance derived from the authors 10 years experience with the product. The following chapters are included: - - Introduction to IQ - Creating, Running and Stopping a Database/Server - Security - SQL - Loading, Extracting and Moving Data - Tables, Data Types and Views - Indexes - Stored Procedures, Functions and Triggers - Transaction Management - Backups, Restores & DR - Multiplex - Java in the IQ - Remote Objects & Application/Language Connectivity - Tips and Tricks - System Tables and Views - System Procedures - Options - Migration from Other Databases

Mastering Cloudforms Automation

Author: Peter McGowan
Publisher: "O'Reilly Media, Inc."
ISBN: 1491957204
Size: 54.86 MB
Format: PDF, ePub, Mobi
View: 3736
Download and Read
Learn how to work with the Automate feature of CloudForms, the powerful Red Hat cloud management platform that lets you administer your virtual infrastructure, including hybrid public and private clouds. This practical hands-on introduction shows you how to increase your operational efficiency by automating day-to-day tasks that now require manual input. Throughout the book, author Peter McGowan provides a combination of theoretical information and practical coding examples to help you learn the Automate object model. With this CloudForms feature, you can create auto-scalable cloud applications, eliminate manual decisions and operations when provisioning virtual machines and cloud instances, and manage your complete virtual machine lifecycle. In six parts, this book helps you: Learn the objects and concepts for developing automation scripts with CloudForms Automate Customize the steps and workflows involved in provisioning virtual machines Create and use service catalogs, items, dialogs, objects, bundles, and hierarchies Use CloudForm’s updated workflow to retire and delete virtual machines and services Orchestrate and coordinate with external services as part of a workflow Explore distributed automation processing as well as argument passing and handling