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Storing and Managing Big Data - NoSQL, Hadoop and More: High-Impact Strategies - What You Need to Know: Definitions, Adoptions,

為了解決Cloud computing wiki的問題，作者Roebuck, Kevin 這樣論述：

Over the last several years there are two important trends that require additional thought when putting together an architecture for a hosted service. The ability to analyze and process enormous amounts of data is increasingly important. From a technology perspective, the two trends to focus on

are: 1. Batch processing -- the increasing awareness of batch processing and the recent uptick in use of the map educe paradigm for that purpose; Distributed computing is a field of computer science that studies distributed systems. 2. NoSQL stores - The rise of so called ""NoSQL"" stores and thei

r use to serve up data to online users; a distributed file system or network file system is any file system that allows access to files from multiple hosts sharing via a computer network. This makes it possible for multiple users on multiple machines to share files and storage resources. Both of th

ese trends represent significant advances in the way that hosted systems are developed. But in order to derive the most value for an entire system, developers must think about how these two areas will work together in some holistic manner. This book is your ultimate resource for Storing and managin

g big data- NoSQL, Hadoop and more. Here you will find the most up-to-date information, analysis, background and everything you need to know. In easy to read chapters, with extensive references and links to get you to know all there is to know about Storing and managing big data- NoSQL, Hadoop and

more right away, covering: Distributed data store, Background Intelligent Transfer Service, BATON Overlay, BitVault, Bootstrapping node, Chimera (software library), Chord (peer-to-peer), Cloud (operating system), CoDeeN, Collaber, Collanos, Comparison of streaming media systems, Comparison of video

hosting services, Content addressable network, Content delivery network, Coral Content Distribution Network, Data center, Distributed file system, Distributed hash table, Distributed Networking, FAROO, Globule (CDN), GlusterFS, Grid casting, Hibari (database), High performance cloud computing, HTTP(

P2P), Hyper distribution, Infrastructure for Resilient Internet Systems, Jigdo, JXTA, Kademlia, Key-based routing, Koorde, Legion (software), MagmaFS, Metalink, NeoEdge Networks, Octoshape, Ono (P2P), Osiris (Serverless Portal System), OverSim, P-Grid, P2P-Next, P2PTV, PAST storage utility, Pastry (

DHT), Peer-to-peer wiki, Prefix hash tree, Proactive network Provider Participation for P2P, Rawflow, Sciencenet, Similarity Enhanced Transfer, Space-based architecture, Superdistribution, Tapestry (DHT), Tulip Overlay, Tuotu, Web acceleration, YaCy, Aquiles, BigTable, Apache Cassandra, Column famil

y, Hector (API), Keyspace (distributed data store), NoSQL, Standard column family, Super column family, Tombstone (data store), Voldemort (distributed data store), Andrew File System, Apache Hadoop, Apache Hive, BigCouch, Ceph, The Circle (file system), Cloudant, Cloudera, CloudStore, DCE Distribute

d File System, Direct Access File System, Distributed File System (Microsoft), FhGFS, Gfarm file system, Global Storage Architecture, Google File System, HAMMER, IBM General Parallel File System, Infinit, Lustre (file system), MapR, Moose File System, OFFSystem, OneFS distributed file system, Parall

el Virtual File System, POHMELFS, Sector/Sphere, Storage@home, Tahoe Least-Authority Filesystem, Wuala, XtreemFS This book explains in-depth the real drivers and workings of Storing and managing big data- NoSQL, Hadoop and more. It reduces the risk of your technology, time and resources investment

decisions by enabling you to compare your understanding of Storing and managing big data- NoSQL, Hadoop and more with the objectivity of experienced professionals.

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公有雲端企業資料庫即時同步備援到企業自有機房之研究

為了解決Cloud computing wiki的問題，作者周建竹 這樣論述：

由於在近十年來網路通訊技術的快速發展，雲端服務在手機時代已經被各企業和個人所採用，在此平台上，提供的服務，可以使租用戶能快速建構符合他們本身所需要的資料系統，另外在以前雲端服務及網路通訊技術尚未普及的年代，資訊系統備援是有地區距離的限制，而現在，在地端和雲端聯結更緊密的時代，在雲端各應用系統的後端的關聯式資料庫儲存重要的交易資料，其中備援設計更是極為重要。在本論文中研究的目的將以雲端的關聯式資料庫層級即時備援到地端，從可用性、即時性、保密安全性、持久性保存和搬遷性等做探討，本研究所採用的方式為在雲端租用和設定環境和地端架設環境，建構本研究之研究模型，進行雲端到地端在關聯式資料庫層級的備援探討

分析，並使用雲端運算業者Azure的計量統計圖表做資料蒐集及資料分析，呈現雲端硬碟讀寫累積使用量和網路頻寬累積使用量的數據並進行分析和探討，企業將可依照自己業務特性，做出符合最佳化的雲端資料庫備援到地端資料庫方式的決策。