Database Decay and What To Do About It – Communications of the ACM
The traditional wisdom for designing database schemas is to use a design tool (typically based on a UML or ER model) to construct an initial data model for one’s data. When one is satisfied with the result, the tool will automatically construct a collection of 3rd normal form relations for the model. Then, applications are coded against this relational schema. When business circumstances change
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先月ã€å¼Šç¤¾ã«ãƒ‡ãƒ¼ã‚¿ãƒ™ãƒ¼ã‚¹ç³»ã®ç ”究をã—ã¦ã„ãŸä¸å›½äººç•™å¦ç”ŸãŒã‚¤ãƒ³ã‚¿ãƒ¼ãƒ³ã«æ¥ã¦ãŠã‚Šã€ãã®å½¼ã«ãŠé¡˜ã„ã—ã¦PostgreSQLã®ãƒ‘ラレルクエリã®ã‚¹ã‚±ãƒ¼ãƒ©ãƒ“リティã®èª¿æŸ»ã¨ã€ãƒ—ãƒãƒ•ã‚¡ã‚¤ãƒªãƒ³ã‚°ï¼‹å¯è¦–化ã®ãƒ„ールã¨ã—ã¦FlameGraphを使ã£ã¦ã‚‚らã„ã¾ã—ãŸã€‚ 大å¦ã®ã‚¹ã‚±ã‚¸ãƒ¥ãƒ¼ãƒ«ã®é–¢ä¿‚上ã€ã‚¤ãƒ³ã‚¿ãƒ¼ãƒ³ã®æœŸé–“ãŒæ€¥é½ã€3週間ã‹ã‚‰2週間ã«çŸç¸®ã•ã‚Œã¦ã—ã¾ã£ãŸãŸã‚ã€çµæžœã‚’ãã¡ã‚“ã¨ã¾ã¨ã‚ãŸã‚Šè¿½è©¦ã‚’ã—ãŸã‚Šã¨ã„ã£ãŸã¨ã“ã‚ã¾ã§ã¯åˆ°é”ã§ããªã‹ã£ãŸã®ã§ã™ãŒã€å€‹äººçš„ã«ã‚‚ãã‚Œãªã‚Šã«é¢ç™½ã„アウトプットã«ãªã£ãŸã¨æ€ã„ã¾ã™ã®ã§ã€ç°¡å˜ã«ã”紹介ã—ãŸã„ã¨æ€ã„ã¾ã™ã€‚ ãªãŠã€ç´°ã‹ã„æ‰‹é †ã®è©³ç´°ãªã©ã¯ã€ã‚¤ãƒ³ã‚¿ãƒ¼ãƒ³ã«å‚åŠ ã—ã¦ã„ãŸå¦ç”Ÿã•ã‚“ã®Githubã«ã¾ã¨ã¾ã£ã¦ã„ã¾ã™ã€‚å‚考文献ã«è¼‰ã›ã¦ãŠãã¾ã™ã®ã§ã€èˆˆå‘³ã®ã‚ã‚‹æ–¹ã¯ãã¡ã‚‰ã‚‚å‚ç…§ã—ã¦ãã ã•ã„。（本テストã¨ç›´æŽ¥é–¢ä¿‚ã®ãªã„内容もå«ã¾ã‚Œã¦ã„ã¾ã™ï¼‰ ■テストã®èƒŒæ™¯ PostgreSQLã®9.6develã«ãƒ‘ラレルシーケン
Jim Gray Microsoft Research Publications
 Publications of Jim Gray, Microsoft Research, (Back to Jim's home page) “SkyServer Traffic Report – The First Five Years,†Vik Singh, Jim Gray, Ani R. Thakar, Alexander S. Szalay, Jordan Raddick, Bill Boroski, Svetlana Lebedeva, Brian Yanny, MSR-TR-2006-190, December 2006 “Cross-Matching Multiple Spatial Observations and Dealing with Missing Dataâ€, J. Gray, A. Szalay, T. Budavári, R. Lupton, M.
A Critique of ANSI SQL Isolation Levels | the morning paper
the morning paper a random walk through Computer Science research, by Adrian Colyer Made delightfully fast by strattic A Critique of ANSI SQL Isolation Levels – Berenson et al. 1995 udpate: 2 minor corrections in the section on A5A per the comment from ‘banks’ – thanks! The ANSI SQL isolation levels were originally defined in prose, in terms of three specific anomalies that they were designed to p
GitHub - rxin/db-readings: Readings in Databases
The Five-Minute Rule Ten Years Later, and Other Computer Storage Rules of Thumb (1997): This paper (and the original one proposed 10 years earlier) illustrates a quantitative formula to calculate whether a data page should be cached in memory or not. It is a delight to read Jim Gray approach to an array of related problems, e.g. how big should a page size be. AlphaSort: A Cache-Sensitive Parallel
Available Courses | Stanford Online
Welcome to Class2Go! We're Stanford Online's internal platform, designed to be an open platform for online learning and research. Coming Winter, 2013, free to the world: Introduction to Databases with Jennifer Widom Fall 2012, we offered two free courses: Computer Networking with Nick McKeown & Philip Levis Solar Cells, Fuel Cells, & Batteries with Bruce Clemens Here's what you will like about Cla
Cassandra vs MongoDB vs CouchDB vs Redis vs Riak vs HBase comparison :: Software architect Kristof Kovacs
Hello, I’m Kristof, a human being like you, and an easy to work with, friendly guy. I've been a programmer, a consultant, CIO in startups, head of software development in government, and built two software companies. Some days I’m coding Golang in the guts of a system and other days I'm wearing a suit to help clients with their DevOps practices. While SQL databases are insanely useful tools, their
「NewOLTPã®æ™‚代ã«NewSQLãŒæ±‚ã‚られã¦ã„る〠マイケル・ストーンプレイカーæ°
Web時代ã«ç”Ÿæˆã•ã‚Œã‚‹å¤§é‡ã®ãƒ‡ãƒ¼ã‚¿ã‚’ã€ãƒˆãƒ©ãƒ³ã‚¶ã‚¯ã‚·ãƒ§ãƒ³ã‚’ç¶æŒã—ã¤ã¤å‡¦ç†ã§ãã‚‹æ–°ã—ã„種類ã®ãƒ‡ãƒ¼ã‚¿ãƒ™ãƒ¼ã‚¹ã€ŒNew SQLã€ãŒæ±‚ã‚られã¦ã„ã‚‹ã¨ã€ãƒ‡ãƒ¼ã‚¿ãƒ™ãƒ¼ã‚¹ç ”究者ã®å¤§å¾¡æ‰€ã€ãƒžã‚¤ã‚±ãƒ«ãƒ»ã‚¹ãƒˆãƒ¼ãƒ³ãƒ–レイカーæ°ãŒç±³è¨ˆç®—æ©Ÿå¦ä¼šACM（Association for Computing Machinery）ã®ã‚³ãƒ©ãƒ 「New SQL: An Alternative to NoSQL and Old SQL for New OLTP Appsã€ï¼ˆNew SQL：New OLTPアプリケーションã®ãŸã‚ã®ã€NoSQLã‚„Old SQLã«æ›¿ã‚るデータベース）ã§æ›¸ã„ã¦ã„ã¾ã™ã€‚ New SQL: An Alternative to NoSQL and Old SQL for New OLTP Apps | blog@CACM | Communications of the ACM ã“ã‚Œã¾ã§ä¼æ¥ã®æƒ…å ±ã‚·ã‚¹ãƒ†ãƒ ã®å®šç•ªã¯ã€å—発注
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Sequel: The Database Toolkit for Ruby
Ruby Sequel is a lightweight database toolkit for Ruby.Sequel provides thread safety, connection pooling and a concise DSL for constructing database queries and table schemas. Sequel also includes a lightweight but comprehensive ORM layer for mapping records to Ruby objects and handling associated records. Sequel supports advanced database features such as prepared statements, bound variables, mas
Oracle Database 10g Express Edition
Multitenant: Get isolation, agility, and economies of scale by managing multiple Pluggable Databases inside your Oracle Multitenant Container Database In-Memory: Support real-time analytics, business intelligence, and reports by keeping your important data in the Oracle Database In-Memory column store Partitioning: Enhance performance, availability, and manageability of your database with data par
MapReduce: A major step backwards | The Database Column
on Jan 17 in Database architecture, Database history, Database innovation posted by DeWitt [Note: Although the system attributes this post to a single author, it was written by David J. DeWitt and Michael Stonebraker] On January 8, a Database Column reader asked for our views on new distributed database research efforts, and we’ll begin here with our views on MapReduce. This is a good time to dis
MOPID | Accelerate Your Hiring Process - Hire the Best, 10x Faster
Hire the best. At 10x the speed.Hire the best. At 10x the speed.Screen and interview candidates 10x faster with MOPID AI Recruiter that saves upto 80% of your time and resources. Hiring 100+ positions? Tryâš¡Blitzhiringâš¡for a change!Hiring 100+ positions?Try âš¡Blitzhiringâš¡ for a changeWe get it. Large scale hiring costs a lot. What if you could hire the perfect talent AND save up to 80% resources? We
Leo's Chronicle: ãœã²æŠ¼ã•ãˆã¦ãŠããŸã„データベースã®æ•™ç§‘書
先日ã®ã‚¨ãƒ³ãƒˆãƒªã§å°‘ã—話ã—ãŸã®ã§ã™ãŒã€åƒ•ãŒåœ¨å¦ã—ã¦ã„ãŸã¨ãã®æ±å¤§ã«ã¯ãƒ‡ãƒ¼ã‚¿ãƒ™ãƒ¼ã‚¹ã‚’å¦ã¶ãŸã‚ã®ã‚³ãƒ¼ã‚¹ã¨ã„ã†ã‚‚ã®ãŒã‚ã‚Šã¾ã›ã‚“ã§ã—ãŸï¼ˆDB関係ã®æŽˆæ¥ã¯å¹´ã«ï¼‘ã¤ã‹ï¼’ã¤ã‚る程度。ç¾åœ¨ã¯ã©ã†ãªã‚“ã ã‚ã†ï¼Ÿï¼‰ã€‚ãã‚“ãªã¨ãã«å½¹ã ã£ãŸã®ã¯ã€ã‚„ã¯ã‚Šæ•™ç§‘書。èªã¿ã‚„ã™ã„ã‚‚ã®ã‹ã‚‰é †ã«ç´¹ä»‹ã—ã¦ã„ãã¾ã™ã€‚（ã¨ã¯ã„ã£ã¦ã‚‚ã™ã¹ã¦è‹±èªžã®æœ¬ã§ã™ã€‚ã‚ã—ã‹ã‚‰ãšï¼‰ 一番ã®ãŠè–¦ã‚ã¯ã€Raghu Ramakrishnan先生 (ç¾åœ¨ã¯ã€Yahoo! Research) ã®ã€ŒDatabase Management Systems (3rd Edition)ã€ã€‚åˆå¦è€…ã‹ã‚‰ç ”究者ã¾ã§å¹…広ã使ãˆã¾ã™ã€‚データベース管ç†ã‚·ã‚¹ãƒ†ãƒ （DBMS）ã®åŸºæœ¬æ¦‚念ã‹ã‚‰ã€å•ã„åˆã‚ã›æœ€é©åŒ–ã€ãƒˆãƒ©ãƒ³ã‚¶ã‚¯ã‚·ãƒ§ãƒ³ç®¡ç†ãªã©ã€ã“れらを実装・評価ã™ã‚‹ãŸã‚ã«å¿…è¦ãªã€ã€ŒDBã®ä¸–ç•Œã§ã®å¸¸è˜ã€ãŒã€ä¸å¯§ãªèªžã‚Šå£ã§ãµã‚“ã ã‚“ã«ç››ã‚Šè¾¼ã¾ã‚Œã¦ã„ã¾ã™ã€‚ã“ã®1冊をèªã‚“ã§ãŠã‘ã°ã€DBã®ä¸–ç•Œã§è°è«–ã™ã‚‹ãŸã‚ã®
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InfluxDB & LevelDB Inside-out
NoDB: Efï¬cient Query Execution on Raw Data Files Ioannis Alagiannis? Renata Borovica? Miguel Branco? Stratos Idreos†Anastasia Ailamaki? ?EPFL, Switzerland {ioannis.alagiannis, renata.borovica, miguel.branco, anastasia.ailamaki}@epfl.ch †CWI, Amst
VoltDB Documentation | VoltDB
Akiban Technologies - Break through the SQL Scalability Barrier
Clustrix - Scale-out RDBMS
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