Reflections on Perl and DBI from an Early Contributor
The name Buzz Moschetti probably isn’t familiar to you. Buzz was the author of the Perl 4 database for Interbase known as Interperl. Back in those days Perl 5 was barely a twinkle in Larry’s eye and database interfaces for Perl 4 required building a custom perl binary. Buzz was one of the four people to get the email on September 29th 1992 from Ted Lemon that started the perldb-interest project wh
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2009å¹´04月19æ—¥ Hadoop 㨠RDBMS ã®æ€§èƒ½ã‚’比較ã—ã¦ã¿ãŸã€‚ã¨ã„ã†è«–文。ã®æ„Ÿæƒ³ã€‚ã®ç¿»è¨³ã€‚ Stonebraker, DeWitt, et al. compare MapReduce to DBMS Map-Reduce (Hadoop)㨠Parallel DBMS (Vertica 㨠DBMS-X) ã®æ€§èƒ½ã‚’比較ã—ãŸã¨ã“ã‚ã€ãŠãŠã‚€ã DB ã®æ–¹ãŒæ€§èƒ½ãŒã‚ˆãã€ã‚±ãƒ¼ã‚¹ã«ã‚ˆã£ã¦ã¯ 6.5å€ã‚‚性能差ãŒã‚ã‚‹ã¨ã„ã†å®Ÿé¨“çµæžœãŒã€SIGMOD09 ã§ç™ºè¡¨ã•ã‚ŒãŸã‚‰ã—ã„。原論文ã¯ã“ã“ã‹ã‚‰ PDF ã§ãƒ€ã‚¦ãƒ³ãƒãƒ¼ãƒ‰ã§ãる。 以下㯠DBMS2 ã¨ã„ã†ãƒ–ãƒã‚°ã«æ›¸ã‹ã‚ŒãŸã€ã“ã®è«–文をèªã‚“ã 人ã®æ„Ÿæƒ³ã®ç¿»è¨³ã€‚ Stonebraker, DeWitt, et al. MapReduce 㨠DBMS ã®æ¯”較 5人ã®å…±è‘—者(主ç†è€…㯠Andy Pavlo ã£ã½ã„)ã¨ã¨ã‚‚ã«ã€Map-Reduce å«Œã„ã§çŸ¥ã‚‰ã‚Œ
EventuallyConsistent - çµæžœæ•´åˆæ€§
EventuallyConsistent - çµæžœæ•´åˆæ€§ 目次 ã“ã®æ–‡æ›¸ã«ã¤ã„㦠çµæžœæ•´åˆæ€§ æ´å²ã®è©± クライアントå´ã®æ•´åˆæ€§ サーãƒå´ã®æ•´åˆæ€§ ã¾ã¨ã‚ çµæžœæ•´åˆæ€§ ã“ã®æ–‡æ›¸ã«ã¤ã„㦠Werner Vogels "Eventually Consistent" ã®æ—¥æœ¬èªžè¨³ã§ã™. http://www.allthingsdistributed.com/2007/12/eventually_consistent.html 推敲æ“è¿Ž: 誤訳, タイãƒ, 訳語ã®ä¸çµ±ä¸€, ãã®ã»ã‹... è¿‘å¹´, データ複製ã®æ–‡è„ˆã§ çµæžœæ•´åˆæ€§(eventual consistency) ã«é–¢ã™ã‚‹è°è«–ãŒç››ã‚“ã . ã“ã®è¨˜äº‹ã§ã¯å¤§è¦æ¨¡ãƒ‡ãƒ¼ã‚¿ã®è¤‡è£½ã«ãŠã‘る原則や抽象, 高å¯ç”¨æ€§ã¨ãƒ‡ãƒ¼ã‚¿æ•´åˆæ€§ã®ãƒˆãƒ¬ãƒ¼ãƒ‰ã‚ªãƒ•ã«é–¢ã™ã‚‹è©±é¡Œã‚’ã„ãã¤ã‹é›†ã‚ã¦ã¿ãŸã„ã¨æ€ã†. ç¾åœ¨é€²è¡Œä¸ã®åˆ†é‡Žã§ã‚ã‚Š, å…¨ã¦ã®å®šç¾©ãŒæœ€åˆã‹ã‚‰æ˜Žå¿«ã§ã‚ã‚‹ã¨ã¯æ€ã‚ãªã„ã§ã»
yohei-y:weblog: CAP 㨠BASE ã«ã¤ã„ã¦èª¿ã¹ãŸã“ã¨
時系列㧠1990年代後åŠ: Eric Brewer (UCB)㌠inktomi ã§ã„ã‚ã„ã‚作る CAPã¨BASEã®åŸºç¤ŽãŒã§ãã‚‹ http://www.ccs.neu.edu/groups/IEEE/ind-acad/brewer/ 2000å¹´7月19æ—¥: Eric Brewer ㌠PODC (Principles of Distributed Computing) ã®åŸºèª¿è¬›æ¼”㧠CAP 定ç†?㨠BASE を発表 CAP 㯠Brewer 予測ã¨ã—ã¦çŸ¥ã‚‰ã‚Œã‚‹ã‚ˆã†ã«ãªã‚‹ ã“ã®æ™‚点ã§ã€inktomiã¨åŒç‰ã‚¹ã‚±ãƒ¼ãƒ«ã®Webサービスã®å•é¡Œã«å¯¾å‡¦ã—ã¦ã„ãŸäººã¯ã‚ã¾ã‚Šã„ãªã‹ã£ãŸã®ã‹ã‚‚ã—ã‚Œãªã„ 2002å¹´ MIT ã® Seth Gilbert 㨠Nancy Lynch ㌠CAP ã‚’å½¢å¼åŒ– ã“ã“㧠Brewer ã® CAP ãŒæ™´ã‚Œã¦å®šç†ã¨ãªã£ãŸ ã“ã®é–“ã€ã‚ˆãã‚ã‹ã‚‰ãš 2007å¹´-: eBay ã®
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CAP 定ç†ã¨ BASE ã®æ¦‚念を考ãˆãŸã®ã¯ UCB ã® Brewer 先生ã§ã€å½¼ã¯ inktomi ã®å‰ã„人ã ã£ãŸã¨ã„ã†ã®ã¯å‰å›žè¿°ã¹ãŸã€‚ 当時ã®inktomiã¯Yahoo!ã‚„ Microsoftã€ãã‚Œã«gooã«ã‚‚検索エンジンをæä¾›ã—ã¦ã„ã¦ã€1億以上ã®Webページ(テラãƒã‚¤ãƒˆç´šã®ãƒ‡ãƒ¼ã‚¿)を扱ã£ã¦ã„ãŸã‚ˆã†ã 。 手元ã®WEB+DB PRESS Vol.49 ã®ã¯ã¦ãªãƒ–ックマークリニューアル記事ã«ã‚ˆã‚‹ã¨ã€ç¾åœ¨ã®ã¯ã¦ãªãƒ–ックマークã¯1160万URLã¨100GBã®HTMLデータ(圧縮済ã¿)を扱ã£ã¦ã„るらã—ã„ã®ã§ã€ã–ã£ãã‚Šã„ã£ã¦98å¹´ã®æ™‚点ã§inktomi ã¯ç¾åœ¨ã®ã¯ã¦ãƒ–ã®10å€ã®ãƒ‡ãƒ¼ã‚¿ã‚’扱ã£ã¦ã„ãŸã¨ã„ã£ã¦ã‚‚ã„ã„。inktomiã§ä½¿ã£ã¦ã„ãŸã‚³ãƒ³ãƒ”ュータã®æ€§èƒ½ã¯ç¾åœ¨ã®PCサ ーãƒã«æ¯”ã¹ã‚Œã°1/10程度ã®æ€§èƒ½ãªã®ã§ã€ã‚·ã‚¹ãƒ†ãƒ 全体ã§ã¿ã‚‹ã¨ç¾åœ¨ã®ã¯ã¦ãƒ–ã®100å€ã®è¦æ¨¡ã«ãªã‚‹ã ã‚ã†ã‹ã€‚ çµæžœçš„ã«ã¯ã€inktom
RDBMSã¯æ»ã«ã¾ã—ã‡ã‚“ - ãã“ã‹ã‚ã„ã„
RDBMSãŒã‚¯ãƒ©ã‚¦ãƒ‰ã‚³ãƒ³ãƒ”ューティングã«æ®ºã•ã‚Œã‚‹ã‚‰ã—ã„ã§ã™ã€‚ ã¨ãã«çµ„ã¿è¾¼ã¿DBã‹ã‚‰æ»ã¬ã‚‰ã—ã„ã§ã™ã€‚ HDDã¯SSDã«ã¨ã£ã¦ã‹ã‚られるらã—ã„ã§ã™ã€‚ http://d.hatena.ne.jp/nowokay/20081212#1229071535 SSDã«å¯¾ã—ã¦ã®åè«–ã¨ã€çµ„ã¿è¾¼ã¿DBãŒæ»ã¬ã“ã¨ã«å¯¾ã—ã¦ã®å論。 RDBMSã¯ã‚µãƒ¼ãƒã‹ã‚‰æ»ã¬ã‚‰ã—ã„ã§ã™ã€‚ http://d.hatena.ne.jp/kazuhooku/20081212/1229077256 ã©ã£ã¡ã‚‚ã³ã¿ã‚‡ã„ã¨ãŠã‚‚ã„ã¾ã™ã€‚一応ã€æ¯Žæ—¥ã‚¦ã‚§ãƒ–アプリをã”ã‚Šã”り書ã„ã¦ãŠã‚Šã€ãªãŠã‹ã¤ORDBMSã‚’ã°ã‚Šã°ã‚Šåˆ©ç”¨ã—ã¦ã„る身ã¨ã—ã¦ã€æ°—ã«ãªã‚‹ç‚¹ã‚’ã らã らã‹ãよ。 大è¦æ¨¡ã‚·ã‚¹ãƒ†ãƒ ã¯RDBMSã‹ã‚‰ã‚¯ãƒ©ã‚¦ãƒ‰ã¸ã€ãれ以外ã¯ã²ãã¤ã¥ãRDBMS㧠RDBMSã®ä¸€ç•ªå¤§ããªå•é¡Œç‚¹ã¯ã€ã„ã¾ã•ã‚‰ã§ã™ãŒã‚¹ã‚±ãƒ¼ãƒ©ãƒ“リティã§ã™ã€‚ã“ã®ã¸ã‚“ã¯ã¯ã¦ãªã¨ã‹mixiã®æŠ€è¡“ãƒã‚¿ã‚’èªã‚
Bigtable: A Distributed Storage System for Structured Data - steps to phantasien t(2006-09-11)
2006-09-11 è¿‘æ³ ä»Šæœˆã¯è²§ä¹ãªã®ã§æ…Žã—ã暮らã—ã¦ã„ã‚‹. 週末もã²ãã“ã‚‚ã‚Šã¨ã—ã¦ã‚ªãƒ³ãƒ©ã‚¤ãƒ³ã®è¨˜äº‹ã‚’èªã‚“ã§éŽã”ã™ã“ã¨ã«. ウェブを眺ã‚ã¦ã„ã‚‹ã¨ã„ã„タイミング㧠Google ã®æ–°ä½œè«–æ–‡ãŒå‡ºã¦ã„ãŸ. ã‚ã‚ŠãŒã¨ã†, Google ã®ä¸ã®äºº. ã“ã‚Œ. GFS, MapReduce, Sawzall ã¨ã¤ã¥ã Google インフラ N 部作㮠4 ç« ãŒå¹•ã‚’ã‚ã’ãŸ. 実ã¯ãƒ‡ãƒ¼ã‚¿ãƒ™ãƒ¼ã‚¹ã‚‚作ã£ã¦ã‚‹ã‚“ã ãœ, ã¨ã„ã†è©±. BigTable ã¨ã„ã†åå‰ã ã‘ã¯ä»¥å‰ã‹ã‚‰ O'Reilly Radar ãªã©ã«ç™»å ´ã—ã¦ã„ãŸ. よã†ã‚„ãå…¬å¼ãªæ–‡æ›¸ãŒã‚らã‚ã‚ŒãŸ. BigTable 㯠GFS ã‚’ã¯ã˜ã‚ã¨ã™ã‚‹ Google インフラã®ä¸Šã«ä½œã‚‰ã‚ŒãŸåˆ†æ•£ãƒ‡ãƒ¼ã‚¿ãƒ™ãƒ¼ã‚¹. å°‘ã—変ã‚ã£ãŸãƒ‡ãƒ¼ã‚¿ãƒ¢ãƒ‡ãƒ«ã¨, é‹ç”¨ã¾ã§ãƒ¯ãƒ³ã‚»ãƒƒãƒˆã®ãƒ˜ãƒ“ーãªå®Ÿè£…ã‚’æŒã¤. 実装ã®è©±ã‚‚ã¾ã‚é¢ç™½ã„ã‚“ã ã‘ã‚Œã©, ãれよりデータモデルãŒå°è±¡çš„ã ã£ãŸ. å…ˆã«ãã®
Google Research Publication: Bigtable: A Distributed Storage System for Structured Data
Bigtable: A Distributed Storage System for Structured Data Fay Chang, Jeffrey Dean, Sanjay Ghemawat, Wilson C. Hsieh, Deborah A. Wallach, Mike Burrows, Tushar Chandra, Andrew Fikes, and Robert E. Gruber Abstract Bigtable is a distributed storage system for managing structured data that is designed to scale to a very large size: petabytes of data across thousands of commodity servers. Many projec
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