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yappo id:yappo

mapreduceã«é–¢ã™ã‚‹yappoã®ãƒ–ãƒƒã‚¯ãƒžãƒ¼ã‚¯ (17)

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ã¸ã€œãŸã®ã‚ã‚‚:Hadoop ã¨ RDBMS ã®æ€§èƒ½ã‚’æ¯”è¼ƒã—ã¦ã¿ãŸã€‚ã¨ã„ã†è«–æ–‡ã€‚ã®æ„Ÿæƒ³ã€‚ã®ç¿»è¨³ã€‚ - livedoor Blogï¼ˆãƒ–ãƒã‚°ï¼‰
2009å¹´04æœˆ19æ—¥ Hadoop ã¨ RDBMS ã®æ€§èƒ½ã‚’æ¯”è¼ƒã—ã¦ã¿ãŸã€‚ã¨ã„ã†è«–æ–‡ã€‚ã®æ„Ÿæƒ³ã€‚ã®ç¿»è¨³ã€‚ Stonebraker, DeWitt, et al. compare MapReduce to DBMS Map-Reduce (Hadoop)ã¨ Parallel DBMS (Vertica ã¨ DBMS-X) ã®æ€§èƒ½ã‚’æ¯”è¼ƒã—ãŸã¨ã“ã‚ã€ãŠãŠã‚€ã DB ã®æ–¹ãŒæ€§èƒ½ãŒã‚ˆãã€ã‚±ãƒ¼ã‚¹ã«ã‚ˆã£ã¦ã¯ 6.5å€ã‚‚æ€§èƒ½å·®ãŒã‚ã‚‹ã¨ã„ã†å®Ÿé¨“çµæžœãŒã€SIGMOD09 ã§ç™ºè¡¨ã•ã‚ŒãŸã‚‰ã—ã„ã€‚åŽŸè«–æ–‡ã¯ã“ã“ã‹ã‚‰ PDF ã§ãƒ€ã‚¦ãƒ³ãƒãƒ¼ãƒ‰ã§ãã‚‹ã€‚ ä»¥ä¸‹ã¯ DBMS2 ã¨ã„ã†ãƒ–ãƒã‚°ã«æ›¸ã‹ã‚ŒãŸã€ã“ã®è«–æ–‡ã‚’èªã‚“ã äººã®æ„Ÿæƒ³ã®ç¿»è¨³ã€‚ Stonebraker, DeWitt, et al. MapReduce ã¨ DBMS ã®æ¯”è¼ƒ 5äººã®å…±è‘—è€…(ä¸»ç†è€…ã¯ Andy Pavlo ã£ã½ã„)ã¨ã¨ã‚‚ã«ã€Map-Reduce å«Œã„ã§çŸ¥ã‚‰ã‚Œ
yappo 2009/04/21
mapreduce
ãƒªãƒ³ã‚¯
MapReduce on Tyrant - mixi engineer blog
å…ˆæ—¥ã€éš…ç”°å·ã®å±‹å½¢èˆ¹ã§èŠ±è¦‹ã¨æ´’è½è¾¼ã‚“ã ã®ã§ã™ãŒã€ãã®æ—¥ã¯ã¾ã ä¸€åˆ†å’²ãã‚‚è¡Œã£ã¦ãªãã¦æ‚²ã—ã„æ€ã„ã‚’ã—ãŸmikioã§ã™ã€‚ä»Šå›žã¯Tokyo Tyrantï¼ˆTTï¼‰ã«æ ¼ç´ã—ãŸãƒ‡ãƒ¼ã‚¿ã‚’å¯¾è±¡ã¨ã—ã¦MapReduceã®ãƒ¢ãƒ‡ãƒ«ã«åŸºã¥ãè¨ˆç®—ã‚’ã™ã‚‹æ–¹æ³•ã«ã¤ã„ã¦è¿°ã¹ã¾ã™ã€‚ MapReduceã¨ã¯ GoogleãŒä½¿ã£ã¦ã„ã‚‹ã¨ã„ã†åˆ†æ•£å‡¦ç†ã®è¨ˆç®—ãƒ¢ãƒ‡ãƒ«ãŠã‚ˆã³ãã®å®Ÿè£…ã®ã“ã¨ã ãã†ã§ã™ãŒã€è©³ã—ã„ã“ã¨ã¯ã‚°ã‚°ã£ã¦ãã ã•ã„ã€‚Googleã«ã‚ˆã‚‹å‡ºè‡ªã®è«–æ–‡ã‚„Apacheãƒ—ãƒã‚¸ã‚§ã‚¯ãƒˆã«ã‚ˆã‚‹Hadoopãªã©ã®ã‚ªãƒ¼ãƒ—ãƒ³ã‚½ãƒ¼ã‚¹å®Ÿè£…ã«ã‚ãŸã‚‹ã®ã‚‚ã‚ˆã„ã§ã—ã‚‡ã†ï¼ˆç§ã¯ä¸¡è€…ã¨ã‚‚è©³ã—ãè¦‹ã¦ã„ã¾ã›ã‚“ãŒï¼‰ã€‚ ä»Šå›žã®è¶£æ—¨ã¯ã€CouchDBãŒMapReduceã¨ç§°ã—ã¦JavaScriptã§å®Ÿç¾ã—ã¦ã„ã‚‹ãƒ‡ãƒ¼ã‚¿é›†è¨ˆæ–¹æ³•ã‚’TTã¨TCã¨Luaã§ã‚„ã£ã¦ã¿ã‚ˆã†ã˜ã‚ƒãªã„ã‹ã¨ã„ã†ã“ã¨ã§ã™ã€‚ç°¡å˜ã«è¨€ãˆã°ã€ä»¥ä¸‹ã®å‡¦ç†ã‚’å®Ÿè£…ã—ã¾ã™ã€‚ ãƒ¦ãƒ¼ã‚¶ã‹ã‚‰è¨ˆç®—é–‹å§‹ãŒæŒ‡ç¤ºã•ã‚Œã‚‹ã¨ã€TTã¯ã€DBå†…ã®
yappo 2009/04/06
mapreduce

tokyotyrant
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Amazon Elastic MapReduceã‚’ä½¿ã£ã¦ã¿ãŸ - moratorium
Amazon Elastic MapReduceã‚’ä½¿ã£ã¦ã¿ãŸ 2009-04-03 (Fri) 3:06 Amazon EC2 é€£æ—¥ã®EC2ãƒã‚¿ã§ã™ã€‚æœ¬æ—¥ã€Amazonã‹ã‚‰Elastic MapReduceã¨ã„ã†ã‚µãƒ¼ãƒ“ã‚¹ãŒãƒªãƒªãƒ¼ã‚¹ã•ã‚Œã¾ã—ãŸã€‚å¤§è¦æ¨¡ãƒ‡ãƒ¼ã‚¿å‡¦ç†æŠ€è¡“ãŒä¸€æ°—ã«æ°‘é–“ã®æ‰‹ã«ä¸‹ã‚Šã¦ãã‚‹ã€ã¾ã•ã«é©å‘½çš„ãªã‚µãƒ¼ãƒ“ã‚¹ã ã¨æ€ã„ã¾ã™ã€‚ Amazon Elastic MapReduce Amazon ElasticMapReduce ç´¹ä»‹ãƒ“ãƒ‡ã‚ª With Hadoop, Amazon Adds A Web-Scale Data Processing Engine To Its Cloud Computer by techcrunch.com Elastic MapReduceã¯ã€Googleã®åŸºç›¤æŠ€è¡“ã®ä¸€ã¤ã§ã‚ã‚‹MapReduceã‚’æ™‚é–“å˜ä½èª²é‡‘ã§å®Ÿè¡Œã§ãã‚‹ã‚µãƒ¼ãƒ“ã‚¹ã§ã™ã€‚MapReduceã«ã¤ã„ã¦ã¯ä»¥
yappo 2009/04/03
mapreduce
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Big Data Platform - Amazon EMR - AWS
Amazon EMR Serverless is a new option in Amazon EMR that makes it easy and cost-effective for data engineers and analysts to run applications built using open source big data frameworks such as Apache Spark, Hive or Presto, without having to tune, operate, optimize, secure or manage clusters.
yappo 2009/04/02
mapreduce
ãƒªãƒ³ã‚¯
DBI ã‚’ãƒãƒƒã‚¯ã‚¨ãƒ³ãƒ‰ã«ã—ãŸ CouchDB ã¿ãŸã„ãªã® - é…’æ—¥è¨˜ ã¯ã¦ãªæ”¯åº—
CouchDB ã¯é¢ç™½ã„ã®ã§ã™ãŒã€Erlang ã§æ›¸ã‹ã‚ŒãŸ daemon ã‚’å‹•ã‹ã™å¿…è¦ãŒã‚ã‚‹ã®ã§ã€ç’°å¢ƒã«ã‚ˆã£ã¦ã¯ä½¿ã„ã«ãã„ã€‚ ã¨ã„ã†ã“ã¨ã§ã€Perl + DBI ã®ã¿ã§ä¼¼ãŸã‚ˆã†ãªå‹•ä½œã‚’ã™ã‚‹ã‚‚ã®ã‚’ä½œã£ã¦ã¿ã¾ã—ãŸã€‚daemon ã˜ã‚ƒãªãã¦ã€Perl ã‹ã‚‰ç›´æŽ¥ DB ã‚’æ‰±ã†ãƒ©ã‚¤ãƒ–ãƒ©ãƒªã§ã™ã€‚ Coderepos ã«ç½®ãã¾ã—ãŸã€‚http://svn.coderepos.org/share/lang/perl/DBIx-CouchLike/trunk ã§ãã‚‹ã“ã¨ã¯å˜ç´”ã€‚ (key => ä»»æ„ã®æ§‹é€ ã® hash ref) ã® CRUD CouchDB ã½ã„ map / reduce å¯¾å¿œã—ã¦ã„ã‚‹ DBD ã¯ã¨ã‚Šã‚ãˆãš SQLite ã¨ PostgreSQL ã§ã€‚ CRUD use DBIx::CouchLike; use DBI; $dbh = DBI->connect("dbi:SQLite:dbna
yappo 2009/02/16
mapreduce

couchdb
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æ¥½å¤©ãƒ†ã‚¯ãƒŽãƒã‚¸ãƒ¼ã‚«ãƒ³ãƒ•ã‚¡ãƒ¬ãƒ³ã‚¹ 2008ã«ã„ã£ã¦ãã¾ã—ãŸ - d.hatena.zeg.la
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yappo 2008/11/30
roma

fairy

mapreduce
ãƒªãƒ³ã‚¯
Parallel-MapReduce-0.09
The London Perl and Raku Workshop takes place on 26th Oct 2024. If your company depends on Perl, please consider sponsoring and/or attending.
yappo 2008/07/21
ã‚ã¨ã§

perl

cpan

mapreduce
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ã¾ã¤ã‚‚ã¨Ã—ç¬¹ç”°ã€Ruby 1.9ã‚’èªžã‚‹ â€• ï¼ IT
2007/12/25 ã€Œãã†ã„ãˆã°ã‚ã®retryã®è©±ã€ã©ã†æ€ã†ï¼Ÿã€ã€ã€Œèª°ã‚‚ä½¿ã£ã¦ãªã„ã‹ã‚‰å®³æ‚ªãŒå¤šã„ã£ã¦ã„ã†è©±ã¯èª¬å¾—åŠ›ã‚ã‚Šã¾ã™ã‚ˆãã€ã€ã€Œã˜ã‚ƒã‚ãªãã™ã‹â€¦â€¦ã€ã†ã‚“ã€ãªãã—ã¨ã„ã¦ã€ã€ã€Œã‚ã€æ±ºã¾ã£ã¡ã‚ƒã£ãŸï¼ˆç¬‘ï¼‰ã€â€•â€•ã€‚ ã¾ã¤ã‚‚ã¨ã‚†ãã²ã‚ã¨ã€ç¬¹ç”°è€•ä¸€ã€‚ã„ã¾ã€ä¸–ç•ŒãŒæ³¨ç›®ã™ã‚‹ãƒ—ãƒã‚°ãƒ©ãƒŸãƒ³ã‚°è¨€èªžã€ŒRubyã€ã®ç”Ÿã¿ã®è¦ªã¨ã€é–‹ç™ºã‚³ã‚¢ãƒ¡ãƒ³ãƒãƒ¼ã®2äººã¯ã€ã“ã¨ã‚‚ãªã’ã«Rubyã®ä»•æ§˜ã‚’è¨˜è€…ã®ç›®ã®å‰ã§å¤‰æ›´ã—ã¦ã—ã¾ã£ãŸã€‚Rubyã®é–‹ç™ºã¯ã©ã®ã‚ˆã†ã«è¡Œã‚ã‚Œã€ã©ã“ã¸å‘ã‹ãŠã†ã¨ã—ã¦ã„ã‚‹ã®ã‹ã€‚ç¾è¡Œã®ãƒãƒ¼ã‚¸ãƒ§ãƒ³1.8ç³»ã‹ã‚‰å¤§ããæ§˜å¤‰ã‚ã‚Šã™ã‚‹æ¬¡æœŸé–‹ç™ºç‰ˆã€ŒRuby 1.9ã€ã®ãƒªãƒªãƒ¼ã‚¹ã‚’12æœˆ25æ—¥ã«æŽ§ãˆãŸ2äººã«ã€å¸«èµ°ã®ç§‹è‘‰åŽŸã§è©±ã‚’èžã„ãŸï¼ˆæ–‡ä¸ã€æ•¬ç§°ç•¥ï¼‰ã€‚ Rubyã®ä»•æ§˜ã¯å¯†å®¤ã§æ±ºã¾ã‚‹!? å†’é ã«ç´¹ä»‹ã—ãŸ2äººã®ä¼šè©±ã¯ã€ã€Œretryã€ã¨ã„ã†Rubyã®æ–‡æ³•ã®2ç¨®é¡žã‚ã‚‹ä½¿ã„æ–¹ã®ã†ã¡ã€ã“ã‚Œã¾ã§ã»ã¨ã‚“ã©ä½¿ã‚ã‚ŒãŸå½¢è·¡ãŒãªã„æ–¹ã‚’æ–‡æ³•ä»•æ§˜ã‹ã‚‰å–ã‚Šé™¤ãã‹ã©
yappo 2007/12/26
mapreduce
ãƒªãƒ³ã‚¯
YappoLogs: Googleã®MapReduceã‚’ã„ã¾ã•ã‚‰å¦„æƒ³ã—ãŸ
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yappo 2007/12/25
mapreduce
ãƒªãƒ³ã‚¯
MapReduce - Cafe Babe
MapReduceã¯ï¼ŒGoogleç¤¾å†…ã§ã‚¯ãƒ©ã‚¹ã‚¿ä¸Šã®ãƒ‡ãƒ¼ã‚¿å‡¦ç†ã«ç”¨ã„ã‚‰ã‚Œã¦ã„ã‚‹ä¸¦åˆ—åˆ†æ•£ãƒ—ãƒã‚°ãƒ©ãƒŸãƒ³ã‚°ãƒ¢ãƒ‡ãƒ«ã§ã‚ã‚‹ï¼Žã¡ã‚‡ã†ã©ä»Šã‚µãƒ³ãƒ•ãƒ©ãƒ³ã‚·ã‚¹ã‚³ã§é–‹å‚¬ã•ã‚Œã‚‹OSDI 2004ã«ç™ºè¡¨äºˆå®šã®è«–æ–‡ãŒï¼Œã™ã§ã«å…¬é–‹ã•ã‚Œã¦ã„ã‚‹ãŒï¼Œã“ã‚ŒãŒéžå¸¸ã«é¢ç™½ã„ï¼Ž http://labs.google.com/papers/mapreduce.html æ¦‚è¦ã¯æ¬¡ã®ã‚ˆã†ãªæ„Ÿã˜ï¼Ž ãƒ‡ãƒ¼ã‚¿å‡¦ç†ã‚’ï¼ŒMapã¨Reduceã®2ã¤ã«åˆ†å‰²ã™ã‚‹ï¼ŽãªãŠï¼Œã“ã®åå‰ã¯åŒæ§˜ãªæ©Ÿèƒ½ã‚’æŒã¤Lispã®é–¢æ•°åãŒç”±æ¥ï¼Ž Mapã§ã¯ï¼Œã‚ã‚‹ã‚ãƒ¼ã¨å€¤ã®çµ„ã‹ã‚‰ï¼Œä¸é–“ã®ã‚ãƒ¼ã¨å€¤ã®çµ„ã®ãƒªã‚¹ãƒˆã‚’ç”Ÿæˆã—ï¼Œãƒãƒ¼ã‚«ãƒ«ãƒ‡ã‚£ã‚¹ã‚¯ã«æ›¸ãè¾¼ã‚€ï¼Ž Reduceã§ã¯ï¼ŒMapãŒç”Ÿæˆã—ãŸã‚ãƒ¼ã¨å€¤ã®çµ„ã‚’ãƒªãƒ¢ãƒ¼ãƒˆãƒ‡ã‚£ã‚¹ã‚¯ã‹ã‚‰èªã¿å‡ºã—ï¼Œå€¤ã®ãƒªã‚¹ãƒˆã‚’è¿”ã™ï¼Ž Mapã¨Reduceã¯ï¼Œè¤‡æ•°ã®ãƒ¯ãƒ¼ã‚«ã«ã‚ˆã£ã¦åˆ†æ•£ã—ãŸãƒžã‚·ãƒ³ä¸Šã§ä¸¦åˆ—ã«å®Ÿè¡Œã•ã‚Œã‚‹ï¼Ž ãŸã¨ãˆã°ï¼Œç´°åˆ†åŒ–ã•ã‚ŒãŸå…¥åŠ›ãƒ•ã‚¡ã‚¤ãƒ«ã‚’Mapã‚’å‡¦ç†ã™ã‚‹ãƒ¯ãƒ¼ã‚«ãŒ
yappo 2007/12/25
mapreduce
ãƒªãƒ³ã‚¯
#318th PTT (in Japanese)
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yappo 2007/12/25
mapreduce
ãƒªãƒ³ã‚¯
MapReduce:Simplified Data Processing on Large Clusters
MapReduce: Simplified Data Processing on Large Clusters
yappo 2007/12/25
mapreduce
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mapreduce
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yappo 2007/12/25
mapreduce
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Apache Hadoop
This is the first release of Apache Hadoop 3.4 line. It contains 2888 bug fixes, improvements and enhancements since 3.3. Users are encouraged to read the overview of major changes. For details of please check release notes and changelog. This is a release of Apache Hadoop 3.3 line. It contains 117 bug fixes, improvements and enhancements since 3.3.5. Users of Apache Hadoop 3.3.5 and earlier shoul
yappo 2007/12/25
mapreduce

hadoop
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1