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e-kuroda id:e-kuroda

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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®
e-kuroda 2009/04/06
MapReduce

TokyoTyrant

mixi
ãƒªãƒ³ã‚¯
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»¥
e-kuroda 2009/04/04
Amazon

AWS

MapReduce
ãƒªãƒ³ã‚¯
Amazon Web Services Developer Community : Amazon Elastic MapReduce
Data Wrangling blogger and AWS developer Peter Skomoroch gives us an introduction to Amazon Elastic MapReduce.
e-kuroda 2009/04/04
Amazon

AWS

MapReduce
ãƒªãƒ³ã‚¯
http://www.docstoc.com/docs/2996433/Hadoop-and-HBase-vs-RDBMS
e-kuroda 2009/04/02
Hadoop

MapReduce
ãƒªãƒ³ã‚¯
æœ¬ã‚’èªã‚€ GREE Labsã§Hadoopã®è©±ã‚’èžã„ã¦ããŸ
GREEã•ã‚“ã§ä¸å®šæœŸã§ã‚„ã£ã¦ã‚‹ã€GREE Labsã‚ªãƒ¼ãƒ—ãƒ³ã‚½ãƒ¼ã‚¹ãƒ†ã‚¯ãƒŽãƒã‚¸ãƒ¼å‹‰å¼·ä¼šã§ã€Hadoopã®è©±ã‚’èžã„ã¦ãã¾ã—ãŸã€‚Hadoopã¯ã€ã¤ã¾ã‚Šã¯Googleã®GFSã‚„MapReduceã®ã‚¯ãƒãƒ¼ãƒ³ã ãã†ã§ã€ã€ŒGoogleã‚’æ”¯ãˆã‚‹æŠ€è¡“ã€ã«ãƒˆã‚ãƒ¡ã„ãŸäººãªã‚‰å¿…è¦‹ã§ã™ãã€‚ ç™ºè¡¨ã¯ã€æŠ€è¡“é¢ã‚’ç°¡æ½”ã«æŠ¼ã•ãˆãŸã†ãˆã§ã‚ã‹ã‚Šã‚„ã™ãã€ãã®ã†ãˆå®Ÿéš›ã®åˆ©ç”¨äº‹ä¾‹ã®è©±ã‚‚èžã‘ãŸã®ãŒé¢ç™½ã‹ã£ãŸã¨æ€ã„ã¾ã™ã€‚æœ€è¿‘ã®Webç³»ã§ã¯ã€ã‚µãƒ¼ãƒ“ã‚¹é¢ã§ã‚‚ãƒžãƒã‚¿ã‚¤ã‚ºé¢ã§ã‚‚ã€ãƒ‡ãƒ¼ã‚¿ãƒžã‚¤ãƒ‹ãƒ³ã‚°ã¨ã‹è¡Œå‹•ã‚¿ãƒ¼ã‚²ãƒ†ã‚£ãƒ³ã‚°ã¨ã‹ãŒã‚¢ãƒ„ã„ã‚“ã ãªãã¨æ€ã„ã¾ã—ãŸã€‚ ãƒ—ãƒ¬ã‚¼ãƒ³è³‡æ–™ã‚‚ustéŒ²ç”»ã‚‚å…¬é–‹ã•ã‚Œã¦ã„ã¾ã™ãŒã€ä»¥ä¸‹ã€è‡ªåˆ†ã®ãƒ¡ãƒ¢ã¨ã„ã†æ„å‘³ã§è¨˜éŒ²ã—ã¦ãŠãã¾ã™ã€‚ Hadoopã«ã¤ã„ã¦ï¼ˆå¤ªç”°ä¸€æ¨¹ï¼‰ Preferred Infrastructureã®CTOã§ã€Sedueã®ä½œè€…ã€‚å¤§é‡ã®ãƒ‡ãƒ¼ã‚¿ã®å‡¦ç†ãŒãƒ†ãƒ¼ãƒžã§ã€åŠåˆ†ã¯é…’ã§ã§ãã¦ã„ã‚‹wã€‚ãã‚“ãªã“ã‚“ãªã§ã€ã¯ã¦ãƒ–æ¤œç´¢ã§ã‚‚ä½¿ã‚ã‚Œã¦ã„
e-kuroda 2009/04/02
Hadoop

MapReduce
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blogeyeã®å®Ÿè£…ã«å¦ã¶ã€Amazon EC2/S3ã§ã®Hadoopæ´»ç”¨è¡“
ã¯ã˜ã‚ã« ã“ã‚“ã«ã¡ã¯ã€‚Hadoopé€£è¼‰ ç¬¬4å›žã¯å¤ªç”°ã•ã‚“ã«ä»£ã‚ã£ã¦å¤§å€‰ãŒæ‹…å½“ã—ã¾ã™ã€‚ ã“ã‚Œã¾ã§ã®é€£è¼‰ã§ã€Hadoopã«ã‚ˆã‚‹ãƒ‡ãƒ¼ã‚¿å‡¦ç†ã®æ¦‚ç•¥ã«ã¤ã„ã¦ã¯ç†è§£ã•ã‚Œã¦ã„ã‚‹ã¨æ€ã„ã¾ã™ã€‚ä»Šå›žã¯Hadoopã‚’åˆ©ç”¨ã—ãŸã‚·ã‚¹ãƒ†ãƒ ã®å®Ÿä¾‹ã¨ã„ã†ã“ã¨ã§ã€ãƒ–ãƒã‚°åˆ†æžã‚’è¡Œã†ã€Œblogeyeã€ã‚·ã‚¹ãƒ†ãƒ ã®æ¦‚ç•¥ã¨ã€ãã®ä¸ã§ã®Hadoopåˆ©ç”¨æ³•ã‚’ç´¹ä»‹ã—ã¾ã™ã€‚ ã¾ãŸã€blogeyeã¯AmazonãŒæä¾›ã—ã¦ã„ã‚‹EC2ï¼ˆãƒ¬ãƒ³ã‚¿ãƒ«ã‚µãƒ¼ãƒï¼‰ã€S3ï¼ˆã‚¹ãƒˆãƒ¬ãƒ¼ã‚¸ï¼‰ã‚’Hadoopã¨çµ„ã¿åˆã‚ã›ã¦åˆ©ç”¨ã—ã¦ã„ã‚‹ã®ã§ã€ãã®è¾ºã‚Šã®å°Žå…¥æ–¹æ³•ã«ã¤ã„ã¦ã‚‚ç´¹ä»‹ã—ã¾ã™ã€‚ ã“ã‚Œã¾ã§ã®é€£è¼‰ Hadoopã€hBaseã§æ§‹ç¯‰ã™ã‚‹å¤§è¦æ¨¡åˆ†æ•£ãƒ‡ãƒ¼ã‚¿å‡¦ç†ã‚·ã‚¹ãƒ†ãƒ Hadoopã®ã‚¤ãƒ³ã‚¹ãƒˆãƒ¼ãƒ«ã¨ã‚µãƒ³ãƒ—ãƒ«ãƒ—ãƒã‚°ãƒ©ãƒ ã®å®Ÿè¡Œ è¤‡æ•°ãƒžã‚·ãƒ³ã¸Hadoopã‚’ã‚¤ãƒ³ã‚¹ãƒˆãƒ¼ãƒ«ã™ã‚‹ blogeyeã¨ã¯ ã€Œblogeyeã€ï¼ˆãƒ–ãƒã‚°ã‚¢ã‚¤ï¼‰ã¯æ—¥æœ¬èªžã®ãƒ–ãƒã‚°ã‚’ã‚¯ãƒãƒ¼ãƒ«ã€ãƒªã‚¢ãƒ«ã‚¿ã‚¤ãƒ ã«åˆ†æžã—ã¦ã€æµè¡Œèªžã¨æ€ã‚
e-kuroda 2009/04/02
Amazon

EC2

S3

Hadoop

MapReduce
ãƒªãƒ³ã‚¯
Hadoopã®è§£æžè³‡æ–™
ã‚ªãƒ¼ãƒ—ãƒ³ã‚½ãƒ¼ã‚¹åˆ†æ•£ã‚·ã‚¹ãƒ†ãƒ ã€ŒHadoopã€ã«é–¢ã™ã‚‹è§£æžè³‡æ–™ã‚’å…¬é–‹ã•ã›ã¦é ‚ã„ã¦ãŠã‚Šã¾ã™ã€‚ã“ã®èª¿æŸ»ã¯NTTãƒ¬ã‚¾ãƒŠãƒ³ãƒˆæ ªå¼ä¼šç¤¾æ§˜ã¨å…±åŒã§è¡Œã„ã¾ã—ãŸ(ãƒ—ãƒ¬ã‚¹ãƒªãƒªãƒ¼ã‚¹)ã€‚ Hadoopè§£æžè³‡æ–™(PDF), æœ€çµ‚æ›´æ–°: 2008/08/25, å…¬é–‹: 2008/08/25 Hadoopã®å®Ÿéš›ã®ã‚¤ãƒ³ã‚¹ãƒˆãƒ¼ãƒ«æ–¹æ³•ãªã©ã«ã¤ãã¾ã—ã¦ã¯ã€å¼Šç¤¾å¤ªç”°ã«ã‚ˆã‚‹ä»¥ä¸‹ã®è¨˜äº‹ã‚‚ã”å‚è€ƒä¸‹ã•ã„ã€‚ Hadoopã€hBaseã§æ§‹ç¯‰ã™ã‚‹å¤§è¦æ¨¡åˆ†æ•£ãƒ‡ãƒ¼ã‚¿å‡¦ç†ã‚·ã‚¹ãƒ†ãƒ Hadoopã®ã‚¤ãƒ³ã‚¹ãƒˆãƒ¼ãƒ«ã¨ã‚µãƒ³ãƒ—ãƒ«ãƒ—ãƒã‚°ãƒ©ãƒ ã®å®Ÿè¡Œ è¤‡æ•°ãƒžã‚·ãƒ³ã¸Hadoopã‚’ã‚¤ãƒ³ã‚¹ãƒˆãƒ¼ãƒ«ã™ã‚‹
e-kuroda 2009/04/02
Hadoop

Java

MapReduce
ãƒªãƒ³ã‚¯
FrontPage - Hadoop Wiki
Apache Hadoop Apache Hadoop is a framework for running applications on large cluster built of commodity hardware. The Hadoop framework transparently provides applications both reliability and data motion. Hadoop implements a computational paradigm named Map/Reduce, where the application is divided into many small fragments of work, each of which may be executed or re-executed on any node in the cl
e-kuroda 2009/04/02
Hadoop

MapReduce
ãƒªãƒ³ã‚¯
MapReduceã¨Hadoopã®å°†æ¥ã«ã¤ã„ã¦ã€Yahooã®Doug Cuttingã«ã‚¤ãƒ³ã‚¿ãƒ“ãƒ¥ãƒ¼
Spring Bootã«ã‚ˆã‚‹APIãƒãƒƒã‚¯ã‚¨ãƒ³ãƒ‰æ§‹ç¯‰å®Ÿè·µã‚¬ã‚¤ãƒ‰ ç¬¬2ç‰ˆ ä½•åƒäººã‚‚ã®é–‹ç™ºè€…ãŒã€InfoQã®ãƒŸãƒ‹ãƒ–ãƒƒã‚¯ã€ŒPractical Guide to Building an API Back End with Spring Bootã€ã‹ã‚‰ã€Spring Bootã‚’ä½¿ã£ãŸREST APIæ§‹ç¯‰ã®åŸºç¤Žã‚’å¦ã‚“ã ã€‚ã“ã®æœ¬ã§ã¯ã€å‡ºç‰ˆæ™‚ã«æ–°ã—ããƒªãƒªãƒ¼ã‚¹ã•ã‚ŒãŸãƒãƒ¼ã‚¸ãƒ§ãƒ³ã§ã‚ã‚‹ Spring Boot 2 ã‚’ä½¿ç”¨ã—ã¦ã„ã‚‹ã€‚ã—ã‹ã—ã€Spring Boot3ãŒæœ€è¿‘ãƒªãƒªãƒ¼ã‚¹ã•ã‚Œã€é‡è¦ãªå¤‰...
e-kuroda 2009/04/02
Hadoop

MapReduce

Yahoo
ãƒªãƒ³ã‚¯
http://news.tokyo.wakhok.ac.jp/x/modules/tinyd1/content/newtech2007/Amazon_EC2_Hadoop-2/siframes.html
e-kuroda 2009/04/02
Hadoop

EC2

Amazon

MapReduce
ãƒªãƒ³ã‚¯
Welcome to Apacheâ„¢ HadoopÂ®!
A wide variety of companies and organizations use Hadoop for both research and production. Users are encouraged to add themselves to the Hadoop PoweredBy wiki page. 8 Aug 2018: Release 3.1.1 available This is the first stable release of Apache Hadoop 3.1 line. It contains 435 bug fixes, improvements and enhancements since 3.1.0 Users are encouraged to read the overview of major changes since 3.1.0
e-kuroda 2009/04/02
MapReduce

Hadoop
ãƒªãƒ³ã‚¯
Hadoop
13. $ env | grep JAVA JAVA_HOME=/System/Library/Frameworks/JavaVM.framework/Versions/CurrentJDK/Home $ java -version java -versionjava version quot;1.5.0_07quot;Java(TM) 2 Runtime Environment, Standard Edition (build 1.5.0_07-154)Java HotSpot(TM) Client VM (build 1.5.0_07-87, mixed mode, sharing) $ curl -O http://www.apache.org/dist/lucene/hadoop/stable/hadoop-0.13.0.tar.gz $ tar zxvf hadoop-0.13.
e-kuroda 2009/04/02
MapReduce

Hadoop
ãƒªãƒ³ã‚¯
space
A Ruby MapReduce Framework Skynet RubyForge Home Documentation See Skynet at RailsConf 08 Sat Mar 31, 2008 4:25pm â€“ 5:15pm PDT @ Portland Ballroom 255 More Info What is Skynet Skynet is an open source Ruby implementation of Googleâ€™s MapReduce framework, created at Geni. With Skynet, one can easily convert a time-consuming serial task, such as a computationally expensive Rails migration, into a di
e-kuroda 2009/04/02
Ruby

MapReduce
ãƒªãƒ³ã‚¯
Skynet â€“ Ruby Implementation of MapReduce
Ruby Weekly is a weekly newsletter covering the latest Ruby and Rails news. Skynet is a new Ruby implementation of Google's MapReduce mechanism developed by Adam Pisoni. Rubyists may already be familiar with the more established Starfish by Lucas Carlson. I must confess that while Starfish's examples make immediate sense to me, without even needing to try the library, Skynet's are a little more fo
e-kuroda 2009/04/02
Ruby

MapReduce
ãƒªãƒ³ã‚¯
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