[B! hadoop] nbqx69ã®ãƒ–ãƒƒã‚¯ãƒžãƒ¼ã‚¯

nbqx69 id:nbqx69

hadoopã«é–¢ã™ã‚‹nbqx69ã®ãƒ–ãƒƒã‚¯ãƒžãƒ¼ã‚¯ (26)

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ã‚°ãƒ¼ã‚°ãƒ«ç™ºã€ŒHadoopã€ã€æ—¥æœ¬ä¼æ¥ã‚‚åˆ©ç”¨ã¸
Hadoopã¯ã€ã‚°ãƒ¼ã‚°ãƒ«ãŒæ¤œç´¢ã‚¨ãƒ³ã‚¸ãƒ³ç”¨ã«é–‹ç™ºã—ãŸãƒãƒƒãƒå‡¦ç†ã‚·ã‚¹ãƒ†ãƒ ã‚’åŸºã«é–‹ç™ºã•ã‚ŒãŸã€ã‚ªãƒ¼ãƒ—ãƒ³ã‚½ãƒ¼ã‚¹ã‚½ãƒ•ãƒˆã ã€‚ã‚°ãƒ¼ã‚°ãƒ«ãŒé–‹ç™ºã—ãŸåˆ†æ•£ãƒ•ã‚¡ã‚¤ãƒ«ã‚·ã‚¹ãƒ†ãƒ ã€ŒGoogle File Systemï¼ˆGFSï¼‰ã€ã‚’æ¨¡ã—ãŸã€ŒHadoop Distributed File Systemï¼ˆHD FSï¼‰ã€ã¨ã€ãƒ‡ãƒ¼ã‚¿å‡¦ç†æ©Ÿæ§‹ã€ŒMapReduceã€ã‚’æ¨¡ã—ãŸã€ŒHadoop MapReduceã€ã§æ§‹æˆã™ã‚‹ã€‚ ç±³å›½ã§ã¯ç±³VISAã‚„ç±³JPãƒ¢ãƒ«ã‚¬ãƒ³ãƒ»ãƒã‚§ãƒ¼ã‚¹ã®ã‚ˆã†ãªå¤§æ‰‹é‡‘èžæ©Ÿé–¢ãŒã€ãƒãƒƒãƒå‡¦ç†ã«Hadoopã‚’ä½¿ç”¨ã™ã‚‹ã€‚ ãã®HadoopãŒã„ã‚ˆã„ã‚ˆã€æ—¥æœ¬ä¼æ¥ã§ã‚‚ä½¿ã‚ã‚Œå§‹ã‚ãŸã€‚ä¾‹ãˆã°æ¥½å¤©ã¯ã€ã‚ã‚‹å•†å“ã«å¯¾ã™ã‚‹ãŠè–¦ã‚å•†å“ã‚’ãƒªã‚¹ãƒˆã‚¢ãƒƒãƒ—ã™ã‚‹ã€Œãƒ¬ã‚³ãƒ¡ãƒ³ãƒ‰å‡¦ç†ã€ã«Hadoopã‚’ä½¿ç”¨ã™ã‚‹ã€‚NTTãƒ‡ãƒ¼ã‚¿ã¯ã€å…¨å›½ã®æ¸‹æ»žæƒ…å ±ã‚’ãƒªã‚¢ãƒ«ã‚¿ã‚¤ãƒ ã«å¯è¦–åŒ–ã™ã‚‹ã‚·ã‚¹ãƒ†ãƒ ã®æ§‹ç¯‰ã«Hadoopã‚’æŽ¡ç”¨ã—ãŸã€‚ä¸‰è±UFJã‚¤ãƒ³ãƒ•ã‚©ãƒ¡ãƒ¼ã‚·ãƒ§ãƒ³ãƒ†ã‚¯ãƒŽãƒã‚¸ãƒ¼ã‚‚Hadoopã‚’ä½¿ã£
nbqx69 2011/01/18
hadoop
ãƒªãƒ³ã‚¯
Hadoopã¯å€Ÿã‚Šã¦ä½¿ãˆ - masayang's diary
NTTãƒ‡ãƒ¼ã‚¿ãŒå…¬é–‹ã—ãŸHadoopè³‡æ–™ãŒè©±é¡Œã«ãªã£ã¦ã„ã‚‹ã€‚ã–ã£ã¨èªã‚€é™ã‚Šã€ã‚³ãƒ¼ãƒ‰äº‹ä¾‹ã‚‚ã‚ã£ã¦å‚è€ƒã«ãªã‚‹ã“ã¨ã¯ç¢ºã‹ã€‚èªã¾ãªã„æ‰‹ã¯ãªã„ã ã‚ã†ã€‚ ã ã‘ã©ã€Hadoopç’°å¢ƒã‚’è‡ªå‰ã§æ§‹ç¯‰ã™ã‚‹ã“ã¨ã«ã¯ç§ã¯ã‚ã¾ã‚Šè³›åŒã§ããªã„ã€‚æŠ€è¡“å±‹ãŒå‹‰å¼·ã™ã‚‹ãŸã‚ã€ã¨ã„ã†ã®ãªã‚‰è©±ã¯åˆ¥ã ã‘ã©ã€äº‹æ¥ã§Hadoopã‚’ä½¿ã†ã®ãªã‚‰ã‚¯ãƒ©ã‚¦ãƒ‰ä¸Šã®ã‚’å€Ÿã‚Šã‚‹ã“ã¨ã‚’ãŠå‹§ã‚ã™ã‚‹ã€‚ ä¾‹ãˆã°1000å°ã®ã‚¯ãƒ©ã‚¹ã‚¿ã‚’æ§‹ç¯‰ã—ã¦ã€ãƒ‡ã‚¤ãƒªãƒ¼ãƒãƒƒãƒå‡¦ç†ãŒ5åˆ†ã§çµ‚ã‚ã‚‹ã‚ˆã†ã«ãªã£ãŸï¼ã€€ã¨å–œã¶ã®ã‚‚è‰¯ã„ã ã‚ã†ã€‚ã§ã‚‚ã€æ®‹ã‚Šã®23æ™‚é–“55åˆ†ã¯ãã®ã‚¯ãƒ©ã‚¹ã‚¿ã©ã†ã™ã‚‹ã®ã‹ï¼Ÿå¯ã‹ã›ã¦ãŠãã®ã§ã‚ã‚Œã°ROIè©•ä¾¡ã¯éžå¸¸ã«ä½Žã„ã‚‚ã®ã«ãªã‚‹ã ã‚ã†ã€‚ ã‹ã¨ã„ã£ã¦ã‚±ãƒã£ã¦5å°ã®ã‚¯ãƒ©ã‚¹ã‚¿ã«ã—ãŸã‚‰ã»ã¼1æ—¥ä¸ç¨¼å‹•ã—ãŸã®ã§ROIã¯é«˜ããªã‚Šã¾ã—ãŸãŒå‡¦ç†æ™‚é–“çŸç¸®ã«ã¯è‡³ã‚Šã¾ã›ã‚“ã§ã—ãŸã€ãªã‚“ã¦ã„ã†ã®ã‚‚é¦¬é¹¿ã’ã¦ã„ã‚‹ã€‚ ã˜ã‚ƒã€ã©ã“ã«æœ€é©ç‚¹ãŒã‚ã‚‹ã®ã‹ï¼Ÿ ç”ã¯ã€Œè‡ªå‰ã§æŒãŸãšã€å¿…è¦ãªã¨ãã«å¿…è¦ãªå°æ•°ã®ã‚¯ãƒ©ã‚¹ã‚¿ã‚’å€Ÿã‚Šã‚‹ã€
nbqx69 2010/09/29
hadoop
ãƒªãƒ³ã‚¯
NTTãƒ‡ãƒ¼ã‚¿ã®Hadoopå ±å‘Šæ›¸ãŒã™ã”ã‹ã£ãŸ - ç§‘å¦ã¨éžç§‘å¦ã®è¿·å®®
æ¥ç•Œãƒˆãƒƒãƒ— ã®ã‚¨ãƒ³ã‚¿ãƒ¼ãƒ—ãƒ©ã‚¤ã‚º Hadoop ä¼æ¥ Cloudera ã«å…¥ç¤¾ã—ã¾ã—ãŸ http://www.cloudera.co.jp/ ä»Šå¹´ã®6æœˆã«ã€ã€Œå¹³æˆï¼’ï¼‘å¹´åº¦ ç”£å¦é€£æºã‚½ãƒ•ãƒˆã‚¦ã‚§ã‚¢å·¥å¦å®Ÿè·µäº‹æ¥å ±å‘Šæ›¸ã€ã¨ã„ã†ãƒ‰ã‚ãƒ¥ãƒ¡ãƒ³ãƒˆç¾¤ãŒçµŒç”£çœã‹ã‚‰å…¬è¡¨ã•ã‚Œã¾ã—ãŸã€‚ ãã®ã†ã¡ã®ä¸€ã¤ã«ã€NTTãƒ‡ãƒ¼ã‚¿ã«å§”è¨—ã•ã‚ŒãŸHadoopã«é–¢ã™ã‚‹å®Ÿè¨¼å®Ÿé¨“ã®å ±å‘Šæ›¸ãŒã‚ã‚Šã¾ã—ãŸã®ã§ã€ä»Šæ›´ãªãŒã‚‰èªã‚“ã§ã¿ã‚‹ã“ã¨ã«ã—ã¾ã—ãŸã€‚ Hadoopç•Œéšˆã®äººã¯ã‚‚ã†ã¿ã‚“ãªã¨ã£ãã«èªã‚“ã§ã‚‹ã®ã‹ã‚‚ã—ã‚Œã¾ã›ã‚“ã‘ã©ã€‚ http://www.meti.go.jp/policy/mono_info_service/joho/downloadfiles/2010software_research/clou_dist_software.pdf ã€Œé«˜ä¿¡é ¼ã‚¯ãƒ©ã‚¦ãƒ‰å®Ÿç¾ç”¨ã‚½ãƒ•ãƒˆã‚¦ã‚§ã‚¢é–‹ç™ºï¼ˆåˆ†æ•£åˆ¶å¾¡å‡¦ç†æŠ€è¡“ç‰ã«ä¿‚ã‚‹ãƒ‡ãƒ¼ã‚¿ã‚»ãƒ³ã‚¿ãƒ¼é«˜ä¿¡é ¼åŒ–ã«å‘ã‘ãŸå®Ÿè¨¼äº‹æ¥ï¼‰ã€ã¨ã„ã†
nbqx69 2010/09/29
hadoop
ãƒªãƒ³ã‚¯
Hadoopã¨MongoDBã‚’æ´»ç”¨ã—ãŸã‚½ãƒ¼ã‚·ãƒ£ãƒ«ã‚¢ãƒ—ãƒªã®ãƒã‚°è§£æž
The document describes the structure of various user activity log collections stored in different databases. It includes collections for errors, access logs, attribute changes, status changes, and purchase charges with details on the fields captured for each user event.Read less
nbqx69 2010/09/28
mongodb

hadoop
ãƒªãƒ³ã‚¯
ãã®åˆ†æžã€Hadoopãªã‚‰é€Ÿãå®‰ãã§ãã¾ã™
ãƒ“ã‚¸ãƒã‚¹ãƒ‡ãƒ¼ã‚¿ã‚’åˆ†æžã™ã‚‹ãƒ“ã‚¸ãƒã‚¹ã‚¤ãƒ³ãƒ†ãƒªã‚¸ã‚§ãƒ³ã‚¹ï¼ˆBIï¼‰åˆ†é‡Žã®æ–°ãŸãªãƒ—ãƒ©ãƒƒãƒˆãƒ•ã‚©ãƒ¼ãƒ ã¨ã—ã¦æ³¨ç›®ã•ã‚Œã¦ã„ã‚‹Hadoopã€‚Hadoopã§ã¯ã€ã©ã®ã‚ˆã†ãªãƒ‡ãƒ¼ã‚¿åˆ†æžãŒå¯èƒ½ãªã®ã§ã—ã‚‡ã†ã‹ï¼Ÿ ç¾åœ¨ã€Hadoopãƒ“ã‚¸ãƒã‚¹ã®ç‰½å¼•å½¹ã§ã‚ã‚‹Clouderaã®Jeff Hammerbracheræ°ãŒã€Hadoopã§ãƒ‡ãƒ¼ã‚¿åˆ†æžãŒå¯èƒ½ãªãƒ“ã‚¸ãƒã‚¹ä¸Šã®èª²é¡Œã‚’ç¤ºã—ãŸã€Œ10 Common Hadoop-able probl emsã€ï¼ˆHadoopåŒ–å¯èƒ½ãª10ã®ä¸€èˆ¬çš„èª²é¡Œï¼‰ã¨é¡Œã—ãŸãƒ—ãƒ¬ã‚¼ãƒ³ãƒ†ãƒ¼ã‚·ãƒ§ãƒ³ã‚’å…¬é–‹ã—ã¦ã„ã¾ã™ã€‚ Hadoopã«ã¨ã£ã¦å¾—æ„ãªå‡¦ç†ã¨ã¯ã€è¤‡é›‘ã§è¤‡æ•°ã®ãƒ‡ãƒ¼ã‚¿ã‚½ãƒ¼ã‚¹ã‹ã‚‰ãªã‚‹å¤§é‡ã®ãƒ‡ãƒ¼ã‚¿ã®åˆ†æžã§ã‚ã‚Šã€ãã‚Œã‚’ãƒãƒƒãƒå‡¦ç†ã®ä¸¦åˆ—å®Ÿè¡Œã«ã‚ˆã£ã¦å®Ÿç¾ã™ã‚‹ã“ã¨ã§ã™ã€‚ å¾“æ¥ã¯ã€ãƒ‡ãƒ¼ã‚¿ãŒã‚ã¾ã‚Šã«è¤‡é›‘ã ã£ãŸã‚Šè†¨å¤§ã ã£ãŸã‚ã«ã€è¨ˆç®—æ™‚é–“ã‚„ã‚³ã‚¹ãƒˆãªã©ã®ç†ç”±ã§å®Ÿç¾ãŒé›£ã—ã‹ã£ãŸå‡¦ç†ã§ã‚‚ã€Hadoopã«ã‚ˆã‚‹ä½Žã‚³ã‚¹ãƒˆåŒ–ã€è¨ˆç®—æ™‚é–“ã®çŸç¸®ã€é«˜ã„æŸ”è»Ÿæ€§ãªã©
nbqx69 2010/08/27
hadoop
ãƒªãƒ³ã‚¯
IBM Developer
IBM Developer is your one-stop location for getting hands-on training and learning in-demand skills on relevant techno logies such as generative AI, data science, AI, and open source.
nbqx69 2010/08/23
hadoop
ãƒªãƒ³ã‚¯
å¤§é‡ãƒ‡ãƒ¼ã‚¿ã®ãƒãƒƒãƒå‡¦ç†ã‚’é«˜é€ŸåŒ–ã™ã‚‹Hadoop
Hadoopã¨ã„ã†ã‚½ãƒ•ãƒˆã‚¦ã‚¨ã‚¢ãŒã€ã„ã¾æ³¨ç›®ã‚’é›†ã‚ã¦ã„ã¾ã™ã€‚ç±³GoogleãŒç™ºè¡¨ã—ãŸè«–æ–‡ã®ã‚¢ã‚¤ãƒ‡ã‚£ã‚¢ã‚’ã‚ªãƒ¼ãƒ—ãƒ³ã‚½ãƒ¼ã‚¹ãƒ»ãƒ¢ãƒ‡ãƒ«ã§å®Ÿè£…ã—ãŸã‚½ãƒ•ãƒˆã‚¦ã‚¨ã‚¢ã§ã™ã€‚è†¨å¤§ãªé‡ã®ãƒ‡ãƒ¼ã‚¿ã‚’å‡¦ç†ã™ã‚‹å¿…è¦ã«è¿«ã‚‰ã‚ŒãŸä¼æ¥ã‚„ç ”ç©¶çµ„ç¹”ãŒã€ç¶šã€…ã¨Hadoopã‚’å®Ÿéš›ã«æ´»ç”¨ã—ã¯ã˜ã‚ã¦ã„ã¾ã™ã€‚ ç§ãŸã¡ã®ç ”ç©¶ã‚°ãƒ«ãƒ¼ãƒ—ã§ã¯ã€Wikipediaãªã©ã®å·¨å¤§ãªãƒ†ã‚ã‚¹ãƒˆãƒ»ãƒ‡ãƒ¼ã‚¿ã‚’è§£æžã™ã‚‹ãŸã‚ã«ã€2007å¹´é ƒã‹ã‚‰Hadoopã‚’åˆ©ç”¨ã—ã¯ã˜ã‚ã¾ã—ãŸãŒã€æ—¥æœ¬å›½å†…ã§ã‚‚2009å¹´ã‚ãŸã‚Šã‹ã‚‰Hadoopã‚’ä½¿ã£ãŸäº‹ä¾‹ã‚’å¤šãè¦‹èžãã™ã‚‹ã‚ˆã†ã«ãªã‚Šã¾ã—ãŸã€‚å›½å†…ã§åˆã‚ã¦ã®Hadoopé–¢é€£ã‚¤ãƒ™ãƒ³ãƒˆãŒ2009å¹´11æœˆã«æ±äº¬ã§é–‹å‚¬ã•ã‚Œã€ã‚ªãƒ©ã‚¤ãƒªãƒ¼ãƒ»ã‚¸ãƒ£ãƒ‘ãƒ³ã‹ã‚‰2010å¹´1æœˆã«Hadoopæœ¬ã®é‚¦è¨³ãŒå‡ºç‰ˆã•ã‚Œã‚‹ãªã©ã€HadoopãŒå¤šãã®é–‹ç™ºè€…ã®æ³¨ç›®ã‚’æµ´ã³ã¦ã„ã¾ã™ã€‚ ã—ã‹ã—ãªãŒã‚‰ã€ã€ŒHadoopã¯ä½•ã¨ãªãã™ã”ãã†ãªã‚“ã ã‘ã©ã€è¤‡é›‘ã ã—ã€ã©ã‚“ãªã‚½ãƒ•ãƒˆãªã®ã‹ã„ã¾ã„ã¡åˆ†ã‹ã‚‰ãªã„ã‚“ã
nbqx69 2010/06/04
hadoop
ãƒªãƒ³ã‚¯
http://shibuya.lisp-users.org/2010/03/21/sllt-5-mov-4/
nbqx69 2010/03/21
clojure

leiningen

hadoop
ãƒªãƒ³ã‚¯
Hadoopã‚’ä½¿ã„ã“ãªã™(1)
ã¾ãšã€ 1 ã®å…¥åŠ›ãƒ•ã‚¡ã‚¤ãƒ«ã‚’åˆ†å‰²ã™ã‚‹æ–¹æ³•ã¯ã€InputFormatã‚¯ãƒ©ã‚¹ã®ã€getSplitsé–¢æ•°ã‚’ä¸Šæ›¸ãã™ã‚‹ã“ã¨ã§ã€ã‚«ã‚¹ã‚¿ãƒžã‚¤ã‚ºã§ãã¾ã™ã€‚ ã¾ãŸã€ 3 ã®InputSplitã‹ã‚‰ã€Keyã¨Valueã‚’æŠ½å‡ºã™ã‚‹å‡¦ç†ã‚‚ã€InputFormatã‚¯ãƒ©ã‚¹ã‚’é€šã˜ã¦ã‚«ã‚¹ã‚¿ãƒžã‚¤ã‚ºã§ãã¾ã™ã€‚ InputFormatã®getRecordReaderé–¢æ•°ã‚’é€šã˜ã¦ã€RecordReaderã‚¯ãƒ©ã‚¹ã‚’ç”Ÿæˆã™ã‚‹ã®ã§ã™ãŒã€ã“ã‚Œã«ä»»æ„ã®RecordReaderã‚¯ãƒ©ã‚¹ã‚’æŒ‡å®šã™ã‚Œã°OKã§ã™ã€‚ 2 ã®Mapå‡¦ç†ã§ã™ãŒã€ãƒ¦ãƒ¼ã‚¶ãŒæŒ‡å®šã—ãŸMapperã‚¯ãƒ©ã‚¹ã®å‡¦ç†ã‚’å®Ÿè¡Œã—ã¾ã™ã€‚ Mapperã‚¯ãƒ©ã‚¹ã¯ã€MapRunnerã‚¯ãƒ©ã‚¹ã‚’é€šã˜ã¦ã€åˆæœŸåŒ–å‡¦ç†ã€mapé–¢æ•°ã‚’ç¹°ã‚Šè¿”ã™éŽç¨‹ã€çµ‚äº†å‡¦ç†ã¨ã„ã£ãŸä¸€é€£ã®æµã‚Œã‚’å®Ÿè¡Œã—ã¾ã™ã€‚ MapRunnerã‚¯ãƒ©ã‚¹ã‚’ã‚«ã‚¹ã‚¿ãƒžã‚¤ã‚ºã™ã‚Œã°ã€ã“ã†ã—ãŸæµã‚Œã‚’åˆ¶å¾¡ã™ã‚‹ã“ã¨ãŒã§ãã¾ã™ã€‚ 0.20.0ã‹ã‚‰ã®æ–°ã—ã„MapRed
nbqx69 2010/03/17
hadoop
ãƒªãƒ³ã‚¯
Measuring Measures: The Agony of Clojure/Hadoop Logging, and How to Fix It
Tuesday, January 19, 2010 The Agony of Clojure/Hadoop Logging, and How to Fix It I recently had a nasty time working out a sane way to deal with logging for Hadoop testing.Â I will talk about testing Hadoop and Cascading (and distributed systems in general) in a separate post. What I want to talk about here is some major gotcha action that I fell prey to with the integration between the Slime/Swan
nbqx69 2010/01/20
clojure

hadoop
ãƒªãƒ³ã‚¯
clojure-hadoop 1.1.0 release â€“ Digital Digressions by Stuart Sierra
nbqx69 2010/01/16
clojure

hadoop
ãƒªãƒ³ã‚¯
Coming soon
nbqx69 2010/01/13
hadoop
ãƒªãƒ³ã‚¯
Coming soon
nbqx69 2010/01/13
clojure

hadoop

reddit
ãƒªãƒ³ã‚¯
Hadoopã‚’æ¥å‹™ã§ä½¿ã£ã¦ã¿ãŸè©± - ã‚¯ãƒƒã‚¯ãƒ‘ãƒƒãƒ‰é–‹ç™ºè€…ãƒ–ãƒã‚°
8æœˆã«å…¥ç¤¾ã—ãŸä½ã€…æœ¨ã§ã™ã€‚ã“ã‚“ã«ã¡ã‚ï¼ å…¥ç¤¾ã—ã¦ã‹ã‚‰ã¯Hadoopã‚’ä½¿ã†ã“ã¨ãŒå¤šãã€æ—¥ã€…ã€å¤§è¦æ¨¡ãƒ‡ãƒ¼ã‚¿ã¨æ ¼é—˜ã—ã¦ã„ã¾ã™ã€‚å¤§å¤‰ã§ã¯ã‚ã‚Šã¾ã™ãŒã€å€‹äººã§ã¯ãªã‹ãªã‹è§¦ã‚‹ã“ã¨ãŒå‡ºæ¥ãªã„ã‚ˆã†ãªå¤§è¦æ¨¡ãƒ‡ãƒ¼ã‚¿ã‚’è§¦ã‚Œã‚‹ã®ã¯æ¥½ã—ã„ã§ã™ã€‚ ã•ã¦ã€Hadoopã¯æœ€è¿‘è‰²ã€…ãªã¨ã“ã‚ã§ä½¿ã‚ã‚Œå§‹ã‚ã¦ãã¦ã„ã‚‹ã¨æ€ã†ã‚“ã§ã™ãŒã€å®Ÿéš›ã«åˆ©ç”¨ã—ã¦ã¿ã¦å›°ã£ãŸäº‹ã‚„tipsãªã©ã€å®Ÿè·µçš„ãªæƒ…å ±ã¯ã¾ã ã‚ã¾ã‚Šå…¬é–‹ã•ã‚Œã¦ã„ã¾ã›ã‚“ã€‚ãã®è¾ºã®æƒ…å ±ã‚’ã¿ã‚“ãªæ±‚ã‚ã¦ã„ã‚‹ã¯ãšâ€¦ï¼ï¼ ãã“ã§ã€åƒ•ãŒå®Ÿéš›ã«è§¦ã£ã¦ã¿ã¦å›°ã£ãŸäº‹ã‚„Hadoopã‚’ä½¿ã†ä¸Šã§ãƒã‚¤ãƒ³ãƒˆã ã¨æ€ã£ãŸã“ã¨ãªã©ã‚’ç¤¾å†…å‹‰å¼·ä¼šã§ç™ºè¡¨ã—ãŸã®ã§å…¬é–‹ã—ã¦ã¿ã¾ã™ã€‚Hadoopã‚’ä½¿ã£ã¦ã„ã‚‹ï¼ˆä½¿ã„ãŸã„ã¨æ€ã£ã¦ã„ã‚‹ï¼‰æ–¹ã®å‚è€ƒã«ãªã‚Œã°å¹¸ã„ã§ã™ã€‚ [slideshare id=2711363&doc=20091214tech blog-091213183529-phpapp02] Hadoopã®åˆ©ç”¨ã¯ã¾ã ã¾ã è©¦è¡ŒéŒ¯èª¤ã®é€£ç¶š
nbqx69 2009/12/18
hadoop
ãƒªãƒ³ã‚¯
Cloudera Blog
nbqx69 2009/11/25
hadoop

clojure
ãƒªãƒ³ã‚¯
Progressive Data Solutions - Ruby on Hadoop Quickstart
After my recent experiences with CouchDB (which is a great product) I was forced to look for something that could handle large amounts of data more efficiently. After doing some research, I settled on Hadoop. If you are dealing with truly large amounts of data, in the multiple terabyte range or larger, there really are only a few options available to efficiently store and process that data. If you
nbqx69 2009/09/23
ruby

hadoop
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ã‚¯ãƒƒã‚¯ãƒ‘ãƒƒãƒ‰ã¨Hadoop - ã‚¯ãƒƒã‚¯ãƒ‘ãƒƒãƒ‰é–‹ç™ºè€…ãƒ–ãƒã‚°
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nbqx69 2009/09/17
hadoop
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blog.katsuma.tv
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nbqx69 2009/08/05
hadoop

javascript

mapreduce
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â– HadoopDBã®ã‚¢ãƒ¼ã‚ãƒ†ã‚¯ãƒãƒ£ã«ã¤ã„ã¦ HadoopDB: An Architectural Hybrid of MapReduce and DBMS Techno logies for Analytical Workloads. Azza Abouzeid, Kamil Bajda-Pawlikowski, Daniel J. Abadi, Avi Silberschatz, Alex Rasin. In Proceedings of VLDB, 2009. ã‚ˆã‚Šã€ HadoopDBã®ã‚¢ãƒ¼ã‚ãƒ†ã‚¯ãƒãƒ£ã«é–¢ã™ã‚‹ç« ã‹ã‚‰ã€Hadoopã«è¿½åŠ ã•ã‚ŒãŸï¼”ã¤ã®ã‚³ãƒ³ãƒãƒ¼ãƒãƒ³ãƒˆã«ã¤ã„ã¦é †ã«èªã‚“ã§ãã¾ã™ã€‚ â–¼Database Connector Database Connectorã¯ã€ã‚¯ãƒ©ã‚¹ã‚¿ã®å„ãƒŽãƒ¼ãƒ‰ã«ã‚ã‚‹å€‹åˆ¥ã®ãƒ‡ãƒ¼ã‚¿ãƒ™ãƒ¼ã‚¹ã¨TaskTrackerã®é–“ã®ã‚¤ãƒ³ã‚¿ãƒ•ã‚§ãƒ¼ã‚¹ã§ã€ Hadoopã®InputFo
nbqx69 2009/08/02
hadoop

db
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HadoopDB | Silicon Soul
ã‚ªãƒ¬ãƒ³ã‚¸ãƒ‹ãƒ¥ãƒ¼ã‚¹ã•ã‚“ã§Hadoopã¨RDBMSã®ãã‚Œãžã‚Œã®ç‰¹æ€§ã‚’ã‚ã‚ã›ãŸã€ŒHadoopDBã€ã¨ã„ã†ProductãŒç´¹ä»‹ã•ã‚Œã¦ã„ã¾ã—ãŸã€‚ é–‹ç™ºè€…ã«ã‚ˆã‚‹ãƒªãƒªãƒ¼ã‚¹ãƒŽãƒ¼ãƒˆã¯ã“ã¡ã‚‰ã§ã™ã€‚ â– Announcing release of HadoopDB (longer version) HadoopDBã®ç‰¹å¾´ã¯ 1. DBMSã¨MapReduceã®ãƒã‚¤ãƒ–ãƒªãƒƒãƒ‰ã§ã€åˆ†æžä½œæ¥ã‚’å¯¾è±¡ã«ã—ã¦ã„ã‚‹ 2. ä¸€èˆ¬çš„ãªã‚µãƒ¼ãƒã§æ§‹ç¯‰ã•ã‚ŒãŸã€ï¼ˆãƒ¡ãƒ¢ãƒªã¨ã‹Diskã¨ã‹ã®ï¼‰å…±æœ‰ç„¡ã—ã®ã‚¯ãƒ©ã‚¹ã‚¿ã¾ãŸã¯ã‚¯ãƒ©ã‚¦ãƒ‰ä¸Šã§å‹•ä½œã™ã‚‹ã‚ˆã†ãƒ‡ã‚¶ã‚¤ãƒ³ã•ã‚Œã¦ã„ã‚‹ 3. ãƒ•ãƒªãƒ¼ãƒ»ã‚ªãƒ¼ãƒ—ãƒ³ã‚½ãƒ¼ã‚¹ä¸¦åˆ—DBã®ãƒžãƒ¼ã‚±ãƒƒãƒˆã®ã‚®ãƒ£ãƒƒãƒ—ã‚’åŸ‹ã‚ã‚‹ã“ã¨ã‚’æ„å›³ã—ã¦ã„ã‚‹ 4. æ—¢å˜ã®ä¸¦åˆ—DBã‚·ã‚¹ãƒ†ãƒ ã‚„DBMS/MapReduceãƒã‚¤ãƒ–ãƒªãƒƒãƒ‰ã‚·ã‚¹ãƒ†ãƒ ã‚ˆã‚Šã‚¹ã‚±ãƒ¼ãƒ©ãƒ–ãƒ« 5. Hadoopã¨åŒæ§˜ã®ã‚¹ã‚±ãƒ¼ãƒ©ãƒ“ãƒªãƒ†ã‚£ã§ã€æ§‹é€ åŒ–ãƒ‡ãƒ¼ã‚¿åˆ†æžä½œæ¥ã«ãŠã„ã¦ã€å„ªã‚ŒãŸãƒ‘ãƒ•ã‚©ãƒ¼ãƒžãƒ³ã‚¹ã‚’
nbqx69 2009/07/24
hadoop
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