Impala
Apache Impala is the open source, native analytic database for open data and table formats. Follow us on Twitter at @ApacheImpala! Do BI-style Queries Impala provides low latency and high concurrency for BI/analytic queries on the Hadoop ecosystem, including Iceberg, open data formats, and most cloud storage options. Impala also scales linearly, even in multitenant environments. Unify Your Infrast
DataTorrent | An Instagram Blogs For Bots, Reviews & Guides
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Cascading
Please note that all new project news and releases have moved to https://cascading.wensel.net The Cascading Ecosystem is a collection of applications, languages, and APIs for developing data-intensive applications. At the ecosystem core is Cascading, a Java API for defining complex data flows and integrating those flows with back-end systems, and a query planner for mapping and executing logical f
Jubatus : Distributed Online Machine Learning Framework¶
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Hadoopã‚’æ¥å‹™ã§ä½¿ã£ã¦ã¿ãŸè©± - クックパッド開発者ブãƒã‚°
8月ã«å…¥ç¤¾ã—ãŸä½ã€…木ã§ã™ã€‚ã“ã‚“ã«ã¡ã‚ï¼ å…¥ç¤¾ã—ã¦ã‹ã‚‰ã¯Hadoopを使ã†ã“ã¨ãŒå¤šãã€æ—¥ã€…ã€å¤§è¦æ¨¡ãƒ‡ãƒ¼ã‚¿ã¨æ ¼é—˜ã—ã¦ã„ã¾ã™ã€‚大変ã§ã¯ã‚ã‚Šã¾ã™ãŒã€å€‹äººã§ã¯ãªã‹ãªã‹è§¦ã‚‹ã“ã¨ãŒå‡ºæ¥ãªã„よã†ãªå¤§è¦æ¨¡ãƒ‡ãƒ¼ã‚¿ã‚’触れるã®ã¯æ¥½ã—ã„ã§ã™ã€‚ ã•ã¦ã€Hadoopã¯æœ€è¿‘色々ãªã¨ã“ã‚ã§ä½¿ã‚れ始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‚“。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‚„Hadoopを使ã†ä¸Šã§ãƒã‚¤ãƒ³ãƒˆã ã¨æ€ã£ãŸã“ã¨ãªã©ã‚’社内勉強会ã§ç™ºè¡¨ã—ãŸã®ã§å…¬é–‹ã—ã¦ã¿ã¾ã™ã€‚Hadoopを使ã£ã¦ã„る（使ã„ãŸã„ã¨æ€ã£ã¦ã„る）方ã®å‚考ã«ãªã‚Œã°å¹¸ã„ã§ã™ã€‚ [slideshare id=2711363&doc=20091214techblog-091213183529-phpapp02] Hadoopã®åˆ©ç”¨ã¯ã¾ã ã¾ã 試行錯誤ã®é€£ç¶š
HadoopDB Project
HadoopDB An Architectural Hybrid of MapReduce and DBMS Technologies for Analytical Workloads. HadoopDB is: A hybrid of DBMS and MapReduce technologies that targets analytical workloads Designed to run on a shared-nothing cluster of commodity machines, or in the cloud An attempt to fill the gap in the market for a free and open source parallel DBMS Much more scalable than currently available parall
A Comparison of Approaches to Large-Scale Data Analysis - MapReduce vs. DBMS Benchmarks
A Comparison of Approaches to Large-Scale Data Analysis: MapReduce vs. DBMS Benchmarks Overview 04/14/2009 - SIGMOD 2009 Paper The following information is meant to provide documentation on how others can recreate the benchmark trials used in our SIGMOD 2009 paper. Our experiments were conducted on a 100-node cluster at the University of Wisconsin-Madison; each node had a single 2.40 GHz Intel Cor
本をèªã‚€ GREE Labsã§Hadoopã®è©±ã‚’èžã„ã¦ããŸ
GREEã•ã‚“ã§ä¸å®šæœŸã§ã‚„ã£ã¦ã‚‹ã€GREE Labsオープンソーステクノãƒã‚¸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€ŒGoogleを支ãˆã‚‹æŠ€è¡“ã€ã«ãƒˆã‚メã„ãŸäººãªã‚‰å¿…見ã§ã™ã。 発表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€‚最近ã®Webç³»ã§ã¯ã€ã‚µãƒ¼ãƒ“スé¢ã§ã‚‚マãƒã‚¿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€‚ プレゼン資料もust録画も公開ã•ã‚Œã¦ã„ã¾ã™ãŒã€ä»¥ä¸‹ã€è‡ªåˆ†ã®ãƒ¡ãƒ¢ã¨ã„ã†æ„味ã§è¨˜éŒ²ã—ã¦ãŠãã¾ã™ã€‚ Hadoopã«ã¤ã„ã¦ï¼ˆå¤ªç”°ä¸€æ¨¹ï¼‰ Preferred Infrastructureã®CTOã§ã€Sedueã®ä½œè€…。大é‡ã®ãƒ‡ãƒ¼ã‚¿ã®å‡¦ç†ãŒãƒ†ãƒ¼ãƒžã§ã€åŠåˆ†ã¯é…’ã§ã§ãã¦ã„ã‚‹w。ãã‚“ãªã“ã‚“ãªã§ã€ã¯ã¦ãƒ–検索ã§ã‚‚使ã‚ã‚Œã¦ã„
Hadoopã®è§£æžè³‡æ–™
オープンソース分散システム「Hadoopã€ã«é–¢ã™ã‚‹è§£æžè³‡æ–™ã‚’公開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(プレスリリース)。 Hadoop解æžè³‡æ–™(PDF), 最終更新: 2008/08/25, 公開: 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‚考下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—ルプãƒã‚°ãƒ©ãƒ ã®å®Ÿè¡Œ 複数マシンã¸Hadoopをインストールã™ã‚‹
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