The Elephant was a Trojan Horse: On the Death of Map-Reduce at Google - Paper Trail
Note: this is a personal blog post, and doesn’t reflect the views of my employers at Cloudera Map-Reduce is on its way out. But we shouldn’t measure its importance in the number of bytes it crunches, but the fundamental shift in data processing architectures it helped popularise. This morning, at their I/O Conference, Google revealed that they’re not using Map-Reduce to process data internally at
pandas - Python Data Analysis Library
pandas is a fast, powerful, flexible and easy to use open source data analysis and manipulation tool, built on top of the Python programming language. Install pandas now!
A Brief History of Decision Support Systems
Summary Information Systems researchers and technologists have built and investigated computerized Decision Support Systems (DSS) for approximately 40 years. This article chronicles and explores the developments related to building and deploying DSS. The journey begins with building model-driven DSS in the late 1960s, theory developments in the 1970s, and implementation of financial planning syste
Hadoop vs MPPデータベース
Kazuki Ohta @kzk_mover MPP DBã¨ã—ã¦å¤å‚ã®SybaseIQã¯15年以上å˜åœ¨ã—ã¦ãŠã‚Šã€å€¤æ®µæ„Ÿã‚‚æ‰‹é ƒãªå¥´ã‚‚ã‚る。対ã—ã¦Hadoopを使ã£ã¦ã‚‹äººã¯ç†ç”±ãŒã‚ã‚‹ã—ã€å®‰ãã¦æ‰‹è»½ãªMPPデータベースãŒå‡ºã¦ããŸã‹ã‚‰å®‰æ˜“ã«Hadoopã‹ã‚‰ãã¡ã‚‰ã«ç§»ã‚‹ã®ã¯ã‚·ã‚¹ãƒ†ãƒ ã®Pros/Consã‚’æ£ã—ãç†è§£ã—ã¦ã„ãªã‹ã£ãŸã‚±ãƒ¼ã‚¹ã€‚ Kazuki Ohta @kzk_mover Twitter/Evernote/Netflixを見ã¦ã„ã‚‹ã¨ã€ç”Ÿã®éžæ§‹é€ 化データをã¨ã«ã‹ãHadoopã«è²¯ã‚ã€MRã§æ§‹é€ 化ã—ãŸãƒ‡ãƒ¼ã‚¿ã‚ューブをMPPDBã«å…¥ã‚Œä½Žãƒ¬ã‚¤ãƒ†ãƒ³ã‚·ã§è§£æžã™ã‚‹ã®ãŒå‹ã¡ãƒ‘ターン。大ä¼æ¥ã§ã¯å…¨ãƒ‡ãƒ¼ã‚¿ã‚½ãƒ¼ã‚¹ã®ã‚¹ã‚ーマをIT部門ãŒç®¡ç†ã™ã‚‹ã®ã¯å›°é›£ã‚‚ã—ãã¯ä¸å¯èƒ½ã€‚
インメモリデータベース「MemSQL 2.0ã€å…¬é–‹ã€‚数百ノードã¸ã‚¹ã‚±ãƒ¼ãƒ«ã‚¢ã‚¦ãƒˆå¯èƒ½ã§å¤§è¦æ¨¡ãƒ‡ãƒ¼ã‚¿ãƒ™ãƒ¼ã‚¹å¯¾å¿œã¸ ï¼ Publickey
データベースをã¾ã‚‹ã”ã¨ãƒ¡ã‚¤ãƒ³ãƒ¡ãƒ¢ãƒªä¸Šã§å‡¦ç†ã™ã‚‹ã“ã¨ã«ã‚ˆã‚Šã€å¾“æ¥ã®ãƒãƒ¼ãƒ‰ãƒ‡ã‚£ã‚¹ã‚¯ãƒ™ãƒ¼ã‚¹ã®ãƒªãƒ¬ãƒ¼ã‚·ãƒ§ãƒŠãƒ«ãƒ‡ãƒ¼ã‚¿ãƒ™ãƒ¼ã‚¹ã‚ˆã‚Šã‚‚劇的ãªé«˜é€ŸåŒ–を実ç¾ã™ã‚‹ã‚¤ãƒ³ãƒ¡ãƒ¢ãƒªãƒ‡ãƒ¼ã‚¿ãƒ™ãƒ¼ã‚¹ã§ã‚ã‚‹MemSQLã®æœ€æ–°ç‰ˆã€ŒMemSQL 2.0ã€ãŒå…¬é–‹ã•ã‚Œã¾ã—ãŸã€‚ MemSQL 2.0ã¯ã‚¤ãƒ³ãƒ¡ãƒ¢ãƒªã®ã‚¹ãƒ”ードã¨SQLã§ã®å•ã„åˆã‚ã›ã€ã‚¹ã‚±ãƒ¼ãƒ«ã‚¢ã‚¦ãƒˆæ©Ÿèƒ½ã€ãã—ã¦ã‚¨ãƒ³ã‚¿ãƒ¼ãƒ—ライズ対応ã®å¯ç”¨æ€§ãªã©ã€4ã¤ã®ç‰¹å¾´ã‚’æŒã¤ã¨èª¬æ˜Žã•ã‚Œã¦ã„ã¾ã™ã€‚ In-memory architecture Ad hoc SQL-based analytics Horizontal scale-out on commodity hardware Enterprise-grade durability and high availability スケールアウトã§ãƒ‡ãƒ¼ã‚¿ã‚¦ã‚§ã‚¢ãƒã‚¦ã‚¹ã«å¯¾å¿œ MemSQL 2.0ã¯ã‚¤ãƒ³ãƒ¡ãƒ¢ãƒªãƒ‡ãƒ¼ã‚¿ãƒ™ãƒ¼ã‚¹ã®ç‰¹å¾´ã§ã‚る高速ãªå‡¦ç†ã«åŠ ãˆã¦ã€
Roundup of Big Data Forecasts and Market Estimates, 2012
From the best-known companies in enterprise software to start-ups, everyone is jumping on the big data bandwagon. The potential of big data to bring insights and intelligence into enterprises is a strong motivator, where managers are constantly looking for the competitive edge to win in their chosen  markets. With so much potential to provide enterprises with enhanced analytics, insights and inte
Data analytics with hadoop hive on multiple data centers
This document discusses GMO Internet's data analytics system for analyzing social game data from over 500 game titles across multiple data centers in Japan and the US. It summarizes the system's architecture, which uses Hadoop/Hive to process logging data from game servers into hourly, daily, weekly, and monthly reports on key performance indicators. The system partitions and stores large volumes
IDC: Analytics a $51B business by 2016 thanks to big data – Old GigaOm
The market for business analytics software grew 14 percent in 2011 and will hit $50.7 billion in revenue by 2016, according to market research firm IDC. And, that segment will grow at a 9.8-percent-a-year clip until then, IDC predicts, driven in part by the current hype around big data. The renewed importance of analytics software comes as the idea of  big data has opened companies’ eyes as to the
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ç·å‹™çœã¯2012å¹´4月27æ—¥ã€ã€Œæƒ…å ±é€šä¿¡å¯©è°ä¼šã€€æƒ…å ±é€šä¿¡æ”¿ç–部会　新事æ¥å‰µå‡ºæˆ¦ç•¥å§”å“¡ä¼šãƒ»ç ”ç©¶é–‹ç™ºæˆ¦ç•¥å§”å“¡ä¼šï¼ˆç¬¬9回）（åˆåŒé–‹å‚¬ï¼‰ ã€ã‚’開催ã—ã€ã€Œ2020å¹´é ƒã«å‘ã‘ãŸICTç·åˆæˆ¦ç•¥ã®æ¤œè¨ŽçŠ¶æ³ã«ã¤ã„ã¦ã€ã¨ã€Œãƒ“ッグデータã®æ´»ç”¨ã«é–¢ã™ã‚‹ã‚¢ãƒ‰ãƒ›ãƒƒã‚¯ã‚°ãƒ«ãƒ¼ãƒ—ã®æ¤œè¨ŽçŠ¶æ³ã€ã«é–¢ã™ã‚‹è³‡æ–™ã‚’公開ã—ã¾ã—ãŸã€‚ 今回ã¯ã€ãƒ“ッグデータã®æ´»ç”¨ã«é–¢ã™ã‚‹ã‚¢ãƒ‰ãƒ›ãƒƒã‚¯ã‚°ãƒ«ãƒ¼ãƒ—ã®å–り組ã¿ã¨ã€æœ¬ã‚°ãƒ«ãƒ¼ãƒ—ã§ãƒ’アリングを実施ã—ãŸå›½å†…ã«ãŠã‘るビッグデータã®æ´»ç”¨ã«é–¢ã™ã‚‹å–り組ã¿äº‹ä¾‹ã«ã¤ã„ã¦ç´¹ä»‹ã—ã¾ã™ã€‚ 本グループã§ã¯ã€æƒ…å ±é€šä¿¡å¯©è°ä¼šICT基本戦略ボードã«ãŠã„ã¦ã€ä»Šå¾Œæˆé•·ãŒæœŸå¾…ã•ã‚Œã¦ã„るビッグデータã®æ´»ç”¨ã„ã¤ã„ã¦ã€ã‚ˆã‚Šå°‚門的ãªè¦³ç‚¹ã‹ã‚課題ã®æŠ½å‡ºç‰ã‚’è¡Œã„ã€ãƒœãƒ¼ãƒ‰ã«å ±å‘Šã™ã‚‹ã“ã¨ã‚’目的ã¨ã—ã¦ã„ã¾ã™ã€‚ 主ãªæ¤œè¨Žäº‹é …㯠ビッグデータã®æ´»ç”¨ã«é–¢ã™ã‚‹ç¾çŠ¶ãƒ»å‹•å‘ã€èª²é¡Œãƒ»å°†æ¥åƒãªã©ã«ã¤ã„ã¦ã§ã™ã€‚ 本グループã§ã¯ã€ãƒ“ッグデータã®æ´»ç”¨ã«é–¢ã™ã‚‹å–り組ã¿äº‹ä¾‹ã€èª²é¡Œã‚„
Analytics at eBay. An interview with Tom Fastner. | ODBMS Industry Watch
Trends and Information on AI, Big Data, New Data Management Technologies, Data Science and Innovation. “How much more complexity can human developers and organizations deal with?â€â€” Tom Fastner, eBay. Much has already been written about analytics at eBay. But what is the current status? Which data platforms and data management technologies do they currently use? I asked a few questions to Tom Fastn
ä¿‚ã‚Šå—ã‘解æž: ã¾ã¨ã‚ - moratorium
ä¿‚ã‚Šå—ã‘解æž: ã¾ã¨ã‚ 2007-06-12 (Tue) 10:24 IS TeXã‚’é ‘å¼µã£ã¦è¦šãˆã¦æœ€çµ‚レãƒãƒ¼ãƒˆã‚’書ã„ãŸã®ã§ã€ã“ã“ã§æ™’ã™äº‹ã«ã—ã¾ã™ã€‚ MEã«ã‚ˆã‚‹æ—¥æœ¬èªžä¿‚ã‚Šå—ã‘è§£æž ç´ æ€§é¸æŠžã‚ˆã‚Šã¯è‰²ã€…ãªè§£æžæ‰‹æ³•ã‚’試ã—ã¦ç²¾åº¦å‘上ã—ãŸã„ãªãã¨æ€ã£ã¦ä½œæ¥ã—ã¦ã„ãŸã®ã§ã™ãŒã€é™ç•ŒãŒè¦‹ãˆã¦ããŸã®ã§æ—©ã‚ã«ã¾ã¨ã‚上ã’ã¾ã—ãŸã€‚ 一緒ã«è¾»äº•ç ”ã«è¡Œã£ã¦ã„ã‚‹tmymæ°ãŒMEã§Linear-time dependency analysis for Japanese [Sassano 04]ã®æ–¹å¼ã‚’試ã—ã¦ã„ã¦ã€é¢ç™½ã„çµæžœãŒå‡ºã¦ã„ã‚‹ã®ã§æœŸå¾…。7500æ–‡/secã£ã¦ä½•ã§ã™ã‹ã€‚ Similar Posts: ä¿‚ã‚Šå—ã‘解æž: è«–æ–‡èªã¿ ä¿‚ã‚Šå—ã‘解æž: 実装 close(2) while select(2)ing Newer: 指ããŸã£ã™ Older: ESPer 2007 Comments:0 Comment Form N
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Microsoft Word - wp-in-database-analytics_12c_V6.docx
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