Google I/O - Building Scalable, Complex Apps on App Engine
Creating relatively simple applications that scale with App Engine can be easy after the initial learning curve. But larger applications with more complex functionality are still hard to get right, especially when you need to scale. This talk will go over more advanced data structures and techniques to use when building complex web applications with Google App Engine, and how to make them scale. T
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Tokyo Cloud Developers Meetup #02 ã«å‚åŠ ã—㦠- kazuhoã®ãƒ¡ãƒ¢ç½®ãå ´
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Entityè¨è¨ˆã«ã¤ã„㦠GAEã§ã¯Entityã¨ã„ã†ãƒ¢ãƒ‡ãƒ«ã‚’定義ã—ã¦JDOを使ã£ã¦ãƒ‡ãƒ¼ã‚¿ã‚’永続化ã™ã‚‹ã€‚Entityã¯ã‚ªãƒ–ジェクトモデルã§ã‚ã‚Šç”»é¢ãªã©å®Ÿéš›ã®æ¥å‹™ã‚¢ãƒ—リケーションや外部インターフェースãªã©ã‚’ç›´æ„Ÿçš„ã«è¡¨ç¾ã§ãã‚‹ã¨ã„ã†ç‚¹ã§å„ªã‚Œã¦ã„る。ã—ã‹ã—ã€éšŽå±¤åž‹ã¨ã„ã†ã“ã¨ã‚‚ã‚ã‚Šã€ãƒªãƒ¬ãƒ¼ã‚·ãƒ§ãƒŠãƒ«ãªãƒ¢ãƒ‡ãƒ«ã¨ã¯ã‚ã¾ã‚Šé¦´æŸ“ã¾ãªã„。もã—ã‹ã—ãŸã‚‰ã€ã“ã‚Œã¾ã§RDBçš„ãªè¨è¨ˆã‚’ä¸å¿ƒã«ã‚„ã£ã¦ã“られãŸæ–¹ã«ã¨ã£ã¦ã¯è‹¦ç—›ã•ãˆæ„Ÿã˜ã‚‹ã‹ã‚‚ã—ã‚Œãªã„。Entityã‚’ã†ã¾ãè¨è¨ˆã™ã‚‹ãŸã‚ã«ã¯ã€ã²ã¨ã¾ãšRDBçš„ãªé をリセットã—ã¦ã‚ªãƒ–ジェクト的ãªç™ºæƒ³ã‚’ã™ã‚‹ã“ã¨ã‚’ãŠã™ã™ã‚ã™ã‚‹ã€‚一度慣れã¦ã—ã¾ã†ã¨èª°ã§ã‚‚ç°¡å˜ã«ã‚µã‚¯ã‚µã‚¯ä½œã‚Œã‚‹ã‚ˆã†ã«ãªã‚‹ã ã‚ã†ã€‚逆ã«ã€RDBã®å‘ªç¸›ã‹ã‚‰é–‹æ”¾ã•ã‚ŒOOã«è¦šé†’ã—ã¦ã—ã¾ã†ã¨ã‚‚ã†å¾Œã«ã¯æˆ»ã‚Œãªã„ã®ã§æ³¨æ„ãŒå¿…è¦ã§ã‚る。RDBã£ã¦ä¸è¦ã˜ã‚ƒã‚“？ã¨ã‹ã€ã“ã‚Œã‹ã‚‰ã®æ™‚代ã¯OOã§Key/Valueã ï¼ãªã©ã¨æ€ã†ã‚ˆã†ã«ãªã‚Œã°è¦šé†’ã—ãŸè¨¼æ‹ ã 。
å‚本多èžã®ã‚½ãƒ•ãƒˆã‚¦ã‚§ã‚¢æ¥ç•Œã‚¤ãƒ³ã‚µã‚¤ãƒ‰ã‚¢ã‚¦ãƒˆ GoogleãŒOracleã¨ãƒ‡ãƒ¼ã‚¿ãƒ™ãƒ¼ã‚¹é ˜åŸŸã§è¡çªã™ã‚‹æ—¥ï¼šBigtable vs Berkeley DB
CNET Japanèªè€…ブãƒã‚¬ãƒ¼ sparklegateã•ã‚“ã®ã‚¨ãƒ³ãƒˆãƒªãƒ¼RDBMSã¯æœ¬å½“ã«ä¾¿åˆ©ãªã®ã‹ã¯å•é¡Œæèµ·ã¨ã—ã¦ãã—ã¦ã€ã„ã‚ã„ã‚寄ã›ã‚‰ã‚ŒãŸã‚³ãƒ¡ãƒ³ãƒˆãŒéžå¸¸ã«èˆˆå‘³æ·±ãé¢ç™½ã‹ã£ãŸã€‚CPUãƒãƒƒã‚¯ã¨ãƒ‡ã‚£ã‚¹ã‚¯ãƒãƒƒã‚¯ã¨ã„ã†ãƒœãƒˆãƒ«ãƒãƒƒã‚¯ã«ã¤ã„ã¦å¯„ã›ã‚‰ã‚ŒãŸä¸¡æ–¹ã®æ„見ã¯RDBMSã‚’ã©ã†ä½¿ã£ã¦ã„ã‚‹ã‹ã¨ã„ã†ä½¿ã„æ–¹ã®å·®ã§ã‚‚ã‚ã‚Šã€ã€Œä½•ã§ã‚‚入る便利ãªå…¥ã‚Œã‚‚ã®ã€ã§ã‚ã‚‹RDBMSã®ç‰¹é•·ãŒã‚ˆãç¾ã‚Œã¦ã„る証左ã ã‚ã†ã€‚ãã—ã¦ã€ã‚ã¾ã‚Šã«ä¾¿åˆ©ã™ãŽã‚‹ãŒã‚†ãˆã«ã€è‹¦æ‰‹ãªé ˜åŸŸã«ã‚‚使ã‚ã‚Œã¦ã‚¹ã‚±ãƒ¼ãƒ©ãƒ“リティ（拡大性）ã®å•é¡Œã«ã¶ã¤ã‹ã‚Šã€ã€Œæœ¬å½“ã«ä¾¿åˆ©ãªã®ã‹ã€ã¨ã„ã†ç´ 朴ãªå˜†ãã«è‡³ã‚‹ã¨ã„ã†çŠ¶æ³ã¯ã€çš®è‚‰ãªã®ã‹æœ¬æ°—ãªã®ã‹ã€ã„ãšã‚Œã«ã—ã‚ã‚ã‚ŠãŒã¡ãªã“ã¨ã ã‚ã†ã€‚ ã²ã£ãã‚Šã¨è¡¨ã«å‡ºã¦ããŸGoogleを支ãˆã‚‹ãƒ‡ãƒ¼ã‚¿ãƒ™ãƒ¼ã‚¹ï¼šBigtable ãã‚“ãªãŠã‚Šã€steps to phantasienã®2006-9-11ã®ã‚¨ãƒ³ãƒˆãƒªãƒ¼ã§Googleã®ã‚¤ãƒ³ãƒ•ãƒ©ã‚’支ãˆã‚‹ãƒ‡ãƒ¼ã‚¿ãƒ™ãƒ¼
Google Research Publication: Bigtable: A Distributed Storage System for Structured Data
Bigtable: A Distributed Storage System for Structured Data Fay Chang, Jeffrey Dean, Sanjay Ghemawat, Wilson C. Hsieh, Deborah A. Wallach, Mike Burrows, Tushar Chandra, Andrew Fikes, and Robert E. Gruber Abstract Bigtable is a distributed storage system for managing structured data that is designed to scale to a very large size: petabytes of data across thousands of commodity servers. Many projec
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