SQL感覚ã§HiveQLを書ãã¨ç—›ã„ç›®ã«ã‚ã†ä¾‹ - still deeper
Hadoop Advent Calendar 2013 4日目ã®è¨˜äº‹ã§ã™ tl;dr explainã¨job historyã‚’èªã‚ 1 reducerã¯æ‚ª data skewã¯æ‚ª å‰æ›¸ã ã¿ã‚“ãªå¤§å¥½ãSQLã§Hadoop上ã§ã®å‡¦ç†ã‚’実行ã§ãã‚‹Hiveã«ã¯ã¿ãªã•ã‚“普段ã‹ã‚‰ãŠä¸–話ã«ãªã£ã¦ã„ã‚‹ã“ã¨ã§ã—ょã†ã€‚ã¡ã‚‡ã£ã¨èª¿ã¹ç‰©ã§ã‚°ã‚°ã‚‹åº¦ã«ç›®ã«å…¥ã‚‹æ„›ã‚‰ã„ã—ã„マスコットãŒã€è’ã‚“ã 心ã«æ¸…涼ãªé¢¨ã‚’ã¯ã“ã‚“ã§ãã‚Œã¾ã™ã€‚ ã§ã™ãŒHiveã®ã‚¯ã‚¨ãƒªè¨€èªžã¯SQLã§ã¯ãªãHiveQLã§ã™ã—ã€å®Ÿè¡Œã‚¨ãƒ³ã‚¸ãƒ³ã‚‚RDBã®ãã‚Œã¨ã¯å…¨ãç•°ãªã‚‹MapReduceã§ã™ã€‚SQLã®ã¤ã‚‚ã‚Šã§HiveQLを書ã„ã¦ã„ã‚‹ã¨åœ°é›·ã‚’è¸ã‚“ã§ã—ã¾ã†ã“ã¨ãŒã¾ã‚Œã«ã‚ˆãã‚ã‚Šã¾ã™ã€‚本エントリã§ã¯é™¥ã‚ŠãŒã¡ãªHiveQLã®è½ã¨ã—ç©´ã‚’2ã¤ç´¹ä»‹ã—ã¾ã™ã€‚ 例1 SELECT count(DISTINCT user_id) FROM access_log SQLã«æ…£ã‚ŒãŸæ–¹ã§ã‚ã‚Œ
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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€
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Bora Beran
Python: Accessing elements from nested dictionaries a la SQL
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