{"url":"https://higepon.hatenablog.com/entry/20090113/1231847268","categories":["study","db","database"],"type":"rich","height":"190","image_url":"http://ecx.images-amazon.com/images/I/51i8D880drL.jpg","title":" Algorithms for Relational Operations - Database Management Systems","version":"1.0","provider_name":"Hatena Blog","blog_url":"https://higepon.hatenablog.com/","description":"Database Management Systems\u306e12\u7ae0\u3002 \u30de\u30a4\u30f3\u30c9\u30de\u30c3\u30d7\u304b\u3089\u518d\u69cb\u6210\u3057\u305f\u307e\u3068\u3081 Selection clustered index \u3042\u308a => index \u3092\u8aad\u3080\u3060\u3051 un-clustered index \u3042\u308a => index + match \u3057\u305f tuple \u306e data \u3092 read index \u306a\u3057 => full scan Projection \u7279\u5fb41\uff1a\u51fa\u529b\u3092 drop -> easy \u7279\u5fb42: \u51fa\u529b\u304b\u3089\u91cd\u8907 drop -> expensive \u91cd\u8907 drop \u306e\u30b9\u30c6\u30c3\u30d7\u306f partitioning \u3067 1.Scan 2.Sort 3.Discard Join \u2026","author_name":"higepon","provider_url":"https://hatena.blog","width":"100%","blog_title":"higepon blog","published":"2009-01-13 20:47:48","html":"<iframe src=\"https://hatenablog-parts.com/embed?url=https%3A%2F%2Fhigepon.hatenablog.com%2Fentry%2F20090113%2F1231847268\" title=\" Algorithms for Relational Operations - Database Management Systems - higepon blog\" class=\"embed-card embed-blogcard\" scrolling=\"no\" frameborder=\"0\" style=\"display: block; width: 100%; height: 190px; max-width: 500px; margin: 10px 0px;\"></iframe>","author_url":"https://blog.hatena.ne.jp/higepon/"}