3.3.4 Retrieving Information from a Table

Select 命令从表格中取回信息

SELECT what_to_select   FROM which_table  WHERE conditions_to_satisfy;

what_to_select 是你想看到的结果,可以是一些列,也可以是“*“表示所有列,which_table是你想查找信息的目标表格,where是可选的,如果选了,

conditions_to_satisfy是一个或者多个必须满足的条件。

3.3.4.1 Selecting All Data

查找所有资料:

mysql> SELECT * FROM pet;

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owEHZxL0Q5CgN1ZqX5GCoQBuOvznwM4vwHnnH//dstXX+/z9dqvZCPIbd8DPNs7PJD96okLo7/5f4ah36c1O/dP8mkbMd/bxD6YWniaqIe2i5mxUVuwsBN5VWaj6EmYZDmY/BrbB5x/yUvcFRlAtpP0Kok5GNIvI9BXYtCLiXSZoGYOP5Kx3odfoyPseL1ubEIXB+tjP4YuxrTNMXerIShoe8vex+bpik4H0M5whApH4N6hmdjI2+uOK8DV3/z5dcPSXtGPoaV2qKrHkatfqjVLo5S7C2lnrkBv4UBYQikVj/UahdHKfaWUs/cgN/CgDAEUqsfarWLoxR7S6lnbsBvYYiFAQAAwLcDYQAAAKCBqSSSWv1Qq10cpdhbSj1zA34LI79vDMq+Pu1C3PGTyKfBeW3/9l7eGmhXsuWzqRHbe1I7zKe9lQX8FkY6YQjbZ8DtbBTveExNaDBBWaQXUX0gDAEI7T2tHQrrKcrHsETx+tOjIorXv5NbIozAupLeQ6t/UF6H0P1GyMeQVBi04Fw+bYuLvyiKy3gIEIaw8nNDZu957VAc9TYkH4O6tdidp4G6LBP3P2jPtjsfg0Ceg3Y+Ix/DQcKgdlvOHbz+wmAE/fCOARKLKMJg5y1YSl7es5SrqIMwKlqAK79F4oxXWvlcPc1N7zkMAasTBmE+BqOTXU5z5mmgYOP+y8c6m/kYBEG3JLHdkI9h5bgRA/X/eqQBM2jXs+OPE286ecZK4oWhZfIWfExe86is0VWpN7u1PnbmHy3cSGxhYMpn62nklshk5lcQJZduhwexN1YSrxPtmmHwOvwoobYduuK+nB73P3wMyl1RIs8h0aCRj+G4bwx67JQII4bG7IwyzuBmdCgbUSf1Tn8Wkq0pKSoooXJCfGFgymfryY0gT6a6EcOMbz6G5WSjy3CeT16Oifuvaar/fCMlDAF5HWSxsJCPwd9v0aaSyE58jzConWa2QfQcHTqTt4DuNM2e3bzB5q/EUwH77FrK5+tZ9IhhPrtcYVDbm5aPgQ3muJ2/QVEL/3wMS/MIysewlhM35zPyMUj9FkUYfDORCT8+T1ONp6xI2y0MbN4CWhikIwb9fP94xWF2reXz9dQ+SOQxXGi+ShiMv063wPNbHZe/Ya2fdz4GTwdu1j9+e0Y+BqW8w0cMitpP0rdDGCY7368TntXdwsDmLWCmWTQhMXIpU79Szp/eGiJPJXHlc/UkMyydzzcKg/Yn5bsC9yu/3vyAfAwB5QStSkI+hlP2MaxDoWdnzAKJl6uekLttIsJUEpO3gJ9/V9ab00uA9Jfxxc+vR5tiuSpbPllP6/ttHoOG+oRBmo9Bn5qglsz5ztMmzccgLudjHPIxfGU+hhM+O09k5odopLLLHMPmsmOxlPtYSj1zA34Lo2xh8J86T3HpfPwQkVR2TbuWztt3wlHKfSylnrkBv4VRqjDM8xKnTVtn4ofopLNLn0rKQhWacu5jKfXMDfgtDLEwAAAA+HYgDAAAADTynEo6nVr9UKtdHKXYW0o9cwN+C6PUbwynU6sfEF01T0qpZ27Ab2EkFAZj3XpltyfCfo4sgTDkiTxGqb00Q7zOPVI+AC7fA8d6/mqyHXMsabRg5GNIKwx5bGJKQXCU2cx9AmHIE0E9w/MxcLvW9+QD2IgKTJajBAWihSR+rCTeXuRjoEkhDFQegqkDXV4WmExSP3+/hW2MckUVpZSc8wNzPHZeisA3LHYzdi35GLrnb/+Y6j/fhSzzf0jzMbjyNMTKB0DGTPOBC7YoyHYVGC0Y+RiOF4aWzkMw9RprrgJN8QqOysnmojDjmSg2Un5wHY+Yl0L2hvU1+Rim+CVDN2mhIHxxLPbGSuJ0wuf4nnwAnyllK9+DF/T2eFEjl9xf5GNYOe4bA10bLqcCczyf6anAbwxr5W0ld0ef5aPSRs1LEfiGVX0+BjWjVH89Xtt2B9Hj8iswx2PlA1grIx4j2pEiZ0MEYzXZ/UU+Bn+/xZ9KovMQsB1f2W+aXJRZNoGPXBii5qUIDA5YfT6G4oVBbXJcfgXleKx8AI1PvgcihIEyzrCOSxq5aESIfAwCv8UWBi4PgVMYiDfukwkTBqU/5V58AoQhZl6KMGFoq8/HUIEwGH8lb4GWpyFWPgDxHDenCgGxFyXtGfkYlPIOFwYuDwHX8ZUex98jLwV/vqcwRMxLIbLri/Ix1CQM3J/045HyAXjkeyCqQXdeAUEzg1YlIR/DKVNJdB4CtuMzvlVk8rIZYx8D+fkhSBjiLYQVdEBflY+hHGGQ5mPgF7lHygfA5HtgUDc96LMlxsuvHxJBRT6Glex3PiOOvxfRFsmksgv3cR+l1DM34LcwshcGxPH3IGCI7SgK+RgypJR65gb8Fkb2wmBOQWTRmzTZNLjZOdGm79PZhfu4h1LqmRvwWxhiYQAAAPDtQBgAAABonD6VlCe1+qFWuzhKsbeUeuYG/BZGAd8Y8iSSHy73V16xuBFdNU9KqWduwG9hpBOGwvIQSBHtqOQX70MYTqaUjkNYT+98DK48B+L171HyMaj7MCyTSbtcpPIbf9zYr+NzdcJvIfknqDwWrvq7SCsMBeUhkBIUOiI7GbCBMOSJoJ6yfAz6T+l4Vl67+WLlY1DQN7vQdm2QzG+sf6QtyidfgufOZyqPhfg+ThwjDMYuaCJev71Neor/Y52v7Yoi31CmGi66nW7xZUiwOeWerW8W1i0X5qsIydC01y6znsjHkBbJcyfJx6ChxO/yOp/5baO28z35GIxOgLJri1R+4/0jFAaffAmygLKaAIjv41yRw0YM6v8TbxBWjRcB5EJrMPkM5g53vX9JHuBAYbBE27auDc9XIYiFwtYX+RhIas3HoF9Cu6Fb57OXi5WPgbxoKmFgypfmsZBe0SNfAhtbiEURY+l9VC56yDcGbU6Tir45h4yey18fvPY2Uk2By2dgDFelYutLOmHQ2I6VxPohDO/7i3wMmcZK+uCbj0E9gYtZ4jGzHzUfwzISJUw+WBikeSyMbwybr+fb+RLEPZiex0J4H2cOnEraiNc/Rd+83Pvn0D/a5nJ/re4gZl3YfAYHdToJhUGUr4L3w6F2IR9DYiJEV+XyMczlm73Ydv4GpZeJnY/hU6o9Aj5aGHz8QPhzrT/9PXnbb0v9+ftC+E0Zn23V38lBwrD2I+wb5XX4eXbtY7hdun68t2SUZvXjDCukWQuDNbVl1VaaryLykCjMrrX5Ih9DGiJ0cMZftVuwFdOQy9+w1i9mPgbtuka3eLwwGH9157EQldbwfvsgizVJqIJnPamijh0xsPH6L/fXOPTjlHXo3T/JZGTc3Dp3TjqCOlD9jWkuh39EffJVRPiuYNTH//5+zkQ+hvTE7OCsP20sFvLri6PlY1ihVumcKAx+eSwUvFZjOvIlyBZx8XkstupJcMo+BjpePzPklOYzyFAYyHU45hId/bufMvTbzsfAfM5JapdqGvIxpEe2KECbWtzIx8DlOZAvdYuSj0FrzKrJnF1u0vmNOc7W38tky2/ewwU2j0XYkkXsfA6kVj+ksgv5GPZRSj1zA34LA8IQSK1+SGUX8jHso5R65gb8FgaEIZBa/ZDOLn0qKQtVaMq5j6XUMzfgtzDEwgAAAODbgTAAAADQwFQSSa1+qNUujlLsLaWeuQG/hXH8NwZ3kJkC4o9O1NrgAjcwUn8NuY+HR2kV30dl8WWey1WBCvwWRmJhWJfka6FSv04YCD9kCoTByWmrbIX1jJBXQJpHofFZ2u+7eYWL6pM2H4Nwy4L4eKzrpi6nSSoMxv7s9va0g6mVS7Afuj7HDcALkYQhlMyFYXeMwmAE9YyTV0CcR8EjH4PfrkAu70LifAxcXoRYx2NdN3U5E+mEgXu3mjqU5SXCGSlPueLyV33kYeUn2BmbxRvJzmeiAvb2bCX0PKnwrnwMEREKw/772DTGplMIA3nlo/MKSPMoMHkFxPkAuLwLqfMxOPJJRDke67qpy5lPTCUMbEu6zNlOPqVtxQ6aOxozv4JVDpcPIE3oBU8/sK9afP4JJr8Cm48hLtKQJ3TYd8F95PI6HITgPjIhB45hb8yfoLwCgjwKXF6B0HwA8sBENIKQJ5v133M81nVTlzOTTBicgaWYmD+f8okOhcivYExlKMLIRSSNilwY9Jd9Nv8El19hw2+xCJ1KMoO8et9HJq/DUVQ3YpjZnVdgLsSvK2HzCgTmAzhBGMj6xzoe67qpy/H3WxbCQLwdOzomM/lPCkJHDHqYcTv/BJtfoQphsO9jaOrBWHyNMKhNyyuvgCyPgiOvgCivg6P+7uMMkv6Kqn+s45y9J5az029pvjHM/4olDPoTO83XJ12pFvqNYTP/BJdf4SuEwecjZ1y+SBiMv7rzCki/1W3kFdi6LlmTI4XBlU8ixvFY101dznJiulVJc3bc5YfUqqRIwmDmJGgf75/x/Ur4DAv9oKZkWEYAdP4JJr9C1sJg11l0H6m8DgfxjcLg1eeK8yg48gr4FyKs5DZBq5Ks73wxjse6bupyJtLuY1A/2dH7GPTvAdoUykZ+BXcSAsHCrDAC10croz92qE6blqMwUP6X3kdlaGzmdTiC+oQhUl4BY8rC5zWT3q8Qvhifq7/k47/k/kr3eUiPx7pu6nKaJrUwpGR7g1XS3RLZ+CEytdrFUYq9pdQzN+C3MOoUhgOmqrPxQ2RqtYujFHtLqWduwG9h1CYM8+RV8vF+Nn6ITK12cZRibyn1zA34LQyxMAAAAPh2IAwAAAA0cp1KOpla/VCrXRyl2FtKPXMDfgvj+G8MycNuc0Hc4lJrgwvd4Eb8tcaw26dRSj1zA34LI5UwqLFClx/+9te4HYp9FetyqZA1OORj8ATCwCCs5+58DHZoFq/7Ql53zesg3oqxN69D6H4j5GNIJAz8xteYOwyKEAYlSmXTNMjH4ATCwCCoZ5x8DHqRPjtmmXwJS9hgz3gM0fI6TNdEPoas8jGQwqCEERXE8Tc2065xto03Go8ADKRytnyeALeByMfwdfkYzkNyX6LkY1Dh4nd5XNc8Z/P5ipXXYS4A+RjyyscwR8tazp87vqB8DIzKiUYMTJ6DuSOz8gS4CY2uutQG+RhKysdwOntjJcnzMaiXFjQ2lzB4JEaNnddBEl0V+RhWUgrD69E2l3s/TuHh5o4vKIge0wgkwsDlOTD6bp+Xo8+vkI/h6/IxnMfuIHpB+Rg+J0iGp7wwqNHcXD+PmtdB1l8hH4O/33YJQ/t499euH+9tuDA0/OyEQBjYPAeBb9+hIwbkYzCuV1Q+hvPYLQxq0/LKx7Bc1xlczzePgvGljS0nIK+DE8mIgbou8jFw7Ert2T0/YaVv10/HFyQMM+bHk/ARg+8VWUK/MSAfg3G9ovIxnEcEYTD+6s7H8MFj8sfjuoQqcMTO6yB5TpGPQSkvpTAsGRGuw8/4jiAM5l8d/Yj7G4P7TB9kqx2Qj4H1c1H5GM4jpjB4pzoI0Wm78Gm1kncpcfM6BK1KQj6GhBvcrsOPvkxqY0qEi+OvHzebqb20mc0HwKUQSC0MjbHqBvkYzEuWk4/hPIQvIlx7Ix4idz4G/+ECc911EwM7+2QSJ6/DxwjkY/iyfAwnU6sfarWLoxR7S6lnbsBvYUAYAqnVD7XaxVGKvaXUMzfgtzAgDIHU6oda7eIoxd5S6pkb8FsYYmEAAADw7UAYAAAAaGAqiaRWP9RqF0cp9pZSz9yA38I44RsDt425aZoo+RiOodYGd7xdjl2KB1DKfSylnrkBv4WRVBi0Je1MegbqJ1UJg3sfRnZAGPJEWM/d+RisP/lc3bXVYNqt4tX+ufwNyMdwUDlNSmHYCLGbLj7oMQTtEBbEQz8LCEOeCOoZKx9DwAY3Nu7/5f76G3qv3YtM/gbkYzionIm0O58drYqJomq9DnTP3/4xR3ieXiVSpSIQERY6wrBakneBOW4EP/GOhbLbrobMk+HOG6Fsjl37LEUYtNDiTehmVxGCIGuntkNJe4uTj0Eo2K64/5/QGpWXwuIAAAXYSURBVOJt7YoAIB9DJfkY5qea0wZuxGAe755TIV3/Jwobm5rgEQMZX8gj74Lr+FKT/eMw//vrmgykIte2t1Gz3eyAiAiJZP6MuIiib57YDvfGShLnY7gOn2EHIfAblzPi/i+dkVgYlJdL5GOoJB/DWl16TlAgDHPegiUzaA5j/90xhaR5F/hYSdw5ae2aRnj2w+kX08l8M71ag1w2f0ZcBB3Hqe1wdxA9aT4GPX7XZtw6Pu7/OvIQCoOevwH5GOrIx6ChBtRby/keYdCmktYhvBFcbDvIINPhzn3onPznELtmc0zB4+tpmKxGfLTfSfn8GXH5GmFQXeqTj8GIo678U5oPgHiD4ctR7OWbBPIxxChnp9/iLFe15ra+UxjMoTrR0wUIw+elLMp31KBC1FkgV/3Xku25bDM4szBxWChfJAzGXzfyMRjfCLduBxP33wq56jWVQaiCZ/2popCPIad8DNZlMGJodD8I8y44p2i07Be7CL+/G8KgdjTaCHKZajC6g3TfFYyaf50w+OVjUGdy7OeX+LVPHgWfEe1m/gbkY0hZzkQyYWDmDXzzLizHz34gOWLsYxDlXXDP3UdbCLvbLue3EHUqgFr9Ms1N6VPJ9ueZmNQnDNHyMaj+95qi3Npn4CUMbP4G5GM4qpymOW4qqToy80O0RTKZ2ZWcUuwtpZ65Ab+FAWEIJCs/+Iz0/YvKx64DKMXeUuqZG/BbGBCGQDLxw7wuKNpSzkzsOoxS7C2lnrkBv4UhFgYAAADfDoQBAACABoQBAACABoQBAACABoQBAACABoQBAACAhiEM56ZVyYda/VCrXRyl2FtKPXMDfgtj228QBpJa/VCrXRyl2FtKPXMDfgsDwhBIrX6o1S6OUuwtpZ65Ab+F4S0MawQ0K3wuF1e9yuO1+qFWu0q3t5R65nYcfovuNwOMGEhq9UOtdnGUYm8p9cwN+C0MTCUFUqsfarWLoxR7S6lnbsBvYUAYAqnVD7XaxVGKvaXUMzfgtzDEwgAAAODbgTAAAADQgDAAAADQgDAAAADQgDAAAADQgDAAAADQKFMYLvfX3+/r0Z5dDy/ax7uUqnpxub/Ge0X2AABMFGG4Dus+6cyf/HOEIWjR9HWwNp13/exnPxO486XlRKN7apvvAQCVMQvD5f5ae732NhbzPn4gAcJg/6Trl378cn/9/fbXzRLI86XlxKW9jQdfEQBwHLMw6C+27eO99UrY3sb37dLexumlVen+LveXGbzJ7keUHlM9n4nopF/3c7JW4OX++hu6ZdDjM+Jhr2u/ia8XXf7z6RYJN14HtW7t471RVe58aTkye+c/rCG3LEXUKwAAqIllKqm9jb9rp7P9avzpK6euZO2YmJFH97SnQaa+Kezd0/rV1Ot9uiqfMrlzul5/K1fOkY4YiEuokzBz+EOXFnLnS8sJsLd7uvUV0QgAqBbt4/P8hrj52t6Y003z+6P5jqwcfz3aeZwxv+DP5cgnrElhWKtt6RBdAnFd+018PUfYFWoaqVXs05WP91avtg13vrQcub2bxmK+EYBqWYSh65eZn+vgMVVCv4GaPfLSYV2Hn2fXXO79c+gfrb6yhZkdEl1dLAz0dbUg5uasVIAwmJ31R3qXMj2EgTxfWo7YXo8C/ZwMACiPjzAYk9Qec9a0MHAjhkkY2sdwu3T9eG8nnTAQfESNIgzUdV1T5xFGDO3jbX7LcfqZO19ajlWxLXupyhtVw/dnAGpF/fi8dgQe6xGZfkHrUPSVM+PQj9Pb7rt/kkv7/fuaqMKglWZ8VzBPCy12QfGJfa3p47nmee58ZzmCinG/3ZziwzcGAKpl/cagzSpsv37ynbiyH0LpRpmpKm2pjEe3q5+vlyMRBsd19T8Rn7j3rEpyF0IIA3++qDIh9qprsbAqCYAvosydz8VQ62s15pEAqBkIQ2KInc/Fg53PANQNhCE5iJUEACgLCAMAAAANCAMAAAANCAMAAAANCAMAAAANCAMAAACV/wNHq4yyRCuVVgAAAABJRU5ErkJggg==" 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Select 命令能方便的查看整个表格,例如,当你从你的源始资料加载到数据库中,你可能突然想到,生日可能不太正确,生日应该是1989年,而不是1979年

最少有两种种方法可以做到

  a.修改pet.txt,然后删除pet 表,再load data

  mysql> DELETE FROM pet; 
  mysql> LOAD DATA LOCAL INFILE 'pet.txt' INTO TABLE pet;

  b.Update 只修改错误的信息

  mysql> UPDATE pet SET birth = '1989-08-31' WHERE name = 'Bowser';   update只修改不符合要求的数据,不用重新加载源数据

3.3.4.2 Selecting Particular Rows

选择指定的行

从前面的情况可以看到,检索整个列表是很简单,只是忽略了Where关键字。但是比较常见的情况是你不需要整个表格,特别是当数据库很大的时候 。

相反,你只需要查看某一特定信息。

下面是查看Bowser的生日信息

mysql> SELECT * FROM pet WHERE name = 'Bowser';

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" 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从结果可以看出来,birth改成了1989年,不再是1979年。

注意,字符串类型是大小写不敏感的,bowser写成BOWSER结果是一样的。

其他任意行的信息你都可以检索,比如:
mysql> SELECT * FROM pet WHERE birth >= '1998-1-1';
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alt="" />

可以使用And语句:mysql> SELECT * FROM pet WHERE species = 'dog' AND sex = 'f';

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AND是逻辑操作符,还有OR

AND 和OR可以混全使用,但AND优先级比OR高,所以用括号是比较好的选择

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" alt="" />

3.3.4.3 Selecting Particular Columns

选择特定的列

有时你不想看整个表,而只对其中的一列信息感兴趣,比如,你只想看宠物的出生,

mysql> SELECT name, birth FROM pet;

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hanxJfHe1HUvqa2OOPbWeAkAz7CIlJD0MLaWEWLEE5P9IKn5LIj6TzNQWOP7ydAUIyZHpGGv+VS0juEGVYWqDoNSvlR+K2a5/9hPmUor4me08IaQ2pQhruoLG3dpmE5HuT2vvr8359F0ysVMyPxG1X+4ji+ZRUGoCQVpIspMZ+Ecd9R3KfZxx/S8RfxKwJYf+1pCupnB9J61Piob8XaX1N8eOHH0nCGiGVJP5ht+jXqsPE4WTUG7czCkm57mEKh4nDyag3bucS0jiYLJ529jBxOBn1xs0TEgAgBQgJgAwcdWi3M4hDGvXGLbeQitsouMmveam3Qayj3rilCclKWzD/8Ke/5hXSspZFdaXY2o+0XKJZFCWy3tnXpP4UttbXBCGNCAPBT1DI+YXnHELK40dyi2RWmRXUO6f5EHpMsvmahjohpIE1QrLSTCj8SGR+JHvOBOdiWja1jPmUNvcj2UhSbEj8QhIB5PI1jQVASAOK2d/91d5/7D2S/EjM3VfVI+XNp7S9H8muWtHZhoTETSxmfp7D1wQhGRRC+r63zeXWvwcvwziiSJq0ymcZEQspcz6lffxImiNk6rX+0gsetHL7miAkg05I7f3VX7v+fWvThdTwoz6FkHLnU9rejzSfV2gyq9RH5K2owZaT4GsKAiEZdFbz7mnStHxdx8RhKUIa8ed0p/dI0hpZtvYjGQSDMUG9hIo4cvuaICSDRkiTI+j6+LxfGYTk/zUwOTX8jBTeU8LmfiRTqfoj27Lw4W2euJS8viYIyaByyLpeo7CQOD9SID9SQ33KYH1NefMp7eVHkndHTL324nhCH1EeX5M5CQhpoN5AuCAOadQbNwiJBHFIo964QUgkiEMa9cYNNgoAMgAhAZABDO1IEIc06o1bdiEF/UK/Na0LMNQbtxX5kZzvNow9ifrJLxRSlvxIzp+ErjD2U88wwUcUas6/BD+ShlQhRabol/YLlWYHP1LCB1nCRzTX/uhF3gfGvwQ/kpLc+ZHmcuj0Ld7trXv+9PfReTHcGovkO9KyvR8pMLGQgvERjQf/831vxSYi61zGY4AfSUvy0G4YV4TWcJTMfOueQyHjSuJHSfi3uR/p+jDdmm+IjFdn+4gaS1RqIVk3R/iRtOTJIUs6I4RC+r6383bFKKIom/uR3FQu0XmirI/I6tmUQnL9S/AjKcmR1dyewDqXU7eQtH4kzwZi/VPlI7LF4wkp6GsK+pfgRxKQQ0iEjwVC8v8a8SN5z5wxnyzjI1pMCQ8Nv+fCov4l+JGiZBHS0kgDIcX/5G63R1YSY5LIRyQZ2kX9S/AjSUgUkmftni+YzHc0bT+/kLL5kewQKRa147/ziITE+pfgR9KRZ2j360Ac0qg3bhASCeKQRr1xg5BIEIc06o2bJyQAQAoQEgAZgJAAyACEBEAGICQAMgAhAZABT0hKV8yvBXFIo964QUgkiEMa9cYNQiJBHNKoN25GSJNFbzn9nvOx/MrtiEP2uFUCeiQSxCGNeuMGIZEgDmnUGzcIiQRxSKPeuOE7EgAZgJAAyACEBEAGICQAMgAhAZABCAmADJxTSKdJD9M0TdPeX2c5VBGX2/chEh0cC0tI9hJnB4/UPkJK+khCpO3QLhmnXyKvMJolI2thFJKzMqNkpc8KSRDS8ifBvEZ0CeT+2nLycvb8V/kZheTeOAVpPIaFl6asR1ZzsRdVNYUs4261MGcRVtlC1cvlRYdV5KdOVdKjsvUu7/Rzpd5KsZFjXYYxlNeIgttfW47ufMc/zFNRF3eQ2OrktTEN7ayV1K8PQepF07bm/FnDb5mebbF87pQoLu3etvjV0ErMpZWUye1jr6Ptramt7ZGIKgJ5jUi4/bXlJJxvbE3wemcDkTgvG8Y7kGQCvDv8G+9P/j3Y2j6u8f36usxpSIwg1QNuUkjzYQuWvWbqXd7pnXXutYll/f35vEY03P7acvTnGz1ZjP8dJiF1/TQSc5NeMdB3OL8FTxf4+vg8u+Zy65+P/t66b36CidCFtauFRNfrJQdwR4kJQvIbN5fXiCOQB0lVjvp8BQWqMwL+aoyQvEG2YMxNC4nrkQYhtffH16Xr37d20JWH4qE5i5CoekND/ww9EpPXiIXbX1vO4sBi5xtPC4L3DQ72y4Y5cIL3m0wcnQvgvll6P/r3cDd99U/y04r82mQVklManWto2i212IlgXqPhZYkTeW7/eH4k2YFxv40OufGM5DA/Izm9fPz2xjd663uU1eyYoaObNyneTEP5lzRCCtTr/ol4pbHmrV24EEJI/P6qg0k5X/tdJd7aRTjnzIbT8Ftv2xjX+UBIhSFmNpwezGxYAiEVB3PtagBCAiADEBIAGYCQAMgAhARABiAkANbzP/E3NiwTzYdFAAAAAElFTkSuQmCC" alt="" />

查看宠物的主人
mysql> SELECT owner FROM pet;

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这条语句只是简单的查出了主人,而有的却出现了多次,为了最小化输出,只需要加入Distinct
mysql> SELECT DISTINCT owner FROM pet;

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你可以通过Where子句来组全行和列。

例如,只得到狗和猫的出生日期

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alt="" />

3.3.4.4 Sorting Rows

对列排序

有时你需要排序,需要用到Order By命令

下面是对出生日期的排序

mysql> SELECT name, birth FROM pet ORDER BY birth;

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" 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默认排序是升序,如果你需要降序,需要加上DESC
mysql> SELECT name, species, birth FROM pet
-> ORDER BY species, birth DESC;

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u8uSBvAHpB3rzsLQ97izcX5A1ALxjiAADABkHeAABggzA56WVvedhbvLkgbwB6yS5v7/FjW5u9dVt7izcX5A1AL4vk7bXEkWcl/rUNa9Zm1W4rsBrLp3i339tQ8eUe/amZ99M083u46BBG7Z/pP4e8ASimaZp58uashFSeruHFqL4L5E0kp9/b4Xz7beqob9gFnzaTuCW+BN84ty4W5QL4du73++xVSwJdyYQfm7mcv7iMsscH7m1kGcX64w362H2Kj/i9vRblilqiRfBps4m4b4jxjUswMUDeAPQyU96mDLG8ay1aazO2Pdqoa+vNlz87/ksezYx6Q3+83f9q6xM/4PfWS1SMvEk+bVYMscv8expsFpNy4iFvAHqZKW9Ty85O9BHm3f3tUg71DktWBnzg3kDSGozTe9o9+AblLd3vbUhCpLz5fdpeRSU+ewucwGn+c8gbgF7eJ2/O0/tXj3ZsnteqOJzra1NfyuLQGet0hXxoBm+uIY5ZhDfeotimvCX6vZmS5shbqk+b2Sjzmdls3ziWVAbYBu969ma/VjD0aMfmea3KS3M6VPXjXLZq5yC9SrAiSfLm21OKtyi2Km/OX4N+b6Pl/6cer8b7tEWKk7/9yf5zyBuAXubKW9tDxb85aXYcjpnOo6kfL1vU+nr3dU/vfw6X+AZpuKM04+1+8l6/m0k+4vc2bE97c1J6szHlNkiyRU08LsgbgF5my1thvwfofd3RmlccXi98nKvL3eyqTO+uKB+41VmcBzHeoigmPgX7BB/wexv2iBxyeZNmnScxIUjtT/Wfe/0IeQNQyxJ52zB7y8Pe4s0FeQPQC/LmZW952Fu8uSBvAHpB3rzsLQ97izcX5A1AL468AQAAbAHkDQAANsifP3+YnByztzzsLd5ckDcAvfznn4cKvzdjjQmrAdL2ldlbt7W3eHNB3gD0MlvenMXvl/m9SatFJK8ikQsMcYJk8Hub4dMmfEJ3bPKUUxRFmv9cgbwBaGaRvMkCliZv0lrvSWvAZwV5E8np99YSdRMj+b31FhPiSl1x5fQtjPSfa0HeAPTyLnmz18D1rKIbJ29OFxbXo80AvzeBnH5vw+ZpvY/xe5PkM7acFP+54SfIG4BSPitvnu7+ea3k7U4Xtt5alPi9TbDc7y28MVCd5PcWMwoMlJPkP9e3HXkDUEuuZ29Ot7LW6M36rWxGsxj83iZY7PdWJPm0Bf3ehtIW+Mal+c91IG8AevmyycmiGOaXyovXXiAL+L1NsNDvzSls0qdtyu+tPD3cMXRSOQH/uSDIG4BevlDeXvKwas+C39sEy/zePNvDihL0e/NoW2I5yf5zfQHIG4Ba3vbm5HCHPn73OvXNyfJyfz7utxVfqsTvbYKMfm9xPm2i35vw7DO5HLOdjN4ANkBueZP93obJomvlzCsmfxiwun83fm8Smfzekn3ahKQNH72585Bp5ZgtRt4ANkH2VUvewoovlbR8SR6ysbd4c0HeAPTyjfL2hsm9r8hDRvYWby7IG4BevkveumnA1ZcyUZ6H7Owt3lyQNwC9OPIGAACwBZA3AADYIN81Ofk29paHvcWbC/IGoBfkzcvMPKS8U64Kjvs8yBuAXlbye/t2kLcgGfzeirDvmo9Jv7e477t9/nDOCmrRTULeAPSy0qol3w7yJpLJ7y3ou+ar1r//yEFiKv8x/nD+1Ux8IG8AellD3sY+Z92H2P2Ns9mtuAudfMSe2yGp27IW8hi6VzMuVwm+Nt5cfm8x/m0m0v62CU6a/23AXjV2lS/kDUAv2eVN8Dlr+/RXr2H+1rhTjrGjfBNpi1SZ6x8a8XpHFd8e74uFfm9R/m1Cdfb+xnrKxyZtktzvD5c0LYG8AehlJb+3F5I3m7Bdz4RndB7sO31p1DLs9u3xdiz0e4vwb3OrC+zfLe+ZNA4W/OEShm4F8gagmT9//mSenPT7nImGON89mpEm39yHcJZt5hfH27PQ7y3g35bo91bVlpRO+MYZ8Uoe60lPT5E3AL3c7/fsjgE+n7OgvI3tBT7NPHkbOkdx9Pbl8fYs9HsL+rf52ifs7/xw+hleUYT84fzTleGikDcApeSWN8nnTJK3Y7P+ApIzmGNn2o4wfM/ejHmwb4+3Y7Hf27TvmvNr//7287aw6A77+CVwxlLdyBuAXnLLm+RzJo7enGd4SgY0Cd1WPwl2u5TWnKTxPZbjZfrN8WbyeyvSTe+E/a1JyMmhm+wP5wwQ40DeAPQyW97y4M4mJc8OrcRaedhbvFuHvAHo5cPy5swUxT07eQNr5WFv8W4d8gaglw/LmztZp6KvL9bMw97i3TbkDUAvjrwBAABsAeQNAAA2yMcnJ3WytzzsLd5ckDcAvSBvXnAMgBjIG4Be5sqbvez9d/bpAZC3IEl+b5IfW+p3b3n83szv9kYhe+MKgbwB6GWJvFlL5er4PDkXyJvIfL83c1kQcR+x2kx+bwb2R4f+uCZA3gD0kkPenBVMPD5n4yVOqtrq3bzOA9679baF/ev1672+j9+bj0S/N8mPTdxfYg2/N+ck9MU1BfIGoJdcozfz35676VH/1ZsmS4t7mesQmv9+CduwcvEqn47h9zZBpN+b5McWVsdwdbn83ryVIm8AmyHPszfLhcS3Un75WnyyK39QxPL08HUo47t1o7u01nX8rLzh99Yi+b31Ozvj1OD+3ury+b31o21PyMgbwGbINjk54XPWrpR/ONfXpr6UxeF8G1RhWMjDb9ZlvTXwHknA722CaL+3CD82yR9uRb+3om+bcy4hbwCbIYu8ic9UhlHLsXleq/LSnA5V/TiXXl8Y85UBcVimWd7wexv+Ovi6RayxKfnDDe3L6fdm1es880PeADZD5tGb6HN2ON8eTf1oqqKorvf6eve9SmBKl+QBpkve8Hub+FOEH1ucomTzexvwvfGLvAFshhW+e/P7nAmTSIFy/I/3lMkbfm8Tfm+SH5vsAyeRxe/NOqnMkKW4wiBvAHph1RIv+L1BDOQNQC/Imxf83iAG8gagl7///ht5G4PfG8RA3gD08p9/HhjiAADA1kDeAABggzjyxmRLy97ysLd4c0HeAPTybnkzXuO2KpK2fwgcAyAG8gagl7nyNs/vTXoPXsv78T3IWxBFfm/Od4QpZ6/V/qAPnAjyBqCXJfKW7PcmLQyf6GPyBpA3EV1+b/PWWwn7uiXcbCFvAHrJIW/mSiKjpdzN7j5e3hauJbgY/N4EtPm9zRh3Tvu6GT5wEyBvAHrJNXrz/XvottyVqLoeX9ruuet/7+JV+L1NoMnvbeY4W6oxZS4BeQPQS55nb7ZVd4bRW+FKxZuHOPi9TaDG7826Q4qfGfbJW8gHTgB5A9BLtslJrxQtkbeRFeo7we9tAjV+b1ajDFeBCb+3qcnJyNsO5A1AL1nkzejlM8rb6xHIR3oQ/N4mUOL3ltSqpPbH3VEhbwB6yT16M+5829vnBfLW9mL32wdeqsTvbQItfm8m0W/wTlSaUA7yBqCX/N+9DZNC18qZV0z+MCClw8oKfm8SyvzeRP+2xPYnl/MKDnkDUIvuRbk+8FJJC35vEAN5A9CLZnkz5zzfXzV+bzAJeQPQi05562bwPvaYCr83iIG8AegFQxwAANggyBsAAGwQnZOTH2dvedhbvLkgbwB6yS5vw7Ml6cukb1hT//3dVvwyvmtANz0P8gaglwXyFvpUSFhNEXkT+Sp5S/J7C/i6DX9K+2RtfAqN1xAQGb5HtCtN9p8rkDcAzSz5rDuwp57FgueBvInM93uzzxlnna3JagW/t77kpo5aSauqu0qtrzKS/edeQSBvAGqZK28T3yOP5c0/aVldf+pLe9fcVO1ttYp35WePYm1joH6gYAVlLJwxKIQhb22BSxb4SGYtvzfZ1y1RzkW/t6L/PjLZS9aQsWT/uaFq5A1AKbMnJ9s+V1I4afTmbq+ubSFV7RqdfJb4PISmYQ3LTdNdug/QWUfxfjqMhybm+orxK9mnspbfm6iCx+Y1BIz7/k/2exukLlnejFu0VP+5fkfkDUAti14t6Xy8xn1ugrz1fqf1UY9HTJq8ebrCoHNC4dle1b/303E07TYetazyqftqfm+h7ZYN7Fy/t2EUmChvlntOqv9cB/IGoJccb04em9G82X7krfDPu8ryZi0xbK+CPx7HODuvNnm7nt+bsN2WbfN/k/zezMR63JdEvzfDQ3yq/UGQNwC95PkwYLR24q7krcOcV5TkzQ5w/CzKWZTSlYG1WMvvTdzuPLudClPwexst/x+aMB8KG2tbZPt9RWk4XQHAQxZ5G699vEt5M6OT5M3s1q1Rbz/J5nS+6z1vc1q+jt+buN2cG4xZO3va7y1yctK9gYhuvw/kDUAvf//99xx5E2bYXB+4pzWa8Wz/enmTfO/kycnKeJ+iGvzwzDcJ29lO+1HQuv5w6/m9ya99GnFFPTOb+i4tSt4ME75Iv7ogyBuAXu73O4tyjdlbHvYWby7IG4BekDcve8vD3uLNBXkD0Avy5mVvedhbvLkgbwB6ceQNAABgCyBvAACwQZA3AADYIMgbAABsEOQNAAA2CPIGAAAbxJG3z5pq6mFvedhbvLkgbwB6Qd687C0Pe4s3F+QNQC/Im5e95WFv8eaCvAHo5SVvwzq/I2MRyTdrk9v3loe9xfuGvAGAEhi9edlbHvYWby7IG4BekDcve8vD3uLNBXkD0Avy5mVvedhbvLkgbwB64bs3AADYIH/99RfyBgAAW+Pff/9F3gAAYGsgbwAAsEGQNwAA2CDIGwAAbJDvlLfD+fb7c7uUn25HFOXl/i1NjeJwvj3OG4oHALaJIW/HZlhhSHn/9Rl5m/WR07EZLddU1V2e40KQ9k8tJxvV1Vq2CgBAIZ28Hc63oe8uT4+vGRu9kRnyNv5JVfdqdDjffn/q42QJ3v1Ty8lLeXq8uUYAgDQ6ebMHGeXlPnV7Xp4e99OhPD3aAYTRiR/ON3cJ2nFvaPT75v7T69L2NdoFHs6336bqB6Axo0+x3vGoaKi0/y+mc/ek8diYbSsv94mmSvunlpMWb/eHYeHgka7bDQAA0EY/OVmeHj9D1zk9THn1+G2HOHSvwiiwuo4n1toedt44YPSrtu9+dbgxZUr7VLU9QjL2SR29eaowp/W6pehDii7tn1rOjHira/gugfWoAEA11qsl3d16jLWHPYHZ3cu74xVj++1SdmO+brDVlZP+IMcrb0OzR2rqL8FT73hUNOyT2KFbSm817CVIj3NpN3uMtH9qOenxTgbLDDYAqKaXt6ru5xKPTcTkm3804OpK3+0em+e1Kg7n+trUl9J++06Yb0yqPVne/PVa5l7uPOcMeXMl53UD0ZcZIW/e/VPLSY43osC4JAMAfIbXmpPOw5uIZzl+eZNGb628lZfmdKjqx7ls1c4h4RWJLPLmqzf0SCnD6K283N1nnME8S/unljNq2FS8vsY7TePtEgDQTOcYYD9vi3jzW+jdrG7Rfrvv0dSPduRxr6/eT8Hie8ys8maV5jxvc3ebW2yPkZNxXe2rMVbmpf2D5SQ0TPrt5KQxz94AQDWDIY41TzU9FJClyPh+zhADYfLTep0vQjzs/e1yUuQtUK/9J88LLEvenAwX4pE3ef+kxsyJ13xflDcnAeDLwO9tVbY6xGFmEgC0g7ytjGfVkq+HVUsAQD/I2+qw5iQAwPtB3gAAYIMgbwAAsEGQNwAA2CDIGwAAbBDkDQAANgjyBgAAGwR5AwCADYK8AQDABkHeAABggyBvAACwPf4fjRSuYAzoVB4AAAAASUVORK5CYII=" alt="" />

事实 上,上面的DESC只根据birth列而对species没有影响。

3.3.4.5 Date Calculations

日期计算

mysql提供了一些函数,方便你计算日期,

计算宠物的寿命,使用TimeStampdiff()函数,参数是你想得到结果的单位,这里是年

mysql> SELECT name, birth, CURDATE(),
-> TIMESTAMPDIFF(YEAR,birth,CURDATE()) AS age
-> FROM pet; 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" alt="" /> 目的是达到了,但是如果结果能按一定的顺序进行排序 ,会比较方便进行查找 ,我们加入Order By试试
mysql> SELECT name, birth, CURDATE(),
-> TIMESTAMPDIFF(YEAR,birth,CURDATE()) AS age
-> FROM pet ORDER BY name;
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" alt="" />


如果需要按年龄排序,只需要简单修改下:
mysql> SELECT name, birth, CURDATE(),
-> TIMESTAMPDIFF(YEAR,birth,CURDATE()) AS age
-> FROM pet ORDER BY age;
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5Ge0L55zBV5dJ2I5/GbhaON2sexPIj4xe3e0iql9X3A+G85HgiV1CSyn8H//249P6kOeIpmbcQQuLRc+IE3QXIQKLuisLwVtxRQvrTa62yli1zN5dWz+rlKG0UrV0Y2pUaR3T9YtRrkgzL8qz0Hxxv3v5StZypz/A2+OQ/PH7vdoGkell555DOS4zneHs35sL65x3lz/dekO5K8fi2C2yuZ3I8UQ8RuguQgUTdFR9jvZ95VYXZdXfZZ371NvqrlVfypcwN+7Q/1V2t/ap+XZO2z4WEOayNSXgrx+vcz6lwlh8Rv2+7QEK9rHT8Os5Liud4+zL6op3RyuUv7ea/pbsRjd0O3QXIQhW6a3ndlnV3/v/+8txsiNbHuqsOXXmdB6XdKWwfrpo2Lzlx+aHOOVHS5T+uTYx30g9jlIDrvOzxGLKh/DMqb+qNaty0VeYtGiGekJEExv7oLsCnbPN9d/pXLt3V+0vHpsmmVUAG3TX+au3Km7fHfrc2BhNJ+0vHtUZSXD9M0e0CzsvVr9D5W29C+csI51hf97Z1V3qKRdBdgAwkj2cerj/+8cyZdNccb9lfnl+v5yOiXoslp+4GVc36N92AWlvtnrWPR42q+svrxzjOdqWRnvOyjaua948cBy7n7W/0M8c2djt0FyALn8zfXYYoS/N39W+xWntiqu8curveWfvrNiOq5qhi3j/U/9R+Y8vMSHHyqNafGfLJzT5P1zU5NS1+qYvVRlR/iVC+77wc+wedsm9+c5ju7pS3aMR4IudfvX+E7gJ8Tq3rRPrX39h0lnA1eWgM8pZGK3lrJU6AqmlRdxP6x2KpJg+NQd7SaCVvrcQJUDVt6e7Us73hl935QHXkoTHIWxqt5K2VOAGqBh9AAACAcqC7AAAA5ai1n3lnyEMa5C2NVvLWSpwAVdOc/67kr5AX6pc0yFsareStlTgBqiZNd9cmMNM03Jy667Ca2c4RYS6/qP9uoh+q9biir61EPh9f/Hfd20VK++92XYLfc4fuAmQhTXflZadyzqxtQ3fz+O/qRYb4oQq+qpKvrVhMLh/f8Zj477bhvxvt97x5nAB/h4y6+zwdEvx3jaWpFuM/o/0XsLqktR0j+Pv6T7Cs/65KiEVMiK9qiF7m8vGdCsB/tw3/3Vi/52lHdBfgc9L9iK5Hdf+p+kvy3xXadlHtXbWNqP6/4O/robz/rnroiKa8x8/c1xDM7eOL/65nu0D59Znj/J6VX6G7AJ+SrruPS98dztfXaMY3dRsm+SIINVSM7q7bMYqfvMXf18M+/rsxEQrHVf5yDfhOmdvHF//d0Eh09vEjCvd7nkB3ATLwke72l+f1OFzfTmpputvJXdARurselzSpV9qX4PL+u8t5ufwSQv1fJYs9s5wEH18n+O96tst5KKy7ot+zE3QXIAOJujs2KIf7WGc9T8fz45XmA6hgjnNJb++GHlGktP/um2g/VNHfLbDRnNvHF/9dz3YprsK6G+v3PO+I7gJ8zge6OzvgHm9fr2cG3TX/6hhm6f6+694zhOL+u++DRk9uXhcu+NqKBWT18cV/17NdoHh7N9rveQTdBchA6roZx9uXPh/jy627kv+uvt0+X1PeX+sfs1v2bq27ef134+bDWI7r8LWVyOPj+z4J/Heb8t9l/i7ADrBOpBXykAZ5S6OVvLUSJ0DVoLtWyEMa5C2NVvLWSpwAVYPuWiEPaZC3NFrJWytxAlQNPoAAAADlQHcBAADKQT+zFfKQBnlLo5W8tRInQNVk112nP24G/90yUL+kQd7SaCVvrcQJUDUf6K42X1aw47X95Bfq7sf+u6s/FfSRlXxw8d/10rT/7tbXFwAEUnXX4zG3tT/u1uzgv7uTj6zgg4v/rregX+O/u8n1BQCRT9arclR2gu/Q6uV6uH9fL5N14NgAinHj2Yzy/rs7+cga5zLFgP+uP+aW/XeLXl8A0EnuZx476yTpldq75vbhPhYyXH/svm87Udx/d28f2XcMNh/cblVNy+C/69kuUHp95qLXFwB0PhpXNfl32q39AnX3cemX7RFdXptS3H93bx9Z068X/93A6NvU3YLXFwBMcoxnVj0SlnL+tu6q686H+O/u7CPr9OvFf1c2OWhVdwtdXwCwkGce0cq/E901/+rx393TR9bv14v/rkS7umv8Fd97gGJk0d217ym66/+Tvn03H1mvXy/+u56zaFx3N7q+ACDxge+90jhY6qkwn915e/u6m81/dx8fWdEHF/9dN6377258fQFAhnUirZCHNMhbGq3krZU4AaoG3bVCHtIgb2m0krdW4gSoGnTXCnlIg7yl0UreWokToGrwAQQAACgHugsAAFAO+pmtkIc0yFsareStlTgBqqas/24zUL+kQd7SaCVvrcQJUDV51mcO9d9thp38d6eJ0WFTKq1TMNX5mpFWysZC+fq8z/x+NfjvKofdUM+kPIv5d4DuAmQgWXeNRf760z1knchW2MF/d9oS7psr+8iOeLwanfGvjpV7HUH8d1U2XTdDyrN1+15xAvwhivnvdlpT7F0lrXdT7FS1Ja4KmwOW99/t5mUOQ9eZEn1kl+L93rQhfrG+RY8V8N+tzH9XRVoMDt97gLLcbrfUdSJd1YrV937WzqXNsarj5tfwfVvMxf13FQ0Iqfe9PrWd/xq54leLibkQ+O96tgsU0TPpXTmsX6TrOnQXIAv//e9/UnTXV614Kmu1/Tetz/w8HVTft/70iqq58lLcfzfS/9XpUzv3K0R+qrdmO6Kx2yXVy/jvdkX0TPdX9m+3gu4CZKCc7tqtFI63r/vQHc7X++166bvD+aH3++00NLq0/26s/6vXp3bcS/0um+QjG+LwY+yP/65ru5yHTfVMsnr0W0Cu9kd3AT4lUXejv+/q35CWqu14+7oP/eV2OgzX17kfZdhAGje0IYX9d6P9X70+tXP5gappjz+iB/IdCP677u1SXFvqWS7R7dBdgCyk6u5YVYWPZ1brx+PtSx1T+rpdX2Ob43m9P206Uf5bb3n/XW173HhmabxxzPuKLZjYxm6XMA4c/92u6zbVM8lf2eu7bAPdBchAsu52aj/wl30QstZFvEz2fZ2Hy1Ot+5Rvn3a/3sja/3P28N+d9wis963zgLW8xU1mNbpSI+fnvH+E/25d/rtSnh353yVOgL/EJ7r7iyEPaZC3NFrJWytxAlQNumuFPKRB3tJoJW+txAlQNeiuFfKQBnlLo5W8tRInQNUYugsAAAAbgu4CAACUg35mK+QhDfKWRit5ayVOgKrJrruJi0wpqwJpAUjbN4b6JQ3ylkYreWslToCqSdZddfLuWhQjV7rIsGJ7Xsr77yb45gpTgaN9VfP50eK/694uUt5/N8mnGd0FyMFHuisra5zuSs45UY46WdnJf3ck6G1D8pGN9VXN5kc7HhP/3Ub8dxXwIwIoSynd1Re4tyw9H6a7Rt0RY9kdxS7+u8tmv6dsiP9uiK9qLj/a5Sf477bmvxuRQ3QXIAP76q7RWT2vVydtN+qO7dZt3sF/173RcTjJfzekHZPbjxb/Xc92gT39d2N6ldBdgAzk+r5rPM9btXe139rN77JQ3n+3i/LN9frUBvqq5vajxX83NBKdXfx3E3ya0V2ADDTWz9x1S1dhf7GaF2WhtP+uUZjXN9fnUytZ7IWW4/CjdYL/rme7nIdd/HdHBD8reznoLsCnNKi776bJ1palJf13LdvdUuf0qY3wVc3tR4v/rme7FNce/rsLwa9W6C5ABoqNZ17eqddTNWLHM/eX59fr+dhwqPOe/rthvrmij2ykr2peP1r8dz3bBXbw312I8GlGdwEycLvdsuqu7L+79NfdB6OLOHoeUYyjexLF/XejfXOFecAJvqp5/GhH8N9txH834X7bNE6Av8Tz+WxwncgNR1SNNJKH6iBvabSSt1biBKiaFnU3pDvx80PUn4cKIW9ptJK3VuIEqJq2dHeavLT5IlaV56FayFsareStlTgBqsbQXQAAANgQdBcAAKAcbfUzF4M8pEHe0mglb63ECVA16K4V8pAGeUujlby1EidA1STrrtt/t3XK++92bl9YG17/3bAFNGz+rNriiBEh4b/r3C5S3n837flFdwEy8JHubrlyxb6U9991+sLaDmvff+XXFLB+k9evd4v1e/HfVSnvv5t2RHQXIANb6K6yZI+2qNBtmF+91frdXOJq0wUxAinuvxvip6si7a+vVxxj8Sb7s/oWPVbAf7cV/110F2A3sutuf3rN9b7ZtpjqOPW3SlsqxKe9EKX9d4P8dIXD6fsri+Afb3H9/3Z/1qiODfx3PdsFyvvvorsAu5Hr+65dJCSvXGF7PX3Xpf13A/x0zcM59n+73cX1HAh+vRGN3S6pXsZ/tyuiZ8b11Z7fLf2VAcDkH//4R+Z+ZmNIjkd3f2l7t1PzEOC/6/CdjfTfHa6axnt8fJXztTYWY5fkxH/Xs13Ow87+u/gAAhTjX/95ZfcjWkrwt3d1/5Y6GrtdXh/ALsB/1+s7a8Yn7G/80P+duOtclbK959ldFP67ru1SXLv77+7smwTwl8itu2o9eLz527vH2/aLLSdQ3n/X7wtr/Nq+v/5NN6Q+lf1ZE/wn8N/1bBfAfxfgD5Fbd5ePi+9+VF971/hOXEmTt7j/buf3hTUR9tf6Rb2NXdkHN3J+zvtH+O/ivwsAbpJ1Nw9mR2J0x+ZGUL+kQd7SaCVvrcQJUDU7667RCRb2PbIA1C9pkLc0WslbK3ECVM3Oumv2M1chuh31SyrkLY1W8tZKnABVY+guAAAAbAi6CwAAUI7d+5nrhDykQd7SaCVvrcQJUDWldVeZ5aIdSNq+E9QvaZC3NFrJWytxAlRNqu7qJkKh6wxI04RqmT40s6X/ruSPGzt/1z4VOMlX1RK/Og91m/md+O8qhy3uv9t1XWzeOnQXIAuf6K62vn+IVEi2dHF2dSUo4r+rrq8k7iMeVvCRTVppy+0XG/FWhP9uK/67G6+LAgAyOXRXXbtKXJeq62J0N2md4Yxs5b8r+eOK+0uIPrLxLXW/X2y4xy3+u63470bm7Q26C5CBXO1d2/8v+mEuBjmtVydtt7QLy64fuZX/rrZIvbKWslu23Ydb+e+m1IwOnYjpjcB/17NdoLj/bmTeJtBdgAzk+b67iGKm9q72W58Z7QZs5r8772woinN/6+EEH9k0X1WrTszfQTddvxf/3a6Inulmf5F5m0B3ATKQrZ/Z53/QdbHfd6cuwX42VyjHdv67Af64kl+vIsZen9r5WHPq0nxk53K28avBf3fOQ1n/XTlvvnLQXYBPyaK7inBm1N13E2SXR30r/93A79aSX+8SX5hfb3jt741/A190/HeXuEr770bmTSkK3QX4lNztXaVttJ6SETueub88v17Pxw5DnTfz3w3wxw2rsgP8eiN8VZ0H3cafFf9dhfL+u7F566Y90V2AT8k/f3fpl7sPRhdx9DyiGOXIynb+u5I/rmtSqR3rfN9oX1Uh/q39WfHf1Sjuv9vF523TOAH+EnWvE7nDiKqRyvLQDOQtjVby1kqcAFVTs+6Gd39tceh68tAQ5C2NVvLWSpwAVVOn7k6TYXZbxKqSPDQHeUujlby1EidA1eADCAAAUI7n84nuAgAAFMLQXfqRRshDGuQtjVby1kqcAFWD7lohD2mQtzRayVsrcQJUTarupvnvNkO7/rty+b5CRH/WjdZ/wH9XOSz+uwB/h090N9p/tx2a9d+Vyg9BXztwYx9Z/HdV8N8F+EPk0F3Dp09tCivmd7owK/afWtNZrQis7ZIxwtl1Z6NaoFn/XaH8MPSLUsxHFv9d/HcB/hK52rvq/1vaW6u6bH4Nl7x11bVz1f9/K+5YmuQH8DFN++9ayg9BcmPcXD/w38V/F+Avkef7rmZmZ7NpmxZqnso3/GJlE8BVsXrfaaiPSizt+u8K5Ttjd/jsbq8f+O92RfQM/12AWsjWz2xv1867HW9f96E7nK/32/XSd4fzQ+/fs+i3sZ77e3+pff+XQZ0AAAScSURBVJyXdv13A8oXRT3E/8cN/rue7XIe8N8F+Ctk0V3xO+XyPB9vX/ehv9xOh+H6OvejDFvKnOp9sSJoRneNv5bx3w0s3xGn0dTbUj/w313iwn8X4O+Qub27GruhbH/drq+xbfG83p+2rjxVUwVP2QZ1t6j/bkD5IrZx6dvpB/67CvjvAvwhNpi/q8wfVbYL/Z+OcuyfkGvT3cr8d8Xy/YXo33c39pHFf1cD/12APwTrVVkhD2mQtzRayVsrcQJUDbprhTykQd7SaCVvrcQJUDXorhXykAZ5S6OVvLUSJ0DV4AMIAABQDnQXAACgHOguAABAOdBdAACAcqC7AAAA5UB3AQAAyvHPf/5T1d00V87fB3lIg7yl0UreWokToGr+9Z8XuruGPKRB3tJoJW+txAlQNeiuFfKQBnlLo5W8tRInQNW8dXdySrf4oEn+o79yO3kgb+QtKk4AiIX2rhXykAZ5S6OVvLUSJ0DVoLtWyEMa5C2NVvLWSpwAVYPuWiEPaZC3NFrJWytxAlSNobsAAACwIeguAABAOdBdAACAcqC7AAAA5UB3AQAAyoHuAgAAlKNN3T2cHz/fj0u/dxxB9JdnK6EGcTg/XudfdD4AAEVRdPd4WxaBq7xi3Ud3kyYvHm+rFfWG65TnsFOQ9o8tJxvDXVtZEAAAwpl093B+LKLSn17NtCYLkqC7658M11kmD+fHz/f16C3Bun9sOXnpT6/CRwQA+CVMuqs3y/rL09eg6U+v5+nQn15jk0tRl8P5Ya6rvq6mFUFS9/cvtj4fUS/wcH783Ia5yR7SXhePu25HLged/wtRHUsajzc1tv7y9IQq7R9bTtz5Tn9YVsNfvXDoAQAAQCBzP3N/en0vdbq/YfeWorGmXup9od083Nd9pGPVn9ZyWv1qFJW3EoSUKe0zXPU2pbJPbHvXcgi1h3YyfnG9akj7x5aTcL7D3f36wpKBAAApaOOqpvZNiMOX3hc9tX7MFp6y/XHpp1by1Dydyon/WGjV3SXslczbS7Acd92OXPaJVBrtFUQL7K2Ur3Ovh71G2j+2nPjz9Z4sHyMAAFKYdXe4zt3Cx1tAP6q9/WQK3qwHx9vXfegO5+v9dr30+phYoes46ujRums/rmY+anZZJ+iuqYXvN5u5zADdte4fW070+QYUGJZkAADQeOuu8YEw4HuhXXel9u6ou/3ldjoM19e5H2XYIGJ8UBbdtR3X9dkyQ3u3vzzN7+jOPEv7x5azCsx3vrbgjdAYWgUAkIA6rmqpZwMmigjVrlZf62NuX7fra2yrPa9365TW8Ko8q+5qpRnfdM3dUoudUXKyPtY4LkzLvLS/s5yIwKTfevv/+b4LAJDC8n1X63L0N55kjVTmASsqJfRja4NsA1RN318vJ0Z3HcfV/2QZvfXJeGZ3IRbdlfePCiblfNVR3IxnBgDIQ5vrVTXDb20U0skMAJAIursxlvWqmof1qgAAkkF3N4f1mQEAYAbdBQAAKAe6CwAAUA50FwAAoBzoLgAAQDmezye6CwAAUAh0FwAAoBzoLgAAQDnQXQAAgHKguwAAAOVAdwEAAIrx/6qDwYQe1lMcAAAAAElFTkSuQmCC" 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一条相似的语句可以查看哪些宠物已经死去,

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" alt="" />
这里因为,我这数据库建立时默认生成的death 是0000-00-00所以也是非NULL,否则应该只有最后一行数据Bowser

如果你想知道哪个动物下个月过生日怎么办?要做这种计算,年和日都是相关的,你只想提取月份数据,mysql提供了几个函数去提取日期中的一部分,比如year(),month(),dayofmonth()

这里要用到的是month函数
mysql> SELECT name, birth, MONTH(birth) FROM pet;

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" 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现在要找出下个月过生的宠物也是很简单的,比如 ,现在 4月,那么下个月就是五月
mysql> SELECT name, birth FROM pet WHERE MONTH(birth) = 5;

aaarticlea/png;base64,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" alt="" />

注意,如果现在是12月,要记住你该查找的是1月而不是13月

你可以通过下面的语句来查询结果,而不用在意现在是哪个月,所以你不要使用特定的月份。Date add()函数能加一定的时间到给定的时间,如果你身Curdate()加一定时间

然后就可以通过month()函数提取你想找的下个月过后日的宠物了。

mysql> SELECT name, birth FROM pet
-> WHERE MONTH(birth) = MONTH(DATE_ADD(CURDATE(),INTERVAL 1 MONTH));
另一种方法是对当前月份取余,对12的余数如果是0,那么加1
mysql> SELECT name, birth FROM pet
-> WHERE MONTH(birth) = MOD(MONTH(CURDATE()), 12) + 1;
aaarticlea/png;base64,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alt="" />

Month()返回1~12的数,Mod()返回0~11的数,所以1应该放在mod()后面,否则,就会从11月直接跳到了1月。

3.3.4.6 Working with NULL Values

处理空值

i当你使用Null时一定会”大吃一斤“,因为Null意味着未知的值,而与其他值有些不同

可以通过is null 和is not null操作符

mysql> SELECT 1 IS NULL, 1 IS NOT NULL;

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不能使用大于号,小于号来操作,看下面
mysql> SELECT 1 = NULL, 1 <> NULL, 1 < NULL, 1 > NULL;
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因为任意一个数与Null运算的结果都是Null,你无法得到任何有意义的结果 在mysql中,0或者Null表示False,任何其他值为True,真值的默认Boolean值为1 两个Null被认为是相等 的, 如果你进行升序排序,Null会排在第一个,降序排在最后一个 一个比较常见的错误是,假想以为不能向一个定义为非空的列中插入0或者空字符串,但事实并不是这样的,可以通过下面的测试看出来
mysql> SELECT 0 IS NULL, 0 IS NOT NULL, '' IS NULL, '' IS NOT NULL;

aaarticlea/png;base64,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" alt="" />

上面的图说明 可以向一个定义为not null的列中插入0 或者空的字符串。

 3.3.4.7 Pattern Matching

 模式匹配

mysql提供标准的类似sql的匹配模式,同时支持正则表达式扩展,类似unix上的vi ,grep,sed。

-    匹配任意单个字符
%    匹配任意个字符,包括0个 在mysql中,sql模式默认是大小写不敏感的,下面是一些例子,不要用= 和<>,e用Like , Not Like 查找以b开头的名字:
mysql> SELECT * FROM pet WHERE name LIKE 'b%';

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nncH2l7zlCHQ9V79nlZFlk2vAaAjyFHonMr2Cc5RcdzL7tIzJCKtcxFTtjA3Hz4+O0wX7a3aaoePwKyFl+jR80hfu+JBSpXMdU7IwNxM2PD9KGeUIj2IRAJH4F5zy/9DmlKIQhS+c6pmJnbCBufrxCGwAAAHw00AYAAACUmOeUggO/rkEq/qZiZ2wgbn580POG4ATy61Z2LgsJnA/WYY2TVOyMDcTNj6i0wW//hrfhuZ4Sfb8Y2vBmUskd7quZbt+8eM/+DXL5e4Uw3zFYrOykc2bc+OPkOx63Tzr4BUUsU+IaZ73S5L9v8Nq/4X14ffsWnRJsgTbEiYOdce3fsLN+sBH9I5j9fR0YXhI36qNTi7LZX8Hyu2hlwSVtASWn6zgSrTaQb4OZ/QDYJanVECx6q35gJe1L1fP7JZjw/C5aX9deEnNuX4cxPkvXQOt/eezrdNQvaufV928o2mddjfbPV+Glr+G63EdR7d8glG+HflPv7+uw5ay4yfFxzKo2+yu4bgimaMDZa25act7+DUy/Y+PkIpvSmhN0jRFlX6o1tQVfi4reDFS6t9bm/L4OY2JVdIXzxX69FNFe7N/AUrSjmBX1j9Nax6E4up7SW/dvYMq3QVpp/8Q5Jeu4GePpUKPF/gryIjoSih67Xkel0ri0QVgUiFuPaF5YaS6frBcvL9C9KVYf59pK9HnaoCHtOaH1+3i//LC+Xh+2f4O6qVR9f728HV5r7237NwjlG2037NPwYm0Q4yDGR3vesNtJ399fwXkXYX0hTsfrOBOdNjDrsIr7AYzret7Kum3qKs9uZbdGkJmukffY8ctTJ2oDv6+DoA2Wewed7dfl929IXhvUpvLS/RssyhcTFjMOfrU22MRBP07sN+9Xsbe/AvOExhg3ZZS2Z7+ReLVBnPfU1rhui7xqHreiHsqcXQJafbYjyu9LtWEzZ7WpXdrXwW7ccBg/v9YWfNX9Gy6gDeSvr9m/wbJ8g50kM75eG8hf2TgYjput3dlfwW1JSkYYLO3kigrZvH/9+vX19XXGvm9LCfr8+9DUw7i3UV+37FZu0ry8dI49XjlU7zfxtUv7Ooh7HB1/xkDssb9eytz01fdvuJI2vHT/BovyRbj3dt6oDdKfxJ9YvW9p2F/B7bUuspylg50MgbXhz58/v3//7vs+9PcN/H4AwljVUA7/SON8bWDfzJH3XeD3dTDsfyc8qvHCoU181P4N6WhDZPs3iOXvF6I/b5D8MnNe3ITjHvtMmOJmPWhQPyKxu+5GotKGxIBfjuVi/4ZDpGJnbCBufkAb/IFfbmD/hmOkYmdsIG5+QBv8gV8eJYd6mSogqVzHVOyMDcTNj1doAwAAgI8G2gAAAIACbQAAAECBNgAAAKBAGwAAAFCgDQAAACisNigrsF8K+HUNUvE3FTtjA3HzI3DcoA0X4Kp+SaTibyp2xgbi5ge0wR/4dQ1S8TcVO2MDcfPjTG1YF4zbrDQnrT+exHH4Faf9V/U3FTtjO464BY/bETBuuABX9UsiFX9TsTM2EDc/MKfkD/y6Bqn4m4qdsYG4+QFt8Ad+XYNU/E3FzthA3Px4hTYAAAD4aKANAAAAKNAGAAAAFGgDAAAACrQBAAAABdoAAACAkrI23Mru59lVcexhvEde9amYasWt7GLZPhoAEJ6NNtyb+avr6F8xfo82eL1EfG82X7EX9fyBu50LpvPHL+lfHIqi1b7mBwBcCaINRa0uYIKOIYOHNmx/UtRLKr+V3c+zvu+WIJ9/K7ufpm5fL5P5Y9i1HACQJPKc0q3s9pNg/hj6xy1/DJuhxq3s6JpQ21SiJE31/P2FopYamSxZLEMfG20T693209dKl/9sMmNe9bR/fW9U2/Zl2HR+/hieXZUXltrg4O/8h3Ulr0170A0DAFwGWRuYaZAtU7ocs8maszRdmZJXlmWb/LUMU/x6oJtfjYlvylY2ZUrnFPWa99X/z9zHDUwV6mzMvLCiKdSG85eY22mDs79Fa5ZYLG8AwDWRtEGZxDCx5v0sW3uRtKesHO+qfB5tzN38uRz3yWtWG9Yka5EuhXq3/fT1HMdsyA2/RsOmLD+UuW72Fvn81Rh7bXDxd9dZvQEAAK4Cqw35Y7CbkBH6oTRPLbns3ny3RXYr67apq1x/10WYJnKq3Vkb+Hq1RdLp9JSHNtC8P83SLGVaaAN7vuqg7ZySk797hrnUCwBIia022AtDJmmDNG4YtSGvmsetqIcyH6WCYPVsVqjdRxu4ek3T6AHGDXnVq5NIu88bhPPXJwQ+e3rY+Lv/zAmPowG4JlQb9uaXCUJq0HKK/o7N0NTD2Oft65Z95d8+3QTVBq008oyBnuZb7II6Zbepa3yWrqmm8fzxqHP/3cbf3bk+PG8A4Jro2rB+3MBsR8ch53GlKCVnFfVS5r1ZpzW0l2cscpx+vl6OizYY6tX/xDzxPvKekrkQRhv2K7XSBh9/1bez8J4SAJ9Cyt9FJ8NVO9eYUALgskAbXoLVC8GJge+iAbgw0IYXgfWUAAAJAW0AAABAgTYAAACgQBsAAABQoA0AAAAo0AYAAAAUaAMAAAAKtAEAAAAF2gAAAIACbQAAAECBNgAAACD8H0vDKWdRpobTAAAAAElFTkSuQmCC" 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以fy结尾的名字
mysql> SELECT * FROM pet WHERE name LIKE '%fy';

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" alt="" /> 包含字母w的名字 mysql> SELECT * FROM pet WHERE name LIKE '%w%'; aaarticlea/png;base64,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" alt="" />
包含5个字母 的名字,用5个 _
mysql> SELECT * FROM pet WHERE name LIKE '_____';

注意,这是5个下划线,
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" alt="" />

其他一些用了正则的匹配模式,当你使用时应该加上REGEXP或者 NOT REGEXP(也可以用RLike 或者Not RLkie)

下面是一些扩展支持的正则的语法: .    匹配任意单字符 [...]  匹配括号内的任意单字符,如:[abc],会匹配a,b,或者c,用横杠表示一个范围,如:[a-z]会匹配任意字母(因为大小写不敏感),[0-9]会匹配任意数字 *     会匹配一个或多个它前面的表达式,如x* 会匹配任意个x,[0-9]*会匹配任意个数字,.*会匹配任意个任何字符 Regexp   只要是这种模式就会匹配成功,而Like则必须匹配完整的值。 ^,$    ^匹配以某某开头,而$匹配以某某结尾 下面是匹配以字母 b开头的名字
mysql> SELECT * FROM pet WHERE name REGEXP '^b';
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" alt="" />

假如你的强迫症又犯了,你说,我就是要大小写敏感,那么也是可以的,用BINARY关键字,使其转化成二进制字符串

下面这条语句 查询以小写的b开头的名字
mysql> SELECT * FROM pet WHERE name REGEXP BINARY '^b';

用$符匹配以fy结尾 的名字:
mysql> SELECT * FROM pet WHERE name REGEXP 'fy$';

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alt="" />

包含字母w的人名:
mysql> SELECT * FROM pet WHERE name REGEXP 'w';

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alt="" />

之所以能匹配成功是因为只要模式相同,正则就能匹配成功,而不用前面那样要在两端加上%通配符

要匹配五个字符的名字,用^来限制开头,$限制结尾,在两者之间加上5个.
mysql> SELECT * FROM pet WHERE name REGEXP '^.....$';

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" alt="" />

你也可以用{n}操作符,表示重复n次
mysql> SELECT * FROM pet WHERE name REGEXP '^.{5}$';
aaarticlea/png;base64,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" alt="" />

3.3.4.8 Counting Rows

计算行数

建立数据库当然是为了用,比如你想知道,谁谁谁有几只宠物,或者你共有几只宠物,其实这只需要知道这个表有多少行就行了,因为一行一只宠物

Count(*)函数统计表有多少行,这样你就知道你有多少宠物了

mysql> SELECT COUNT(*) FROM pet;

aaarticlea/png;base64,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" alt="" />

如果你想知道每个人有几只宠物,
mysql> SELECT owner, COUNT(*) FROM pet GROUP BY owner;
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" alt="" />

这里用了Group By 让每个主人的宠物组合在一起

下面是统计不同种类动物的数量
mysql> SELECT species, COUNT(*) FROM pet GROUP BY species;

aaarticlea/png;base64,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" alt="" />

不同性别的动物
mysql> SELECT sex, COUNT(*) FROM pet GROUP BY sex;

aaarticlea/png;base64,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" alt="" />

第一行空白,表示性别未知。

每种动物,不同性别数量
mysql> SELECT species, sex, COUNT(*) FROM pet GROUP BY species, sex;

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" 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有时你并不想知道整个列表的数据,比如你只想看看dog和cat的情况:
mysql> SELECT species, sex, COUNT(*) FROM pet
-> WHERE species = 'dog' OR species = 'cat'
-> GROUP BY species, sex;
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alt="" />

或者你想忽略那些性别未知的动物
mysql> SELECT species, sex, COUNT(*) FROM pet
-> WHERE sex IS NOT NULL
-> GROUP BY species, sex;
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" alt="" />

那么,这里有一点问题,上面的bird那个空白怎么解释呢,如果你记得前面的内容,空字符串与Null是不相等的。

如果你只选择其中的一列,那么Group By也就选择对方列,否则下面的情况就会发生 
如果选择了完全匹配分组模式
mysql> SET sql_mode = 'ONLY_FULL_GROUP_BY';
下面的语句就会报错:
mysql> SELECT owner, COUNT(*) FROM pet;
ERROR 1140 (42000): Mixing of GROUP columns (MIN(),MAX(),COUNT()...)
with no GROUP columns is illegal if there is no GROUP BY clause
如果没有选择完全匹配分组模式:

这条语句就会把整个表当成一个组,然后选择的内容可能是任意一列的内容,就是说结果是随机的

mysql> SET sql_mode = '';
Query OK, 0 rows affected (0.00 sec) mysql> SELECT owner, COUNT(*) FROM pet;
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DGnyauDPsjIeTKhxdlZkp5zfVwrAxvF2J0BZPY6xCEmfCGgFzTQexqUg92NW0KyDUl2DMMFgVyBUANkCsAaoBcAVAD5AqAGv78+fPz8wO5AqCAX79+VVUFuQKggD9/mp+f/0GuACgAcgVADZArAFr4P1N0xLa2ZrKkAAAAAElFTkSuQmCC" alt="" />

3.3.4.9 Using More Than one Table

使用多张表格

这张表只保存了现在这些宠物的部分信息,如果你想保存别的信息,或者又有小宠物出生blablabla

那么再建一张表吧

mysql> CREATE TABLE event (name VARCHAR(20), date DATE,
-> type VARCHAR(15), remark VARCHAR(255));

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一定要加上路径:

aaarticlea/png;base64,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" alt="" />

mysql> SELECT pet.name,
-> (YEAR(date)-YEAR(birth)) - (RIGHT(date,5)<RIGHT(birth,5)) AS age,
-> remark
-> FROM pet INNER JOIN event
-> ON pet.name = event.name
-> WHERE event.type = 'litter';
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alt="" />
当从多张表格组合(join)信息时,你需要确认有多少记录可以匹配到另外一张表,这里很容易实现是因为都有name这一列,这里用了on子句去匹配 ,因为两张表里面都有name这一列

组合两张不同的表格是不必要的,有时你只需要在一张表格里面组合就行了(此处翻译可能有错误,请根据结果揣摩一下)

例如,你需要知道哪些可以繁殖配对。
mysql> SELECT p1.name, p1.sex, p2.name, p2.sex, p1.species
-> FROM pet AS p1 INNER JOIN pet AS p2
-> ON p1.species = p2.species AND p1.sex = 'f' AND p2.sex = 'm';
aaarticlea/png;base64,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" alt="" />
在这条语句中,我们对列指定了别名,然后直接使用相对应的列。

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