mysql累积聚合

累积聚合为聚合从序列内第一个元素到当前元素的数据，如为每个员工返回每月开始到现在累积的订单数量和平均订单数量

行号问题有两个解决方案，分别是为使用子查询和使用连接。子查询的方法通常比较直观，可读性强。但是在要求进行聚合时，子查询需要为每个聚合扫描一次数据，而连接方法通常只需要扫描一次就可以得到结果。下面的查询使用连接来得到结果

SELECT

  a.empid,

  a.ordermonth,a.qty AS thismonth,

  SUM(b.qty) AS total,

  CAST(AVG(b.qty) AS DECIMAL(5,2)) AS avg

FROM emporders a

INNER JOIN emporders b

    ON a.empid=b.empid

    AND b.ordermonth <= a.ordermonth

GROUP BY a.empid,a.ordermonth,a.qty

ORDER BY a.empid,a.ordermonth

如果只是查询2015年的累积订单，可以加上以where条件

WHERE DATE_FORMAT(a.ordermonth,'%Y')='2015' AND DATE_FORMAT(b.ordermonth,'%Y')='2015'

运行结果如下

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" alt="" />

此外可能还需要筛选数据，例如只需要返回每个员工到达某一目标之前每月订单的情况。这里假设统计每个员工的合计订单数量达到1000之前的累积情况。

这里可以使用HAVING过滤器来完成查询

SELECT

  a.empid,

  a.ordermonth,a.qty AS thismonth,

  SUM(b.qty) AS total,

  CAST(AVG(b.qty) AS DECIMAL(5,2)) AS avg

FROM emporders a

INNER JOIN emporders b

    ON a.empid=b.empid

    AND b.ordermonth <= a.ordermonth

WHERE DATE_FORMAT(a.ordermonth,'%Y')='2015' AND DATE_FORMAT(b.ordermonth,'%Y')='2015'

GROUP BY a.empid,a.ordermonth,a.qty

HAVING total<1000

ORDER BY a.empid,a.ordermonth

这里并没有统计到达到1000时该月的情况，如果要进行统计，则情况又有点复杂。如果指定了total <= 1000，则只有该月订单数量正好为1000才进行统计，否则不会对该月进行统计。因此这个问题的过滤，可以从另外一个方面来考虑。当累积累积订单小于1000时，累积订单与上个月的订单之差是小于1000的，同时也能对第一个订单数量超过1000的月份进行统计。故该解决方案的SQL语句如下

SELECT

  a.empid,

  a.ordermonth,a.qty AS thismonth,

  SUM(b.qty) AS total,

  CAST(AVG(b.qty) AS DECIMAL(5,2)) AS avg

FROM emporders a

INNER JOIN emporders b

    ON a.empid=b.empid

    AND b.ordermonth <= a.ordermonth

WHERE DATE_FORMAT(a.ordermonth,'%Y')='2015' AND DATE_FORMAT(b.ordermonth,'%Y')='2015'

GROUP BY a.empid,a.ordermonth,a.qty

HAVING total-a.qty < 1000

ORDER BY a.empid,a.ordermonth

运行结果如下

aaarticlea/png;base64,iVBORw0KGgoAAAANSUhEUgAAAWgAAAETCAIAAACUYguAAAAgAElEQVR4nO2dzY7bSJLH+VRGgU/g19hygwc/RV9b7QF48zMIM+4uYwE+gC91XIzt8UXAzkfNzuzCh+nuscsfXY3cA8lkZEZkiJQoMiMYPwhGmUqREUHxLyap+Kv4/Yv/tIc97GGPSY/i9y/+0xmGYUxBknD88ssva4eQF+oLIjFBiTHzkBmZcAhGfUEkJigxZh7xwvHzzz+vHUJeqC+IxAQlxsxDZmTCIRj1BZGYoMSYeUw4tKG+IBITlBgzjxzhONRlWR/Q4p9++mn2dV6EpbZ1VkEwS5Zo3OZmTnBeLvEuzRIyowyEA++AxC7517/+NedWZsdvYqkj8KyCeJiwL5HIlCrNk+DIeKY+e4l3aZaQGXXC8euvD58+f83l8affXV397m248OHht3/+7/+dHie1zkuFvcC2zi/ISmGP39xsCY6MZ+qzl3iX5vdoM7r/9CV6dMLx9dcH/Ny0x9tnV0XL1e7tl/u3z66uvrm+KoqiuL55t+v+CJaDJc/eBGsoinYJeDw8/PY///gnEefwqm9uPnVr2z0B/43WScTZj0/FzG3Fj+nGF0Vx9eQb9Oz8j2RBpj3YsPtd8+Z7P+jZm6WqNFOCo9P//l0cf/jsUATwzhn7Ll3pQcTcpfbl/tPL69QxgjLCa55LOPog+rfLm7fPrtpYb74p/B9w+af2qfZwffbm08tr+P4bvUv8q958f1U8edlWoX8X4nWSccL3PRUzWA+xlW5MrIDxs3M/ZnuPMmEPJeqKdvPkm5ulqrTQQTi82VD8ibfi/c03XXbZC0cc86cvN09AzZ+8pI4RIiO8wl44vv768f7z6Y83QLSKoiie/Pjm2dXVs9ftU/AP/9/7zx/vX14XV7sbtDwY0z0efvvt7u//wHEGr4Lbjdbjt56KE4dKxsxsBf+RyGWWR6ogp+y7VNjdkpfXba2WrdJsCZ6WfptvvHD4ZH69YsyTsoMx33/+ePOkuH758f7zj9dXuzdj9wJe83zCEW0yW+FIxTky5i0Kh99Zoz8S9AnHm2dXxdXuDfteyk04cMz3nz/e/2l39eTH+5fXXkfOEY4vX3/98PHTGY+b66K4/hEsef39o6vvX+M//H8/fvrw45NiWHJzXVx99/rTh4+fXu+uCj+mfzw8/PbXv/0dx+m3+3p3VVzffIDrJ9aZjpOJGbyK2AocXDz5IbXOuR+pgkx+MGH3/17v3n74+OnDx7ffXV199+NCVZotwZHp4/gT0XbvpRVjHp9aFHP/9/X1k0fdPh2OEWYv4JV3wvH5y9d/f7g/6/F698ifFD3a/fH17tGj3R/b5fAPOKy4/gEO+OG6e/X1dbcEPB4efvvLX++IOIcVhmtrH3idqThxqNEfqa2Av9utBfFH8cz3SBZk+iMZdhf8zX/4gn33ZrEqzZjgqPTb1GD84bP9W6mPfNWYJ6VGVBsk6I+R7oigMsJrnk84Rj5OPZBy2yWrP9QXRGKCEmMeHj9cF9c3ZEZ4cC8cn7/+8u+PSzz+uHv0aPdf01/48PDw57/8bbk4s3+oL4jEBCXG/Ad/Pllc/yGREX5VJxyfPn/5+ZcPOT9+fXj47z//Nf84rSBbTlBizGMywss74fiTYRjGaPxXzgXw9evXtUPIC/UFkZigxJh5yIwyaHIbjb6+wzNRXxCJCUqMmSfX7tjR6NslZ6K+IBITlBgzjwmHNtQXRGKCEmPmMeHQhvqCSExQYsw8JhzaUF8QiQlKjJlHknBUpZtmynaonxfFt0XxbVE872yZmhfdkupdMLR5Udbv/d/9q74tylfxJses4Zzx5yLyPdq4onBF4cq6W1AV3ZKicJGjVi4JNu5x4R4X7mkf867oljwu3D6HmKdECJ+9TS/xyBCOQ+2KwhVThaOpXjTdXy+K8tXBvauKdsn7uvy26p57X5ffFsW3gXBEB/nAuDWcPv58cjmuxtO4onBNuKxCSzxZJNgQh9OOOsBaVoh5YoS3lds1zjl3V7vHFb0EIkM4nHPu4MqpwgFe/KosXx2AIhzq5/C4Df7LCMfINZw8fgayOK6m0FTxOYXLXjhuK/oTOx/hmBrh8NTBPS3dHbUEsg3h6I5SqAihOsTCEU1wPCPXcPL4GcjhuJoEnJX052TDQj958eSQIDzn3zXxwqcZxDw1wl04Q7mllkC2IBzdPOWkw758dehnFkXxvK7HrGHq+HnJ4biaxHBycXAlNWfJ8BpH8GlMzQhWv8YxNUITjgivGm76xKGd4ERrs6nKzMBZSV3GMoGX5JAgPJD2ZXwQ4iVrCse4CG2qAl9SPw9vi5CXKruR/jD2l1QP9XN0sWPUGs4Yfz45HFeTaKp+PuLPOJp+zkKdg+SQ4G3Vn+37z/OmnxFQn/CrXOM4HiEIVefF0e6uSjgNbmF2iZ8ygAsWxM1ROOxFE9zEfdHgtY5Yw1njzyWH42oqdRneeT24MrG7XTYJ7svwvubBPUXXFDyrxHw8wlDjFN6OZcjkbZQP6gsiMUGJMfOYcGhDfUEkJigxZh4TDm2oL4jEBCXGzGPCoQ31BZGYoMSYeTjh+MkwDCNBUjhEQCawZdQXRGKCEmPmMeHQhvqCSExQYsw8JhzaUF8QiQlKjJnHhEMb6gsiMUGJMfOYcGhDfUEkJigxZh5JwpGpAxixFXY8scU5yfw9CrsHisIVoAmiqWKvJrzErZIg+LK27w07/wval+C2co/7hrRUPHAMBPuDif/KedYOYGgrR8abA1jP0N7W/l0FfYx4ScvyCQ69pE13yOEGsH3ZN4A0xGG5TMy3lXtadZ2sqRY1OCYi6p3X0OTmXPYOYMNWxo237ljQ+XqoXVkHuxgv8awpHOmW8xPcK+blrnZP6yNN8dGYiCjsDbfVD6+9vANYvJJj4zcvHP50o9MIN+xivASySoI7dA6PbW/8LGZ5P45OERwnZHhMROQPtnEjH7eQAxiYp5gD2HHA6Ybvqe8epavQEsjyCfqT9n3ZnbQTBxW4DoIvClw6Zt9B3z3KuF/+lhqDtcOP3x+2LhzLOIARVzdO2uIMiBAOeHVjAO/iHM44ws/n9myCO40ffWJ/Ecb4dyXOODzHc1QuHMs4gKGtHBmPtzgrAoSD8vXqlmcoHM7tkPMNc+FwX65qVnw4cnEUjgmMfJA/mIaLozk7gFFb4cYTW5yV/IWjLqnTDZevcIy6HYt+/QiyvHAQEeIxUDgoBzPxt2MZ8j9OFkZ9QSQmKDFmHhMObagviMQEJcbMY8KhDfUFkZigxJh5TDi0ob4gEhOUGDMPJxyT7IAMw9gUSeEQAZnAllFfEIkJSoyZx4RDG+oLIjFBiTHzmHBoQ31BJCYoMWYeEw5tqC+IxAQlxsxjwqEN9QWRmKDEmHkkCUemDmBwPP6JZHMAG0EFemHbHYWXeFZIkPrKeeo75qS/1sVjBhHCH6lP/ej0nmqtUvij00IcwHA3rTmAjaJCPW94iWf5BLEDWKsa+HBK+WtdPOYmaDDZH4iYiSzCyKOWNg1Nbs6JcADDL7S2+lGIEQ7Qe4o/tBl/rSVjbqPFMeMlEM7TbHNt9cNrL+0AdnhV4skIM96EI8BPTHzXLF7iWSVB7AD2OOwl5f21louZ6o7FHb1Y9UhPsy0b+bilHMAmjjfhoKjQFQ28ZPkEOQewvjMd+2utErN3MMQx4yXRC004IMs4gHX4KxrHx5twUNRlLBN4ydIJ8g5g2GF0vTOOXUFPRval2zdEFtFrbariX7KEA9j7ugLCNOriaLzFWZEnHE1vzuSdwfASwPIJkg5g8OZF8Gm8inAc3NNwAoJjxktg8DovjubsAOaairXzMgewYxxcGe1cvASQye1YPzeJrxesIRx3dTBR6q7RHr0de4g9jbXdjmWQd5xcGPUFkZigxJh5TDi0ob4gEhOUGDOPCYc21BdEYoISY+Yx4dCG+oJITFBizDyccEyyAzIMY1MkhUMEZAJbRn1BJCYoMWYeEw5tqC+IxAQlxsxjwqEN9QWRmKDEmHlMOLShviASE5QYM48JhzbUF0RighJj5pEkHLk6gHW8q0hvHnMACwFfJy/rxBLnXLN+W/0OfHN8zNexp35Be06QA1j0JfTHFeUSFgK9AiL3AKlfOc/aAaxf/ryqmH5ZcwDraIb2k65lnlpSrGrk0x11vXDgdq992TeM9W5aJ7SEzQlyAIN0LXnsGId65zU0uTmXtQPY+7p8Xh+OeIJZWz0i1UTfVPFyyEIJho44yZZz7F6RhwPYAO7fpdrqHRKODbfVD6+9oANYpxrxSpLjqS3OiRjhwDu0XwKdilfrjiWFA8gEbJONHDpG2t5cBHSQDw4A6TEtu3Ais3EjH3dhB7DWNBA8yvqdOYCNgDH7GgxHV/TjYIUDXi94fKpf1iWI5yDU6QY5T8EDNi4cCzqA2VRlNLxFIHQqXs0BjJ2q4GE5TFWSVzfYMZj4HGpzU5VFHMDolUza4qzkLhwHV0aqgZY0VXDDZfUzDuYy4b7sjsyVL44iBzC/8JYZAwc0hMuZ+IujWTuAgSgT8x1zABuAu7K924qXOOfqkv41JrfkXRVgYh7fmKR+jWnF27GEAxgQteQYKBxg8gVvvsi+HcuQ+XGyPOoLIjFBiTHzmHBoQ31BJCYoMWYeEw5tqC+IxAQlxsxjwqEN9QWRmKDEmHk44ZhkB2QYxqZICocIyAS2jPqCSExQYsw8JhzaUF8QiQlKjJnHhEMb6gsiMUGJMfOYcGhDfUEkJigxZh4TDm2oL4jEBCXGzCNBOEiHqB5ulyzqAJZy9DIHMJqmip2ZsMPbZM+3C3NbDe4+LTvU/YWXuAVjPjlCp/BHp7FDFIDbJUs5gDGOXuYARtJUrqyGrkXs8Hai59slua3c02rofItcwsglnmViPidC3NKmocnNc2qT9WUdwIj/njh+BvIXjkPtyhq1O6d9fSJWSfCu7rvC4FGX7rKPWCDmMyPkXM5kt9U7+p00apdc0gGMWsPJ42cgc+HoVMNJEo7umHT5Csf5EXJmiLKNfKh5ilvfAYxYw9Tx85K5cPh++e7hpSFj4diXoWO4P/CyEY7zI1QrHKRquHwcwGyqMhU5ZxwDuZ5xJAPY9FQFe0YBjt1VWcoBLCEE5gCWxITjEkyKEBj5KLw4SjpEeZhdspgDGOvoZQ5gCQ7orgpweDvN8+3igKMOu4ThJZ5VhON4hKG3oLrbsSxijpOlUF8QiQlKjJnHhEMb6gsiMUGJMfOYcGhDfUEkJigxZh4TDm2oL4jEBCXGzMMJxyQ7IMMwNkVSOERAJrBl1BdEYoISY+Yx4dCG+oJITFBizDwmHNpQXxCJCUqMmceEQxvqCyIxQYkx85hwaEN9QSQmKDFmHgnCkbkDGLEVdjyxxTnJ/D0aNRAUoAkCeoJVYMxJDiwzwHtn7UA3avcT8NQvUbcsEHMUT/QT04+r4Gel49+1D9eg5SvnmTuAoa0cGW8OYD1NNXwSRJ5gVeFSTTwLJDjGOyvuNG/oA6xlGeFIbf22ck9rty+BwCFNVNjkBsnXAWzYyrjx1h17cGWvDtgTbF3haMPjO1+jA/W2oj/GW9YUjr6TbRAOqoVXY1u9J2cHsHglx8ZvXjj86QbpCVadNjmdkRHCAScmcKawQ5q35FQlmii1pxvRGKxxao18XOYOYGCeYg5gxwGnG0lPMOfc1MnprBGOt8DZH8LP53GH2YXYQV2gHDf2JTH1UCsceTuAEVc3TtriDIgQDnh1Y4A6ozx1cno2o4WjnQLAQ2uYFPQsuVPg1ofTjTB4HKHGqUrmDmBoK0fG4y3OigDhAKcb8fJWOPzlcGpkFsLR9POR/iM9OESXP+NA8eBIdgUaYw5gJMs4gFFb4cYTW5yV/IWjLqnTDQeEA9yAr1B9lrurcsw7K7qi4R2D8RWEi8eciCe43oFvx5oDmOFRXxCJCUqMmceEQxvqCyIxQYkx85hwaEN9QSQmKDFmHhMObagviMQEJcbMwwnHJDsgwzA2RVI4REAmsGXUF0RighJj5jHh0Ib6gkhMUGLMPCYc2lBfEIkJSoyZx4RDG+oLIjFBiTHzmHBoQ31BJCYoMWYeGcJRUYZRLdwuWcYBjFjDOePPReJ7NLV/oSeYJ5MEhz76MObbirDJWSXmSRE6hV85Bw5g03oll3EAYx29zAHsOIn9G3mCebJIsAlaQoJu1GpsL+llmRihwiY3CDaGGrdLLu8AlnT0sLb6CVRpTzBPbgn69vO72j2tJzShL8aYCDW21TvnersX3Eo6apcs4AB2VDjMyIcF7l/SE8yTT4JtO2xwTLq8hGN8hGqNfFpO8oNaxAEMrMEcwE6m3b/YEwySW4Kt45bvqe8eOcWcivAuHKNZOJoqNmg4tkuWcQCzqco8xPs37zOOFn8toCOnM46WMREqnKoc6uEsY9oZxzIOYHgNZ4w/n9yOq6Nw+zdX4birh8uNu8i5Jw/hGBWhbgcw1wxnrZP8oJZxACPWcNb4c8nhuJoGs39zFQ7/20uEp3kewjEqQnMAMzzqCyIxQYkx85hwaEN9QSQmKDFmHhMObagviMQEJcbMY8KhDfUFkZigxJh5OOGYZAdkGMamSAqHCMgEtoz6gkhMUGLMPCYc2lBfEIkJSoyZx4RDG+oLIjFBiTHzmHBoQ31BJCYoMWYeEw5tqC+IxAQlxswjQziydgAjtsKOJ7Y4J7m/R8EPSg8/Pd2ES8gxPSskCH6u2f+MM/F17CYe41ks5h3l0PMYfME89bPYTuFXzjN3AENbOTJ+4w5gYG92LW0NclrBYwArJAjctHyLerek6Q/Lhj7AWhaI+a4mmuWh39fgA9YQ1oEam9wA+TqADVsZN966Y/uPgaaKpQGPgaybYHv4Ya+K24r+GG9ZKOawvy7y+xqEYyNt9S25O4DFKzk23oSj73ytCjndseCg8jLhpSTZjbqGcJB+X7v0VEW5kU++DmBgnmIOYGPwu3I4izy4MvxswLvbrZrgoBfgesHj6DALe9VblhcO7Pe176ce+5KYeigXjlwdwIirGydtcQZECAdUBDj9hBMTUjXcegnGdjgt+MQ+dBVvWWWqEiwMn8IRKpyq5O4AhrZyZDze4qzkLhwHV4Y7samCmykNNQay1l0V8hLGvuxmBLcVmBpkcMaBF+78HMpHaA5gJMs4gFFb4cYTW5yVzIXjUAdGxK1keHfitnjkGM/yCXY3LOAdWerOq58dYIlZ7q4KvsgS+n0FEZoDmOFRXxCJCUqMmceEQxvqCyIxQYkx85hwaEN9QSQmKDFmHhMObagviMQEJcbMwwnHJDsgwzA2RVI4REAmsGXUF0RighJj5jHh0Ib6gkhMUGLMPCYc2lBfEIkJSoyZx4RDG+oLIjFBiTHzmHBoQ31BJCYoMWYeGcKRtQMYHI+/Em8OYAjYR9/vluDb5dFXzqOdvkKCpHcW+tb50Fk/6V06d4SwZQbGHH1xHgcZZcSPlyAcYhzAcDetOYARxG5M2AEMPlmt36tCeGdhvy/gErZCdyzlUcb7fcX+hqyDGR4vQTgAeTuA4RdaWz1BtBM5BzDk0OHWFY6+YYz3+xrpXnEh2mg5vy+qf5fLaHS/b47CkbcD2OFViScjzPitCwecmDAOYPh0w62UYOSdlfL7ahtkR/aSXoQRfl/E6UY6o9R4McLRkrED2MTxGxYOT7s3kw5g1OmGWyPBW+Sdxft9YcufxWL2m8Yxd1ABOyajxHhhwpGrA1iHv6JxfLwJR3/FKuUARp5uuOUTpLyzeL8vf9B6lok5cDZM+H2Rpw8u7WCWGi9AODJ3AHtfV0CYRl0cjbc4K7kLh7/U3Z9QEA5gLnm64dZIEHtnYb+vu3o42FY440AeZYTfl+POJmgHs8TphhMhHJk7gLmmYu28zAEsBPzYErxZFtydda4u6dMNl83t2Njvq0leI3CXj5nwKEvEHJw+hLqAHczi8QAJwsGS+3GyOOoLIjFBiTHzmHBoQ31BJCYoMWYeEw5tqC+IxAQlxsxjwqEN9QWRmKDEmHk44ZhkB2QYxqZICocIyAS2jPqCSExQYsw8JhzaUF8QiQlKjJnHhEMb6gsiMUGJMfOYcGhDfUEkJigxZh4TDm2oL4jEBCXGzCNDOPJ2AOt4V5HePOYAdgzwJfT6kFgCWCVB5geZo771Hf69+FUcwJAjGe/oRT6byjGVUWbCkbkDWL/8eVUx/bLmAJZi2KeNK0p3oJZAlk9wX/btJ8BNC7v1dMfeKsKBHMB4R7JUz2v0LM7RI0E4AHk6gL2vy+f14YgnmLXVJxhk4uDKSDj6JZDlE9yFJxq3aOEAtttyzq3hAAaJQ033vEbPahCObB3AOtWIV5IcT21xTsQJhwNTUeifkM9UZRc2jEYmYHG/6brCgZw4sCPZyNMNl8rROSdIOFrycwBrTQPBo6zfmQPYFLw5U11217DwEsgKCYIrCPg4DNw31hYObAUSLxx9usGvVphwZO0AZlOVEwgnI3Xp6gYtWcmGj4DShWBqsKpwkKrhQkey8acbkJG+7XkJR+YOYPRKJm1xVoQJh3NVEXuC4SWQFRMcjG0ayl/LrSccyAGMdiTj/USj/6ZydM6JEI7cHcA8yfmOOYCx5H87Fv32Epy8+A9zeEdzYc9RwgGMciQ76gCGn53kaZaZcLDIO04ujPqCSExQYsw8JhzaUF8QiQlKjJnHhEMb6gsiMUGJMfOYcGhDfUEkJigxZh5OOCbZARmGsSmSwiECMoEto74gEhOUGDOPCYc21BdEYoISY+Yx4dCG+oJITFBizDwmHNpQXxCJCUqMmceEQxvqCyIxQYkx88gQjrwdwE5zDNuuA9iwNwtg2FO4ohh+aNqPOdFIYQ6gl9d4v691HMCQ35fDrmWUS9gA6yGG+2UlCEfuDmCTHcM27gAWuzE1sUD4HuhDvU5bPfbyGuP3lYkDWNvJ6jti7+peSrBLWGIN7bPEGgAShAOQpQPYZMcw4r/zIU44mir+MBgGrOgAFva5jvX7WtuPw/Wh7uCJBm8FgGif5dcgRjiydQCbPh5vcU5ECAecmMCZS3uiAZXl1I+Ks0HCMcrva1XhgH5fpN1hRyLI6FluDYKEoyU/B7BTx29YODzt3gzOL3o/jtyEw3PE7yuPM47gfAEd9im/n+hZVcKRtQPYpPEmHP0VKygN8ZJspiqeI35fGQhHe20iNdEYqRru2GRHgHDk7gB2mmPYZoWjid29mqq/mQKWrHtxtA1mOFrG+32tJBzY74u4tIlcwoJ00LPyL45m7gA23TFs0w5gwN0L3ixLuZyvcjs29vIa5/e1ogMY6fcV3UwlXMKAcBDPir8dy5L7cbI46gsiMUGJMfOYcGhDfUEkJigxZh4TDm2oL4jEBCXGzGPCoQ31BZGYoMSYeTjhmGQHZBjGpkgKhwjIBLaM+oJITFBizDwmHNpQXxCJCUqMmceEQxvqCyIxQYkx85hwaEN9QSQmKDFmHhMObagviMQEJcbMI0k4msoVk1qeFnIAw2s4Z/y5SHmPBnsTOYC1VGh3u1UTvK2ATw/+JWrn3HoOYC0nR+ioL5hr+Mp5U7mymtgruZADGOfoZQ5gJMHeRA5grm1vK4jPCbdegreVe1r1PWwNcTit6QB2doS4pU1+k5tzh9qV9TlN1hd1AKP+e+L4GchfOKK9iR3A+nHE7nYrJXhX911hpbtz7rZKNKev11Z/ZoS4iV5DW/3Qdn2acFzWAQyv4eTxM5C5cOC9iR3A+qG5CEd3TLrgoKIbYddrqz8zQmzbI97Ix/dcd48yeHbELlnEAQyswRzAGPDeLJEDmPP/zUM4Wku+4VHGNhacQ4dz7vIxnx+hQuEYOOWMYykHMJuqTAWccUQOYNGAiDUTpPw4j3iCOeeWjPnUCBVOVQamCscyDmB4DWeMPx9xwoEdwKIBETkIx20FpgYZnHGcGCF4SufF0Y6JwrGQA9gRRy9zAEsA9iZ2AOvuqlC2bzkIhwOzA/9hvqYD2GkRhpqi83ZsCjHHyVKoL4jEBCXGzGPCoQ31BZGYoMSYeUw4tKG+IBITlBgzjwmHNtQXRGKCEmPm4YRjkh2QYRibIikcIiAT2DLqCyIxQYkx85hwaEN9QSQmKDFmHhMObagviMQEJcbMY8KhDfUFkZigxJh5TDi0ob4gEhOUGDOPJOHI1AGM2Ao7ntjinOT/Hh366MMOCOj3lRrjVmqrD3pPK2KJJ/Dg6lkg5l0UDPih7PYr50zM0RpUfeU8XwcwtJUj4zfuANYEP1LfKm3s90WN8ayb4NA8Ri0JPLgAF4+5Gbpj2l7YoSO2IYSMzEJhk5sAB7BhK+PGW3ds2FCf6oWtkKvgmglGnabhksiDC7JkzG07/CAcOB6chcq2ehkOYPFKjo3ftnC07bCBIqCdS4xxzq1tVpw63cAeXJBlYm7bYfFEI/IQxFk4lUY+MhzAwDzFHMBGUhXHbXuCMc65FRNkTzewBxdk4TOO/WGYaOzLcKJBnW44lcIxkK8DGHF146QtzoAg4Wgq4LWREI5gjHNuXZfz9NWNgbWnKreV29VBDNABjI5Z5VRlIE8HMLSVI+PxFmclc+E41MMZROqMIznGObdWguzpRjxyceG4qwdpaM84dt5M6MD6j5oDGGYZBzBqK9x4Youzkrlw+N9egtZesd8XNcazSoL7Mv6gxks6VjnjaIZZEtSL6BpHHLM5gBke9QWRmKDEmHlMOLShviASE5QYM48JhzbUF0RighJj5jHh0Ib6gkhMUGLMPJxwTLIDMgxjUySFQwRkAltGfUEkJigxZh4TDm2oL4jEBCXGzGPCoQ31BZGYoMSYeUw4tKG+IBITlBgzjwmHNtQXRGKCEmPmkSQcmTqAwfH4C9LmAIbpv1Fe9l9/9n5fvnw5OIDtKP+bwRSn/5a3b6tn/LUWi3mIkPrKOfMVcvJZDV85l+AAhrtpzQEM0cQuG3XZN6Q0/QfD2g5gnQqEwhG4ezXJw89RHajL7H9jqXAAAAGbSURBVBQYIXYA25d9G0vCE0xhk5sQBzD8Qmurj2mqWAiq8EQjOmdbzQEs7FWL3L1uq9gdJ3jhOPeKeYkixA5gvL+GwrZ6CQ5gh1clnoww47crHFURd77Cxnl4frGyAxg4WrC7165A3ag9pOHFpWMm/cciB7Bd2CYbCZ9CIx8hDmATx29YOPqJnSvbvw+uBPsXn3Gs48cBjkDs7jXG4WLJmHGEe+wABq564HmWQuEYyNcBrMNf0Tg+3oQDX7+g9u9qDmDU+Tl52j/GX2u5ndJGeEg6gA1jwtcpnKoMZOkA9r6ugDCNujgab3FWMheOpgITT3SVtH0qCwcwVjgGgWD8tQBLC4dLOIA556CdjzmAkSzjAOaairXzMgewGD/37G+Rx3dnV3cAg/dWg0sY1Pwl6a8FWF44iNux4f1j52JN0Xk7NkX+x8nCqC+IxAQlxsxjwqEN9QWRmKDEmHlMOLShviASE5QYM48JhzbUF0RighJj5uGEY5IdkGEYmyIpHCIgE9gy6gsiMUGJMfOYcGhDfUEkJigxZh4yo/8HPHYxD/oraj4AAAAASUVORK5CYII=" alt="" />

如果只想返回达到累积订单数为1000的当月数据，不返回之前的月份，则可以对上述SQL语句

进一步过滤，再添加累积订单数量大于等于1000的条件。该问题的SQL语句如下，

SELECT

  a.empid,

  a.ordermonth,a.qty AS thismonth,

  SUM(b.qty) AS total,

  CAST(AVG(b.qty) AS DECIMAL(5,2)) AS avg

FROM emporders a

INNER JOIN emporders b

    ON a.empid=b.empid

    AND b.ordermonth <= a.ordermonth

WHERE DATE_FORMAT(a.ordermonth,'%Y')='2015' AND DATE_FORMAT(b.ordermonth,'%Y')='2015'

GROUP BY a.empid,a.ordermonth,a.qty

HAVING total-a.qty < 1000 AND total >= 1000

ORDER BY a.empid,a.ordermonth

运行结果如下

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

巴特西

mysql累积聚合

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