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  • 有没有好心的大神给我稍微给点思路啊,我都要哭了。。。查询数据集行不通啊,人数要循环分配 现有一批货物要进行装箱,每箱最大可装数目是一定的,装箱操作人员是从数据库中取出的,数量不确定。要求根据输入的总货物数、每箱装箱,装箱人数分配装箱任务,即生成装箱卡片每箱的操作员是按照操作员表及输入的操作人数循环分配(参数栏中的操作员数>表中人数时,取前N个,参数栏的操作员数<表中人数时,取表中人数)
  • 跪求好心人教教我怎么做这个TT,头都要秃了。。93491 table中展示FRDemo的所有表名,当选择某张表时,后面的col显示出这张表中所有的字段。选中某些字段点击查询,得到相关数据。 编辑于 2018-1-24 14:21 编辑于 2018-1-24 14:21
  • 8.0计器本地预览没问题,部署到服务器就打不开了,该怎么办啊?
  • 有没有好心人教我一下,有一组数据排名,数据被修改但是不提交,排名就不对了是为什么?
  • 我现在有两张表,季度和月份的表,现在需要通过两个下拉框,第一个下拉框选择季度或月份,第二个下拉框联动改变显示可以分别选择4个季度或12个月份,求好心人教教我。 参数联动那种是不是只能用在一个表里?或者我下拉框获取单元格数据他只能显示我的第一个数据。 有没有好心人教教我怎么做??
  • 数据库中现有一条记录,两个字段,包含一串文件名及文件地址, 从求大神们叫我怎么把字符串按列这种单元格显示呢?data:image/png;base64,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:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAJUAAACyCAYAAABLC43BAAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAAAJcEhZcwAADsQAAA7EAZUrDhsAAAhySURBVHhe7ZvhcfQ2Doa9Xwf5m2sjreQquS6SSlLLtZHfKSFn5PzOwBiCpEhIXq+eZ0YjEgBBiXzNtbjax9/vvAEU8uPjDFAGooJyEBWUg6igHEQF5SAqKAdRQTmICspBVFAOooJyHu8HX9PAEtk3fI//Hvju75fH4+09/qMGd8a0kEmHjz8oB1FBOZeJypbLSMvmif5e/CjXiNn2O3EzbXfv4xm47H+qrG3LLlt2buF9Vm4x8kdm+spQTLyu2XY9LGZEzNFrM+qvheX78n/UfdvsBlsD4W29/mP+Xq5enojFztLKf6TfXl++3Uyenr8C6+PLRBUHytq38sgW40XLN2sT6lN9iVhvkcW07N5m5YzZa4i+Xk6R5arCriEV1fvxj2fmIno3PqLVtpdPAye/jx3lmomdwbdr5TGiXbnN1vL1crT8szaP91t5ll7OiOV9qo8/keWT3c6GYry9l0vtIjFPLI+IsVnbo3aPYuxsZHlG9PqZuY4RliOTzqVbChoMO8eyr/sb9gM8wsdZO+XxZY/va7aPK9B1ta7Z8D6VY/0rOV1UNkCaMH/jOrdshp9wnVu08hve7suRVlwWa/l9bO+6DJ/Pt/N1EW0+zvt0HhHjsnaz+Y7w44ykHhv40eB77Hp0Tb6c0csv36w/1luYz66pFyN8PsXHuu6x5feHsPJoTGavz5jJd5QfZySdQf3GAVDZzt5uqE20e0Z+ob51ZLaI2XUdFViumev19PrX9XlaNk8v3wpf9jWNbrR1Q7LFwVA9xmcoRytefevIbEJ5fGyWewfljEckXp9oXXcWexaXPP1pUKytL3uUO/q93bfxdbUxYjuR5RE9u9HyiRhztA/R88unvmbIrsHoXccMlufLtxTgteiJircUoBxEBeXYByyfZ7BE+j/Vu2NaVI/O5yjci54W+PiDchAVlIOooBxEBeUgKigHUUE5W1sK//7X7x+lt7c//vzPRym3G+Zr2cROnhErbaBNd3vJRDWLD//1598+Sv9H9cxuWHnkF6O46Idr6Unn0o+/0Soxu4qw2jw3y6LyE7v7sWLtdZxFzO/79HYx8kPO9kplA767clh7HWdNYLxG1Vv96p58DMyzJaoKQT0jEtmr3t/ZLIvqlQc8rlRwjOUtBRv4iCbB+/zEXGH39Uj0z+Q3ejnvyilbCt+R3jaFZzbuzvS0ULpSvTKsVp/prVS8pAdL9LRw6eYn3ANEBeUgKigHUUE5/EQLluHpD0rh6Q8uBVFBOYgKykFUUA6ignIQFZSztaXwePz1UbI9i58+SrndMF8WK+Q/kmeGlTbQprelsCyqljisntlVNjK/52geuJan2aeqEgFiem6WRZWtIitYex1nEfP7Pr1djPyQs71S2YDvCMra+kMTqHLVpFo+j+qxX8PKshs6wxxbotLgn4Um9upJtf4k5qv7fgWWRVU14JYno+c7E90bglpj6+kvoknwPj8xV9h9PRL9M/mNXs67csqWwnekJaqWYGbj7swpoop/za8OovoMKxWU09PCpZufcA8QFZSDqKAcRAXl8BMtWIanPyiFpz+4FEQF5SAqKAdRQTmICspBVFDO1paCf1Mhvioi4rf7vddIom8lf49e33CM3pbC1qsvcaKtntlVNloTG31ZnswO1/I0+1TZ5COM12JZVN9ttbBrtEOoHu1i5Iec7ZXKBnxHUFl7s7UmNbOPiH2obmflFFaW3dAZ5tgSlQZ/B02oJtVPriY29pHZq7C8uqaz+nhllkVVOeBeID6nF5gns1ehe6u6v7tR+sMHTYL3ZSJpTZj8q3nM3soron8mv9HLeVdO2VL4jrRE1RLMbNydOUVU8a/51UFUn2GlgnJ6Wrh08xPuAaKCchAVlIOooBx+ogXL8PQHpfD0B5eCqKAcRAXlICooB1FBOYgKytnaUvBvKsRXRUT8dr/1GsnRPL38PVp9wxq9LYWtV1/iRFs9s6ts9PytsqF6ZodreZp9qtHkI47XYFlUlauFtdcxYrXfmF/1aBcjP+Rsr1Q24LsrjLXXMTuBR/uNsaq3+lVuHwPzbImqQlArnN2v5bY+vur+vjvLonpVQRnqA0GtUfrDB02C9/mJqbCP+vXtI9E/06/Ry3lXTtlS+I60RNUSzGzcnTlFVPGv+dVBVJ9hpYJyelq4dPMT7gGignIQFZSDqKAcfqIFy/D0B6Xw9AeXgqigHEQF5SAqKAdRQTmICsrZ2lLwbyrEV0VE/Ha/9VpJRP6V/D1i37BOb0th69WXONFWz+wqG5nfk+XJ7HAtT7NPVTH5COj5WRZV5Wph7XXMovjZfmN+1aNdjPyQs71S2YDvCMra+kMTqHI2qTF+hMV6VG/lsbLshs4wx5aoNPhnoYm9elKtP7u3s+/vVVkWVdWAW56Mlq8XX4XuDUGtUfrDB02C9/mJucLu65Hon8lv9HLelVO2FL4jLVG1BDMbd2dOEVX8a351ENVnWKmgnJ4WLt38hHuAqKAcRAXlICooh59owTI8/UEpPP3BpSAqKAdRQTmICspBVFAOooJytkRlbyro8GR2o2UTR/IYvVwtjsbDGluvvrTeOcrsKhut10iir5fH6OWC83mafapMAFEwI47Gw7UsiyquGs8+yXaNWt0M1aNdjPyQs71S2YDvCCprb7bWpK72F9uobmf1JdSHj4F5tv9R3x1wTagm1U+uJtb30Yuvwvfh+4Y5lkVVOeCWR7l8zkwwWXwVurczct+B0h8+aBK8z09MZhfyj/KIVnwrTkR/lt/bjV7Ou9J7+rvVqy8tUbUEMxt3Z04RVfxrfnUQ1WdYqaCcnhYu3fyEe4CooBxEBeUgKiiHn2jBMiVPfwAz8PEH5SAqKAdRQTmICspBVFAOooJyEBWUg6igmLe3/wGTn9G7H88FHQAAAABJRU5ErkJggg==
  • 例如-1000和-4000,需要得到25%的结果,-1000和4000,需要得到-25%的结果 我是想把两个数都取正,先计算出正数的百分比,然后自定义标签,判断两个数乘积>0则显示当前百分比,小于零则显示当前百分比的负数 求大神教我自定义标签的js怎么写,怎么判断!!!!!! 或者有什么其他方法能实现我想要的功能! 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CKIeAAipUS8FtvvSVdGnDrrrz1UqhvkX0AjKtS3gensL322h8zQ0frGffnZZfbVwptJ7cBGDeh98FHDrgMK/O1SXnrGfdz+4faAcZVLQGnZZ/Q+iLhDIXarQN02bPPPmteffWVtLZdr7fL3HvvPeamm3b+906VBJwDKwPshi2rjbf38YVWbudbD9B1V65cMU899cvk0nXgwIS5++6709p2rRjBCfdxA5oVWt82of0AdJ0v5FnhJrV9Fp0CJ0tI6MlAoj4cfHdf3MZ9ALTYu3evuf/+B5JLkhfuLLW/BudQhtrkOkZtIW5fAC1oBH/llZfNnXe+P20Ja8UIHhNG6uMGWu6Ll2UbgEY0gseEO0vpAadwypKF1seElPdDfeU+8/YPMO4aew1OQuvddqrLkJPYJweAcVbaa/C80VSG0Q2nG16Wt08JYYdxVtnbZADQvNpOsgFAeyDgAIoh4ACKIeAAikWfZAOA7sEIDqAYAg6gGAIOoBgCDqAYAg6gGAIOoBgCDqAYAg6gGAIOoBg+yVahffv2pEsQ6yPfejNdglin/ul6urQTRnAAxRBwAMUQcADFEHAAxUoP+P79/t+GCinaH3bq9Xrp0mDZV2DLTz+z8z/vCynSlxTtX7VaR3AKs1uy2iHOxsbGZohpmYq77HKfAHxFIwpgkTP11LdIaH39mwz9yG+TxYTx0qXBL7JSX98yyVrXVU2/TcYh9YWc1sn2vHpdqnibLCZgfL1Fw0xoG3m78+ply3qbrJSAh4JKfGENhdnXt8uaCHjWyFsk0NoCnrVfuT42jLHbxO5vFK17H9wNNF0STeGuE4VRBpuCyeGUyy7ejrd16+MoNoyyHy1TkNuo1BFcBtZtk3yB9rV1XZ0jOIWSgpwVThl07s/y6nWpYrSLCR9fb5GgurfVHa3rGL1JbVN037LbRrJCHNOnK5oKOAcztEyK1utSVcCz9jvqeon71hVuUssUXQY5hNZTob6hwn1geBROKu6yi9e5fbk+ziigw6g73HlKP8nm8q0PbZO3r67BCF5cFcGICat7vTKkvu1Dt5O3qzPk+LLJmKOwjjsKW6jEiNlGhpoufU8MdWss4DRauwVGJ0ddXqbLJkbjrpKjcCzfiN2GkFc2RZeBxRS9WjydjhmpuV8o8HIfTTwpuCEpQ0zI+HrdoGZtKwOcdbtj+oyi0rPoENbEB126rqoQaIbX4ABjCgEHUAxTdADFMIIDKIaAAyiGgAMohoADKIaAAyiGgAMohoADKIaAAyiGgAMohk+yVei5519IlwCqdcftt6VL22EErxh9+RIFpcqSBSN4hWgEpz/AxMRdgwaAkvX7zxgKMEZwgDGEgAMohoA35MycfX1k5+9JscuNOTO4DYeX03qZ5uyO7f439e2V5F0RbUM3aE5uCMNCwBtAj/OZVWOWLtDvntmykq6oyPLhBp5E6ErNaWOmB9XExLwxBxfC4aUDszo7OCgrcsNqNHJcaoaAN+Di+cHl1MTgslE2R5SnszZ7paGgLhz0h3TFhn71uO2T1iU6MIem0gqUAQFvC/uAPyynyunUORns0nVzGdP6ZDTidbYs2234ZcDCuu1gZwxynbvNjplzev071kfcFnPCjtJLj6QVlw39kr04Uc4UnO4D3TZ6TuHbs7nn9LZyO9+HzOOSbuP9O1jB64s5Lg1AwGvEDwqanpOZ9IHAgcuzarc7bUfbCxQQuyyDSg9WWpdM+W2Zt7ODaTv1p+WlQ7ZTOvPldWT+rK3blwm0eht6sM7Ydns9yTZ20F13Ztah25I83FftHo9kTE+OHLN9Hk8rjoNDjOB24D9hL/i+HE/DOTdp//Hch7zjkitwfSR8XJqBgNeIXoLSA+m0fVARDmTsA4sCR5PeiTQD5y/af+wDaM2Gm9eVoX/KhsFeLvK03e6YbvK59KUF8d6WTXZ6nnWfko3OJbd9wKaOnukePzrUa+91G6SjdFvtdZ61xzN5uUHPM7TOhjoZTe0TFpH3YVje60tlH5f6IeDQAjYS9Ew3ZV+bh07AZbHPPqGnhVk7cvMITaWUcw0Z19c2CHhLLdvHehQ7ihyz80QaqTKjIQfMHDz68NQzObltL48dGdTz5VxZn4ZRzyg/ZdvKGGLJgcH0OfRKYFPOTY3+O7QUAt4W9sG+aEcGnlKety9T6QEag15L0xSaX9O7r+vnF+0/ds496axL3nK2r1NpOs7Xmwygdnii15DcNmkvaSSMeylhN561ezyVEZtTa7aPnY5XiabP9BrZPjPxMZH3nXiPywh/hzbCZ9ErNLafRachf9KOxN43+On1th0WL9hnJfcJg05vH7fTh1Lfs9MNn0WH+tHZxCU79/W9np6bsaO3HTp9s4EDNtzrJU3RIYGAQzXodYOxYZYZpxGaPt0WOlPOTww0Nx7mZBvsgCl6hfB1UagapugAYwwBB1AMAQdQDAFvi77zJQcfeocprw+MRtnfAQFvQPItrhZ802h4fXsfep0/0d39v0M+BLxLpkv8PPXY+F/zww/9B30BrDwd+jsg4DXK+342OWgLTRGTdWJ0SUabtH3H1DCdMm6WAqPSmbme3YbL3Obb1tvbt0brvr0hvd5kch9WZ3j94a370F+2t3/ndgl7ALidy2HeMGM7ui1zy3L94HYmt8UejK3DN5hZbO4zoI1/h6og4DWK+R7y6oIxi7bN/T5x8LvbFn04TO4v9iegKDgz5rTdZiMtK5vfkppe4TZb7I05NzMI1YS9IRv2htB9mD3Nfc6m9+GMmZs8b28/t582ZobDb9fNnDNLF9J19J3ZQ0vmJG1I4Z5cM8d4XXJ94knDWl0z5mS639Ozq+Zxe2Mm5hfN7Pra1sfe+6fM2vqsWcz50Hzb/g5VQsBbZpjvE0/Roy0dieJfF58xj68eMkuPBD5VJkfbyYXkCym5+ufNOXtDZni73gzdrFz9U2tmfXZxK2AT82Zxdn3bfZ9dnN/8dCs9+Qw+DDdtjtp+a2nCaT/0SzK06tXv/rP59w9/2JYvmt/0njSPJcsfNv/13d8nffPU93eoFgKuQDKq2BHDDh522jx4gI32+HJGWzuM+UasHS6eN+s2GRdom83Co/sgjAuTafhp/ye3Qjus6UdsEtdO2cn5GXNi4eDm6P0Xn/pv86Wf/cyWR80HNv7OfDJZ/pn5l0/9ZbK+CuX/HUaHgDelwPezY9mBbfPXYs7Lnaej8fZR5YAdcWzgfL+NlozEW86ccEfwifSr2849mD5qp8wL/p9bs9Pw4+dk+Dn4dm9HjplDq8e3puTU184upg6k9Sw02h+00/Tlx83q7NFk1C2k8b9DtRDwBoS+n50l+N1tXpcW+r0397vb/fMyrmzCjjj2tfS5meRBNyjpSbZ0isyj7fGppWRUkpKRc2Ey3Y5fL0+bleT1M+/PFj4JlgRxwd5nsU5c39nTB7dG9+T1+NYTQJ7po3bbhVUze7RYvNvxd6gWvmxSIXzZRKDRy05bT4sTeXSS7/jUBXM2NskhtO/jU+bC2dGn/F2DL5tAS9FJPvoR1VEjSecL7OgtTsLBFgQc6jH9iFk6tP0M+7mlCyP9ByaD9+pH349mmKJXCFN0qBqm6ABjDAEHUAwBB1AMr8ErtPUa/FeDhhGcmfuHzf/TbPb0Y2ZlmvZcoeUvGrNwwV7Zvxmzcl/aCG3T7/8NXoNrML3yfbOx8bXBFyTqMP+oMRs23Ks/tI8i7xgAHYCAQwY7cs/aUbzh/0APhoeA16hvp729w0+YfjKpGqCp9+HlFzeXe72tMncmZuT8tZnrrZgzvM/+E+bwjnrGPs+sFLgu6BoEvEYT858ws+vr4r/t+rV5fPWjZnH+PUltMA1Py4WHzTn7onszqEOx4Z98zixuPJbu1065ZxbNctEp9/mX0gXoGgS8VveZo3bKu3ZqEJj+8g/N6uwDZjo5FWelo2lSJk863+AaQv8Fc878xMz0Ppnu98s7v589PZeEP3jSzj7pGPNNY3pftPvDKN81CHjNph952Ji1p+00/cXkP9lceuSv0jV2tJ35g1m6kI62dgQf+XzaxefM+qGHzYXNEZzKo2Z+osAZePuywZjPGWO3M0W2g1ZAwOs28dfmmB2bT5152qzZCB/hb0gko+2WMyeKjOB/SL93/KJZflhsN/2AfUlw0v/9bJbOGvg8gNfU4CUEdA8CXrv3mvnF95mFmZPm4OKMmeDp+cTfm0U7fV+YHEynj089LL6DbYN7mKbYn09/7HDQZ3Bi7D4z+Go2tX3erB2T291nVpLX8jxFt8U5yWcO3JHMFNbxOlslfNClQmV+0KU69ORBTwxfM2fn35u2CTRFP/qYnQ1get5G+KALBCVv2yWjfiDc5td2ujBJv+4EHYWAj7GJ+UeTE2/ecNNHVXtfNmb2Ezi51mEIOPglH1X9Pj6H3nEIOIBiCDiAYgg4gGJ4m6xC+E02qBp+kw1gjCHgAIoh4ACKIeAAiiHgAIoh4ACKIeAAiiHgAIoh4ACKIeAAiiHgAIoh4ACKIeAAiiHgAIoh4ACKIeAAiiHgAIoh4ACKIeAAiiHgAIoh4ACKIeAAiiHgAIoh4ACKIeAAiiHgAIoh4ACKIeAAiiHgAIoh4ACKIeAAiiHgAIoh4ACKIeAAiiHgAIoh4ACKIeAAiiHgAIoh4ACKIeAAiiHgAIoh4ACKIeAAiiHgAIr1Xnrp5Y10eZubb35XugTDeu75F0wvXQaoCgX4jttvG1QcGMErRgcfBaXKkgUjOIBiGMEBFEPAARRDwAEUQ8ABFEPAARTDWfQKPf/8C+kSQLVuD7wPjoBXiAI+MXFXWgOoRr//TDDgmKIDKIaAAyiGgAMohoB3SK+3/asrbr3NfLfdLZJbZ6H+LNSepeg2VfcvEwKuED2g8srAaTOX1Ofs0mguLh9K9x3el7zujY3BuV265OUQ3o4K9w9tQ+18HU2Qt5VLVnvVEPCOoAcEP3jlA8StMzcIbn1gxqxsPGFm09ooDsyv233790W3bed1FxPaXt5/LmW2E1+7r43J28rLbr0uCHjHhB4wXC/bxeXlkUZ3evDzbctaZrTMddkeIu87L8si2+WyLFntzG1364zrvvtHdblcPWP+H+1wY3dF2vzdAAAAAElFTkSuQmCC 编辑于 2018-4-9 21:20 编辑于 2018-4-9 21:20
  • a. 用分组表组件按照层级展示用户的“部门名称”、“职位”、“姓名”、“用户名”;94778这是怎么回事啊。。是不是我的表关联有问题,每个部门分组下都是所有职位名称。。。求好心人教教我吧。。94779整个是一团浆糊。。。。救救我
  • 求好心人给我回答一下下面几个问题,或者告诉我具体帮助文档在哪里,我不太懂这个是不是全局更新还是什么呀。。。 95020
  • 新人小白,实在不知道错在哪里了,求好心人解救 94832 94833 要求是如下效果, 94832

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