看別人用得很順,
function saveComplete(s, e) {
var r = e.result;
var result = r.split(',');
switch (result[0]) {
case "p1":
break;
case "p2":
break;
}
我套用到自己的程式,
function GetValues(value) {//value="gghh,yyyi"
var r = value;
//alert(r);
var result = r.split(",");
lb1.SetText(result[0]);
lb2.SetText(result[1]);
}
可以alert可是label的Text就是出不來,
試了很久才發現,
原來接進來的r不是字串,
要先將r轉換成字串才不會在split的時候出錯,
在split出錯也不會跳通知,因為是Javascript,
修改成,
function GetValues(value) {//value="gghh,yyyi"
var r = value;
//alert(r);
var result = r.toString().split(",");
lb1.SetText(result[0]);
lb2.SetText(result[1]);
}
就可以了,加油。
0014DerMiniBlog
2018年5月10日 星期四
2018年3月13日 星期二
[SQL Server 2017-SSIS] OLE DB目的地錯誤輸出,資料存取模式,資料表快速載入的差別
若要知道怎麼使用錯誤輸出可參考以下。
[參考網址1] SSIS-轉檔中如何抓出pk重覆的資料
[參考網址2] [SQL Server 2017-SSIS] 使用OLE DB來源與目的地的資料匯入
此篇用圖來顯示[資料存取模式]中,
[資料表或檢視表]與[資料表或檢視表-快速載入]的錯誤輸出差別,
若選擇[資料表或檢視表-快速載入]則資料列全部都變成錯誤輸出。
改用[資料表或檢視表]沒錯的資料才有進到DB裡,
真正錯誤的資料列才會輸出到txt檔。
以上,
錯誤輸出的目的地,
可以看你需要輸出成怎麼樣的,
我選擇用txt檔案來存。
[參考網址1] SSIS-轉檔中如何抓出pk重覆的資料
[參考網址2] [SQL Server 2017-SSIS] 使用OLE DB來源與目的地的資料匯入
此篇用圖來顯示[資料存取模式]中,
[資料表或檢視表]與[資料表或檢視表-快速載入]的錯誤輸出差別,
若選擇[資料表或檢視表-快速載入]則資料列全部都變成錯誤輸出。
改用[資料表或檢視表]沒錯的資料才有進到DB裡,
真正錯誤的資料列才會輸出到txt檔。
以上,
錯誤輸出的目的地,
可以看你需要輸出成怎麼樣的,
我選擇用txt檔案來存。
2018年3月12日 星期一
2018年3月8日 星期四
[SQL Server 2017-SSMS] WITH AS、 ROW_NUMBER()、PARTITION BY查詢的資料變化
整個語法如下:
WITH TETABLE AS
(
SELECT [TraTitle],[TraDate],[TraTime],[TraNum],[TraContent], ROW_NUMBER() OVER (PARTITION BY [TraTitle],[TraDate],[TraTime],[TraNum],[TraContent] ORDER BY [TraTitle]) AS SORT
FROM
[dbo].[ForeignTra]
)
SELECT [TraTitle],[TraDate],[TraTime],[TraNum],[TraContent],SORT
FROM TETABLE WHERE SORT>1
查詢的資料變化如下:
1.
2.
3.
4.
以上方便以後參考。
WITH TETABLE AS
(
SELECT [TraTitle],[TraDate],[TraTime],[TraNum],[TraContent], ROW_NUMBER() OVER (PARTITION BY [TraTitle],[TraDate],[TraTime],[TraNum],[TraContent] ORDER BY [TraTitle]) AS SORT
FROM
[dbo].[ForeignTra]
)
SELECT [TraTitle],[TraDate],[TraTime],[TraNum],[TraContent],SORT
FROM TETABLE WHERE SORT>1
查詢的資料變化如下:
1.
2.
3.
4.
以上方便以後參考。
[SQL Server 2017-SSMS] SQL語法刪除重複資料
因為資料庫為測試資料匯入用,
所以沒有設唯一值(KEY),
裡面有很多重複資料想刪除,
上網找了語法參考了幾篇文章,
我使用的是WITH、PARTITION 與 ROW_NUMBER()的語法搭配,
因為我沒有可參考的ID(流水號)。
[參考文章1] 如何刪除 SQL Server 資料庫中重複的資料 (兩種不同解法)
[參考文章2] [SQL] 於多筆重複資料中取得該重複群組中最新一筆資料
因為我的SQL版本是2017就遇到了資料庫相容性的問題
![](data:image/png;base64,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)
使用以下語法:
ALTER DATABASE TestDB2
SET COMPATIBILITY_LEVEL = 90
![](data:image/png;base64,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)
因SQL2017最低只能相容到100,所以有錯誤訊息。
使用以下語法:
ALTER DATABASE TestDB2
SET COMPATIBILITY_LEVEL = 100
![](data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAQAAAAD3CAYAAADykopzAAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAAAJcEhZcwAADsMAAA7DAcdvqGQAABTfSURBVHhe7d1PqB3XfQfw8xSDlLiVrKiOHBNwoRUklCJMFtkXZyFTLURb9aG6GFTjhbKxFu7KyLKdQBIpyFDowi4qBiOCStBCxW/jLrroIosstAixLWNk6ir6Q8yTjN02etHL/d17f0+/+3u/c+bM3DN/zpzvBw4zc86cuXPnnt9v/tynq5Xrv76x6SJ8/bH90+na3TX3zp13pvPs6T1Pu0O7D82Xtrtw4YI7duzYfAkAhmLHfAoABUICACgYEgBAwZAAAAqGBABQMCQAgIJlmQBWVmaF53nK84SXfXWhotcNWZmsULdU9ZOsZV2YVcdkmyx1+Fanem6ruUnoWZYJYNPzlwuynuf1urQs2/R6vmnI5mQlKtY8T2U9k3VWu0WvT4UDWbZpso1LCvTStCkqCP78FHUL4Bvzy8SCL5Cq6mP6UWDTct0zdSzfPlg40EO7UmNzMBB4BtChtgK5iVT7opMCkkBekAAUGsxcUqFgSx38vE0q9c7k6fel6soAhgsJQKHBzCUVCtA6QUo4SPWU8Tap1AnoZvtiTyXaZI3dgIHINgHwgJPToasbeBysdftpVoKovy8PiiQ3TW1IAnnBFUDH6pyt25ZqXxD0+RptAuBBaQ1Oq03XWeuEcDDJoJJ1XDS5DtN1cqrnqfDZ3GqTdTyV9VV4Nd+U8Jmfir5CgGHLOgHwYLMGHdVx0aw2XaeXq1iX67JOFsmq13Vy2SrMaqsqVWgVLr5lnvI85AO3AMu6d8+5l15ybnXVubNnnbt/f1Z/40Ye9bT/Icu8v1u3ZnUwWEgAy/r0U+e++MK5U6ecu3bNuddfnw38N9/Mo572P2SZ9/fb3843AkPV2U+CSaP6ebBPPnFu3z7ndu1y7qOPnHv11dlZc+/e2Zlx6PU//rFz3/jG/M0Ylnl/lAB27pxvCIYIvwkIUDDcAgAUDAkAoGCdJABc/uevzt8OSE37QTeSPwPQD/wsKRPCK6+84l5++eX50gM85ui7aZrnqUW36e+zQ/1Yndcj+jUsMnD4O/tQMMV8r29pY5sSbb/udqz3HqOvY5biOMVIfVxauQKgAPeVlELBT++Rivyc+HhxGy8T2abJNi6S7/WIXF/Ox6IPS3/Qss5qb2LZbYaCrIkm+8CsvrLOaq9Lb6vJ+2/SZ5l9t/qO/hlA1bFqeCy3+nHwM9+81PQ1ie/Djx0UNOj0wIvZptVvWbzN1NvV2jhmGm1Lr9P0vXG/Jn3roH3ONgH4zv6EPld57Hyfc9PjW9Uvcly1hgeOHkQ0Tx+6NVirhIJFvl4suS9N9ic1+R7kvsj9rLOPVf24TrfJfnVfs4nWEsDRo0e3lS5Njt3k4M0XFKpvclyb9usaDxweREzOp8TbbWv7XaB9T3nMqvpxe9Ptp9JaArh48eK20jU6tlbAUn2T496035DQIG/7rBKL92Uo++PTdB+X7dekb12jfAYgj5svCZCYYLb65poEaEDRGafvsw7jfRnSPmlNj9kyx5r7Ne1fx2gfAvqCXotdT+N+9PnobTTdZsm6ONu1iQM+tbaPS9Z/B1D1NSAfO/5cfMfSCuIY8vOW/fU4CLWFhAaVHBh6ndg2ItubbpPROk33pc426XMn9mffzTGz6rTYdersC7P6NTkunfxjoLaEvgkYA9+HVhLfMfAn/zKOWarj0sktQMxVQRP0RjnrjRV9cFRKE3rfVYl/zMcs9XHJ/hlA6A3njjI2l9KE3nvoMw/1G4PQ+2tyXEb7EBAAqiEBABQMCQCgYEgAAAVDAgAoWJYJgL7JsIqvTbPqY+sAxiTLBMDfZNCUC7PaZBDTvFVPy4TreMr1AGM0mluAmEDl4Gc6CQCUZhQJAEEM0EzWCYAC3xf83EYFl/EAtqwTAAW2L7i5HsEP4DeKW4BQEvBdIfhwHyQOKMFoHgL6yCSgEwICHUqXZQLgIJbBzHxtvMxJgIoMfr0+89UDjEGWCYACl4tmtVUtE1knp3o9gDEZ/S0AAPghAQAUDAkAoGBIAAAFQwIAKBgSAEDBRp0A9M8gWz+LXBocA5CyTgA8mH0DWv8EsvVTynVUvZ6P1U/WydI266ehm7L2n8uyQtsa+/8F0aXsrwBSDugqy7yW7svzXC/bciL3PeX7CG2Lfv8eSSANPAMYkFTBEzp7+uqb8O1v7PtIuS/QzGgTQNXg8rVzfahvG+ruC9fpdprnsycV3TcUnLwtLrJOz8fy9aV53z7GwFVAGqNMAHJwWXyDT9brtrbQa1ivU7UvXMfty9Lb0lPZrvclhNfnvkzOQ3+KvAUY0uDTgZECBRyXVNo4Zqn3EerDM4CBSBlgnFS4xKD1OCBj+yyDX6eL1wI/JICEhnhPGnuGRUCWaZQJgAYxn82IDALZRkUO+FBbarR9OdWq9sXXv2k/Ivsxvb6eEquO+drkfhKrb0jV/4UPcUZ7BUADTBbJV09CbVXqDMiY1wmtk7KNgk/WU+GAlHXWMrHqWGyb1Q7tyz4ByLNI25Z5rS73sy4KPt4/Ln0HJO+HBWf/dLJOAF2fPZq+XtN+XZL7OIT9DO0Lgj+dzhLAhQsXtgoADENnCeDYsWNbBQCGYbQPAQGgGhIAQME6SQC47M9D6Ml7SNN+0L+V67++EfXI9+uP7Z9O1+6uuXfuvDOdZ0/vedod2n1oOh/zkC9VQuAxRw+KaZ6nFt2mHy6H+rE6r0f0a1hk4PAT71AwNX1C38Y2Jdp+3e1Y7x261coVgHzgp0sqNHZozFCRY5vHEbfxMpFtmmzjIvlej8j15XwsGvw6AGSd1d7EstsMJZEmmuwDpDWKZwBVY6jpGON+HPzMNy81fU3iC4rYYKFA1cEas02r37J4m6m3C2lkmwBo3Mox5YuNpuOuql9kLLaGA0oHF81TUFOpG3ShBCNfL5bclyb7A+1rLQEcPXp0W0mNxqtvTFF9k/HWtF/XOKA4uJicT4m329b2oR+tJYCLFy9uK22g8WgFLNU3GatN+w0JJYahnG15X4ayP7Ao21sAOZ58SYDEBLPVN9ckQIGmrwr6xPsypH2CB7J+CBh7UoldT+N+NG71Nppus2S4ChiebP8OgMaSDEw+ufjGmBXEMeRJS/aX9STUFsJnbIsMGL1ObBuR7U23yWidpvtSZ5vQjeQJAOrB4Mcx6FMntwD4J8CGe/ece+ml6SwFwNaZ8saNWf3qqnNnzzp3//5o6xfet14fOpH1M4Csffqpc1984TZ/+Uu3+b3vuc2f/MS5W7ece/PNab07dcq5a9ece/310dZv3rzpNl991W2ePLm4/sbG/CBB2zq5BaArgJR/BjwKn3zi3L59zu3a5dxHHzk3CYTpVcHevbMzYcn1VJ54Yn6goE29JIDbtz+bz8EQfO1ruycn6bvzJSgJbgEACtbrFcCjj/7hdAr9wlP4cuEKAKBgWSYA+ubIKr42zaqPrdP4q6w6paqfZC3rwqw6JttkgbJlmQD4apWmXJjVJsc5zVv1tEy4jqdcH0KXz3wJred5KuuZrLPaLXp9KhzIsk2TbVwARnMLEDOeOfgZzcsk0IQvkKrqY/pRYNNyW2dq3z5AOUaRAFqKj+SGdMmNy38gWScAGsO+ccxtVPo+0VGwpQ443iaVOmfyNvYF8pV1AqBx7xv7XN938BMK0LqX2xykesp4m1TqBHSTfYHxGsUtgG88U33dkx33aSNG6gYeB+uyAWslCCQBIKN5COhD45zHv5wnbQV6SJ2zdduGtC/QjywTAI9ba/z62niZkwAVGfx6fear1ziYZFDJOi6aXIfpOjnV81T4bG61yTqeynooW5YJgMY7F81qq1omsk5O9Xo+1uW6rJNFsup1nVy2CrPaqgqUbfS3AK2jf9La8Q9pJK8nH388m0JR8M+Bl7Tj9i33lX865/737551X/7Xf3G/e+KP3f//zd+6XW+ddzvurGdR/wc/+oG7/d+33ObOXfN3BaXoLAFI3/3u4flc/nZc/x+3+dWvToPnSx9fc185+0O3snHP3d+z133+yvfzqd/15fk7gpLgF4EACoZnAAAFQwIAKBgSAEDBkAAACoYEAFAwJACAgiEBABQMCQCgYEgAAAVDAgAoGBIAQMGQAAAKhgQAUDAkAICCIQEAFAwJAKBgSAAABUMCACgYEgBAwVb+47/eG92Pw//Zn/zRfA4AQlY2NjZGlQD+8+cfIgEARMItAEDBkAAAClb0LcD5t37mjj/7V/OlRTdu3p7PAYzPY/sfnU7nVwBr7vmHHnIPTcvzkyXmq5c861w9577j7dM/Cn6A0k0TwNrzh527vOEmVwPuV2euuMPPz8LWV79g7ZI7f/zydJ3Lx8+70+euzqrPvOgOXn7D+f+/oP4g+AFmJglgzV06f9wdmUfqgb9cdd++8p676q2PMDn7n75yxr04wOhH8AM8sP0h4IFvuoO/+JX7cL64xVd/6EV35srh6S3A4UnCOH3ywOzsf/qkOzBfJaVz//yWe+LP/2KhUF0MBD/AogTfAhxwJ38+u03Y2Jhc8m+d/WOeH9R38sSz7h/+/q/nS246T3UxfA/8AEq1PQFcfc9d+fa33J/OF7f46hdcdeee+albfXty9lfPBi4lfBp46h9PTAOfCs3XgSQA8MAkARxyR0SAXv33n7pfHPzm5Lzuqw9Ym5z5D552k7uA1lHg1w1+hiQAMLODHuwfeuOyc4dnl+vfevGgu/zG7Omdr942OfufvuLO8JO/Q0fc8fPzZwMDfCCIJACAfwsAULQEDwEBIFdIAAAFw+8BABRsZX19fXQJAADi4BYAoGBIAAAFQwIAKNjK+++/P9pnAPv375/PAYBlZXNiPj8qH3zwARIAQIVRJ4CxQmKDVLYSwN27d6cVTezevXs+NxxjvQK4efMmEgAks5AAjhw5Mq2s49KlS6NIACsrK/M5vyFcLCEBQEqtJwAOLB08vnoSCsbYIGySAELvn95n7Gu3CQkAUurka0Bf4IQCitq4Xc63jQJdF4Cx2nYFIAd87LLvCoDOqhy4PO87u8sAz/EK4JFHHnHr6+vzpdmyJts13d8HVwCQUutXABRYHPyEpnqelyVrvWXxvliFPPzww9NA1yUGBa8Meg5mmvoCm9bnYi0DtK2TZwBW8PrqCQekJTYRWFcAn332mTtx4oT7/PPP5zUPvPDCC+7JJ590r732mvvww22/fTx9n77XtgKWEwIHv5xnVh3x1RNcAUBKg7gF8AUWCSWKECsB0Lb0eyBUR5566in33HPPudXV1emyRH3q7kdMAvBBAoAudHYLwCiIdGG8riyh+tTeffddt3PnzvlSPRTMXOqgQNcFoCud/x2AFbwyCUhyXd86PlVXAPK98hWB1cbqXgHIREBBTcs6uEPJwpcIcAUAKW27AqCBziVmOYQDmKY6mLn40PrcTlPZP4U67yMGn/05qDmAq87o1K4LQFc6++fAdYJYBj9LnQToLC+LT2yCaBrAMnHIBALQhVZvATiQZUBbQazbeJnIvsRax1LnISDjNus4UH3oNWXgchKgOjlPdJtex5qXcAsAKS0kgKbqPAPoSp1nAITrfMmBVCWAUEATq02vQ0JtSACQ0lYCGJtlrgCaHBIKVqaDnPkCW/ZlOvAZEgCkVFwCeOaZZ8w/BCL0l4Bvv/12owTQFSQASKm4BBADCQBK0dm3AENAgR1TAEox6isAAAgbbQIAgGor//azy0gAAIXq5Qrg+vXr7vHHH58vjcMY3xOMX1EPAQFgERIAQMGQAAAKhgQAULBBJQD6Sz1d6gj1l/NMrwNQmsFdAfCXEk2/nPD1l8sc9E1fA2AsBpUAQkEbY9n+AKXJ4hkAn7HlJbucjyH7yalUd5sAucsiAdCZnAKTptZ8FbkO9ZFTVnebAGOQRQLQOEhjA1UHu0+dbQKMQZYJgIKUz9Yp8TZTbxdgqLJMAG3DVQCUYnAJgINPBqGuozM0zVPheabXJb46Wa+3CVCCwSUACj4uLFTH84zrQ3Vy2aoHKAVuAQAKhgQAUDAkAICCIQEAFAwJAKBgK+vr67089tb/TVbu0z179szfGUA+evlR0Dt37rj/+914Lj4e27cbXx9ClnqLQgqasaArAIAc9ZYAbvym+X9HPjR0GwCQoyyuAOpeLXR9dYErAMjV4J4B1Aleuoqou34baB/wDAByZCaAtv9BDCUAumyODUgKsCHfMuz60n18CwBZ2pYA+F/ItZ0AQt8CxJzVdUII9Wk7eeAKAHK1LQq7GshVQU5By8Vatsh1qtZNCc8AIFeD/RaAEgQXa3lI8C0A5GqQzwAoyGVb1TIJJYaqZLMsPAOAXPWWAFI/A5CsBNEmer02jxdAW3q7Bag6Y3MAW1Oel3zbi0kmy8IzAMjVoJ8B6HVoWQc0LVvrMqtPangGALnyfg1I2rqsDT0D4GCVbTrArXVYqK0teAYAuTKfAbSt6hlAbijp9HAYAZY2yGcAucEzAMjVYJ8B5ATPACBXuAJIAFcAkCtcASSAKwDIFa4AEsAVAOSqtx8FJXTmpOAZwxTfAkCOevsacEzfm4/t/UA5ersFAID+IQEAFCyLBCD/PDlG3fUBSjW4BEDBq0vKegB4YFsC6Dtg6JmkLnXrfQUAFi0kAAp6GTB9JQGZhHgfrDpJt8sCALbBPgOQichatsh1qtYFAJUAhhQw+gyulwFged4rAAq0PhOCPovrZYtMElwAwG+wtwA6iPWyphOEXgaA7cwEQEHWZ+DIwLWmPC/5EoOvHgCMBCCDv8/gsZIQLet9omVrXWb1AYCZhQTAgcJB1Qd+7aqA5v2jZbmutd++bQGUbiEBcDDJ0jXrda1l376F2gBg0WAfAgJA+5AAAAqGBABQMCQAgIIhAQAUrNcfBR0T/CYg5Ag/CpoAfhQUcoVbAICCIQEAFCyLBGD9eS/jPwvmYtVxPQAsGsUVgPXnv1xntQHAjJkAhn7WtPaN6hDoAPVsSwAcSFT6SAL0mrroel5mNK+DX64v1wWAB7YlgL7Popx8ZAnVE5rXQW6tBwCLvM8AKKCGEDy8H1Vn8Zh1AGCR9xlA7vg9cAIBgO3MBEABM4QzqgzeuvvD63N/ANjOewswRL4kQHUc7Ah6gHiDfQbge30rCVCdXlcmBACwLSQAChYuVvB1Ieb1fYHN/WR/XrbWByibc78HQBj5PvZXZc8AAAAASUVORK5CYII=)
還是會有錯誤提示,但我發現其實能查詢,那就先這樣吧。
[參考文章3] ALTER DATABASE (TRANSACT-SQL) 相容性層級
WITH和 ROW_NUMBER()語法可參考這邊。
[參考文章4] SQL 中使用 WITH AS 提高性能
[參考文章5] ROW_NUMBER (Transact-SQL)
所以沒有設唯一值(KEY),
裡面有很多重複資料想刪除,
上網找了語法參考了幾篇文章,
我使用的是WITH、PARTITION 與 ROW_NUMBER()的語法搭配,
因為我沒有可參考的ID(流水號)。
[參考文章1] 如何刪除 SQL Server 資料庫中重複的資料 (兩種不同解法)
[參考文章2] [SQL] 於多筆重複資料中取得該重複群組中最新一筆資料
因為我的SQL版本是2017就遇到了資料庫相容性的問題
使用以下語法:
ALTER DATABASE TestDB2
SET COMPATIBILITY_LEVEL = 90
因SQL2017最低只能相容到100,所以有錯誤訊息。
使用以下語法:
ALTER DATABASE TestDB2
SET COMPATIBILITY_LEVEL = 100
還是會有錯誤提示,但我發現其實能查詢,那就先這樣吧。
[參考文章3] ALTER DATABASE (TRANSACT-SQL) 相容性層級
WITH和 ROW_NUMBER()語法可參考這邊。
[參考文章4] SQL 中使用 WITH AS 提高性能
[參考文章5] ROW_NUMBER (Transact-SQL)
2018年3月7日 星期三
[SQL Server 2017-SSMS] 無法使用特殊主體 'sa'
在[資料庫引擎祖態]的[伺服器組態]的驗證模式中,
[Windows 驗證模式]或[混合模式(SQL Server驗證與Windows驗證)],
選的是[Windows 驗證模式],
所以安裝完後,
SQL Server就將SQL Server驗證的'sa'帳戶設為特殊主體,
導致就算我啟用了'sa'帳號,
我要將'sa'的權限加到資料庫中也是不給加,
Google完後找到的方法真的能使用,
只是這樣以後我新增了新的資料庫,
還是得用語法把'sa'帳號的權限加入到資料庫中,
只好記個筆記了,還有感謝網友。
網友使用的是SQL2008,方式如下:
◆資料庫的相容性層級需要是:90
可用下列的指令調整:
USE [master]
GO
EXEC dbo.sp_dbcmptlevel @dbname=N'資料庫名稱', @new_cmptlevel=90
GO
◆資料庫應該要具備有效的擁有者。
請使用以下的指令來進行調整:
USE master
GO
ALTER AUTHORIZATION ON DATABASE::資料庫名稱 TO sa
或
USE [資料庫名稱]
GO
EXEC dbo.sp_changedbowner @loginame = N'sa', @map = false
GO
而我使用的是SQL2017,我只使用到如下:
USE master
GO
ALTER AUTHORIZATION ON DATABASE::資料庫名稱 TO sa
就解決了,供參考。
[參考作者]哇哈哈學習筆記
[參考文章]無法使用特殊主體 'sa'
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