小编use*_*162的帖子

我将图像文件作为 XML 数据接收，图像的每个字节都是一个带有十进制值的节点，例如对于这个示例 .png 文件， ，我得到的xml是：

DECLARE @xml XML = N'<?xml version="1.0" encoding="utf-16" standalone="yes"?>
<XmlData>
    <Element>
        <id>Test</id>
        <image>
            <Element>137</Element><Element>80</Element><Element>78</Element><Element>71</Element><Element>13</Element><Element>10</Element><Element>26</Element><Element>10</Element><Element>0</Element><Element>0</Element><Element>0</Element><Element>13</Element><Element>73</Element><Element>72</Element><Element>68</Element><Element>82</Element><Element>0</Element><Element>0</Element><Element>0</Element><Element>20</Element><Element>0</Element><Element>0</Element><Element>0</Element><Element>20</Element><Element>8</Element><Element>6</Element><Element>0</Element><Element>0</Element><Element>0</Element><Element>141</Element><Element>137</Element><Element>29</Element><Element>13</Element><Element>0</Element><Element>0</Element><Element>0</Element><Element>4</Element><Element>103</Element><Element>65</Element><Element>77</Element><Element>65</Element><Element>0</Element><Element>0</Element><Element>177</Element><Element>143</Element><Element>11</Element><Element>252</Element><Element>97</Element><Element>5</Element><Element>0</Element><Element>0</Element><Element>0</Element><Element>9</Element><Element>112</Element><Element>72</Element><Element>89</Element><Element>115</Element><Element>0</Element><Element>0</Element><Element>14</Element><Element>193</Element><Element>0</Element><Element>0</Element><Element>14</Element><Element>193</Element><Element>1</Element><Element>184</Element><Element>145</Element><Element>107</Element><Element>237</Element><Element>0</Element><Element>0</Element><Element>0</Element><Element>24</Element><Element>116</Element><Element>69</Element><Element>88</Element><Element>116</Element><Element>83</Element><Element>111</Element><Element>102</Element><Element>116</Element><Element>119</Element><Element>97</Element><Element>114</Element><Element>101</Element><Element>0</Element><Element>112</Element><Element>97</Element><Element>105</Element><Element>110</Element><Element>116</Element><Element>46</Element><Element>110</Element><Element>101</Element><Element>116</Element><Element>32</Element><Element>52</Element><Element>46</Element><Element>48</Element><Element>46</Element><Element>54</Element><Element>252</Element><Element>140</Element><Element>99</Element><Element>223</Element><Element>0</Element><Element>0</Element><Element>0</Element><Element>108</Element><Element>73</Element><Element>68</Element><Element>65</Element><Element>84</Element><Element>56</Element><Element>79</Element><Element>99</Element><Element>24</Element><Element>5</Element><Element>184</Element><Element>192</Element><Element>114</Element><Element>32</Element><Element>254</Element><Element>14</Element><Element>196</Element><Element>30</Element><Element>96</Element><Element>30</Element><Element>21</Element><Element>192</Element><Element>126</Element><Element>32</Element><Element>254</Element><Element>15</Element><Element>196</Element><Element>9</Element><Element>96</Element><Element>30</Element><Element>21</Element><Element>192</Element><Element>48</Element><Element>55</Element><Element>80</Element><Element>7</Element><Element>136</Element><Element>29</Element><Element>208</Element><Element>240</Element><Element>121</Element><Element>32</Element><Element>6</Element><Element>25</Element><Element>216</Element><Element>142</Element><Element>36</Element><Element>6</Element><Element>195</Element><Element>34</Element><Element>64</Element><Element>140</Element><Element>23</Element><Element>128</Element><Element>98</Element><Element>19</Element><Element>164</Element><Element>153</Element><Element>88</Element><Element>60</Element><Element>27</Element><Element>136</Element><Element>241</Element><Element>130</Element><Element>213</Element><Element>64</Element><Element>12</Element><Element>242</Element><Element>34</Element><Element>50</Element><Element>126</Element><Element>15</Element><Element>196</Element><Element>32</Element><Element>205</Element><Element>215</Element><Element>145</Element><Element>196</Element><Element>96</Element><Element>56</Element><Element>3</Element><Element>136</Element><Element>73</Element><Element>6</Element><Element>32</Element><Element>141</Element><Element>32</Element><Element>3</Element><Element>71</Element><Element>147</Element><Element>13</Element><Element>249</Element><Element>128</Element><Element>234</Element><Element>6</Element><Element>250</Element><Element>0</Element><Element>113</Element><Element>5</Element><Element>16</Element><Element>43</Element><Element>128</Element><Element>121</Element><Element>163</Element><Element>0</Element><Element>1</Element><Element>24</Element><Element>24</Element><Element>0</Element><Element>127</Element><Element>60</Element><Element>48</Element><Element>197</Element><Element>152</Element><Element>102</Element><Element>243</Element><Element>130</Element><Element>0</Element><Element>0</Element><Element>0</Element><Element>0</Element><Element>73</Element><Element>69</Element><Element>78</Element><Element>68</Element><Element>174</Element><Element>66</Element><Element>96</Element><Element>130</Element>
        </image>
    </Element>
</XmlData>'

在二进制中：

SELECT * FROM OPENROWSET(BULK 'C:\test.png', SINGLE_BLOB) AS q;
==========
BulkColumn
----------
0x89504E470D0A1A0A0000000D49484452000000140000001408060000008D891D0D0000000467414D410000B18F0BFC6105000000097048597300000EC100000EC101B8916BED0000001874455874536F667477617265007061696E742E6E657420342E302E36FC8C63DF0000006C49444154384F631805B8C07220FE0EC41E601E15C07E20FE0FC409601E15C030375007881DD0F079200619D88E2406C322408C17806213A499583C1B88F182D5400CF222327E0FC420CDD791C4603803884906208D200347930DF980EA06FA007105102B8079A300011818007F3C30C59866F3820000000049454E44AE426082

如何从 xml 中检索图像文件作为 varbinary？

不久前我也问过类似的问题，所以我尝试了以下查询，但结果二进制数据不正确：

SELECT r.c.value('id[1]', 'varchar(50)') AS id,
CONVERT(VARBINARY(MAX), (SELECT (t.u.value('.','tinyint')) FROM r.c.nodes('image/Element') AS t(u) FOR XML PATH(''))) AS image
FROM @xml.nodes('/XmlData/Element') AS r(c);
=============
id      image
-------------
Test    0x31003300370038003000370038003700310031003300310030003200360031003000300030003000310033003700330037003200360038003800320030003000300032003000300030003000320030003800360030003000300031003400310031003300370032003900310033003000300030003400310030003300360035003700370036003500300030003100370037003100340033003100310032003500320039003700350030003000300039003100310032003700320038003900310031003500300030003100340031003900330030003000310034003100390033003100310038003400310034003500310030003700320033003700300030003000320034003100310036003600390038003800310031003600380033003100310031003100300032003100310036003100310039003900370031003100340031003000310030003100310032003900370031003000350031003100300031003100360034003600310031003000310030003100310031003600330032003500320034003600340038003400360035003400320035003200310034003000390039003200320033003000300030003100300038003700330036003800360035003800340035003600370039003900390032003400350031003800340031003900320031003100340033003200320035003400310034003100390036003300300039003600330030003200310031003900320031003200360033003200320035003400310035003100390036003900390036003300300032003100310039003200340038003500350038003000370031003300360032003900320030003800320034003000310032003100330032003600320035003200310036003100340032003300360036003100390035003300340036003400310034003000320033003100320038003900380031003900310036003400310035003300380038003600300032003700310033003600320034003100310033003000320031003300360034003100320032003400320033003400350030003100320036003100350031003900360033003200320030003500320031003500310034003500310039003600390036003500360033003100330036003700330036003300320031003400310033003200330037003100310034003700310033003200340039003100320038003200330034003600320035003000300031003100330035003100360034003300310032003800310032003100310036003300300031003200340032003400300031003200370036003000340038003100390037003100350032003100300032003200340033003100330030003000300030003000370033003600390037003800360038003100370034003600360039003600310033003000

我想使用维护计划缩小多个数据库的事务日志文件。这些数据库是镜像的，因此无法在MIRROR数据库上执行收缩任务，但必须在两台服务器上都配置维护计划。我正在SQL Server 2012 Standard (SP1)我们的开发系统上使用，但代码也需要处理2008 R2。

我试着用下面的脚本，它可以处理一个数据库，称为DR内的，Execute T-SQL Statement Task：

IF EXISTS (SELECT NULL FROM sys.databases WHERE [name] = 'DR' AND [state_desc] = 'ONLINE')
BEGIN
    PRINT 'test';
    USE DR;
    DBCC SHRINKFILE (DR_log, 2048);
END
GO

这在 上运行良好PRINCIPLE，但是会导致在 上出现以下错误消息MIRROR：

Msg 954, Level 14, State 1, Line 4
The database "DR" cannot be opened. It is acting as a mirror database.

IF该USE命令似乎忽略了该块。本Print如果不执行USE …