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（六）Berkeley DB -- 补充一些东西
(2006-02-16 17:14:27)前面漏掉的一些东东。
腐烂数据的处理或者说数据库文件的瘦身：
当你从Btree或Hash数据库删除key/data对时，它并不把这个返回给文件系统，这使得数据重用成为可能。也就是说Btree和Hash数据库都是只增的。当你删除大量key/data对时，你可能想使数据库文件也缩减，你应该建立一个新的数据库文件，把记录从旧文件复制过去。应该是导入导出记录，而不是直接copy文件。
字节序的问题：
例如：数字254~257。在一个小数在前（little-endian）的系统上是：
254 fe 0 0 0
255ff 0 0 0
256 0 1 0 0
257 1 1 0 0
如果你把他们当成字符串处理那么他们的排序是糟糕的:
255
256
257
如果你把他们当成字符串处理那么他们的排序是糟糕的:
256
257
254
255
在一个大数在前（big-endian）系统上是:
257
254
255
在一个大数在前（big-endian）系统上是:
254 0 0 0 fe
2550 0 0 ff
2560 0 1 0
2570 0 1 1
and so, if you treat them as strings they sort nicely. Which means, if you use steadily increasing integers as keys on a big-endian system Berkeley DB behaves well and you get compact trees, but on a little-endian system Berkeley DB produces much less compact trees. To avoid this problem, you may want to convert the keys to flat text or big-endian representations, or provide your own Btree comparison function.
255
256
257
and so, if you treat them as strings they sort nicely. Which means, if you use steadily increasing integers as keys on a big-endian system Berkeley DB behaves well and you get compact trees, but on a little-endian system Berkeley DB produces much less compact trees. To avoid this problem, you may want to convert the keys to flat text or big-endian representations, or provide your own Btree comparison function.
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