首先，请阅读本： TPT纸 我不知道其他的选择可能存在什么安排节点来提高性能。任何东西，从后父母为了一个字节数组，像TPT的，到的东西更像是K-阶B树;我不知道有什么好的选择是已知的时刻？

First, read this: TPT paper I was wondering what other options might exist for arranging nodes to boost performance. Anything from post-parent order in a byte array, like TPT's, to something more like a k-order b-tree; I'm wondering what good options are known at the moment?

更多关于这个问题有一点： 我有在稀疏组发现的元素，给相邻的给定的指针一些概念的一个非常快速的方式。我想知道我怎么能最好地在存储帕特里夏·特里利用了这一点。

A bit more on the problem: I have an extremely fast way of finding elements within a sparse set, given some concept of adjacency to a given pointer. I was wondering how I could best take advantage of this in storing a patricia trie.

您可以对特里是否会随机访问，只读，写，很少，或只添加假设。请注意他们，如果你这样做，但我实际上使用了TPT和涨幅均pretty的显著所以我愿意考虑一定的制约。

You can make assumptions about whether the trie will be random-access, read only, write-seldom, or add-only. Please note them if you do, but I've actually used a TPT and the gains were pretty significant so I'm willing to consider certain constraints.

更新

我想在某种意义上，这是一个有点不清楚。我正在寻找在这里是安排在内存中的东西，优化一个性能度量或那样的方式。该TPT类，通过一些技巧，使用节点以优化磁盘读取和空间每个节点。我很好奇：

I guess in some senses this was a little unclear. What I'm looking for here is ways of arranging things in memory that optimize one performance metric or another. The TPTs, through some tricks, use node order to optimize disk reads and space-per-node. I'm curious about:

全部缺失，其结构从内存中完全删除。 插入，特别是在人口稠密的结构。 删除，再次，尤其是在人口密集的结构。

Total deletion, where the structure is removed from memory entirely. Inserts, particularly in densely populated structures. Deletes, again, particularly in densely populated structures.

推荐答案

一个DAWG或最小DFA（见this问题或纸张拿捏词库），因为六君煎尺寸较小甚至可能比TPT更好。

A DAWG or a minimal DFA (see this question or the paper "How to squeeze a lexicon") may be even better than a TPT because the totel size is smaller.