We introduced and discussed an implementation in below post.
The implementation used in above post uses an array of alphabet size with every node. It can be made memory efficient. One way to implementing Trie is linked set of nodes, where each node contains an array of child pointers, one for each symbol in the alphabet. This is not efficient in terms of time as we can’t quickly find a particular child.
The efficient way is an implementation where we use hash map to store children of a node. Now we allocate memory only for alphabets in use, and don’t waste space storing null pointers.
1 1 0 1 1
Space used here with every node here is proportional to number of children which is much better than proportional to alphabet size, especially if alphabet is large.
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- Pattern Searching using a Trie of all Suffixes
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- Longest Common Prefix using Trie
- Count of distinct substrings of a string using Suffix Trie
- Boggle | Set 2 (Using Trie)
- Sorting array of strings (or words) using Trie
- Sorting array of strings (or words) using Trie | Set-2 (Handling Duplicates)
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- Longest prefix matching - A Trie based solution in Java
- Overview of Data Structures | Set 3 (Graph, Trie, Segment Tree and Suffix Tree)
- Trie | (Display Content)