Can anyone provide real examples of when is the best way to store your data is treap?
I want to understand in which situations treap will be better than heaps and tree structures.
If it's possible, please provide some examples from real situations.
I've tried to search cases of using treaps here and by googling, but did not find anything.
Thank you.
A treap stores items in sorted order and offers efficient lookup, addition and removal of items. If you could use only one data structure, which one would you choose? A hash table? While it supports the basic lookup, addition and removal operations, it doesn't keep the elements sorted.
Like Red-Black and AVL Trees, Treap is a Balanced Binary Search Tree, but not guaranteed to have height as O(Log n). The idea is to use Randomization and Binary Heap property to maintain balance with high probability.
Splay trees and treaps are self-balancing but not height-balanced, as their height is not guaranteed to be logarithmic in the number of items.
Noun. treap (plural treaps) (computer science) A type of randomized binary search tree where nodes are labelled with randomly chosen priority values and which is simultaneously a heap on those priorities.
If hash values are used as priorities, treaps provide unique representation of the content.
Consider an order set of items implemented as an AVL-tree or rb-tree. Inserting items in different orders will typically end up in trees with different shapes (although all of them are balanced). For a given content a treap will always be of the same shape regardless of history.
I have seen two reasons for why unique representation could be useful:
I can not provide you any real-world examples. But I do use treaps to solve some problems in programming contests:
These are not actually real problems, but they make sense.
You can use it as a tree-based map implementation. Depending on the application, it could be faster. A couple of years ago I implemented a Treap and a Skip list myself (in Java) just for fun and did some basic benchmarking comparing them to TreeMap, and the Treap was the fastest. You can see the results here.
One of its greatest advantages is that it's very easy to implement, compared to Red-Black trees, for example. However, as far as I remember, it doesn't have a guaranteed cost in its operations (search is O(log n) with high
probability), in comparison to Red-Black trees, which means that you wouldn't be able to use it in safety-critical applications where a specific time bound is a requirement.
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