Advantages Of Binary Search Trees Over Hash Tables


Answer :

One advantage that no one else has pointed out is that binary search tree allows you to do range searches efficiently.

In order to illustrate my idea, I want to make an extreme case. Say you want to get all the elements whose keys are between 0 to 5000. And actually there is only one such element and 10000 other elements whose keys are not in the range. BST can do range searches quite efficiently since it does not search a subtree which is impossible to have the answer.

While, how can you do range searches in a hash table? You either need to iterate every bucket space, which is O(n), or you have to look for whether each of 1,2,3,4... up to 5000 exists. (what about the keys between 0 and 5000 are an infinite set? for example keys can be decimals)


Remember that Binary Search Trees (reference-based) are memory-efficient. They do not reserve more memory than they need to.

For instance, if a hash function has a range R(h) = 0...100, then you need to allocate an array of 100 (pointers-to) elements, even if you are just hashing 20 elements. If you were to use a binary search tree to store the same information, you would only allocate as much space as you needed, as well as some metadata about links.


One "advantage" of a binary tree is that it may be traversed to list off all elements in order. This is not impossible with a Hash table but is not a normal operation one design into a hashed structure.


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