What factors should I take into account when I need to choose between a hash table or a balanced binary tree in order to implement a set or an associative array?
The main advantage of the hash table over self-balancing binary search trees is the constant speed of access. It is partially efficient when the maximum number of entries is known so that the underlying bucket array can be allocated once and never be resized.
What is the advantage of a hash table over BST? Explanation: Hash table and BST both are examples of data structures. Hash table has an advantage that it has a better time complexity for performing insert, delete and search operations.
Hashes are typically faster, although binary searches have better worst-case characteristics.
Hash tables have better time complexity bounds on search, delete, and insert operations in comparison to self-balancing binary search trees.
This question cannot be answered, in general, I fear.
The issue is that there are many types of hash tables and balanced binary trees, and their performances vary widely.
So, the naive answer is: it depends on the functionality you need. Use a hash table if you do not need ordering and a balanced binary tree otherwise.
For a more elaborate answer, let's consider some alternatives.
Hash Table (see Wikipedia's entry for some basics)
Binary Tree
Let's not forget that O(1) is an asymptotic complexity. For few elements, the coefficient is usually more important (performance-wise). Which is especially true if your hash function is slow...
Finally, for sets, you may also wish to consider probabilistic data structures, like Bloom Filters.
Hash tables are generally better if there isn't any need to keep the data in any sort of sequence. Binary trees are better if the data must be kept sorted.
If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
Donate Us With