Compare and contrast Hash Table vs. STL map
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In a hash table, a value is stored by applying hash function on a key. Thus, values are not stored in a hash table in sorted order. Additionally, since hash tables use the key to find the index that will store the value, an insert/lookup can be done in amortised O(1) time (assuming only a few collisions in the hashtable). One must also handle potential collisions in a hashtable.
1) find min element
2) find max element
3) print elements in sorted order
4) find the exact element or, if the element is not found, find the next smallest number
1. A good hash function is required (e.g.: operation % prime number) to ensure that the hash values are uniformly distributed.
2. A collision resolving method is also needed: chaining (good for dense table entries), probing (good for sparse table entries), etc.
3. Implement methods to dynamically increase or decrease the hash table size on a given criterion. For example, when the [number of elements] by [table size] ratio is greater than the fixed threshold, increase the hash table size by creating a new hash table and transfer the entries from the old table to the new table by computing the index using new hash function.
You can use an STL map. Although this takes O(log n) time, since the number of inputs is small, this time is negligible.
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