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I won’t be doing a detailed evaluation right here, however I have included just a little statistics program that prints the average probe size of the hash desk created from the distinctive words in the input. First let’s consider what API we wish: we'd like a technique to create and destroy a hash table, get the worth for a given key, set a price for a given key, get the variety of items, and iterate over the items. When the hash table gets too full, we have to allocate a larger array and transfer the gadgets over.
It’s up to the caller to make sure that the worth pointer is legitimate for the lifetime of the hash table. I recently wrote a counter package deal in Go which implements an analogous kind of hash desk. Note that FNV is just not a randomized or cryptographic hash operate, so it’s doable for an attacker to create keys with numerous collisions and trigger lookups to gradual manner down - Python switched away from FNV for that reason. However, a fast, non-scientific efficiency comparability with Go’s map implementation exhibits that it compares pretty nicely - with half 1,000,000 English phrases, this C version is about 50% slower for lookups and 40% sooner for insertion.
If you don’t resize it early enough, collisions will turn into more and more widespread, and lookups and inserts will get slower and slower.