Żewġ ċwievet distinti jistgħu jhashu għall-istess bucket — kolliżjoni. It-tabelli tal-hash jibqgħu O(1) bla mistendu billi jsolvu l-kolliżjonijiet u jirrisizzaw qabel ma jidolqu l-buckets, ikkontrollat mill-load factor.
Separate chaining: each bucket holds a list
[3] -> ("cat",9) -> ("rat",2) # both hashed to 3
Open addressing: probe to the next free slot
hash=3 taken -> try 4 -> try 5 ... (linear probing)
load factor α = number_of_entries / number_of_buckets
α rises -> more collisions -> slower lookups
When α exceeds a threshold (e.g. 0.75):
-> allocate a bigger array (usually 2x)
-> REHASH every existing key into new buckets
# Conceptual resize
def _resize(self):
old = self.buckets
self.buckets = [None] * (len(old) * 2)
for entry in all_entries(old):
self._insert(entry.key, entry.value) # rehash into new array
| Operazzjoni | Medja | Agħar każ |
|---|---|---|
| lookup / insert / delete | O(1) | O(n) |
| resize wieħed | — | O(n) |
| insert (amortized, b'resizing) | O(1) | — |
Resize huwa O(n) iżda jiġri rarament, għalhekk jamortizza għal O(1) kull insert.
Dawk il-dettalji interni jispjegaw għaliex il-hash maps huma mabsutin fuq medja iżda jistgħu jaqfgħu għal O(n) — kruċjali għal code sensittiv għal performance u defenzi kontra hash-flooding. /tħatti l-load factor wkoll tisplika l-knobs ta' tuning memory/speed esposti mill-libreriji reali.