The load factor α is the ratio of stored items to total buckets, how full the table is. It directly controls performance: at low α collisions are rare and operations are near O(1), but as α rises toward 1, collisions and probe-sequence lengths grow, and for open addressing performance degrades sharply past roughly 0.7-0.8 (probe chains get long, every operation scans more slots). A general-purpose hash table watches α and resizes, allocates a larger table and rehashes all keys, when it crosses a threshold, amortizing that cost across many inserts. On a fixed embedded table you can't resize cheaply, so you size generously up front to keep α low for your worst-case occupancy. Keeping α in check is the single biggest lever on whether a hash table stays O(1)-ish or creeps toward O(n).
Data Structures & Algorithms · Interview question
What is the load factor and why does it matter?
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From the lesson
Hash Tables
O(1)-average keyed lookup by mapping keys to array slots: collisions, load factor, and why open addressing into a fixed array beats chaining when you have no heap.