Hashing and Hash Tables Questions

How hash tables and hash-based structures work internally, and how to reason about their performance and correctness. Covers hash function properties (determinism, uniform distribution, speed, avalanche effect), cryptographic versus non-cryptographic hash choices, collision resolution (separate chaining, open addressing: linear probing, quadratic probing, double hashing, Robin Hood hashing, cuckoo hashing), load factor and amortized-cost resizing, and what makes an object hashable (the __hash__/__eq__ contract, immutability, custom composite keys). Covers hash-map-backed cache design (LRU and LFU eviction, TTL) and thread-safe concurrent hash maps (lock striping, CAS-based updates, safe concurrent resizing). Also covers hash-based structures beyond arrays and strings: consistent hashing for distributed routing and sharding, hash joins, hash-flooding and algorithmic-complexity security attacks and their mitigations, and probabilistic membership/cardinality structures such as Bloom filters, Cuckoo filters, Count-Min Sketch, and HyperLogLog. Excludes using a hash map purely as an optimization trick inside an array or string problem (two-sum, group anagrams, longest substring without repeating characters); that pattern belongs to Arrays, Strings, and Hashing. This topic is about the hash table itself: how it is built, how it fails under skewed or adversarial input, and how it scales.