PtrHash: Minimal Perfect Hashing at RAM Throughput

Given a set $K$ of $n$ keys, a minimal perfect hash function (MPHF) is a collision-free bijective map $\mathsf{H_{mphf}}$ from $K$ to $\{0, \dots, n-1\}$. This work presents a (minimal) perfect hash function that first prioritizes query throughput, while also allowing efficient construction for $10^9$ or more elements using 2.4 bits of memory per key. Both PTHash and PHOBIC first map all $n$ keys to $n/\lambda < n$ buckets. Then, each bucket stores a pilot that controls the final hash value of the keys mapping to it. PtrHash builds on this by using 1) fixed-width (uncompressed) 8-bit pilots, 2) a construction algorithm similar to cuckoo-hashing to find suitable pilot values. Further, it 3) uses the same number of buckets and slots for each part, with 4) a single remap table to map intermediate positions $\geq n$ to $<n$, 5) encoded using per-cacheline Elias-Fano coding. Lastly, 6) PtrHash support streaming queries, where we use prefetching to answer a stream of multiple queries more efficiently than one-by-one processing. With default parameters, PtrHash takes 2.0 bits per key. On 300 million string keys, PtrHash is as fast or faster to build than other MPHFs, and at least $2.1\times$ faster to query. When streaming multiple queries, this improves to $3.3\times$ speedup over the fastest alternative, while also being significantly faster to construct. When using $10^9$ integer keys instead, query times are as low as 12 ns/key when iterating in a for loop, or even down to 8 ns/key when using the streaming approach, just short of the 7.4 ns inverse throughput of random memory accesses.