feat: add perfect hashing function to nippy-jar

[joshieDo]

Adds two implementations of perfect hashing functions.

In computer science, a perfect hash function h for a set S is a hash function that maps distinct elements in S to a set of m integers, with no collisions. In mathematical terms, it is an injective function.

This is particularly useful for when querying transactions or blocks using their hashes. Instead of storing them, and iterating over each value when querying for a specific hash, we can use this function to give us an integer. Then, use that to find the offset of the provided value in the file

Example: If giving the transaction hash 0xdeadbeef to the function would provide us the integer 5, we could use this information to look-up in a separate list, the offset where the associated transaction is located.

[codecov]

Codecov Report

Merging #4601 (45e3b05) into joshie/nippy-jar (d8cfa06) will increase coverage by 0.12%.
The diff coverage is 77.31%.

Files Changed	Coverage Δ
crates/storage/nippy-jar/src/phf/fmph.rs	59.32% <59.32%> (ø)
crates/storage/nippy-jar/src/phf/go_fmph.rs	60.00% <60.00%> (ø)
crates/storage/nippy-jar/src/phf/mod.rs	93.33% <93.33%> (ø)
crates/storage/nippy-jar/src/compression/mod.rs	38.23% <100.00%> (+1.87%)	⬆️
crates/storage/nippy-jar/src/filter/cuckoo.rs	85.36% <100.00%> (ø)
crates/storage/nippy-jar/src/filter/mod.rs	83.33% <100.00%> (+1.51%)	⬆️
crates/storage/nippy-jar/src/lib.rs	92.78% <100.00%> (+1.91%)	⬆️

... and 18 files with indirect coverage changes

Flag	Coverage Δ
integration-tests	16.50% <0.00%> (-0.04%)	⬇️
unit-tests	64.20% <77.31%> (+0.13%)	⬆️

Flags with carried forward coverage won't be shown. Click here to find out more.

Components	Coverage Δ
reth binary	30.85% <ø> (ø)
blockchain tree	83.58% <ø> (+0.74%)	⬆️
pipeline	90.53% <ø> (ø)
storage (db)	75.63% <77.31%> (+0.05%)	⬆️
trie	94.88% <ø> (+0.03%)	⬆️
txpool	49.74% <ø> (+0.47%)	⬆️
networking	77.32% <ø> (+0.10%)	⬆️
rpc	57.36% <ø> (+<0.01%)	⬆️
consensus	63.40% <ø> (+0.43%)	⬆️
revm	31.56% <ø> (ø)
payload builder	6.12% <ø> (ø)
primitives	86.52% <ø> (+0.06%)	⬆️