Rename solana-runtime to sealevel (#6239)

automerge

runtime/src/bloom.rs

@@ -1,160 +0,0 @@
-//! Simple Bloom Filter
-use bv::BitVec;
-use fnv::FnvHasher;
-use rand::{self, Rng};
-use serde::{Deserialize, Serialize};
-use std::cmp;
-use std::hash::Hasher;
-use std::marker::PhantomData;
-
-/// Generate a stable hash of `self` for each `hash_index`
-/// Best effort can be made for uniqueness of each hash.
-pub trait BloomHashIndex {
-    fn hash_at_index(&self, hash_index: u64) -> u64;
-}
-
-#[derive(Serialize, Deserialize, Default, Clone, Debug, PartialEq)]
-pub struct Bloom<T: BloomHashIndex> {
-    pub keys: Vec<u64>,
-    pub bits: BitVec<u64>,
-    num_bits_set: u64,
-    _phantom: PhantomData<T>,
-}
-
-impl<T: BloomHashIndex> Bloom<T> {
-    pub fn new(num_bits: usize, keys: Vec<u64>) -> Self {
-        let bits = BitVec::new_fill(false, num_bits as u64);
-        Bloom {
-            keys,
-            bits,
-            num_bits_set: 0,
-            _phantom: PhantomData::default(),
-        }
-    }
-    /// create filter optimal for num size given the `FALSE_RATE`
-    /// the keys are randomized for picking data out of a collision resistant hash of size
-    /// `keysize` bytes
-    /// https://hur.st/bloomfilter/
-    pub fn random(num_items: usize, false_rate: f64, max_bits: usize) -> Self {
-        let m = Self::num_bits(num_items as f64, false_rate);
-        let num_bits = cmp::max(1, cmp::min(m as usize, max_bits));
-        let num_keys = Self::num_keys(num_bits as f64, num_items as f64) as usize;
-        let keys: Vec<u64> = (0..num_keys).map(|_| rand::thread_rng().gen()).collect();
-        Self::new(num_bits, keys)
-    }
-    pub fn num_bits(num_items: f64, false_rate: f64) -> f64 {
-        let n = num_items;
-        let p = false_rate;
-        ((n * p.ln()) / (1f64 / 2f64.powf(2f64.ln())).ln()).ceil()
-    }
-    pub fn num_keys(num_bits: f64, num_items: f64) -> f64 {
-        let n = num_items;
-        let m = num_bits;
-        1f64.max(((m / n) * 2f64.ln()).round())
-    }
-    fn pos(&self, key: &T, k: u64) -> u64 {
-        key.hash_at_index(k) % self.bits.len()
-    }
-    pub fn clear(&mut self) {
-        self.bits = BitVec::new_fill(false, self.bits.len());
-        self.num_bits_set = 0;
-    }
-    pub fn add(&mut self, key: &T) {
-        for k in &self.keys {
-            let pos = self.pos(key, *k);
-            if !self.bits.get(pos) {
-                self.num_bits_set += 1;
-                self.bits.set(pos, true);
-            }
-        }
-    }
-    pub fn contains(&self, key: &T) -> bool {
-        for k in &self.keys {
-            let pos = self.pos(key, *k);
-            if !self.bits.get(pos) {
-                return false;
-            }
-        }
-        true
-    }
-}
-
-fn slice_hash(slice: &[u8], hash_index: u64) -> u64 {
-    let mut hasher = FnvHasher::with_key(hash_index);
-    hasher.write(slice);
-    hasher.finish()
-}
-
-impl<T: AsRef<[u8]>> BloomHashIndex for T {
-    fn hash_at_index(&self, hash_index: u64) -> u64 {
-        slice_hash(self.as_ref(), hash_index)
-    }
-}
-
-#[cfg(test)]
-mod test {
-    use super::*;
-    use solana_sdk::hash::{hash, Hash};
-
-    #[test]
-    fn test_bloom_filter() {
-        //empty
-        let bloom: Bloom<Hash> = Bloom::random(0, 0.1, 100);
-        assert_eq!(bloom.keys.len(), 0);
-        assert_eq!(bloom.bits.len(), 1);
-
-        //normal
-        let bloom: Bloom<Hash> = Bloom::random(10, 0.1, 100);
-        assert_eq!(bloom.keys.len(), 3);
-        assert_eq!(bloom.bits.len(), 48);
-
-        //saturated
-        let bloom: Bloom<Hash> = Bloom::random(100, 0.1, 100);
-        assert_eq!(bloom.keys.len(), 1);
-        assert_eq!(bloom.bits.len(), 100);
-    }
-    #[test]
-    fn test_add_contains() {
-        let mut bloom: Bloom<Hash> = Bloom::random(100, 0.1, 100);
-        //known keys to avoid false positives in the test
-        bloom.keys = vec![0, 1, 2, 3];
-
-        let key = hash(b"hello");
-        assert!(!bloom.contains(&key));
-        bloom.add(&key);
-        assert!(bloom.contains(&key));
-
-        let key = hash(b"world");
-        assert!(!bloom.contains(&key));
-        bloom.add(&key);
-        assert!(bloom.contains(&key));
-    }
-    #[test]
-    fn test_random() {
-        let mut b1: Bloom<Hash> = Bloom::random(10, 0.1, 100);
-        let mut b2: Bloom<Hash> = Bloom::random(10, 0.1, 100);
-        b1.keys.sort();
-        b2.keys.sort();
-        assert_ne!(b1.keys, b2.keys);
-    }
-    // Bloom filter math in python
-    // n number of items
-    // p false rate
-    // m number of bits
-    // k number of keys
-    //
-    // n = ceil(m / (-k / log(1 - exp(log(p) / k))))
-    // p = pow(1 - exp(-k / (m / n)), k)
-    // m = ceil((n * log(p)) / log(1 / pow(2, log(2))));
-    // k = round((m / n) * log(2));
-    #[test]
-    fn test_filter_math() {
-        assert_eq!(Bloom::<Hash>::num_bits(100f64, 0.1f64) as u64, 480u64);
-        assert_eq!(Bloom::<Hash>::num_bits(100f64, 0.01f64) as u64, 959u64);
-        assert_eq!(Bloom::<Hash>::num_keys(1000f64, 50f64) as u64, 14u64);
-        assert_eq!(Bloom::<Hash>::num_keys(2000f64, 50f64) as u64, 28u64);
-        assert_eq!(Bloom::<Hash>::num_keys(2000f64, 25f64) as u64, 55u64);
-        //ensure min keys is 1
-        assert_eq!(Bloom::<Hash>::num_keys(20f64, 1000f64) as u64, 1u64);
-    }
-}