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lib.rs
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// (C)opyleft 2013-2021 Frank Denis
//! HyperLogLog implementation for Rust
#![crate_name = "hyperloglog"]
#![warn(non_camel_case_types, non_upper_case_globals, unused_qualifications)]
#![allow(non_snake_case)]
#![allow(clippy::unreadable_literal)]
use std::cmp::Ordering::{Equal, Greater, Less};
use std::hash::{Hash, Hasher};
use std::iter::repeat;
use siphasher::sip::SipHasher13;
/// A HyperLogLog counter
#[derive(Clone, Debug)]
#[cfg_attr(feature = "serde", derive(serde::Serialize, serde::Deserialize))]
pub struct HyperLogLog {
alpha: f64,
p: u8,
m: usize,
M: Vec<u8>,
sip: SipHasher13,
}
impl HyperLogLog {
/// Create a new HyperLogLog counter with the given error rate and seed.
pub fn new_deterministic(error_rate: f64, seed: u128) -> Self {
let key0 = (seed >> 64) as u64;
let key1 = seed as u64;
assert!(error_rate > 0.0 && error_rate < 1.0);
let sr = 1.04 / error_rate;
let p = f64::ln(sr * sr).ceil() as u8;
assert!(p <= 64);
let alpha = Self::get_alpha(p);
let m = 1usize << p;
HyperLogLog {
alpha,
p,
m,
M: repeat(0u8).take(m).collect(),
sip: SipHasher13::new_with_keys(key0, key1),
}
}
/// Create a new HyperLogLog counter with the given error rate and a random
/// seed.
pub fn new(error_rate: f64) -> Self {
let seed: u128 = rand::random();
Self::new_deterministic(error_rate, seed)
}
/// Create a new HyperLogLog counter with the same parameters as an
/// existing one.
pub fn new_from_template(hll: &HyperLogLog) -> Self {
HyperLogLog {
alpha: hll.alpha,
p: hll.p,
m: hll.m,
M: repeat(0u8).take(hll.m).collect(),
sip: hll.sip,
}
}
/// Insert a new value into the HyperLogLog counter.
pub fn insert<V: Hash>(&mut self, value: &V) {
let sip = &mut self.sip.clone();
value.hash(sip);
let x = sip.finish();
self.insert_by_hash_value(x);
}
/// Insert a new u64 value into the HyperLogLog counter.
pub fn insert_by_hash_value(&mut self, x: u64) {
let j = x as usize & (self.m - 1);
let w = x >> self.p;
let rho = Self::get_rho(w, 64 - self.p);
let mjr = &mut self.M[j];
if rho > *mjr {
*mjr = rho;
}
}
/// Return the cardinality of the HyperLogLog counter.
pub fn len(&self) -> f64 {
let V = Self::vec_count_zero(&self.M);
if V > 0 {
let H = self.m as f64 * (self.m as f64 / V as f64).ln();
if H <= Self::get_treshold(self.p) {
H
} else {
self.ep()
}
} else {
self.ep()
}
}
/// Return `true` if the HyperLogLog counter is empty.
pub fn is_empty(&self) -> bool {
self.len() == 0.0
}
/// Merge another HyperLogLog counter into the current one.
pub fn merge(&mut self, src: &HyperLogLog) {
assert!(src.p == self.p);
assert!(src.m == self.m);
let sip1 = &mut src.sip.clone();
let sip2 = &mut self.sip.clone();
42.hash(sip1);
42.hash(sip2);
assert!(sip1.finish() == sip2.finish());
for i in 0..self.m {
let (src_mir, mir) = (src.M[i], &mut self.M[i]);
if src_mir > *mir {
*mir = src_mir;
}
}
}
/// Wipe the HyperLogLog counter.
pub fn clear(&mut self) {
self.M.iter_mut().all(|x| {
*x = 0;
true
});
}
fn get_treshold(p: u8) -> f64 {
TRESHOLD_DATA[p as usize]
}
fn get_alpha(p: u8) -> f64 {
assert!((4..=16).contains(&p));
match p {
4 => 0.673,
5 => 0.697,
6 => 0.709,
_ => 0.7213 / (1.0 + 1.079 / (1usize << (p as usize)) as f64),
}
}
fn bit_length(x: u64) -> u8 {
let mut bits: u8 = 0;
let mut xm = x;
while xm != 0 {
bits += 1;
xm >>= 1;
}
bits
}
fn get_rho(w: u64, max_width: u8) -> u8 {
let rho = max_width - Self::bit_length(w) + 1;
assert!(rho > 0);
rho
}
fn vec_count_zero(v: &[u8]) -> usize {
bytecount::count(v, 0)
}
fn estimate_bias(E: f64, p: u8) -> f64 {
let bias_vector = BIAS_DATA[(p - 4) as usize];
let nearest_neighbors = Self::get_nearest_neighbors(E, RAW_ESTIMATE_DATA[(p - 4) as usize]);
let sum = nearest_neighbors
.iter()
.fold(0.0, |acc, &neighbor| acc + bias_vector[neighbor]);
sum / nearest_neighbors.len() as f64
}
fn get_nearest_neighbors(E: f64, estimate_vector: &[f64]) -> Vec<usize> {
let ev_len = estimate_vector.len();
let mut r: Vec<(f64, usize)> = repeat((0.0f64, 0usize)).take(ev_len).collect();
for i in 0..ev_len {
let dr = E - estimate_vector[i];
r[i] = (dr * dr, i);
}
r.sort_by(|a, b| {
if a < b {
Less
} else if a > b {
Greater
} else {
Equal
}
});
r.truncate(6);
r.iter()
.map(|&ez| {
let (_, b) = ez;
b
})
.collect()
}
fn ep(&self) -> f64 {
let sum = self
.M
.iter()
.fold(0.0, |acc, &x| acc + 2.0f64.powi(-(x as i32)));
let E = self.alpha * (self.m * self.m) as f64 / sum;
if E <= (5 * self.m) as f64 {
E - Self::estimate_bias(E, self.p)
} else {
E
}
}
}
#[cfg(feature = "serde")]
#[test]
fn hyperloglog_serialize() {
let hll = HyperLogLog::new(0.00408);
let bytes = bincode::serialize(&hll).unwrap();
let _: HyperLogLog = bincode::deserialize(&bytes).unwrap();
}
#[test]
fn hyperloglog_test_simple() {
let mut hll = HyperLogLog::new(0.00408);
let keys = ["test1", "test2", "test3", "test2", "test2", "test2"];
for k in &keys {
hll.insert(k);
}
assert!((hll.len().round() - 3.0).abs() < std::f64::EPSILON);
assert!(!hll.is_empty());
hll.clear();
assert!(hll.is_empty());
assert!(hll.len() == 0.0);
}
#[test]
fn hyperloglog_test_merge() {
let mut hll = HyperLogLog::new(0.00408);
let keys = ["test1", "test2", "test3", "test2", "test2", "test2"];
for k in &keys {
hll.insert(k);
}
assert!((hll.len().round() - 3.0).abs() < std::f64::EPSILON);
let mut hll2 = HyperLogLog::new_from_template(&hll);
let keys2 = ["test3", "test4", "test4", "test4", "test4", "test1"];
for k in &keys2 {
hll2.insert(k);
}
assert!((hll2.len().round() - 3.0).abs() < std::f64::EPSILON);
hll.merge(&hll2);
assert!((hll.len().round() - 4.0).abs() < std::f64::EPSILON);
}
static TRESHOLD_DATA: [f64; 15] = [
10.0, 20.0, 40.0, 80.0, 220.0, 400.0, 900.0, 1800.0, 3100.0, 6500.0, 11500.0, 20000.0, 50000.0,
120000.0, 350000.0,
];
static RAW_ESTIMATE_DATA: &[&[f64]] = &[
&[
11.0, 11.717, 12.207, 12.7896, 13.2882, 13.8204, 14.3772, 14.9342, 15.5202, 16.161,
16.7722, 17.4636, 18.0396, 18.6766, 19.3566, 20.0454, 20.7936, 21.4856, 22.2666, 22.9946,
23.766, 24.4692, 25.3638, 26.0764, 26.7864, 27.7602, 28.4814, 29.433, 30.2926, 31.0664,
31.9996, 32.7956, 33.5366, 34.5894, 35.5738, 36.2698, 37.3682, 38.0544, 39.2342, 40.0108,
40.7966, 41.9298, 42.8704, 43.6358, 44.5194, 45.773, 46.6772, 47.6174, 48.4888, 49.3304,
50.2506, 51.4996, 52.3824, 53.3078, 54.3984, 55.5838, 56.6618, 57.2174, 58.3514, 59.0802,
60.1482, 61.0376, 62.3598, 62.8078, 63.9744, 64.914, 65.781, 67.1806, 68.0594, 68.8446,
69.7928, 70.8248, 71.8324, 72.8598, 73.6246, 74.7014, 75.393, 76.6708, 77.2394,
],
&[
23.0, 23.1194, 23.8208, 24.2318, 24.77, 25.2436, 25.7774, 26.2848, 26.8224, 27.3742,
27.9336, 28.503, 29.0494, 29.6292, 30.2124, 30.798, 31.367, 31.9728, 32.5944, 33.217,
33.8438, 34.3696, 35.0956, 35.7044, 36.324, 37.0668, 37.6698, 38.3644, 39.049, 39.6918,
40.4146, 41.082, 41.687, 42.5398, 43.2462, 43.857, 44.6606, 45.4168, 46.1248, 46.9222,
47.6804, 48.447, 49.3454, 49.9594, 50.7636, 51.5776, 52.331, 53.19, 53.9676, 54.7564,
55.5314, 56.4442, 57.3708, 57.9774, 58.9624, 59.8796, 60.755, 61.472, 62.2076, 63.1024,
63.8908, 64.7338, 65.7728, 66.629, 67.413, 68.3266, 69.1524, 70.2642, 71.1806, 72.0566,
72.9192, 73.7598, 74.3516, 75.5802, 76.4386, 77.4916, 78.1524, 79.1892, 79.8414, 80.8798,
81.8376, 82.4698, 83.7656, 84.331, 85.5914, 86.6012, 87.7016, 88.5582, 89.3394, 90.3544,
91.4912, 92.308, 93.3552, 93.9746, 95.2052, 95.727, 97.1322, 98.3944, 98.7588, 100.242,
101.1914, 102.2538, 102.8776, 103.6292, 105.1932, 105.9152, 107.0868, 107.6728, 108.7144,
110.3114, 110.8716, 111.245, 112.7908, 113.7064, 114.636, 115.7464, 116.1788, 117.7464,
118.4896, 119.6166, 120.5082, 121.7798, 122.9028, 123.4426, 124.8854, 125.705, 126.4652,
128.3464, 128.3462, 130.0398, 131.0342, 131.0042, 132.4766, 133.511, 134.7252, 135.425,
136.5172, 138.0572, 138.6694, 139.3712, 140.8598, 141.4594, 142.554, 143.4006, 144.7374,
146.1634, 146.8994, 147.605, 147.9304, 149.1636, 150.2468, 151.5876, 152.2096, 153.7032,
154.7146, 155.807, 156.9228, 157.0372, 158.5852,
],
&[
46.0, 46.1902, 47.271, 47.8358, 48.8142, 49.2854, 50.317, 51.354, 51.8924, 52.9436,
53.4596, 54.5262, 55.6248, 56.1574, 57.2822, 57.837, 58.9636, 60.074, 60.7042, 61.7976,
62.4772, 63.6564, 64.7942, 65.5004, 66.686, 67.291, 68.5672, 69.8556, 70.4982, 71.8204,
72.4252, 73.7744, 75.0786, 75.8344, 77.0294, 77.8098, 79.0794, 80.5732, 81.1878, 82.5648,
83.2902, 84.6784, 85.3352, 86.8946, 88.3712, 89.0852, 90.499, 91.2686, 92.6844, 94.2234,
94.9732, 96.3356, 97.2286, 98.7262, 100.3284, 101.1048, 102.5962, 103.3562, 105.1272,
106.4184, 107.4974, 109.0822, 109.856, 111.48, 113.2834, 114.0208, 115.637, 116.5174,
118.0576, 119.7476, 120.427, 122.1326, 123.2372, 125.2788, 126.6776, 127.7926, 129.1952,
129.9564, 131.6454, 133.87, 134.5428, 136.2, 137.0294, 138.6278, 139.6782, 141.792,
143.3516, 144.2832, 146.0394, 147.0748, 148.4912, 150.849, 151.696, 153.5404, 154.073,
156.3714, 157.7216, 158.7328, 160.4208, 161.4184, 163.9424, 165.2772, 166.411, 168.1308,
168.769, 170.9258, 172.6828, 173.7502, 175.706, 176.3886, 179.0186, 180.4518, 181.927,
183.4172, 184.4114, 186.033, 188.5124, 189.5564, 191.6008, 192.4172, 193.8044, 194.997,
197.4548, 198.8948, 200.2346, 202.3086, 203.1548, 204.8842, 206.6508, 206.6772, 209.7254,
210.4752, 212.7228, 214.6614, 215.1676, 217.793, 218.0006, 219.9052, 221.66, 223.5588,
225.1636, 225.6882, 227.7126, 229.4502, 231.1978, 232.9756, 233.1654, 236.727, 238.1974,
237.7474, 241.1346, 242.3048, 244.1948, 245.3134, 246.879, 249.1204, 249.853, 252.6792,
253.857, 254.4486, 257.2362, 257.9534, 260.0286, 260.5632, 262.663, 264.723, 265.7566,
267.2566, 267.1624, 270.62, 272.8216, 273.2166, 275.2056, 276.2202, 278.3726, 280.3344,
281.9284, 283.9728, 284.1924, 286.4872, 287.587, 289.807, 291.1206, 292.769, 294.8708,
296.665, 297.1182, 299.4012, 300.6352, 302.1354, 304.1756, 306.1606, 307.3462, 308.5214,
309.4134, 310.8352, 313.9684, 315.837, 316.7796, 318.9858,
],
&[
92.0, 93.4934, 94.9758, 96.4574, 97.9718, 99.4954, 101.5302, 103.0756, 104.6374, 106.1782,
107.7888, 109.9522, 111.592, 113.2532, 114.9086, 116.5938, 118.9474, 120.6796, 122.4394,
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