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// Licensed to the Apache Software Foundation (ASF) under one
// or more contributor license agreements. See the NOTICE file
// distributed with this work for additional information
// regarding copyright ownership. The ASF licenses this file
// to you under the Apache License, Version 2.0 (the
// "License"); you may not use this file except in compliance
// with the License. You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing,
// software distributed under the License is distributed on an
// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
// KIND, either express or implied. See the License for the
// specific language governing permissions and limitations
// under the License.
//! # HyperLogLog
//!
//! `hyperloglog` is a module that contains a modified version
//! of [redis's implementation](https://github.com/redis/redis/blob/4930d19e70c391750479951022e207e19111eb55/src/hyperloglog.c)
//! with some modification based on strong assumption of usage
//! within datafusion, so that function can
//! be efficiently implemented.
//!
//! Specifically, like Redis's version, this HLL structure uses
//! 2**14 = 16384 registers, which means the standard error is
//! 1.04/(16384**0.5) = 0.8125%. Unlike Redis, the register takes
//! up full [`u8`] size instead of a raw int* and thus saves some
//! tricky bit shifting techniques used in the original version.
//! This results in a memory usage increase from 12Kib to 16Kib.
//! Also only the dense version is adopted, so there's no automatic
//! conversion, largely to simplify the code.
//!
//! This module also borrows some code structure from [pdatastructs.rs](https://github.com/crepererum/pdatastructs.rs/blob/3997ed50f6b6871c9e53c4c5e0f48f431405fc63/src/hyperloglog.rs).
use ahash::RandomState;
use std::hash::Hash;
use std::marker::PhantomData;
/// The greater is P, the smaller the error.
const HLL_P: usize = 14_usize;
/// The number of bits of the hash value used determining the number of leading zeros
const HLL_Q: usize = 64_usize - HLL_P;
const NUM_REGISTERS: usize = 1_usize << HLL_P;
/// Mask to obtain index into the registers
const HLL_P_MASK: u64 = (NUM_REGISTERS as u64) - 1;
#[derive(Clone, Debug)]
pub(crate) struct HyperLogLog<T>
where
T: Hash + ?Sized,
{
registers: [u8; NUM_REGISTERS],
phantom: PhantomData<T>,
}
/// Fixed seed for the hashing so that values are consistent across runs
///
/// Note that when we later move on to have serialized HLL register binaries
/// shared across cluster, this SEED will have to be consistent across all
/// parties otherwise we might have corruption. So ideally for later this seed
/// shall be part of the serialized form (or stay unchanged across versions).
const SEED: RandomState = RandomState::with_seeds(
0x885f6cab121d01a3_u64,
0x71e4379f2976ad8f_u64,
0xbf30173dd28a8816_u64,
0x0eaea5d736d733a4_u64,
);
impl<T> Default for HyperLogLog<T>
where
T: Hash + ?Sized,
{
fn default() -> Self {
Self::new()
}
}
impl<T> HyperLogLog<T>
where
T: Hash + ?Sized,
{
/// Creates a new, empty HyperLogLog.
pub fn new() -> Self {
let registers = [0; NUM_REGISTERS];
Self::new_with_registers(registers)
}
/// Creates a HyperLogLog from already populated registers
/// note that this method should not be invoked in untrusted environment
/// because the internal structure of registers are not examined.
pub(crate) fn new_with_registers(registers: [u8; NUM_REGISTERS]) -> Self {
Self {
registers,
phantom: PhantomData,
}
}
/// choice of hash function: ahash is already an dependency
/// and it fits the requirements of being a 64bit hash with
/// reasonable performance.
#[inline]
fn hash_value(&self, obj: &T) -> u64 {
SEED.hash_one(obj)
}
/// Adds an element to the HyperLogLog.
pub fn add(&mut self, obj: &T) {
let hash = self.hash_value(obj);
let index = (hash & HLL_P_MASK) as usize;
let p = ((hash >> HLL_P) | (1_u64 << HLL_Q)).trailing_zeros() + 1;
self.registers[index] = self.registers[index].max(p as u8);
}
/// Get the register histogram (each value in register index into
/// the histogram; u32 is enough because we only have 2**14=16384 registers
#[inline]
fn get_histogram(&self) -> [u32; HLL_Q + 2] {
let mut histogram = [0; HLL_Q + 2];
// hopefully this can be unrolled
for r in self.registers {
histogram[r as usize] += 1;
}
histogram
}
/// Merge the other [`HyperLogLog`] into this one
pub fn merge(&mut self, other: &HyperLogLog<T>) {
assert!(
self.registers.len() == other.registers.len(),
"unexpected got unequal register size, expect {}, got {}",
self.registers.len(),
other.registers.len()
);
for i in 0..self.registers.len() {
self.registers[i] = self.registers[i].max(other.registers[i]);
}
}
/// Guess the number of unique elements seen by the HyperLogLog.
pub fn count(&self) -> usize {
let histogram = self.get_histogram();
let m = NUM_REGISTERS as f64;
let mut z = m * hll_tau((m - histogram[HLL_Q + 1] as f64) / m);
for i in histogram[1..=HLL_Q].iter().rev() {
z += *i as f64;
z *= 0.5;
}
z += m * hll_sigma(histogram[0] as f64 / m);
(0.5 / 2_f64.ln() * m * m / z).round() as usize
}
}
/// Helper function sigma as defined in
/// "New cardinality estimation algorithms for HyperLogLog sketches"
/// Otmar Ertl, arXiv:1702.01284
#[inline]
fn hll_sigma(x: f64) -> f64 {
if x == 1. {
f64::INFINITY
} else {
let mut y = 1.0;
let mut z = x;
let mut x = x;
loop {
x *= x;
let z_prime = z;
z += x * y;
y += y;
if z_prime == z {
break;
}
}
z
}
}
/// Helper function tau as defined in
/// "New cardinality estimation algorithms for HyperLogLog sketches"
/// Otmar Ertl, arXiv:1702.01284
#[inline]
fn hll_tau(x: f64) -> f64 {
if x == 0.0 || x == 1.0 {
0.0
} else {
let mut y = 1.0;
let mut z = 1.0 - x;
let mut x = x;
loop {
x = x.sqrt();
let z_prime = z;
y *= 0.5;
z -= (1.0 - x).powi(2) * y;
if z_prime == z {
break;
}
}
z / 3.0
}
}
impl<T> AsRef<[u8]> for HyperLogLog<T>
where
T: Hash + ?Sized,
{
fn as_ref(&self) -> &[u8] {
&self.registers
}
}
impl<T> Extend<T> for HyperLogLog<T>
where
T: Hash,
{
fn extend<S: IntoIterator<Item = T>>(&mut self, iter: S) {
for elem in iter {
self.add(&elem);
}
}
}
impl<'a, T> Extend<&'a T> for HyperLogLog<T>
where
T: 'a + Hash + ?Sized,
{
fn extend<S: IntoIterator<Item = &'a T>>(&mut self, iter: S) {
for elem in iter {
self.add(elem);
}
}
}
#[cfg(test)]
mod tests {
use super::{HyperLogLog, NUM_REGISTERS};
fn compare_with_delta(got: usize, expected: usize) {
let expected = expected as f64;
let diff = (got as f64) - expected;
let diff = diff.abs() / expected;
// times 6 because we want the tests to be stable
// so we allow a rather large margin of error
// this is adopted from redis's unit test version as well
let margin = 1.04 / ((NUM_REGISTERS as f64).sqrt()) * 6.0;
assert!(
diff <= margin,
"{} is not near {} percent of {} which is ({}, {})",
got,
margin,
expected,
expected * (1.0 - margin),
expected * (1.0 + margin)
);
}
macro_rules! sized_number_test {
($SIZE: expr, $T: tt) => {{
let mut hll = HyperLogLog::<$T>::new();
for i in 0..$SIZE {
hll.add(&i);
}
compare_with_delta(hll.count(), $SIZE);
}};
}
macro_rules! typed_large_number_test {
($SIZE: expr) => {{
sized_number_test!($SIZE, u64);
sized_number_test!($SIZE, u128);
sized_number_test!($SIZE, i64);
sized_number_test!($SIZE, i128);
}};
}
macro_rules! typed_number_test {
($SIZE: expr) => {{
sized_number_test!($SIZE, u16);
sized_number_test!($SIZE, u32);
sized_number_test!($SIZE, i16);
sized_number_test!($SIZE, i32);
typed_large_number_test!($SIZE);
}};
}
#[test]
fn test_empty() {
let hll = HyperLogLog::<u64>::new();
assert_eq!(hll.count(), 0);
}
#[test]
fn test_one() {
let mut hll = HyperLogLog::<u64>::new();
hll.add(&1);
assert_eq!(hll.count(), 1);
}
#[test]
fn test_number_100() {
typed_number_test!(100);
}
#[test]
fn test_number_1k() {
typed_number_test!(1_000);
}
#[test]
fn test_number_10k() {
typed_number_test!(10_000);
}
#[test]
fn test_number_100k() {
typed_large_number_test!(100_000);
}
#[test]
fn test_number_1m() {
typed_large_number_test!(1_000_000);
}
#[test]
fn test_u8() {
let mut hll = HyperLogLog::<[u8]>::new();
for i in 0..1000 {
let s = i.to_string();
let b = s.as_bytes();
hll.add(b);
}
compare_with_delta(hll.count(), 1000);
}
#[test]
fn test_string() {
let mut hll = HyperLogLog::<String>::new();
hll.extend((0..1000).map(|i| i.to_string()));
compare_with_delta(hll.count(), 1000);
}
#[test]
fn test_empty_merge() {
let mut hll = HyperLogLog::<u64>::new();
hll.merge(&HyperLogLog::<u64>::new());
assert_eq!(hll.count(), 0);
}
#[test]
fn test_merge_overlapped() {
let mut hll = HyperLogLog::<String>::new();
hll.extend((0..1000).map(|i| i.to_string()));
let mut other = HyperLogLog::<String>::new();
other.extend((0..1000).map(|i| i.to_string()));
hll.merge(&other);
compare_with_delta(hll.count(), 1000);
}
#[test]
fn test_repetition() {
let mut hll = HyperLogLog::<u32>::new();
for i in 0..1_000_000 {
hll.add(&(i % 1000));
}
compare_with_delta(hll.count(), 1000);
}
}