histogram/lib.rs
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//! A native rust implementation of a histogram and percentiles which can offer
//! specified precision across the full range of stored values. This library is
//! inspired by the `HdrHistogram` project.
//!
//! # Goals
//! * maintain precision across full value range
//! * provide percentile metrics for stored data
//! * pre-allocated datastructure
//!
//! # Future work
//! * unknown
//!
//! # Usage
//!
//! Create a new histogram, call increment for every value, retrieve percentile
//! stats.
//!
//! Note that the incremented and decremented values have the
//! precision which is given upon creation of the histogram (by
//! default 3 decimals). This means that increment of x and decrement
//! of y might lead net effect of zero, if x and y are of similar
//! size.
//!
//! # Example
//!
//! Create a histogram, increment values, show percentiles
//!
//! ```
//! use histogram::Histogram;
//!
//! // create a histogram with default config
//! let mut histogram = Histogram::new();
//!
//! let mut value = 0;
//!
//! for i in 1..100 {
//! histogram.increment(i);
//! }
//!
//! // print percentiles from the histogram
//! println!("Percentiles: p50: {} ns p90: {} ns p99: {} ns p999: {}",
//! histogram.percentile(50.0).unwrap(),
//! histogram.percentile(90.0).unwrap(),
//! histogram.percentile(99.0).unwrap(),
//! histogram.percentile(99.9).unwrap(),
//! );
//!
//! // print additional statistics
//! println!("Latency (ns): Min: {} Avg: {} Max: {} StdDev: {}",
//! histogram.minimum().unwrap(),
//! histogram.mean().unwrap(),
//! histogram.maximum().unwrap(),
//! histogram.stddev().unwrap(),
//! );
//! ```
#![cfg_attr(feature = "cargo-clippy", deny(missing_docs))]
#![cfg_attr(feature = "cargo-clippy", deny(warnings))]
use std::fmt;
use std::mem;
/// A configuration struct for building custom `Histogram`s.
#[derive(Clone, Copy)]
pub struct Config {
precision: u32,
max_memory: u32,
max_value: u64,
radix: u32,
}
impl Default for Config {
fn default() -> Config {
Config {
precision: 3,
max_memory: 0,
max_value: 60_000_000_000,
radix: 10,
}
}
}
impl Config {
/// create a new Histogram Config with defaults
///
/// # Example
/// ```
/// # use histogram::Histogram;
/// let mut c = Histogram::configure();
/// ```
pub fn new() -> Config {
Default::default()
}
/// set HistogramConfig precision
///
/// # Example
/// ```
/// # use histogram::Histogram;
/// let mut c = Histogram::configure();
/// c.precision(4); // set to 4 significant figures
/// ```
pub fn precision(mut self, precision: u32) -> Self {
self.precision = precision;
self
}
/// set HistogramConfig memory limit
///
/// # Example
/// ```
/// # use histogram::Histogram;
/// let mut c = Histogram::configure();
/// c.max_memory(1024*1024); // cap Histogram at 1MB of data
/// ```
pub fn max_memory(mut self, bytes: u32) -> Self {
self.max_memory = bytes;
self
}
/// set HistogramConfig value limit
///
/// # Example
/// ```
/// # use histogram::Histogram;
/// let mut c = Histogram::configure();
/// c.max_value(1000); // values above 1000 will not be stored
/// ```
pub fn max_value(mut self, max: u64) -> Self {
self.max_value = max;
self
}
/// Build a new histogram based on the current configuration
/// values. Return `None` if the new histogram would require more
/// than the [configured memory size](#method.max_memory).
pub fn build(self) -> Option<Histogram> {
Histogram::configured(self)
}
}
#[derive(Clone, Copy)]
struct Counters {
entries_total: u64,
missed_unknown: u64,
missed_large: u64,
}
impl Default for Counters {
fn default() -> Counters {
Counters {
entries_total: 0,
missed_unknown: 0,
missed_large: 0,
}
}
}
impl Counters {
fn new() -> Counters {
Default::default()
}
fn clear(&mut self) -> &mut Self {
self.entries_total = 0;
self.missed_unknown = 0;
self.missed_large = 0;
self
}
}
#[derive(Clone)]
struct Data {
data: Vec<u64>,
counters: Counters,
}
#[derive(Clone, Copy)]
struct Properties {
buckets_inner: u32,
linear_max: u64,
linear_power: u32,
}
/// the main datastructure
#[derive(Clone)]
pub struct Histogram {
config: Config,
data: Data,
properties: Properties,
}
/// value-quantized section of `Histogram`
#[derive(Clone, Copy, Debug)]
pub struct Bucket {
id: u64,
count: u64,
value: u64,
width: u64,
}
impl Bucket {
/// return the sample value for the bucket
///
/// # Example
/// ```
/// # use histogram::Histogram;
/// let mut h = Histogram::new();
/// let b = h.into_iter().next().unwrap();
/// assert_eq!(b.value(), 0);
/// ```
pub fn value(self) -> u64 {
self.value
}
/// return the sample counts for the bucket
///
/// # Example
/// ```
/// # use histogram::Histogram;
/// let h = Histogram::new();
/// let b = h.into_iter().next().unwrap();
/// assert_eq!(b.count(), 0);
/// ```
pub fn count(self) -> u64 {
self.count
}
/// return the bucket id
///
/// # Example
/// ```
/// # use histogram::Histogram;
/// let h = Histogram::new();
/// let b = h.into_iter().next().unwrap();
/// assert_eq!(b.id(), 0);
/// ```
pub fn id(self) -> u64 {
self.id
}
/// return the width of the bucket
///
/// # Example
/// ```
/// # use histogram::Histogram;
/// let h = Histogram::new();
/// let b = h.into_iter().next().unwrap();
/// assert_eq!(b.width(), 1);
/// ```
pub fn width(self) -> u64 {
self.width
}
}
/// Iterator over a Histogram's buckets.
pub struct Iter<'a> {
hist: &'a Histogram,
index: usize,
}
impl<'a> Iter<'a> {
fn new(hist: &'a Histogram) -> Iter<'a> {
Iter { hist, index: 0 }
}
}
impl<'a> Iterator for Iter<'a> {
type Item = Bucket;
fn next(&mut self) -> Option<Bucket> {
let limit = self.hist.get_index(self.hist.config.max_value).unwrap();
if self.index > limit {
None
} else {
let current = self.index;
// clamp the value at max value
let mut value = self.hist.index_value(current);
if value > self.hist.config.max_value {
value = self.hist.config.max_value;
self.index = limit + 1;
}
// measure width of current bucket
let width = if current == 0 {
1
} else {
value - self.hist.index_value(current - 1)
};
self.index += 1;
Some(Bucket {
id: current as u64,
count: self.hist.data.data[current],
value,
width,
})
}
}
}
impl<'a> IntoIterator for &'a Histogram {
type Item = Bucket;
type IntoIter = Iter<'a>;
fn into_iter(self) -> Self::IntoIter {
Iter::new(self)
}
}
impl fmt::Debug for Histogram {
fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
write!(f, "({} total)", self.data.counters.entries_total)
}
}
impl Default for Histogram {
fn default() -> Histogram {
Config::new().build().unwrap()
}
}
impl Histogram {
/// create a new Histogram
///
/// # Example
/// ```
/// # use histogram::Histogram;
/// let mut h = Histogram::new();
/// ```
pub fn new() -> Histogram {
Default::default()
}
/// configure a Histogram
///
/// # Example
/// ```
/// # use histogram::Histogram;
/// let mut h = Histogram::configure()
/// .max_value(10_000)
/// .build()
/// .unwrap();
/// ```
pub fn configure() -> Config {
Config::default()
}
fn configured(config: Config) -> Option<Histogram> {
let buckets_inner: u32 = config.radix.pow(config.precision);
let linear_power: u32 = 32 - buckets_inner.leading_zeros();
let linear_max: u64 = 2.0_f64.powi(linear_power as i32) as u64;
let max_value_power: u32 = 64 - config.max_value.leading_zeros();
let buckets_outer = if max_value_power > linear_power {
max_value_power - linear_power
} else {
0
};
let buckets_total = buckets_inner * buckets_outer + linear_max as u32;
let memory_used = buckets_total * mem::size_of::<u64>() as u32;
if config.max_memory > 0 && config.max_memory < memory_used {
return None;
}
let data = vec![0; buckets_total as usize];
let counters = Counters::new();
Some(Histogram {
config,
data: Data { data, counters },
properties: Properties {
buckets_inner,
linear_max,
linear_power,
},
})
}
/// clear the histogram data
///
/// # Example
/// ```
/// # use histogram::Histogram;
/// let mut h = Histogram::new();
///
/// h.increment(1);
/// assert_eq!(h.entries(), 1);
/// h.clear();
/// assert_eq!(h.entries(), 0);
/// ```
pub fn clear(&mut self) {
// clear everything manually, weird results in practice?
self.data.counters.clear();
for x in &mut self.data.data {
*x = 0;
}
}
/// increment the count for a value
///
/// # Example
/// ```
/// use histogram::Histogram;
///
/// let mut h = Histogram::new();
///
/// h.increment(1);
/// assert_eq!(h.get(1).unwrap(), 1);
/// ```
pub fn increment(&mut self, value: u64) -> Result<(), &'static str> {
self.increment_by(value, 1_u64)
}
/// record additional counts for value
///
/// # Example
/// ```
/// # use histogram::Histogram;
/// let mut h = Histogram::new();
///
/// h.increment_by(1, 1);
/// assert_eq!(h.get(1).unwrap(), 1);
///
/// h.increment_by(2, 2);
/// assert_eq!(h.get(2).unwrap(), 2);
///
/// h.increment_by(10, 10);
/// assert_eq!(h.get(10).unwrap(), 10);
/// ```
pub fn increment_by(&mut self, value: u64, count: u64) -> Result<(), &'static str> {
self.data.counters.entries_total = self.data.counters.entries_total.saturating_add(count);
if value > self.config.max_value {
self.data.counters.missed_large = self.data.counters.missed_large.saturating_add(count);
Err("sample value too large")
} else {
match self.get_index(value) {
Some(index) => {
self.data.data[index] = self.data.data[index].saturating_add(count);
Ok(())
}
None => {
self.data.counters.missed_unknown =
self.data.counters.missed_unknown.saturating_add(count);
Err("sample unknown error")
}
}
}
}
/// decrement the count for a value. This functionality is best
/// used to remove previously inserted from the histogram.
///
/// # Example
/// ```
/// # use histogram::Histogram;
/// let mut h = Histogram::new();
///
/// h.increment(1).unwrap();
/// assert_eq!(h.get(1).unwrap(), 1);
/// h.decrement(1).unwrap();
/// assert_eq!(h.get(1).unwrap(), 0);
/// ```
pub fn decrement(&mut self, value: u64) -> Result<(), &'static str> {
self.decrement_by(value, 1_u64)
}
/// remove count for value from histogram. This functionality is
/// best used to remove previously inserted from the
/// histogram.
///
/// # Example
/// ```
/// # use histogram::Histogram;
/// let mut h = Histogram::new();
///
/// h.increment_by(1, 1).unwrap();
/// h.increment_by(2, 2).unwrap();
/// h.decrement_by(1, 1).unwrap();
///
/// assert_eq!(h.get(2).unwrap(), 2);
/// assert_eq!(h.get(1).unwrap(), 0);
/// ```
pub fn decrement_by(&mut self, value: u64, count: u64) -> Result<(), &'static str> {
if value > self.config.max_value {
if let Some(new_missed_large) = self.data.counters.missed_large.checked_sub(count) {
self.data.counters.missed_large = new_missed_large;
self.data.counters.entries_total =
self.data.counters.entries_total.saturating_sub(count);
Err("sample value too large")
} else {
Err("large sample value underflow")
}
} else {
match self.get_index(value) {
Some(index) => {
if let Some(new_index_value) = self.data.data[index].checked_sub(count) {
self.data.data[index] = new_index_value;
self.data.counters.entries_total =
self.data.counters.entries_total.saturating_sub(count);
Ok(())
} else {
Err("underflow")
}
}
None => {
self.data.counters.missed_unknown =
self.data.counters.missed_unknown.saturating_add(count);
Err("sample unknown error")
}
}
}
}
/// get the count for a value
///
/// # Example
/// ```
/// # use histogram::Histogram;
/// let mut h = Histogram::new();
/// assert_eq!(h.get(1).unwrap(), 0);
/// ```
pub fn get(&self, value: u64) -> Option<u64> {
match self.get_index(value) {
Some(index) => Some(self.data.data[index]),
None => None,
}
}
// calculate the index for a given value
fn get_index(&self, value: u64) -> Option<usize> {
if value <= (self.properties.linear_max + 2_u64.pow(self.config.precision)) {
return Some(value as usize);
}
let l_max = self.properties.linear_max as u32;
let outer = 63 - value.leading_zeros();
let l_power = 63 - self.properties.linear_max.leading_zeros();
let remain = value as f64 - 2.0_f64.powi(outer as i32);
let inner = (f64::from(self.properties.buckets_inner) * remain as f64 /
2.0_f64.powi((outer) as i32))
.floor() as u32;
// this gives the shifted outer index
let outer = outer as u32 - l_power;
let index = l_max + self.properties.buckets_inner * outer + inner + 1;
Some(index as usize)
}
// calculate the nominal value of the given index
fn index_value(&self, index: usize) -> u64 {
// in this case, the index is linear
let index = index as u32;
let linear_max = self.properties.linear_max as u32;
if index <= linear_max {
return u64::from(index);
}
let log_index = index - linear_max;
let outer = (f64::from(log_index) / f64::from(self.properties.buckets_inner)).floor() as
u32;
let inner = log_index - outer * self.properties.buckets_inner as u32;
let mut value = 2.0_f64.powi((outer as u32 + self.properties.linear_power) as i32);
value += f64::from(inner) * (value as f64 / f64::from(self.properties.buckets_inner));
if value > self.config.max_value as f64 {
return self.config.max_value as u64;
}
value.ceil() as u64
}
/// return the value for the given percentile
///
/// # Example
/// ```
/// # use histogram::Histogram;
/// let mut h = Histogram::new();
/// for value in 1..1000 {
/// h.increment(value).unwrap();
/// }
///
/// assert_eq!(h.percentile(50.0).unwrap(), 501);
/// assert_eq!(h.percentile(90.0).unwrap(), 901);
/// assert_eq!(h.percentile(99.0).unwrap(), 991);
/// assert_eq!(h.percentile(99.9).unwrap(), 999);
/// ```
pub fn percentile(&self, percentile: f64) -> Result<u64, &'static str> {
if self.entries() < 1 {
return Err("no data");
}
if percentile <= 100.0 && percentile >= 0.0 {
let total = self.entries();
let mut need = (total as f64 * (percentile / 100.0_f64)).ceil() as u64;
if need > total {
need = total;
}
need = total - need;
let mut index: isize = (self.buckets_total() - 1) as isize;
let mut step: isize = -1 as isize;
let mut have = if percentile < 50.0 {
index = 0 as isize;
step = 1 as isize;
need = total - need;
0
} else {
self.data.counters.missed_large
};
if need == 0 {
need = 1;
}
if have >= need {
if index == 0 {
return Err("underflow");
}
return Err("overflow");
}
loop {
have += self.data.data[index as usize];
if have >= need {
return Ok(self.index_value(index as usize) as u64);
}
index += step;
if index >= self.buckets_total() as isize {
break;
}
if index < 0 {
break;
}
}
}
Err("unknown failure")
}
/// convenience function for min
///
/// # Example
/// ```
/// # use histogram::Histogram;
/// let mut h = Histogram::new();
/// for value in 1..1000 {
/// h.increment(value);
/// }
/// assert_eq!(h.minimum().unwrap(), 1);
/// ```
pub fn minimum(&self) -> Result<u64, &'static str> {
self.percentile(0.0_f64)
}
/// convenience function for max
///
/// # Example
/// ```
/// # use histogram::Histogram;
/// let mut h = Histogram::new();
/// for value in 1..1000 {
/// h.increment(value);
/// }
/// assert_eq!(h.maximum().unwrap(), 999);
/// ```
pub fn maximum(&self) -> Result<u64, &'static str> {
self.percentile(100.0_f64)
}
/// arithmetic mean approximation across the histogram
///
/// # Example
/// ```
/// # use histogram::Histogram;
/// let mut h = Histogram::new();
/// for value in 1..1000 {
/// h.increment(value);
/// }
/// assert_eq!(h.mean().unwrap(), 500);
/// ```
pub fn mean(&self) -> Result<u64, &'static str> {
if self.entries() < 1 {
return Err("no data");
}
let total = self.entries();
let mut mean = 0.0_f64;
for index in 0..(self.buckets_total() as usize) {
mean += (self.index_value(index) as f64 * self.data.data[index] as f64) as f64 /
total as f64;
}
Ok(mean.ceil() as u64)
}
/// standard variance approximation across the histogram
///
/// # Example
/// ```
/// # use histogram::Histogram;
/// let mut h = Histogram::new();
/// for value in 1..11 {
/// h.increment(value);
/// }
/// assert_eq!(h.stdvar().unwrap(), 9);
/// ```
pub fn stdvar(&self) -> Result<u64, &'static str> {
if self.entries() < 1 {
return Err("no data");
}
let total = self.entries() as f64;
let m = self.mean().unwrap() as f64;
let mut stdvar = 0.0_f64;
for index in 0..(self.buckets_total() as usize) {
let v = self.index_value(index) as f64;
let c = self.data.data[index] as f64;
stdvar += (c * v * v) - (2_f64 * c * m * v) + (c * m * m);
}
stdvar /= total;
Ok(stdvar.ceil() as u64)
}
/// standard deviation approximation across the histogram
///
/// # Example
/// ```
/// # use histogram::Histogram;
/// let mut h = Histogram::new();
///
/// for value in 1..11 {
/// h.increment(value);
/// }
///
/// assert_eq!(h.stddev().unwrap(), 3);
///
/// h.clear();
///
/// for value in 1..4 {
/// h.increment(value);
/// }
/// for _ in 0..26 {
/// h.increment(1);
/// }
///
/// assert_eq!(h.stddev().unwrap(), 1);
/// ```
pub fn stddev(&self) -> Option<u64> {
if self.entries() < 1 {
return None;
}
let stdvar = self.stdvar().unwrap() as f64;
let stddev = stdvar.sqrt();
Some(stddev.ceil() as u64)
}
/// merge one Histogram into another Histogram
///
/// # Example
/// ```
/// # use histogram::Histogram;
/// let mut a = Histogram::new();
/// let mut b = Histogram::new();
///
/// assert_eq!(a.entries(), 0);
/// assert_eq!(b.entries(), 0);
///
/// a.increment(1);
/// b.increment(2);
///
/// assert_eq!(a.entries(), 1);
/// assert_eq!(b.entries(), 1);
///
/// a.merge(&mut b);
///
/// assert_eq!(a.entries(), 2);
/// assert_eq!(a.get(1).unwrap(), 1);
/// assert_eq!(a.get(2).unwrap(), 1);
/// ```
pub fn merge(&mut self, other: &Histogram) {
for bucket in other {
let _ = self.increment_by(bucket.value, bucket.count);
}
}
/// return the number of entries in the Histogram
///
/// # Example
/// ```
/// # use histogram::Histogram;
/// let mut h = Histogram::new();
///
/// assert_eq!(h.entries(), 0);
/// h.increment(1);
/// assert_eq!(h.entries(), 1);
/// ```
pub fn entries(&self) -> u64 {
self.data.counters.entries_total
}
/// return the number of buckets in the Histogram
///
/// # Example
/// ```
/// # use histogram::Histogram;
/// let mut h = Histogram::new();
///
/// assert!(h.buckets_total() > 1);
/// ```
pub fn buckets_total(&self) -> u64 {
(self.get_index(self.config.max_value).unwrap() + 1) as u64
}
}
#[cfg(test)]
mod tests {
use super::Histogram;
#[test]
fn test_too_large() {
let h = Histogram::configure()
.max_value(10_000)
.precision(3)
.max_memory(8192)
.build();
if let Some(_) = h {
panic!("Created histogram which used too much memory");
}
}
#[test]
fn test_increment_0() {
let mut h = Histogram::new();
for op in 1..1000000 {
h.increment(1).unwrap();
assert_eq!(h.entries(), op);
}
}
#[test]
fn test_increment_1() {
let mut h = Histogram::configure()
.max_value(10)
.precision(3)
.build()
.unwrap();
// increment values across the entire range
// including 0 and max_value
for v in 0..11 {
h.increment(v).unwrap();
assert_eq!(h.entries(), v + 1);
}
}
#[test]
fn test_decrement_0() {
let mut h = Histogram::new();
let m = 1000000;
for _ in 0..m {
h.increment(2).unwrap();
}
for op in 1..m {
h.decrement(2).unwrap();
assert_eq!(h.entries(), m - op);
}
}
#[test]
fn test_decrement_1() {
let mut h = Histogram::configure()
.max_value(20_000)
.precision(3)
.build()
.unwrap();
let v = h.properties.linear_max + 2;
let m = 1_000_000;
for _ in 0..m {
h.increment(v).unwrap();
}
for op in 1..m {
h.decrement(v).unwrap();
assert_eq!(h.entries(), m - op);
}
}
#[test]
#[should_panic(expected = "large sample value underflow")]
fn test_decrement_4() {
let mut h = Histogram::new();
let v = h.config.max_value + 1;
h.decrement(v).unwrap();
}
#[test]
#[should_panic(expected = "sample value too large")]
fn test_decrement_5() {
let mut h = Histogram::new();
let v = h.config.max_value + 1;
let _ = h.increment(v);
h.decrement(v).unwrap();
}
#[test]
fn test_decrement_example_0() {
let mut h = Histogram::new();
h.increment(1).unwrap();
assert_eq!(h.get(1).unwrap(), 1);
h.decrement(1).unwrap();
assert_eq!(h.get(1).unwrap(), 0);
}
#[test]
fn test_decrement_by_example_0() {
let mut h = Histogram::new();
h.increment_by(1, 1).unwrap();
h.increment_by(2, 2).unwrap();
h.decrement_by(1, 1).unwrap();
assert_eq!(h.get(2).unwrap(), 2);
assert_eq!(h.get(1).unwrap(), 0);
}
#[test]
fn test_get() {
let mut h = Histogram::new();
h.increment(1).unwrap();
assert_eq!(h.get(1), Some(1));
h.increment(1).unwrap();
assert_eq!(h.get(1), Some(2));
h.increment(2).unwrap();
assert_eq!(h.get(2), Some(1));
assert_eq!(h.get(3), Some(0));
}
#[test]
fn test_get_index_0() {
let h = Histogram::configure()
.max_value(32)
.precision(3)
.build()
.unwrap();
// all values should index directly to value
// no estimated buckets are needed given the precision and max
for i in 0..32 {
assert_eq!(h.get_index(i), Some(i as usize));
assert_eq!(h.index_value(i as usize), i);
}
}
#[test]
fn test_index_value_0() {
let h = Histogram::configure()
.max_value(100)
.precision(1)
.build()
.unwrap();
assert_eq!(h.index_value(1), 1);
assert_eq!(h.index_value(2), 2);
assert_eq!(h.index_value(15), 15);
assert_eq!(h.index_value(16), 16);
assert_eq!(h.index_value(26), 32);
assert_eq!(h.index_value(36), 64);
}
#[test]
fn test_index_value_1() {
let h = Histogram::configure()
.max_value(1_000)
.precision(2)
.build()
.unwrap();
assert_eq!(h.index_value(0), 0);
assert_eq!(h.index_value(1), 1);
assert_eq!(h.index_value(126), 126);
assert_eq!(h.index_value(128), 128);
assert_eq!(h.index_value(228), 256);
assert_eq!(h.index_value(328), 512);
}
#[test]
fn test_index_value_2() {
let h = Histogram::configure()
.max_value(10_000)
.precision(3)
.build()
.unwrap();
assert_eq!(h.index_value(0), 0);
assert_eq!(h.index_value(1), 1);
assert_eq!(h.index_value(1023), 1023);
assert_eq!(h.index_value(1024), 1024);
assert_eq!(h.index_value(2024), 2048);
}
#[test]
fn test_iterator() {
let h = Histogram::configure()
.max_value(100)
.precision(1)
.build()
.unwrap();
let mut buckets_seen = 0;
for bucket in &h {
println!("Bucket: {:?}", bucket);
assert_eq!(bucket.id(), buckets_seen);
assert_eq!(bucket.value(), h.index_value(bucket.id() as usize));
assert_eq!(bucket.count(), 0);
buckets_seen += 1;
}
assert_eq!(h.buckets_total(), buckets_seen);
}
#[test]
fn test_percentile() {
let mut h = Histogram::configure()
.max_value(1_000)
.precision(4)
.build()
.unwrap();
for i in 100..200 {
h.increment(i).ok().expect("error");
}
assert_eq!(h.percentile(0.0).unwrap(), 100);
assert_eq!(h.percentile(10.0).unwrap(), 109);
assert_eq!(h.percentile(25.0).unwrap(), 124);
assert_eq!(h.percentile(50.0).unwrap(), 150);
assert_eq!(h.percentile(75.0).unwrap(), 175);
assert_eq!(h.percentile(90.0).unwrap(), 190);
assert_eq!(h.percentile(95.0).unwrap(), 195);
assert_eq!(h.percentile(100.0).unwrap(), 199);
}
#[test]
fn test_percentile_bad() {
let mut h = Histogram::configure()
.max_value(1_000)
.precision(4)
.build()
.unwrap();
let _ = h.increment(5_000);
assert!(h.percentile(0.0).is_err());
assert!(h.percentile(50.0).is_err());
assert!(h.percentile(100.0).is_err());
let _ = h.increment(1);
assert!(h.percentile(0.0).is_ok());
let _ = h.increment(500);
let _ = h.increment(500);
assert!(h.percentile(50.0).is_ok());
}
#[test]
fn test_width_1() {
let mut h = Histogram::configure()
.max_value(100)
.precision(3)
.build()
.unwrap();
for v in 0..101 {
let _ = h.increment(v);
}
assert_eq!(h.data.counters.missed_large, 0);
let mut prev_id = 0;
for b in &h {
println!("Bucket: {:?}", b);
if b.id() >= 1 {
assert!(b.id() - 1 == prev_id);
prev_id = b.id();
}
assert!(b.width() != 0, "width should not be 0");
assert_eq!(b.width(), b.count());
}
}
#[test]
fn test_width_2() {
let mut h = Histogram::configure()
.max_value(1000)
.precision(2)
.build()
.unwrap();
for v in 0..1001 {
let _ = h.increment(v);
}
assert_eq!(h.data.counters.missed_large, 0);
let mut prev_id = 0;
let mut prev_value = 0;
for b in &h {
println!("Bucket: {:?}", b);
if b.id() >= 1 {
assert_eq!(b.width(), b.value() - prev_value);
assert!(b.id() - 1 == prev_id);
prev_id = b.id();
prev_value = b.value();
}
assert!(b.width() != 0, "width should not be 0");
}
}
#[test]
fn test_width_3() {
let mut h = Histogram::configure()
.max_value(10_000)
.precision(3)
.build()
.unwrap();
for v in 0..10_000 {
let _ = h.increment(v + 1);
}
assert_eq!(h.data.counters.missed_large, 0);
let mut prev_id = 0;
let mut prev_value = 0;
for b in &h {
println!("Bucket: {:?}", b);
if b.id() >= 1 {
assert_eq!(b.width(), b.value() - prev_value);
assert!(b.id() - 1 == prev_id);
prev_id = b.id();
prev_value = b.value();
}
assert!(b.width() != 0, "width should not be 0");
}
}
}