mirror of
https://github.com/logos-blockchain/lssa.git
synced 2026-07-17 21:29:51 +00:00
952 lines
29 KiB
Rust
952 lines
29 KiB
Rust
#![expect(
|
|
clippy::float_arithmetic,
|
|
reason = "One should expect floating point arithmetic in statistic calculations"
|
|
)]
|
|
#![expect(
|
|
clippy::cast_precision_loss,
|
|
reason = "Operated numbers is not big enough to have precision loss"
|
|
)]
|
|
|
|
use std::{collections::HashMap, path::Path};
|
|
|
|
use anyhow::{Context as _, Result};
|
|
use sequencer_service_rpc::{RpcClient as _, SequencerClient, SequencerClientBuilder};
|
|
use serde::{Deserialize, Serialize};
|
|
use url::Url;
|
|
|
|
use crate::config::SequencerConnectionData;
|
|
|
|
#[derive(Debug, Clone, Serialize, Deserialize)]
|
|
pub struct Metrics {
|
|
pub latency_avg: f32,
|
|
pub latency_var: f32,
|
|
pub sample_size: usize,
|
|
pub latest_block_id: u64,
|
|
pub errors: u64,
|
|
}
|
|
|
|
#[derive(Debug, Clone)]
|
|
pub struct MetricsUpdate {
|
|
pub latency: f32,
|
|
pub new_latest_block_id: Option<u64>,
|
|
pub is_failed: bool,
|
|
}
|
|
|
|
impl Metrics {
|
|
pub fn apply_updates(&mut self, updates: &[MetricsUpdate]) {
|
|
let CumulativeUpdates {
|
|
failure_count,
|
|
latest_block_id,
|
|
cumulative_latency,
|
|
cumulative_latency_squares,
|
|
additional_sample_size,
|
|
} = CumulativeUpdates::from_metric_updates(updates);
|
|
|
|
self.errors = self.errors.saturating_add(failure_count);
|
|
if let Some(latest_block_id) = latest_block_id {
|
|
self.latest_block_id = latest_block_id;
|
|
}
|
|
|
|
#[expect(clippy::as_conversions, reason = "int to float conversion is safe")]
|
|
let orig_size_f = self.sample_size as f32;
|
|
#[expect(clippy::as_conversions, reason = "int to float conversion is safe")]
|
|
let mod_size_f = additional_sample_size as f32;
|
|
|
|
let latency_avg_old = self.latency_avg;
|
|
let latency_avg_new =
|
|
cumulative_avg(latency_avg_old, cumulative_latency, orig_size_f, mod_size_f);
|
|
|
|
let latency_var_new = cumulative_var(
|
|
latency_avg_old,
|
|
latency_avg_new,
|
|
self.latency_var,
|
|
cumulative_latency,
|
|
cumulative_latency_squares,
|
|
orig_size_f,
|
|
mod_size_f,
|
|
);
|
|
|
|
self.latency_avg = latency_avg_new;
|
|
self.latency_var = latency_var_new;
|
|
self.sample_size = self.sample_size.saturating_add(additional_sample_size);
|
|
}
|
|
}
|
|
|
|
#[derive(Clone)]
|
|
pub struct MultiSequencerClient {
|
|
// For now we store only leader, it is possible, that
|
|
// in future for important sends(for example for transactions)
|
|
// we would want to distribute call between known sequencers
|
|
pub leader: SequencerClient,
|
|
pub leader_url: Url,
|
|
}
|
|
|
|
impl MultiSequencerClient {
|
|
pub async fn new(
|
|
conn_data: &[SequencerConnectionData],
|
|
metrics: &mut HashMap<Url, Metrics>,
|
|
callibration_limit: usize,
|
|
) -> Result<Self> {
|
|
let mut client_list = HashMap::new();
|
|
|
|
for SequencerConnectionData {
|
|
sequencer_addr,
|
|
basic_auth,
|
|
} in conn_data
|
|
{
|
|
let sequencer_client = {
|
|
let mut builder = SequencerClientBuilder::default();
|
|
if let Some(basic_auth) = &basic_auth {
|
|
builder = builder.set_headers(
|
|
std::iter::once((
|
|
"Authorization".parse().expect("Header name is valid"),
|
|
format!("Basic {basic_auth}")
|
|
.parse()
|
|
.context("Invalid basic auth format")?,
|
|
))
|
|
.collect(),
|
|
);
|
|
}
|
|
builder
|
|
.build(sequencer_addr)
|
|
.context("Failed to create sequencer client")?
|
|
};
|
|
|
|
// If there is no metrics for client, callibrate it
|
|
if metrics.contains_key(sequencer_addr) {
|
|
let metric_updates = actualize_client(&sequencer_client).await;
|
|
|
|
log::debug!(
|
|
"Metered call for {sequencer_addr:?}, metric updates is {metric_updates:?}"
|
|
);
|
|
|
|
let metric_mut = metrics.get_mut(sequencer_addr).unwrap();
|
|
metric_mut.apply_updates(&[metric_updates]);
|
|
// Otherwise actualize client data
|
|
} else {
|
|
metrics.insert(
|
|
sequencer_addr.clone(),
|
|
callibrate_client(&sequencer_client, callibration_limit).await,
|
|
);
|
|
}
|
|
|
|
client_list.insert(sequencer_addr.clone(), sequencer_client);
|
|
}
|
|
|
|
let (leader_url, leader) = choose_leader(&client_list, metrics)
|
|
.ok_or_else(|| anyhow::anyhow!("Failed to find leader"))?;
|
|
|
|
log::info!("Chosen leader is {leader_url:?}");
|
|
|
|
// Dropping client list, for reasons why, see comment in structure definition.
|
|
Ok(Self { leader, leader_url })
|
|
}
|
|
|
|
#[must_use]
|
|
pub const fn leader_ref(&self) -> &SequencerClient {
|
|
&self.leader
|
|
}
|
|
|
|
#[must_use]
|
|
pub fn leader_clone(&self) -> SequencerClient {
|
|
self.leader.clone()
|
|
}
|
|
|
|
// Keeping this call abstract, in case if we need to do more than one request
|
|
pub async fn metered_call<R, E, I: AsyncFn(&SequencerClient) -> Result<R, E>>(
|
|
&self,
|
|
call: I,
|
|
) -> (Result<R, E>, MetricsUpdate) {
|
|
let resp = tokio::join!(call(self.leader_ref()), actualize_client(self.leader_ref()));
|
|
|
|
log::debug!(
|
|
"Metered call for {:?}, metric updates is {:?}",
|
|
self.leader_url,
|
|
resp.1
|
|
);
|
|
|
|
resp
|
|
}
|
|
}
|
|
|
|
struct CumulativeUpdates {
|
|
pub failure_count: u64,
|
|
pub latest_block_id: Option<u64>,
|
|
/// Necessary for cumulative average calculation.
|
|
pub cumulative_latency: f32,
|
|
/// Necessary for cumulative variance calculation.
|
|
pub cumulative_latency_squares: f32,
|
|
pub additional_sample_size: usize,
|
|
}
|
|
|
|
impl CumulativeUpdates {
|
|
fn from_metric_updates(metric_updates: &[MetricsUpdate]) -> Self {
|
|
let (failure_count, latest_block_id, cumulative_latency, cumulative_latency_squares) =
|
|
metric_updates
|
|
.iter()
|
|
.fold((0_u64, None, 0_f32, 0_f32), |acc, x| {
|
|
let MetricsUpdate {
|
|
latency,
|
|
new_latest_block_id,
|
|
is_failed,
|
|
} = x;
|
|
(
|
|
if *is_failed {
|
|
acc.0.saturating_add(1)
|
|
} else {
|
|
acc.0
|
|
},
|
|
match (acc.1, new_latest_block_id) {
|
|
(None, None) => None,
|
|
(None, Some(val)) | (Some(val), None) => Some(val),
|
|
(Some(val_old), Some(val_new)) => Some(std::cmp::max(val_old, val_new)),
|
|
},
|
|
if *is_failed { acc.2 } else { acc.2 + latency },
|
|
if *is_failed {
|
|
acc.3
|
|
} else {
|
|
latency.mul_add(*latency, acc.3)
|
|
},
|
|
)
|
|
});
|
|
|
|
Self {
|
|
failure_count,
|
|
latest_block_id: latest_block_id.copied(),
|
|
cumulative_latency,
|
|
cumulative_latency_squares,
|
|
additional_sample_size: metric_updates.len().saturating_sub(
|
|
usize::try_from(failure_count).expect("Sample size should fit usize"),
|
|
),
|
|
}
|
|
}
|
|
}
|
|
|
|
pub fn extract_metrics_from_path(path: &Path) -> Result<HashMap<Url, Metrics>, anyhow::Error> {
|
|
match std::fs::File::open(path) {
|
|
Ok(file) => {
|
|
let reader = std::io::BufReader::new(file);
|
|
Ok(serde_json::from_reader(reader)?)
|
|
}
|
|
Err(err) if err.kind() == std::io::ErrorKind::NotFound => {
|
|
println!("Metrics not found, choosing empty");
|
|
Ok(HashMap::new())
|
|
}
|
|
Err(err) => Err(err).context("IO error"),
|
|
}
|
|
}
|
|
|
|
pub async fn callibrate_client(client: &SequencerClient, callibration_limit: usize) -> Metrics {
|
|
let mut latencies = vec![];
|
|
let mut latest_block_id = 0;
|
|
let mut errors: u64 = 0;
|
|
|
|
// ToDo: Add some DDoS adaptation
|
|
for _ in 0..callibration_limit {
|
|
let now = tokio::time::Instant::now();
|
|
|
|
let block_id = client.get_last_block_id().await;
|
|
|
|
let latency = tokio::time::Instant::now().duration_since(now).as_millis();
|
|
|
|
let Ok(block_id) = block_id else {
|
|
errors = errors.saturating_add(1);
|
|
continue;
|
|
};
|
|
|
|
latest_block_id = block_id;
|
|
latencies.push(latency);
|
|
}
|
|
|
|
// Precision loss if fine there
|
|
let sample_size = latencies.len();
|
|
#[expect(clippy::as_conversions, reason = "int to float conversion is safe")]
|
|
let latency_avg = (latencies.iter().sum::<u128>() as f32) / (sample_size as f32);
|
|
#[expect(clippy::as_conversions, reason = "int to float conversion is safe")]
|
|
let latency_var = latencies.iter().fold(0_f32, |acc, x| {
|
|
((*x as f32) - latency_avg).mul_add((*x as f32) - latency_avg, acc)
|
|
}) / (sample_size as f32);
|
|
|
|
Metrics {
|
|
latency_avg,
|
|
latency_var,
|
|
sample_size,
|
|
latest_block_id,
|
|
errors,
|
|
}
|
|
}
|
|
|
|
pub async fn actualize_client(client: &SequencerClient) -> MetricsUpdate {
|
|
let now = tokio::time::Instant::now();
|
|
|
|
let block_id = client.get_last_block_id().await.ok();
|
|
|
|
#[expect(clippy::as_conversions, reason = "int to float conversion is safe")]
|
|
let latency = tokio::time::Instant::now().duration_since(now).as_millis() as f32;
|
|
|
|
MetricsUpdate {
|
|
latency,
|
|
new_latest_block_id: block_id,
|
|
is_failed: block_id.is_none(),
|
|
}
|
|
}
|
|
|
|
#[must_use]
|
|
pub fn choose_leader(
|
|
client_list: &HashMap<Url, SequencerClient>,
|
|
metrics: &HashMap<Url, Metrics>,
|
|
) -> Option<(Url, SequencerClient)> {
|
|
let mut client_vec = vec![];
|
|
|
|
// Sort out all unmetered clients
|
|
client_vec = client_list
|
|
.keys()
|
|
.filter(|item| metrics.contains_key(*item))
|
|
.collect();
|
|
|
|
if client_vec.is_empty() {
|
|
return None;
|
|
}
|
|
|
|
// Considering the nature of our requests, the latest_block_id is the dominant characteristic
|
|
let max_block_id_addr = client_vec.iter().fold(client_vec[0], |acc, x| {
|
|
let old_latest_block_id = metrics.get(acc).unwrap().latest_block_id;
|
|
let new_latest_block_id = metrics.get(*x).unwrap().latest_block_id;
|
|
if new_latest_block_id > old_latest_block_id {
|
|
*x
|
|
} else {
|
|
acc
|
|
}
|
|
});
|
|
|
|
let max_block_id = metrics.get(max_block_id_addr).unwrap().latest_block_id;
|
|
|
|
// Sort out all clients running late
|
|
client_vec = client_vec
|
|
.iter()
|
|
.filter_map(|x| {
|
|
let latest_block_id = metrics.get(*x).unwrap().latest_block_id;
|
|
|
|
(latest_block_id == max_block_id).then_some(*x)
|
|
})
|
|
.collect();
|
|
|
|
// Get the clients with lesser or equal to average error count
|
|
#[expect(clippy::as_conversions, reason = "int to float conversion is safe")]
|
|
let avg_err_count = (client_vec.iter().fold(0_u64, |acc, x| {
|
|
acc.saturating_add(metrics.get(*x).unwrap().errors)
|
|
}) as f32)
|
|
/ (client_vec.len() as f32);
|
|
|
|
client_vec.sort_by(|a, b| {
|
|
metrics
|
|
.get(*a)
|
|
.unwrap()
|
|
.errors
|
|
.cmp(&metrics.get(*b).unwrap().errors)
|
|
});
|
|
|
|
#[expect(clippy::as_conversions, reason = "int to float conversion is safe")]
|
|
let client_vec = client_vec[..(client_vec
|
|
.iter()
|
|
.position(|item| (metrics.get(*item).unwrap().errors as f32) > avg_err_count)
|
|
.unwrap_or(client_vec.len()))]
|
|
.to_vec();
|
|
|
|
// Choose clients with least latency and variance
|
|
let min_lat_var_addr = client_vec.iter().fold(client_vec[0], |acc, x| {
|
|
let old = metrics.get(acc).unwrap();
|
|
let (old_lat, old_var) = (old.latency_avg, old.latency_var);
|
|
let new = metrics.get(*x).unwrap();
|
|
let (new_lat, new_var) = (new.latency_avg, new.latency_var);
|
|
|
|
let new_std = new_var.sqrt();
|
|
let old_std = old_var.sqrt();
|
|
|
|
// Client is better if its averabe is better and variance does not make it worse
|
|
// So basically we want this:
|
|
// [-old_std............new_lat.......old_lat...............+new_std.........+old_std]
|
|
//
|
|
// However one can argue that this:
|
|
//
|
|
// [-old_std...................old_lat........new_lat.........+new_std.......+old_std]
|
|
//
|
|
// is still better, but it is up to discussion
|
|
if (new_lat <= old_lat) && ((new_lat + new_std) < (old_lat + old_std)) {
|
|
*x
|
|
} else {
|
|
acc
|
|
}
|
|
});
|
|
|
|
Some((
|
|
min_lat_var_addr.clone(),
|
|
client_list.get(min_lat_var_addr).unwrap().clone(),
|
|
))
|
|
}
|
|
|
|
/// Helperfunction to calculate cumulative average.
|
|
///
|
|
/// Cumulative average calculation is the following problem:
|
|
///
|
|
/// We want to calculate avarage of a sample of size `N + N_1`
|
|
/// where average for `N` is known.
|
|
///
|
|
/// To do so we need:
|
|
/// - old average value
|
|
/// - sum_{`i=1}^{N_1}{n_i`}
|
|
/// - `N`
|
|
/// - `N_1`
|
|
fn cumulative_avg(
|
|
latency_avg_old: f32,
|
|
cumulative_latency: f32,
|
|
orig_size_f: f32,
|
|
mod_size_f: f32,
|
|
) -> f32 {
|
|
latency_avg_old.mul_add(orig_size_f, cumulative_latency) / (orig_size_f + mod_size_f)
|
|
}
|
|
|
|
/// Helperfunction to calculate cumulative variance.
|
|
///
|
|
/// Cumulative variance calculation is the following problem:
|
|
///
|
|
/// We want to calculate variance of a sample of size `N + N_1`
|
|
/// where average for `N` is known.
|
|
///
|
|
/// To do so we need:
|
|
/// - old average value
|
|
/// - new average value
|
|
/// - old variance
|
|
/// - sum_{`i=1}^{N_1}{n_i`}
|
|
/// - sum_{`i=1}^{N_1}{n_i^2`}
|
|
/// - `N`
|
|
/// - `N_1`
|
|
fn cumulative_var(
|
|
latency_avg_old: f32,
|
|
latency_avg_new: f32,
|
|
latency_var: f32,
|
|
cumulative_latency: f32,
|
|
cumulative_latency_squares: f32,
|
|
orig_size_f: f32,
|
|
mod_size_f: f32,
|
|
) -> f32 {
|
|
// The formula was atrocious before.
|
|
// `mul_add` function have less precision loss with drawback of being absolutely unreadable
|
|
((2_f32 * cumulative_latency).mul_add(
|
|
-latency_avg_new,
|
|
mod_size_f.mul_add(
|
|
latency_avg_new * latency_avg_new,
|
|
latency_var.mul_add(
|
|
orig_size_f,
|
|
(latency_avg_new - latency_avg_old)
|
|
* (latency_avg_new - latency_avg_old)
|
|
* orig_size_f,
|
|
),
|
|
),
|
|
) + cumulative_latency_squares)
|
|
/ (orig_size_f + mod_size_f)
|
|
}
|
|
|
|
#[cfg(test)]
|
|
mod tests {
|
|
use std::collections::HashMap;
|
|
|
|
use sequencer_service_rpc::{SequencerClient, SequencerClientBuilder};
|
|
use url::Url;
|
|
|
|
use crate::multi_client::{
|
|
CumulativeUpdates, Metrics, MetricsUpdate, choose_leader, cumulative_avg, cumulative_var,
|
|
};
|
|
|
|
fn update_metrics(
|
|
metrics: &mut HashMap<Url, Metrics>,
|
|
leader_url: &Url,
|
|
metric_updates: &[MetricsUpdate],
|
|
) -> Result<(), anyhow::Error> {
|
|
let leader_metric = metrics
|
|
.get_mut(leader_url)
|
|
.ok_or_else(|| anyhow::anyhow!("Leader URL is not present in metrics"))?;
|
|
|
|
leader_metric.apply_updates(metric_updates);
|
|
|
|
Ok(())
|
|
}
|
|
|
|
fn client_from_url_unchecked(url: &Url) -> SequencerClient {
|
|
let builder = SequencerClientBuilder::default();
|
|
builder.build(url).unwrap()
|
|
}
|
|
|
|
#[test]
|
|
fn cumulative_updates_test() {
|
|
let metrics_updates_vec = vec![
|
|
MetricsUpdate {
|
|
latency: 100_f32,
|
|
new_latest_block_id: Some(15),
|
|
is_failed: false,
|
|
},
|
|
MetricsUpdate {
|
|
latency: 115_f32,
|
|
new_latest_block_id: Some(16),
|
|
is_failed: false,
|
|
},
|
|
MetricsUpdate {
|
|
latency: 50_f32,
|
|
new_latest_block_id: None,
|
|
is_failed: true,
|
|
},
|
|
];
|
|
|
|
let CumulativeUpdates {
|
|
failure_count,
|
|
latest_block_id,
|
|
cumulative_latency,
|
|
cumulative_latency_squares,
|
|
additional_sample_size,
|
|
} = CumulativeUpdates::from_metric_updates(&metrics_updates_vec);
|
|
|
|
let epsilon = 0.01_f32;
|
|
|
|
let sum_squared_manual = 100_f32.mul_add(100_f32, 115_f32 * 115_f32);
|
|
|
|
assert_eq!(additional_sample_size, 2);
|
|
assert_eq!(failure_count, 1);
|
|
assert_eq!(latest_block_id, Some(16));
|
|
assert!((cumulative_latency - 215_f32).abs() < epsilon);
|
|
assert!((cumulative_latency_squares - sum_squared_manual).abs() < epsilon);
|
|
}
|
|
|
|
#[test]
|
|
fn cumulative_avg_test() {
|
|
let mut sample = vec![100_f32; 40];
|
|
|
|
#[expect(clippy::as_conversions, reason = "int to float conversion is safe")]
|
|
let old_sample_size_f = sample.len() as f32;
|
|
|
|
let old_avg = sample.iter().sum::<f32>() / old_sample_size_f;
|
|
|
|
let new_samples = vec![
|
|
101_f32, 110_f32, 112_f32, 97_f32, 78_f32, 25_f32, 75_f32, 189_f32, 120_f32, 50_f32,
|
|
];
|
|
|
|
#[expect(clippy::as_conversions, reason = "int to float conversion is safe")]
|
|
let mod_sample_size_f = new_samples.len() as f32;
|
|
|
|
let cumulative = new_samples.iter().sum();
|
|
|
|
sample.extend_from_slice(&new_samples);
|
|
|
|
#[expect(clippy::as_conversions, reason = "int to float conversion is safe")]
|
|
let new_sample_size_f = sample.len() as f32;
|
|
|
|
let new_avg_1 = sample.iter().sum::<f32>() / new_sample_size_f;
|
|
|
|
let new_avg_2 = cumulative_avg(old_avg, cumulative, old_sample_size_f, mod_sample_size_f);
|
|
|
|
let epsilon = 0.01_f32;
|
|
|
|
assert!((new_avg_1 - new_avg_2).abs() < epsilon);
|
|
}
|
|
|
|
#[test]
|
|
fn cumulative_var_test() {
|
|
let mut sample = vec![100_f32; 40];
|
|
|
|
#[expect(clippy::as_conversions, reason = "int to float conversion is safe")]
|
|
let old_sample_size_f = sample.len() as f32;
|
|
let old_avg = sample.iter().sum::<f32>() / old_sample_size_f;
|
|
|
|
let old_var = sample
|
|
.iter()
|
|
.fold(0_f32, |acc, x| (x - old_avg).mul_add(x - old_avg, acc))
|
|
/ old_sample_size_f;
|
|
|
|
let new_samples = vec![
|
|
101_f32, 110_f32, 112_f32, 97_f32, 78_f32, 25_f32, 75_f32, 189_f32, 120_f32, 50_f32,
|
|
];
|
|
|
|
#[expect(clippy::as_conversions, reason = "int to float conversion is safe")]
|
|
let mod_sample_size_f = new_samples.len() as f32;
|
|
|
|
let cumulative = new_samples.iter().sum();
|
|
let cumulative_squares = new_samples
|
|
.iter()
|
|
.fold(0_f32, |acc, x| (*x).mul_add(*x, acc));
|
|
|
|
let new_avg = cumulative_avg(old_avg, cumulative, old_sample_size_f, mod_sample_size_f);
|
|
|
|
sample.extend_from_slice(&new_samples);
|
|
|
|
#[expect(clippy::as_conversions, reason = "int to float conversion is safe")]
|
|
let new_var_1 = sample
|
|
.iter()
|
|
.fold(0_f32, |acc, x| (x - new_avg).mul_add(x - new_avg, acc))
|
|
/ (sample.len() as f32);
|
|
|
|
let new_var_2 = cumulative_var(
|
|
old_avg,
|
|
new_avg,
|
|
old_var,
|
|
cumulative,
|
|
cumulative_squares,
|
|
old_sample_size_f,
|
|
mod_sample_size_f,
|
|
);
|
|
|
|
let epsilon = 0.01_f32;
|
|
|
|
assert!((new_var_1 - new_var_2).abs() < epsilon);
|
|
}
|
|
|
|
#[test]
|
|
fn metric_updates_correctness() {
|
|
let metrics_updates_vec = vec![
|
|
MetricsUpdate {
|
|
latency: 100_f32,
|
|
new_latest_block_id: Some(105),
|
|
is_failed: false,
|
|
},
|
|
MetricsUpdate {
|
|
latency: 115_f32,
|
|
new_latest_block_id: Some(106),
|
|
is_failed: false,
|
|
},
|
|
MetricsUpdate {
|
|
latency: 50_f32,
|
|
new_latest_block_id: None,
|
|
is_failed: true,
|
|
},
|
|
];
|
|
|
|
let addr_leader = Url::parse("https://127.0.0.1:3040").unwrap();
|
|
|
|
let leader_metrics = Metrics {
|
|
latency_avg: 100_f32,
|
|
latency_var: 25_f32,
|
|
sample_size: 10,
|
|
latest_block_id: 100,
|
|
errors: 5,
|
|
};
|
|
|
|
let cumulative_latency = 100_f32 + 115_f32;
|
|
let cumulative_latency_squares = 100_f32.mul_add(100_f32, 115_f32 * 115_f32);
|
|
|
|
let avg_manual = cumulative_avg(
|
|
leader_metrics.latency_avg,
|
|
cumulative_latency,
|
|
10_f32,
|
|
2_f32,
|
|
);
|
|
let var_manual = cumulative_var(
|
|
leader_metrics.latency_avg,
|
|
avg_manual,
|
|
leader_metrics.latency_var,
|
|
cumulative_latency,
|
|
cumulative_latency_squares,
|
|
10_f32,
|
|
2_f32,
|
|
);
|
|
|
|
let mut metric_map = HashMap::new();
|
|
metric_map.insert(addr_leader.clone(), leader_metrics);
|
|
|
|
update_metrics(&mut metric_map, &addr_leader, &metrics_updates_vec).unwrap();
|
|
|
|
let Metrics {
|
|
latency_avg,
|
|
latency_var,
|
|
sample_size,
|
|
latest_block_id,
|
|
errors,
|
|
} = metric_map[&addr_leader];
|
|
|
|
let epsilon = 0.01_f32;
|
|
|
|
assert_eq!(errors, 6);
|
|
assert_eq!(latest_block_id, 106);
|
|
assert_eq!(sample_size, 12);
|
|
assert!((latency_avg - avg_manual).abs() < epsilon);
|
|
assert!((latency_var - var_manual).abs() < epsilon);
|
|
}
|
|
|
|
#[test]
|
|
fn choose_leader_latest_block() {
|
|
let addr_leader = Url::parse("http://127.0.0.1:3040").unwrap();
|
|
let addr_1 = Url::parse("http://127.0.0.1:3041").unwrap();
|
|
let addr_2 = Url::parse("http://127.0.0.1:3042").unwrap();
|
|
let addr_3 = Url::parse("http://127.0.0.1:3043").unwrap();
|
|
|
|
let leader = client_from_url_unchecked(&addr_leader);
|
|
let client_1 = client_from_url_unchecked(&addr_1);
|
|
let client_2 = client_from_url_unchecked(&addr_2);
|
|
let client_3 = client_from_url_unchecked(&addr_3);
|
|
|
|
let mut client_list = HashMap::new();
|
|
|
|
client_list.insert(addr_leader.clone(), leader);
|
|
client_list.insert(addr_1.clone(), client_1);
|
|
client_list.insert(addr_2.clone(), client_2);
|
|
client_list.insert(addr_3.clone(), client_3);
|
|
|
|
let mut metrics = HashMap::new();
|
|
|
|
metrics.insert(
|
|
addr_3,
|
|
Metrics {
|
|
latency_avg: 100_f32,
|
|
latency_var: 10_f32,
|
|
sample_size: 10,
|
|
latest_block_id: 97,
|
|
errors: 5,
|
|
},
|
|
);
|
|
|
|
metrics.insert(
|
|
addr_2,
|
|
Metrics {
|
|
latency_avg: 100_f32,
|
|
latency_var: 10_f32,
|
|
sample_size: 10,
|
|
latest_block_id: 98,
|
|
errors: 5,
|
|
},
|
|
);
|
|
|
|
metrics.insert(
|
|
addr_1,
|
|
Metrics {
|
|
latency_avg: 100_f32,
|
|
latency_var: 10_f32,
|
|
sample_size: 10,
|
|
latest_block_id: 99,
|
|
errors: 5,
|
|
},
|
|
);
|
|
|
|
metrics.insert(
|
|
addr_leader.clone(),
|
|
Metrics {
|
|
latency_avg: 100_f32,
|
|
latency_var: 10_f32,
|
|
sample_size: 10,
|
|
latest_block_id: 100,
|
|
errors: 5,
|
|
},
|
|
);
|
|
|
|
let (leader_url, _) = choose_leader(&client_list, &metrics).unwrap();
|
|
|
|
assert_eq!(leader_url, addr_leader);
|
|
}
|
|
|
|
#[test]
|
|
fn choose_leader_least_errors() {
|
|
let addr_leader = Url::parse("http://127.0.0.1:3040").unwrap();
|
|
let addr_1 = Url::parse("http://127.0.0.1:3041").unwrap();
|
|
let addr_2 = Url::parse("http://127.0.0.1:3042").unwrap();
|
|
let addr_3 = Url::parse("http://127.0.0.1:3043").unwrap();
|
|
|
|
let leader = client_from_url_unchecked(&addr_leader);
|
|
let client_1 = client_from_url_unchecked(&addr_1);
|
|
let client_2 = client_from_url_unchecked(&addr_2);
|
|
let client_3 = client_from_url_unchecked(&addr_3);
|
|
|
|
let mut client_list = HashMap::new();
|
|
|
|
client_list.insert(addr_leader.clone(), leader);
|
|
client_list.insert(addr_1.clone(), client_1);
|
|
client_list.insert(addr_2.clone(), client_2);
|
|
client_list.insert(addr_3.clone(), client_3);
|
|
|
|
let mut metrics = HashMap::new();
|
|
|
|
metrics.insert(
|
|
addr_3,
|
|
Metrics {
|
|
latency_avg: 100_f32,
|
|
latency_var: 10_f32,
|
|
sample_size: 10,
|
|
latest_block_id: 100,
|
|
errors: 5,
|
|
},
|
|
);
|
|
|
|
metrics.insert(
|
|
addr_2,
|
|
Metrics {
|
|
latency_avg: 100_f32,
|
|
latency_var: 10_f32,
|
|
sample_size: 10,
|
|
latest_block_id: 100,
|
|
errors: 4,
|
|
},
|
|
);
|
|
|
|
metrics.insert(
|
|
addr_1,
|
|
Metrics {
|
|
latency_avg: 100_f32,
|
|
latency_var: 10_f32,
|
|
sample_size: 10,
|
|
latest_block_id: 100,
|
|
errors: 3,
|
|
},
|
|
);
|
|
|
|
metrics.insert(
|
|
addr_leader.clone(),
|
|
Metrics {
|
|
latency_avg: 100_f32,
|
|
latency_var: 10_f32,
|
|
sample_size: 10,
|
|
latest_block_id: 100,
|
|
errors: 2,
|
|
},
|
|
);
|
|
|
|
let (leader_url, _) = choose_leader(&client_list, &metrics).unwrap();
|
|
|
|
assert_eq!(leader_url, addr_leader);
|
|
}
|
|
|
|
#[test]
|
|
fn choose_leader_simple_latency_check() {
|
|
let addr_leader = Url::parse("http://127.0.0.1:3040").unwrap();
|
|
let addr_1 = Url::parse("http://127.0.0.1:3041").unwrap();
|
|
let addr_2 = Url::parse("http://127.0.0.1:3042").unwrap();
|
|
let addr_3 = Url::parse("http://127.0.0.1:3043").unwrap();
|
|
|
|
let leader = client_from_url_unchecked(&addr_leader);
|
|
let client_1 = client_from_url_unchecked(&addr_1);
|
|
let client_2 = client_from_url_unchecked(&addr_2);
|
|
let client_3 = client_from_url_unchecked(&addr_3);
|
|
|
|
let mut client_list = HashMap::new();
|
|
|
|
client_list.insert(addr_leader.clone(), leader);
|
|
client_list.insert(addr_1.clone(), client_1);
|
|
client_list.insert(addr_2.clone(), client_2);
|
|
client_list.insert(addr_3.clone(), client_3);
|
|
|
|
let mut metrics = HashMap::new();
|
|
|
|
metrics.insert(
|
|
addr_3,
|
|
Metrics {
|
|
latency_avg: 103_f32,
|
|
latency_var: 10_f32,
|
|
sample_size: 10,
|
|
latest_block_id: 100,
|
|
errors: 5,
|
|
},
|
|
);
|
|
|
|
metrics.insert(
|
|
addr_2,
|
|
Metrics {
|
|
latency_avg: 102_f32,
|
|
latency_var: 10_f32,
|
|
sample_size: 10,
|
|
latest_block_id: 100,
|
|
errors: 5,
|
|
},
|
|
);
|
|
|
|
metrics.insert(
|
|
addr_1,
|
|
Metrics {
|
|
latency_avg: 101_f32,
|
|
latency_var: 10_f32,
|
|
sample_size: 10,
|
|
latest_block_id: 100,
|
|
errors: 5,
|
|
},
|
|
);
|
|
|
|
metrics.insert(
|
|
addr_leader.clone(),
|
|
Metrics {
|
|
latency_avg: 100_f32,
|
|
latency_var: 10_f32,
|
|
sample_size: 10,
|
|
latest_block_id: 100,
|
|
errors: 5,
|
|
},
|
|
);
|
|
|
|
let (leader_url, _) = choose_leader(&client_list, &metrics).unwrap();
|
|
|
|
assert_eq!(leader_url, addr_leader);
|
|
}
|
|
|
|
#[test]
|
|
fn choose_leader_latency_var_check() {
|
|
let addr_leader = Url::parse("http://127.0.0.1:3040").unwrap();
|
|
let addr_1 = Url::parse("http://127.0.0.1:3041").unwrap();
|
|
let addr_2 = Url::parse("http://127.0.0.1:3042").unwrap();
|
|
let addr_3 = Url::parse("http://127.0.0.1:3043").unwrap();
|
|
|
|
let leader = client_from_url_unchecked(&addr_leader);
|
|
let client_1 = client_from_url_unchecked(&addr_1);
|
|
let client_2 = client_from_url_unchecked(&addr_2);
|
|
let client_3 = client_from_url_unchecked(&addr_3);
|
|
|
|
let mut client_list = HashMap::new();
|
|
|
|
client_list.insert(addr_leader.clone(), leader);
|
|
client_list.insert(addr_1.clone(), client_1);
|
|
client_list.insert(addr_2.clone(), client_2);
|
|
client_list.insert(addr_3.clone(), client_3);
|
|
|
|
let mut metrics = HashMap::new();
|
|
|
|
metrics.insert(
|
|
addr_3,
|
|
Metrics {
|
|
latency_avg: 100_f32,
|
|
latency_var: 13_f32,
|
|
sample_size: 10,
|
|
latest_block_id: 100,
|
|
errors: 5,
|
|
},
|
|
);
|
|
|
|
metrics.insert(
|
|
addr_2,
|
|
Metrics {
|
|
latency_avg: 100_f32,
|
|
latency_var: 12_f32,
|
|
sample_size: 10,
|
|
latest_block_id: 100,
|
|
errors: 5,
|
|
},
|
|
);
|
|
|
|
metrics.insert(
|
|
addr_1,
|
|
Metrics {
|
|
latency_avg: 100_f32,
|
|
latency_var: 11_f32,
|
|
sample_size: 10,
|
|
latest_block_id: 100,
|
|
errors: 5,
|
|
},
|
|
);
|
|
|
|
metrics.insert(
|
|
addr_leader.clone(),
|
|
Metrics {
|
|
latency_avg: 100_f32,
|
|
latency_var: 10_f32,
|
|
sample_size: 10,
|
|
latest_block_id: 100,
|
|
errors: 5,
|
|
},
|
|
);
|
|
|
|
let (leader_url, _) = choose_leader(&client_list, &metrics).unwrap();
|
|
|
|
assert_eq!(leader_url, addr_leader);
|
|
}
|
|
}
|