#![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, 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, callibration_limit: usize, ) -> Result { 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 Result>( &self, call: I, ) -> (Result, 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, /// 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, 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::() 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, metrics: &HashMap, ) -> 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, 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::() / 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::() / 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::() / 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); } }