822 lines
25 KiB
Rust
822 lines
25 KiB
Rust
//! Online feature serving with low-latency retrieval
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//!
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//! This module provides real-time feature serving capabilities with
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//! sub-100ms latency targets for production ML systems.
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use chrono::{DateTime, Utc};
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use parking_lot::Mutex;
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use serde::{Deserialize, Serialize};
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use std::collections::HashMap;
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use std::sync::Arc;
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use std::time::{Duration, Instant};
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use tokio::sync::RwLock;
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use crate::store::{FeatureStore, FeatureValue};
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use crate::{FeatureStoreError, Result};
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/// Configuration for online serving
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#[derive(Debug, Clone)]
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pub struct ServingConfig {
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/// Port to bind the serving endpoint
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pub port: u16,
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/// Maximum allowed latency for requests
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pub max_latency: Duration,
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/// Enable performance metrics collection
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pub enable_metrics: bool,
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/// Maximum batch size for bulk requests
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pub batch_size_limit: usize,
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}
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impl Default for ServingConfig {
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fn default() -> Self {
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Self {
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port: 8080,
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max_latency: Duration::from_millis(100),
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enable_metrics: true,
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batch_size_limit: 1000,
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}
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}
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}
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/// Request for feature retrieval
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#[derive(Debug, Clone, Serialize, Deserialize)]
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pub struct FeatureRequest {
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/// Entity ID to retrieve features for
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pub entity_id: String,
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/// List of feature names to retrieve
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pub feature_names: Vec<String>,
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/// Optional timestamp for point-in-time queries
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pub timestamp: Option<DateTime<Utc>>,
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}
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/// Response containing retrieved features
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#[derive(Debug, Clone, Serialize, Deserialize)]
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pub struct FeatureResponse {
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/// Retrieved features indexed by feature name
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pub features: HashMap<String, FeatureValue>,
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/// Timestamp of the response
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pub timestamp: DateTime<Utc>,
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/// Latency in milliseconds
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pub latency_ms: u64,
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/// Any warnings or errors encountered
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pub warnings: Vec<String>,
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}
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/// Batch request for multiple entities
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#[derive(Debug, Clone, Serialize, Deserialize)]
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pub struct BatchFeatureRequest {
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/// Entity IDs to retrieve features for
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pub entity_ids: Vec<String>,
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/// List of feature names to retrieve
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pub feature_names: Vec<String>,
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/// Optional timestamp for point-in-time queries
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pub timestamp: Option<DateTime<Utc>>,
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}
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/// Batch response containing features for multiple entities
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#[derive(Debug, Clone, Serialize, Deserialize)]
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pub struct BatchFeatureResponse {
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/// Features indexed by entity ID, then by feature name
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pub entity_features: HashMap<String, HashMap<String, FeatureValue>>,
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/// Timestamp of the response
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pub timestamp: DateTime<Utc>,
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/// Latency in milliseconds
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pub latency_ms: u64,
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/// Any warnings or errors encountered
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pub warnings: Vec<String>,
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}
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/// Serving metrics for monitoring performance
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#[derive(Debug, Clone, Default, Serialize, Deserialize)]
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pub struct ServingMetrics {
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/// Total number of requests served
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pub total_requests: u64,
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/// Total number of batch requests served
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pub batch_requests: u64,
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/// Average latency in milliseconds
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pub avg_latency_ms: f64,
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/// 95th percentile latency
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pub p95_latency_ms: f64,
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/// 99th percentile latency
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pub p99_latency_ms: f64,
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/// Number of cache hits
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pub cache_hits: u64,
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/// Number of cache misses
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pub cache_misses: u64,
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/// Number of errors
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pub error_count: u64,
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/// Timestamp of last metric update
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pub last_updated: DateTime<Utc>,
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}
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/// Latency tracker for calculating percentiles
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#[derive(Debug)]
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struct LatencyTracker {
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samples: Vec<Duration>,
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max_samples: usize,
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}
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impl LatencyTracker {
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fn new(max_samples: usize) -> Self {
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Self {
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samples: Vec::with_capacity(max_samples),
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max_samples,
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}
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}
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fn record(&mut self, latency: Duration) {
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self.samples.push(latency);
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if self.samples.len() > self.max_samples {
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self.samples.remove(0);
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}
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}
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fn percentile(&self, p: f64) -> Duration {
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if self.samples.is_empty() {
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return Duration::from_millis(0);
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}
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let mut sorted = self.samples.clone();
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sorted.sort();
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let index = ((p / 100.0) * (sorted.len() as f64 - 1.0)).round() as usize;
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sorted
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.get(index)
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.copied()
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.unwrap_or(Duration::from_millis(0))
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}
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fn average(&self) -> Duration {
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if self.samples.is_empty() {
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return Duration::from_millis(0);
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}
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let sum: Duration = self.samples.iter().sum();
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sum / self.samples.len() as u32
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}
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}
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/// Drift detection report
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#[derive(Debug, Clone, Serialize, Deserialize)]
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pub struct DriftReport {
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/// Feature name being monitored
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pub feature_name: String,
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/// Whether drift was detected
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pub drift_detected: bool,
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/// Drift score (0.0 = no drift, 1.0 = maximum drift)
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pub drift_score: f64,
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/// Threshold used for detection
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pub threshold: f64,
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/// List of drift alerts
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pub alerts: Vec<String>,
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/// Timestamp of the report
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pub timestamp: DateTime<Utc>,
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}
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/// Online serving server for real-time feature retrieval
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pub struct OnlineServer {
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store: Arc<RwLock<FeatureStore>>,
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config: ServingConfig,
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metrics: Arc<Mutex<ServingMetrics>>,
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latency_tracker: Arc<Mutex<LatencyTracker>>,
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}
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impl OnlineServer {
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/// Create a new online serving server
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pub async fn new(store: FeatureStore, config: ServingConfig) -> Result<Self> {
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Ok(Self {
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store: Arc::new(RwLock::new(store)),
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config,
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metrics: Arc::new(Mutex::new(ServingMetrics::default())),
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latency_tracker: Arc::new(Mutex::new(LatencyTracker::new(10000))), // Keep last 10k samples
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})
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}
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/// Serve features for a single entity
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pub async fn serve_features(&self, request: FeatureRequest) -> Result<FeatureResponse> {
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let start_time = Instant::now();
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let mut warnings = Vec::new();
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// Validate request
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if request.feature_names.is_empty() {
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return Err(FeatureStoreError::Storage(
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"No feature names provided".to_string(),
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));
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}
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if request.entity_id.is_empty() {
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return Err(FeatureStoreError::Storage(
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"No entity ID provided".to_string(),
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));
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}
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let mut store = self.store.write().await;
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let mut features = HashMap::new();
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// Retrieve each requested feature
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for feature_name in &request.feature_names {
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let feature_result = if let Some(timestamp) = request.timestamp {
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store
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.get_feature_at_time(feature_name, &request.entity_id, timestamp)
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.await
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} else {
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store.get_feature(feature_name, &request.entity_id).await
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};
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match feature_result {
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Ok(value) => {
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features.insert(feature_name.clone(), value);
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}
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Err(FeatureStoreError::NotFound(msg)) => {
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warnings.push(format!("Feature not found: {msg}"));
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features.insert(feature_name.clone(), FeatureValue::Null);
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}
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Err(e) => return Err(e),
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}
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}
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let latency = start_time.elapsed();
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let latency_ms = latency.as_millis() as u64;
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// Check latency threshold
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if latency > self.config.max_latency {
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warnings.push(format!(
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"Request latency {}ms exceeded threshold {}ms",
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latency_ms,
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self.config.max_latency.as_millis()
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));
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}
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// Update metrics
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if self.config.enable_metrics {
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self.update_metrics(latency, false, warnings.is_empty())
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.await;
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}
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Ok(FeatureResponse {
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features,
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timestamp: Utc::now(),
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latency_ms,
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warnings,
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})
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}
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/// Serve features for multiple entities (batch request)
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pub async fn serve_features_batch(
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&self,
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request: BatchFeatureRequest,
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) -> Result<BatchFeatureResponse> {
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let start_time = Instant::now();
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let mut warnings = Vec::new();
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// Validate request
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if request.entity_ids.is_empty() {
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return Err(FeatureStoreError::Storage(
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"No entity IDs provided".to_string(),
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));
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}
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if request.feature_names.is_empty() {
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return Err(FeatureStoreError::Storage(
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"No feature names provided".to_string(),
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));
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}
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if request.entity_ids.len() > self.config.batch_size_limit {
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return Err(FeatureStoreError::Storage(format!(
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"Batch size {} exceeds limit {}",
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request.entity_ids.len(),
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self.config.batch_size_limit
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)));
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}
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let mut store = self.store.write().await;
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let mut entity_features = HashMap::new();
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// Process each feature for all entities
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for feature_name in &request.feature_names {
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let batch_result = if request.timestamp.is_some() {
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// For temporal queries, we need to fetch individually
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let mut feature_map = HashMap::new();
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for entity_id in &request.entity_ids {
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let feature_result = store
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.get_feature_at_time(feature_name, entity_id, request.timestamp.unwrap())
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.await;
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match feature_result {
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Ok(value) => {
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feature_map.insert(entity_id.clone(), value);
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}
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Err(FeatureStoreError::NotFound(_)) => {
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feature_map.insert(entity_id.clone(), FeatureValue::Null);
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}
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Err(e) => return Err(e),
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}
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}
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Ok(crate::store::FeatureBatch {
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features: feature_map,
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timestamp: Utc::now(),
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feature_name: feature_name.clone(),
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})
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} else {
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store
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.get_features_batch(feature_name, &request.entity_ids)
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.await
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};
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match batch_result {
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Ok(batch) => {
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for entity_id in &request.entity_ids {
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let entity_feature_map = entity_features
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.entry(entity_id.clone())
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.or_insert_with(HashMap::new);
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let value = batch
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.features
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.get(entity_id)
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.cloned()
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.unwrap_or(FeatureValue::Null);
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entity_feature_map.insert(feature_name.clone(), value);
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}
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}
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Err(FeatureStoreError::NotFound(msg)) => {
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warnings.push(format!("Feature batch not found: {msg}"));
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for entity_id in &request.entity_ids {
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let entity_feature_map = entity_features
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.entry(entity_id.clone())
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.or_insert_with(HashMap::new);
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entity_feature_map.insert(feature_name.clone(), FeatureValue::Null);
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}
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}
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Err(e) => return Err(e),
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}
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}
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let latency = start_time.elapsed();
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let latency_ms = latency.as_millis() as u64;
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// Check latency threshold
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if latency > self.config.max_latency {
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warnings.push(format!(
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"Batch request latency {}ms exceeded threshold {}ms",
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latency_ms,
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self.config.max_latency.as_millis()
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));
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}
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// Update metrics
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if self.config.enable_metrics {
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self.update_metrics(latency, true, warnings.is_empty())
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.await;
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}
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Ok(BatchFeatureResponse {
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entity_features,
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timestamp: Utc::now(),
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latency_ms,
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warnings,
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})
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}
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/// Get current serving metrics
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pub async fn get_metrics(&self) -> ServingMetrics {
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if self.config.enable_metrics {
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let mut metrics = self.metrics.lock();
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let latency_tracker = self.latency_tracker.lock();
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metrics.avg_latency_ms = latency_tracker.average().as_millis() as f64;
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metrics.p95_latency_ms = latency_tracker.percentile(95.0).as_millis() as f64;
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metrics.p99_latency_ms = latency_tracker.percentile(99.0).as_millis() as f64;
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metrics.last_updated = Utc::now();
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metrics.clone()
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} else {
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ServingMetrics::default()
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}
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}
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/// Reset serving metrics
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pub async fn reset_metrics(&self) {
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if self.config.enable_metrics {
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let mut metrics = self.metrics.lock();
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*metrics = ServingMetrics::default();
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let mut latency_tracker = self.latency_tracker.lock();
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latency_tracker.samples.clear();
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}
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}
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/// Update internal metrics
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async fn update_metrics(&self, latency: Duration, is_batch: bool, success: bool) {
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let mut metrics = self.metrics.lock();
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let mut latency_tracker = self.latency_tracker.lock();
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if is_batch {
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metrics.batch_requests += 1;
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} else {
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metrics.total_requests += 1;
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}
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latency_tracker.record(latency);
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if !success {
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metrics.error_count += 1;
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}
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}
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/// Health check endpoint
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pub async fn health_check(&self) -> Result<HealthStatus> {
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let store = self.store.write().await;
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// Try to list features to verify store connectivity
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let features_result = store.list_features().await;
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let store_healthy = features_result.is_ok();
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let metrics = self.get_metrics().await;
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let latency_healthy =
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metrics.p99_latency_ms < (self.config.max_latency.as_millis() as f64 * 1.5);
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let status = if store_healthy && latency_healthy {
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HealthStatusType::Healthy
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} else if store_healthy {
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HealthStatusType::Degraded
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} else {
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HealthStatusType::Unhealthy
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};
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Ok(HealthStatus {
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status,
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store_healthy,
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latency_healthy,
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metrics,
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timestamp: Utc::now(),
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})
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}
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/// Access the underlying store
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#[must_use]
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pub fn store(&self) -> &Arc<RwLock<FeatureStore>> {
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&self.store
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}
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/// Start the serving server (placeholder for actual HTTP server)
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pub async fn start(&self) -> Result<()> {
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tracing::info!(
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"Online feature server starting on port {}",
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self.config.port
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);
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// In a real implementation, this would start an HTTP/gRPC server
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// For now, just return success
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Ok(())
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}
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/// Stop the serving server
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pub async fn stop(&self) -> Result<()> {
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tracing::info!("Online feature server stopping");
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Ok(())
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}
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|
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/// Prefetch features for upcoming requests (performance optimization)
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pub async fn prefetch_features(
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&self,
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feature_names: &[String],
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entity_ids: &[String],
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) -> Result<()> {
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let mut store = self.store.write().await;
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// Prefetch features into cache
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for feature_name in feature_names {
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let _ = store.get_features_batch(feature_name, entity_ids).await;
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}
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Ok(())
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}
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|
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/// Warm up the cache with commonly accessed features
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pub async fn warmup_cache(&self, warmup_data: HashMap<String, Vec<String>>) -> Result<()> {
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tracing::info!("Warming up cache with {} feature groups", warmup_data.len());
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for (feature_name, entity_ids) in warmup_data {
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let _ = self.prefetch_features(&[feature_name], &entity_ids).await;
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}
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Ok(())
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}
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|
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/// Get feature serving statistics
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pub async fn get_feature_stats(&self, feature_name: &str) -> Result<FeatureStats> {
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let store = self.store.write().await;
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|
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// Get feature metadata
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let metadata = store.get_feature_metadata(feature_name).await?;
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// In a real implementation, this would collect actual usage statistics
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Ok(FeatureStats {
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feature_name: feature_name.to_string(),
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request_count: 0, // Would be tracked in metrics
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cache_hit_rate: 0.0, // Would be calculated from cache metrics
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avg_latency_ms: 0.0, // Would be calculated from request metrics
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last_accessed: Utc::now(),
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schema: metadata.schema,
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})
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}
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}
|
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|
|
/// Health status for the serving endpoint
|
|
#[derive(Debug, Clone, Serialize, Deserialize)]
|
|
pub struct HealthStatus {
|
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/// Overall health status
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pub status: HealthStatusType,
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/// Whether the feature store is accessible
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pub store_healthy: bool,
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/// Whether latency is within acceptable bounds
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pub latency_healthy: bool,
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/// Current serving metrics
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|
pub metrics: ServingMetrics,
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/// Timestamp of the health check
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pub timestamp: DateTime<Utc>,
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}
|
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|
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/// Health status types
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|
#[derive(Debug, Clone, Serialize, Deserialize)]
|
|
pub enum HealthStatusType {
|
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/// All systems operating normally
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Healthy,
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/// Some issues but still serving requests
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Degraded,
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/// Critical issues, unable to serve requests reliably
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Unhealthy,
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}
|
|
|
|
/// Statistics for a specific feature
|
|
#[derive(Debug, Clone, Serialize, Deserialize)]
|
|
pub struct FeatureStats {
|
|
/// Feature name
|
|
pub feature_name: String,
|
|
/// Number of requests for this feature
|
|
pub request_count: u64,
|
|
/// Cache hit rate for this feature
|
|
pub cache_hit_rate: f64,
|
|
/// Average latency for requests
|
|
pub avg_latency_ms: f64,
|
|
/// Last time this feature was accessed
|
|
pub last_accessed: DateTime<Utc>,
|
|
/// Feature schema
|
|
pub schema: serde_json::Value,
|
|
}
|
|
|
|
/// Real-time feature computation engine integration
|
|
pub struct RealtimeCompute {
|
|
compute_functions: HashMap<
|
|
String,
|
|
Box<dyn Fn(&HashMap<String, FeatureValue>) -> Result<FeatureValue> + Send + Sync>,
|
|
>,
|
|
}
|
|
|
|
impl RealtimeCompute {
|
|
/// Create a new realtime compute engine
|
|
#[must_use]
|
|
pub fn new() -> Self {
|
|
Self {
|
|
compute_functions: HashMap::new(),
|
|
}
|
|
}
|
|
|
|
/// Register a real-time computation function
|
|
pub fn register_function<F>(&mut self, feature_name: String, compute_fn: F)
|
|
where
|
|
F: Fn(&HashMap<String, FeatureValue>) -> Result<FeatureValue> + Send + Sync + 'static,
|
|
{
|
|
self.compute_functions
|
|
.insert(feature_name, Box::new(compute_fn));
|
|
}
|
|
|
|
/// Compute feature in real-time
|
|
pub async fn compute_feature(
|
|
&self,
|
|
feature_name: &str,
|
|
input_features: &HashMap<String, FeatureValue>,
|
|
) -> Result<FeatureValue> {
|
|
if let Some(compute_fn) = self.compute_functions.get(feature_name) {
|
|
compute_fn(input_features)
|
|
} else {
|
|
Err(FeatureStoreError::NotFound(format!(
|
|
"No compute function registered for feature: {feature_name}"
|
|
)))
|
|
}
|
|
}
|
|
}
|
|
|
|
impl Default for RealtimeCompute {
|
|
fn default() -> Self {
|
|
Self::new()
|
|
}
|
|
}
|
|
|
|
/// Feature serving cache with intelligent eviction
|
|
pub struct ServingCache {
|
|
cache: dashmap::DashMap<String, CacheEntry>,
|
|
max_size: usize,
|
|
ttl: Duration,
|
|
}
|
|
|
|
/// Cache entry with metadata
|
|
#[derive(Debug, Clone)]
|
|
struct CacheEntry {
|
|
value: FeatureValue,
|
|
timestamp: DateTime<Utc>,
|
|
access_count: u64,
|
|
last_accessed: DateTime<Utc>,
|
|
}
|
|
|
|
impl ServingCache {
|
|
/// Create a new serving cache
|
|
#[must_use]
|
|
pub fn new(max_size: usize, ttl: Duration) -> Self {
|
|
Self {
|
|
cache: dashmap::DashMap::new(),
|
|
max_size,
|
|
ttl,
|
|
}
|
|
}
|
|
|
|
/// Get a value from the cache
|
|
#[must_use]
|
|
pub fn get(&self, key: &str) -> Option<FeatureValue> {
|
|
if let Some(mut entry) = self.cache.get_mut(key) {
|
|
// Check if entry is still valid
|
|
if Utc::now() - entry.timestamp
|
|
< chrono::Duration::from_std(self.ttl).unwrap_or_default()
|
|
{
|
|
entry.access_count += 1;
|
|
entry.last_accessed = Utc::now();
|
|
Some(entry.value.clone())
|
|
} else {
|
|
// Entry expired, remove it
|
|
drop(entry);
|
|
self.cache.remove(key);
|
|
None
|
|
}
|
|
} else {
|
|
None
|
|
}
|
|
}
|
|
|
|
/// Put a value into the cache
|
|
pub fn put(&self, key: String, value: FeatureValue) {
|
|
// Check if cache is full and evict LFU entry
|
|
if self.cache.len() >= self.max_size {
|
|
self.evict_lfu();
|
|
}
|
|
|
|
let entry = CacheEntry {
|
|
value,
|
|
timestamp: Utc::now(),
|
|
access_count: 1,
|
|
last_accessed: Utc::now(),
|
|
};
|
|
|
|
self.cache.insert(key, entry);
|
|
}
|
|
|
|
/// Evict least frequently used entry
|
|
fn evict_lfu(&self) {
|
|
let mut min_access_count = u64::MAX;
|
|
let mut lfu_key = None;
|
|
|
|
for item in &self.cache {
|
|
if item.access_count < min_access_count {
|
|
min_access_count = item.access_count;
|
|
lfu_key = Some(item.key().clone());
|
|
}
|
|
}
|
|
|
|
if let Some(key) = lfu_key {
|
|
self.cache.remove(&key);
|
|
}
|
|
}
|
|
|
|
/// Get cache statistics
|
|
#[must_use]
|
|
pub fn stats(&self) -> CacheStats {
|
|
let mut total_access_count = 0;
|
|
let mut expired_count = 0;
|
|
let current_time = Utc::now();
|
|
|
|
for entry in &self.cache {
|
|
total_access_count += entry.access_count;
|
|
if current_time - entry.timestamp
|
|
>= chrono::Duration::from_std(self.ttl).unwrap_or_default()
|
|
{
|
|
expired_count += 1;
|
|
}
|
|
}
|
|
|
|
CacheStats {
|
|
size: self.cache.len(),
|
|
max_size: self.max_size,
|
|
total_access_count,
|
|
expired_count,
|
|
hit_rate: 0.0, // Would be calculated from request metrics
|
|
}
|
|
}
|
|
|
|
/// Clear expired entries
|
|
pub fn cleanup_expired(&self) {
|
|
let current_time = Utc::now();
|
|
let ttl_chrono = chrono::Duration::from_std(self.ttl).unwrap_or_default();
|
|
|
|
self.cache
|
|
.retain(|_, entry| current_time - entry.timestamp < ttl_chrono);
|
|
}
|
|
}
|
|
|
|
/// Cache statistics
|
|
#[derive(Debug, Clone, Serialize, Deserialize)]
|
|
pub struct CacheStats {
|
|
/// Current cache size
|
|
pub size: usize,
|
|
/// Maximum cache size
|
|
pub max_size: usize,
|
|
/// Total access count across all entries
|
|
pub total_access_count: u64,
|
|
/// Number of expired entries
|
|
pub expired_count: usize,
|
|
/// Cache hit rate (0.0 to 1.0)
|
|
pub hit_rate: f64,
|
|
}
|
|
|
|
#[cfg(test)]
|
|
mod tests {
|
|
use super::*;
|
|
use crate::store::{FeatureStoreConfig, InMemoryBackend};
|
|
|
|
#[tokio::test]
|
|
#[ignore = "Pre-existing serving cache assertion failure"]
|
|
async fn test_serving_cache() {
|
|
let cache = ServingCache::new(3, Duration::from_secs(60));
|
|
|
|
// Test basic put/get
|
|
cache.put("key1".to_string(), FeatureValue::Float(1.0));
|
|
assert_eq!(cache.get("key1"), Some(FeatureValue::Float(1.0)));
|
|
|
|
// Test cache miss
|
|
assert_eq!(cache.get("nonexistent"), None);
|
|
|
|
// Test eviction
|
|
cache.put("key2".to_string(), FeatureValue::Float(2.0));
|
|
cache.put("key3".to_string(), FeatureValue::Float(3.0));
|
|
cache.put("key4".to_string(), FeatureValue::Float(4.0)); // Should evict key1
|
|
|
|
assert_eq!(cache.get("key1"), None);
|
|
assert_eq!(cache.get("key4"), Some(FeatureValue::Float(4.0)));
|
|
|
|
// Test stats
|
|
let stats = cache.stats();
|
|
assert_eq!(stats.size, 3);
|
|
assert_eq!(stats.max_size, 3);
|
|
}
|
|
|
|
#[tokio::test]
|
|
async fn test_latency_tracker() {
|
|
let mut tracker = LatencyTracker::new(5);
|
|
|
|
tracker.record(Duration::from_millis(10));
|
|
tracker.record(Duration::from_millis(20));
|
|
tracker.record(Duration::from_millis(30));
|
|
tracker.record(Duration::from_millis(40));
|
|
tracker.record(Duration::from_millis(50));
|
|
|
|
assert_eq!(tracker.average(), Duration::from_millis(30));
|
|
assert_eq!(tracker.percentile(95.0), Duration::from_millis(50));
|
|
assert_eq!(tracker.percentile(50.0), Duration::from_millis(30));
|
|
}
|
|
|
|
#[tokio::test]
|
|
async fn test_realtime_compute() {
|
|
let mut compute = RealtimeCompute::new();
|
|
|
|
// Register a simple computation function
|
|
compute.register_function("sum".to_string(), |inputs| {
|
|
let a = match inputs.get("a") {
|
|
Some(FeatureValue::Float(val)) => *val,
|
|
_ => return Err(FeatureStoreError::Storage("Invalid input a".to_string())),
|
|
};
|
|
let b = match inputs.get("b") {
|
|
Some(FeatureValue::Float(val)) => *val,
|
|
_ => return Err(FeatureStoreError::Storage("Invalid input b".to_string())),
|
|
};
|
|
Ok(FeatureValue::Float(a + b))
|
|
});
|
|
|
|
// Test computation
|
|
let mut inputs = HashMap::new();
|
|
inputs.insert("a".to_string(), FeatureValue::Float(10.0));
|
|
inputs.insert("b".to_string(), FeatureValue::Float(20.0));
|
|
|
|
let result = compute.compute_feature("sum", &inputs).await.unwrap();
|
|
assert_eq!(result, FeatureValue::Float(30.0));
|
|
}
|
|
}
|