sklears_compose/
distributed.rs

1//! Distributed pipeline execution components
2//!
3//! This module provides distributed execution capabilities including cluster management,
4//! fault tolerance, load balancing, and MapReduce-style operations.
5
6use scirs2_core::ndarray::{s, Array1, Array2, ArrayView1, ArrayView2};
7use sklears_core::{
8    error::{Result as SklResult, SklearsError},
9    traits::{Estimator, Fit, Untrained},
10    types::Float,
11};
12use std::collections::HashMap;
13use std::net::SocketAddr;
14use std::sync::{Arc, Mutex, RwLock};
15use std::thread::{self, JoinHandle};
16use std::time::{Duration, SystemTime};
17
18use crate::{PipelinePredictor, PipelineStep};
19
20/// Distributed node identifier
21pub type NodeId = String;
22
23/// Distributed task identifier
24pub type TaskId = String;
25
26/// Cluster node information
27#[derive(Debug, Clone)]
28pub struct ClusterNode {
29    /// Node identifier
30    pub id: NodeId,
31    /// Node address
32    pub address: SocketAddr,
33    /// Node status
34    pub status: NodeStatus,
35    /// Available resources
36    pub resources: NodeResources,
37    /// Current load
38    pub load: NodeLoad,
39    /// Heartbeat timestamp
40    pub last_heartbeat: SystemTime,
41    /// Node metadata
42    pub metadata: HashMap<String, String>,
43}
44
45/// Node status enumeration
46#[derive(Debug, Clone, PartialEq)]
47pub enum NodeStatus {
48    /// Node is healthy and available
49    Healthy,
50    /// Node is under heavy load but responsive
51    Stressed,
52    /// Node is temporarily unavailable
53    Unavailable,
54    /// Node has failed
55    Failed,
56    /// Node is shutting down
57    ShuttingDown,
58}
59
60/// Node resource specification
61#[derive(Debug, Clone)]
62pub struct NodeResources {
63    /// Available CPU cores
64    pub cpu_cores: u32,
65    /// Available memory in MB
66    pub memory_mb: u64,
67    /// Available disk space in MB
68    pub disk_mb: u64,
69    /// GPU availability
70    pub gpu_count: u32,
71    /// Network bandwidth in Mbps
72    pub network_bandwidth: u32,
73}
74
75/// Current node load metrics
76#[derive(Debug, Clone)]
77pub struct NodeLoad {
78    /// CPU utilization (0.0 - 1.0)
79    pub cpu_utilization: f64,
80    /// Memory utilization (0.0 - 1.0)
81    pub memory_utilization: f64,
82    /// Disk utilization (0.0 - 1.0)
83    pub disk_utilization: f64,
84    /// Network utilization (0.0 - 1.0)
85    pub network_utilization: f64,
86    /// Active task count
87    pub active_tasks: usize,
88}
89
90impl Default for NodeLoad {
91    fn default() -> Self {
92        Self {
93            cpu_utilization: 0.0,
94            memory_utilization: 0.0,
95            disk_utilization: 0.0,
96            network_utilization: 0.0,
97            active_tasks: 0,
98        }
99    }
100}
101
102/// Distributed task specification
103#[derive(Debug)]
104pub struct DistributedTask {
105    /// Task identifier
106    pub id: TaskId,
107    /// Task name
108    pub name: String,
109    /// Pipeline component to execute
110    pub component: Box<dyn PipelineStep>,
111    /// Input data shards
112    pub input_shards: Vec<DataShard>,
113    /// Task dependencies
114    pub dependencies: Vec<TaskId>,
115    /// Resource requirements
116    pub resource_requirements: ResourceRequirements,
117    /// Task configuration
118    pub config: TaskConfig,
119    /// Task metadata
120    pub metadata: HashMap<String, String>,
121}
122
123/// Data shard for distributed processing
124#[derive(Debug, Clone)]
125pub struct DataShard {
126    /// Shard identifier
127    pub id: String,
128    /// Data content
129    pub data: Array2<f64>,
130    /// Target values (optional)
131    pub targets: Option<Array1<f64>>,
132    /// Shard metadata
133    pub metadata: HashMap<String, String>,
134    /// Source node
135    pub source_node: Option<NodeId>,
136}
137
138/// Resource requirements for tasks
139#[derive(Debug, Clone)]
140pub struct ResourceRequirements {
141    /// Required CPU cores
142    pub cpu_cores: u32,
143    /// Required memory in MB
144    pub memory_mb: u64,
145    /// Required disk space in MB
146    pub disk_mb: u64,
147    /// GPU requirement
148    pub gpu_required: bool,
149    /// Estimated execution time
150    pub estimated_duration: Duration,
151    /// Priority level
152    pub priority: TaskPriority,
153}
154
155/// Task priority levels
156#[derive(Debug, Clone, PartialEq, Eq, PartialOrd, Ord)]
157pub enum TaskPriority {
158    /// Low
159    Low,
160    /// Normal
161    Normal,
162    /// High
163    High,
164    /// Critical
165    Critical,
166}
167
168/// Task execution configuration
169#[derive(Debug, Clone)]
170pub struct TaskConfig {
171    /// Maximum retry attempts
172    pub max_retries: usize,
173    /// Timeout duration
174    pub timeout: Duration,
175    /// Failure tolerance
176    pub failure_tolerance: FailureTolerance,
177    /// Checkpoint interval
178    pub checkpoint_interval: Option<Duration>,
179    /// Result persistence
180    pub persist_results: bool,
181}
182
183/// Failure tolerance strategies
184#[derive(Debug, Clone)]
185pub enum FailureTolerance {
186    /// Fail fast on any error
187    FailFast,
188    /// Retry on specific node
189    RetryOnNode { max_retries: usize },
190    /// Migrate to different node
191    MigrateNode,
192    /// Skip failed shard
193    SkipFailed,
194    /// Use fallback computation
195    Fallback {
196        fallback_fn: fn(&DataShard) -> SklResult<Array2<f64>>,
197    },
198}
199
200/// Task execution result
201#[derive(Debug, Clone)]
202pub struct TaskResult {
203    /// Task identifier
204    pub task_id: TaskId,
205    /// Execution status
206    pub status: TaskStatus,
207    /// Result data
208    pub result: Option<Array2<f64>>,
209    /// Error information
210    pub error: Option<SklearsError>,
211    /// Execution metrics
212    pub metrics: ExecutionMetrics,
213    /// Executed on node
214    pub node_id: NodeId,
215}
216
217/// Task execution status
218#[derive(Debug, Clone, PartialEq)]
219pub enum TaskStatus {
220    /// Pending
221    Pending,
222    /// Running
223    Running,
224    /// Completed
225    Completed,
226    /// Failed
227    Failed,
228    /// Retrying
229    Retrying,
230    /// Cancelled
231    Cancelled,
232}
233
234/// Task execution metrics
235#[derive(Debug, Clone)]
236pub struct ExecutionMetrics {
237    /// Start time
238    pub start_time: SystemTime,
239    /// End time
240    pub end_time: Option<SystemTime>,
241    /// Execution duration
242    pub duration: Option<Duration>,
243    /// Resource usage
244    pub resource_usage: NodeLoad,
245    /// Data transfer metrics
246    pub data_transfer: DataTransferMetrics,
247}
248
249/// Data transfer metrics
250#[derive(Debug, Clone)]
251pub struct DataTransferMetrics {
252    /// Bytes sent
253    pub bytes_sent: u64,
254    /// Bytes received
255    pub bytes_received: u64,
256    /// Transfer duration
257    pub transfer_time: Duration,
258    /// Network errors
259    pub network_errors: usize,
260}
261
262/// Distributed cluster manager
263#[derive(Debug)]
264pub struct ClusterManager {
265    /// Available cluster nodes
266    nodes: Arc<RwLock<HashMap<NodeId, ClusterNode>>>,
267    /// Active tasks
268    active_tasks: Arc<Mutex<HashMap<TaskId, DistributedTask>>>,
269    /// Task results
270    task_results: Arc<Mutex<HashMap<TaskId, TaskResult>>>,
271    /// Load balancer
272    load_balancer: LoadBalancer,
273    /// Fault detector
274    fault_detector: FaultDetector,
275    /// Cluster configuration
276    config: ClusterConfig,
277}
278
279/// Cluster configuration
280#[derive(Debug, Clone)]
281pub struct ClusterConfig {
282    /// Heartbeat interval
283    pub heartbeat_interval: Duration,
284    /// Node failure timeout
285    pub failure_timeout: Duration,
286    /// Max concurrent tasks per node
287    pub max_tasks_per_node: usize,
288    /// Data replication factor
289    pub replication_factor: usize,
290    /// Load balancing strategy
291    pub load_balancing: LoadBalancingStrategy,
292}
293
294impl Default for ClusterConfig {
295    fn default() -> Self {
296        Self {
297            heartbeat_interval: Duration::from_secs(10),
298            failure_timeout: Duration::from_secs(30),
299            max_tasks_per_node: 10,
300            replication_factor: 2,
301            load_balancing: LoadBalancingStrategy::RoundRobin,
302        }
303    }
304}
305
306/// Load balancing strategies
307#[derive(Debug, Clone)]
308pub enum LoadBalancingStrategy {
309    /// Round-robin assignment
310    RoundRobin,
311    /// Least loaded node
312    LeastLoaded,
313    /// Random assignment
314    Random,
315    /// Locality-aware (prefer nodes with data)
316    LocalityAware,
317    /// Custom balancing function
318    Custom {
319        balance_fn: fn(&[ClusterNode], &ResourceRequirements) -> Option<NodeId>,
320    },
321}
322
323/// Load balancer component
324#[derive(Debug)]
325pub struct LoadBalancer {
326    strategy: LoadBalancingStrategy,
327    round_robin_index: Mutex<usize>,
328    node_assignments: Arc<Mutex<HashMap<TaskId, NodeId>>>,
329}
330
331impl LoadBalancer {
332    /// Create a new load balancer
333    #[must_use]
334    pub fn new(strategy: LoadBalancingStrategy) -> Self {
335        Self {
336            strategy,
337            round_robin_index: Mutex::new(0),
338            node_assignments: Arc::new(Mutex::new(HashMap::new())),
339        }
340    }
341
342    /// Select a node for task execution
343    pub fn select_node(
344        &self,
345        nodes: &[ClusterNode],
346        requirements: &ResourceRequirements,
347    ) -> SklResult<NodeId> {
348        let available_nodes: Vec<_> = nodes
349            .iter()
350            .filter(|node| {
351                node.status == NodeStatus::Healthy
352                    && self.can_satisfy_requirements(node, requirements)
353            })
354            .collect();
355
356        if available_nodes.is_empty() {
357            return Err(SklearsError::InvalidInput(
358                "No available nodes satisfy requirements".to_string(),
359            ));
360        }
361
362        match &self.strategy {
363            LoadBalancingStrategy::RoundRobin => {
364                let mut index = self.round_robin_index.lock().unwrap();
365                let selected = &available_nodes[*index % available_nodes.len()];
366                *index = (*index + 1) % available_nodes.len();
367                Ok(selected.id.clone())
368            }
369            LoadBalancingStrategy::LeastLoaded => {
370                let least_loaded = available_nodes
371                    .iter()
372                    .min_by_key(|node| {
373                        (node.load.cpu_utilization * 100.0) as u32 + node.load.active_tasks as u32
374                    })
375                    .unwrap();
376                Ok(least_loaded.id.clone())
377            }
378            LoadBalancingStrategy::Random => {
379                use scirs2_core::random::thread_rng;
380                let mut rng = thread_rng();
381                let selected = &available_nodes[rng.gen_range(0..available_nodes.len())];
382                Ok(selected.id.clone())
383            }
384            LoadBalancingStrategy::LocalityAware => {
385                // Simplified: prefer first available node for now
386                Ok(available_nodes[0].id.clone())
387            }
388            LoadBalancingStrategy::Custom { balance_fn } => {
389                let nodes_vec: Vec<ClusterNode> = available_nodes.into_iter().cloned().collect();
390                balance_fn(&nodes_vec, requirements).ok_or_else(|| {
391                    SklearsError::InvalidInput("Custom balancer failed to select node".to_string())
392                })
393            }
394        }
395    }
396
397    /// Check if node can satisfy resource requirements
398    fn can_satisfy_requirements(
399        &self,
400        node: &ClusterNode,
401        requirements: &ResourceRequirements,
402    ) -> bool {
403        node.resources.cpu_cores >= requirements.cpu_cores
404            && node.resources.memory_mb >= requirements.memory_mb
405            && node.resources.disk_mb >= requirements.disk_mb
406            && (!requirements.gpu_required || node.resources.gpu_count > 0)
407            && node.load.active_tasks < 10 // Max tasks per node
408    }
409}
410
411/// Fault detection and recovery
412#[derive(Debug)]
413pub struct FaultDetector {
414    /// Node failure history
415    failure_history: Arc<Mutex<HashMap<NodeId, Vec<SystemTime>>>>,
416    /// Recovery strategies
417    recovery_strategies: HashMap<String, RecoveryStrategy>,
418}
419
420/// Recovery strategies for different failure types
421#[derive(Debug)]
422pub enum RecoveryStrategy {
423    /// Restart task on same node
424    RestartSameNode,
425    /// Migrate task to different node
426    MigrateTask,
427    /// Replicate task on multiple nodes
428    ReplicateTask { replicas: usize },
429    /// Use cached results
430    UseCachedResults,
431    /// Skip failed task
432    SkipTask,
433}
434
435impl Default for FaultDetector {
436    fn default() -> Self {
437        Self::new()
438    }
439}
440
441impl FaultDetector {
442    /// Create a new fault detector
443    #[must_use]
444    pub fn new() -> Self {
445        let mut recovery_strategies = HashMap::new();
446        recovery_strategies.insert("node_failure".to_string(), RecoveryStrategy::MigrateTask);
447        recovery_strategies.insert(
448            "task_failure".to_string(),
449            RecoveryStrategy::RestartSameNode,
450        );
451        recovery_strategies.insert(
452            "network_partition".to_string(),
453            RecoveryStrategy::ReplicateTask { replicas: 2 },
454        );
455
456        Self {
457            failure_history: Arc::new(Mutex::new(HashMap::new())),
458            recovery_strategies,
459        }
460    }
461
462    /// Detect if a node has failed
463    #[must_use]
464    pub fn detect_node_failure(&self, node: &ClusterNode, timeout: Duration) -> bool {
465        node.last_heartbeat.elapsed().unwrap_or(Duration::MAX) > timeout
466    }
467
468    /// Record a failure event
469    pub fn record_failure(&self, node_id: &NodeId) {
470        let mut history = self.failure_history.lock().unwrap();
471        history
472            .entry(node_id.clone())
473            .or_default()
474            .push(SystemTime::now());
475    }
476
477    /// Get recovery strategy for failure type
478    #[must_use]
479    pub fn get_recovery_strategy(&self, failure_type: &str) -> Option<&RecoveryStrategy> {
480        self.recovery_strategies.get(failure_type)
481    }
482}
483
484impl ClusterManager {
485    /// Create a new cluster manager
486    #[must_use]
487    pub fn new(config: ClusterConfig) -> Self {
488        Self {
489            nodes: Arc::new(RwLock::new(HashMap::new())),
490            active_tasks: Arc::new(Mutex::new(HashMap::new())),
491            task_results: Arc::new(Mutex::new(HashMap::new())),
492            load_balancer: LoadBalancer::new(config.load_balancing.clone()),
493            fault_detector: FaultDetector::new(),
494            config,
495        }
496    }
497
498    /// Add a node to the cluster
499    pub fn add_node(&self, node: ClusterNode) -> SklResult<()> {
500        let mut nodes = self.nodes.write().unwrap();
501        nodes.insert(node.id.clone(), node);
502        Ok(())
503    }
504
505    /// Remove a node from the cluster
506    pub fn remove_node(&self, node_id: &NodeId) -> SklResult<()> {
507        let mut nodes = self.nodes.write().unwrap();
508        nodes.remove(node_id);
509        Ok(())
510    }
511
512    /// Submit a distributed task
513    pub fn submit_task(&self, task: DistributedTask) -> SklResult<TaskId> {
514        let task_id = task.id.clone();
515
516        // Select node for execution
517        let nodes = self.nodes.read().unwrap();
518        let available_nodes: Vec<ClusterNode> = nodes.values().cloned().collect();
519        drop(nodes);
520
521        let selected_node = self
522            .load_balancer
523            .select_node(&available_nodes, &task.resource_requirements)?;
524
525        // Record task
526        let mut active_tasks = self.active_tasks.lock().unwrap();
527        active_tasks.insert(task_id.clone(), task);
528        drop(active_tasks);
529
530        // Execute task (simplified - in real implementation this would be async)
531        self.execute_task_on_node(&task_id, &selected_node)?;
532
533        Ok(task_id)
534    }
535
536    /// Execute a task on a specific node
537    fn execute_task_on_node(&self, task_id: &TaskId, node_id: &NodeId) -> SklResult<()> {
538        let active_tasks = self.active_tasks.lock().unwrap();
539        let task = active_tasks
540            .get(task_id)
541            .ok_or_else(|| SklearsError::InvalidInput(format!("Task {task_id} not found")))?;
542
543        let start_time = SystemTime::now();
544        let mut metrics = ExecutionMetrics {
545            start_time,
546            end_time: None,
547            duration: None,
548            resource_usage: NodeLoad::default(),
549            data_transfer: DataTransferMetrics {
550                bytes_sent: 0,
551                bytes_received: 0,
552                transfer_time: Duration::ZERO,
553                network_errors: 0,
554            },
555        };
556
557        // Simulate task execution
558        let result = self.execute_pipeline_component(&task.component, &task.input_shards);
559
560        let end_time = SystemTime::now();
561        metrics.end_time = Some(end_time);
562        metrics.duration = start_time.elapsed().ok();
563
564        // Store result
565        let (result_data, error_info) = match result {
566            Ok(data) => (Some(data), None),
567            Err(e) => (None, Some(e)),
568        };
569
570        let task_result = TaskResult {
571            task_id: task_id.clone(),
572            status: if result_data.is_some() {
573                TaskStatus::Completed
574            } else {
575                TaskStatus::Failed
576            },
577            result: result_data,
578            error: error_info,
579            metrics,
580            node_id: node_id.clone(),
581        };
582
583        let mut results = self.task_results.lock().unwrap();
584        results.insert(task_id.clone(), task_result);
585
586        Ok(())
587    }
588
589    /// Execute pipeline component on data shards
590    fn execute_pipeline_component(
591        &self,
592        component: &Box<dyn PipelineStep>,
593        shards: &[DataShard],
594    ) -> SklResult<Array2<f64>> {
595        let mut all_results = Vec::new();
596
597        for shard in shards {
598            let mapped_data = shard.data.view().mapv(|v| v as Float);
599            let result = component.transform(&mapped_data.view())?;
600            all_results.push(result);
601        }
602
603        // Concatenate results
604        if all_results.is_empty() {
605            return Ok(Array2::zeros((0, 0)));
606        }
607
608        let total_rows: usize = all_results
609            .iter()
610            .map(scirs2_core::ndarray::ArrayBase::nrows)
611            .sum();
612        let n_cols = all_results[0].ncols();
613
614        let mut concatenated = Array2::zeros((total_rows, n_cols));
615        let mut row_idx = 0;
616
617        for result in all_results {
618            let end_idx = row_idx + result.nrows();
619            concatenated
620                .slice_mut(s![row_idx..end_idx, ..])
621                .assign(&result);
622            row_idx = end_idx;
623        }
624
625        Ok(concatenated)
626    }
627
628    /// Get task result
629    pub fn get_task_result(&self, task_id: &TaskId) -> Option<TaskResult> {
630        let results = self.task_results.lock().unwrap();
631        results.get(task_id).cloned()
632    }
633
634    /// Get cluster status
635    pub fn cluster_status(&self) -> ClusterStatus {
636        let nodes = self.nodes.read().unwrap();
637        let active_tasks = self.active_tasks.lock().unwrap();
638        let task_results = self.task_results.lock().unwrap();
639
640        let healthy_nodes = nodes
641            .values()
642            .filter(|n| n.status == NodeStatus::Healthy)
643            .count();
644        let total_nodes = nodes.len();
645        let pending_tasks = active_tasks.len();
646        let completed_tasks = task_results
647            .values()
648            .filter(|r| r.status == TaskStatus::Completed)
649            .count();
650        let failed_tasks = task_results
651            .values()
652            .filter(|r| r.status == TaskStatus::Failed)
653            .count();
654
655        /// ClusterStatus
656        ClusterStatus {
657            total_nodes,
658            healthy_nodes,
659            pending_tasks,
660            completed_tasks,
661            failed_tasks,
662            cluster_load: self.calculate_cluster_load(&nodes),
663        }
664    }
665
666    /// Calculate overall cluster load
667    fn calculate_cluster_load(&self, nodes: &HashMap<NodeId, ClusterNode>) -> f64 {
668        if nodes.is_empty() {
669            return 0.0;
670        }
671
672        let total_load: f64 = nodes.values().map(|node| node.load.cpu_utilization).sum();
673
674        total_load / nodes.len() as f64
675    }
676
677    /// Start health monitoring
678    pub fn start_health_monitoring(&self) -> JoinHandle<()> {
679        let nodes = Arc::clone(&self.nodes);
680        let fault_detector = FaultDetector::new();
681        let heartbeat_interval = self.config.heartbeat_interval;
682        let failure_timeout = self.config.failure_timeout;
683
684        thread::spawn(move || {
685            loop {
686                thread::sleep(heartbeat_interval);
687
688                let mut nodes_guard = nodes.write().unwrap();
689                let mut failed_nodes = Vec::new();
690
691                for (node_id, node) in nodes_guard.iter_mut() {
692                    if fault_detector.detect_node_failure(node, failure_timeout) {
693                        node.status = NodeStatus::Failed;
694                        failed_nodes.push(node_id.clone());
695                        fault_detector.record_failure(node_id);
696                    }
697                }
698
699                drop(nodes_guard);
700
701                // Handle failed nodes (simplified)
702                for failed_node in failed_nodes {
703                    println!("Node {failed_node} has failed");
704                }
705            }
706        })
707    }
708}
709
710/// Cluster status information
711#[derive(Debug, Clone)]
712pub struct ClusterStatus {
713    /// Total number of nodes
714    pub total_nodes: usize,
715    /// Number of healthy nodes
716    pub healthy_nodes: usize,
717    /// Number of pending tasks
718    pub pending_tasks: usize,
719    /// Number of completed tasks
720    pub completed_tasks: usize,
721    /// Number of failed tasks
722    pub failed_tasks: usize,
723    /// Overall cluster load (0.0 - 1.0)
724    pub cluster_load: f64,
725}
726
727/// MapReduce-style distributed pipeline
728#[derive(Debug)]
729pub struct MapReducePipeline<S = Untrained> {
730    state: S,
731    mapper: Option<Box<dyn PipelineStep>>,
732    reducer: Option<Box<dyn PipelineStep>>,
733    cluster_manager: Arc<ClusterManager>,
734    partitioning_strategy: PartitioningStrategy,
735    map_tasks: Vec<TaskId>,
736    reduce_tasks: Vec<TaskId>,
737}
738
739/// Data partitioning strategies
740#[derive(Debug)]
741pub enum PartitioningStrategy {
742    /// Equal-sized partitions
743    EqualSize { partition_size: usize },
744    /// Hash-based partitioning
745    HashBased { num_partitions: usize },
746    /// Range-based partitioning
747    RangeBased { ranges: Vec<(f64, f64)> },
748    /// Custom partitioning function
749    Custom {
750        partition_fn: fn(&Array2<f64>) -> Vec<DataShard>,
751    },
752}
753
754/// Trained state for `MapReduce` pipeline
755#[derive(Debug)]
756pub struct MapReducePipelineTrained {
757    fitted_mapper: Box<dyn PipelineStep>,
758    fitted_reducer: Box<dyn PipelineStep>,
759    cluster_manager: Arc<ClusterManager>,
760    partitioning_strategy: PartitioningStrategy,
761    n_features_in: usize,
762    feature_names_in: Option<Vec<String>>,
763}
764
765impl MapReducePipeline<Untrained> {
766    /// Create a new `MapReduce` pipeline
767    pub fn new(
768        mapper: Box<dyn PipelineStep>,
769        reducer: Box<dyn PipelineStep>,
770        cluster_manager: Arc<ClusterManager>,
771    ) -> Self {
772        Self {
773            state: Untrained,
774            mapper: Some(mapper),
775            reducer: Some(reducer),
776            cluster_manager,
777            partitioning_strategy: PartitioningStrategy::EqualSize {
778                partition_size: 1000,
779            },
780            map_tasks: Vec::new(),
781            reduce_tasks: Vec::new(),
782        }
783    }
784
785    /// Set partitioning strategy
786    #[must_use]
787    pub fn partitioning_strategy(mut self, strategy: PartitioningStrategy) -> Self {
788        self.partitioning_strategy = strategy;
789        self
790    }
791}
792
793impl Estimator for MapReducePipeline<Untrained> {
794    type Config = ();
795    type Error = SklearsError;
796    type Float = Float;
797
798    fn config(&self) -> &Self::Config {
799        &()
800    }
801}
802
803impl Fit<ArrayView2<'_, Float>, Option<&ArrayView1<'_, Float>>> for MapReducePipeline<Untrained> {
804    type Fitted = MapReducePipeline<MapReducePipelineTrained>;
805
806    fn fit(
807        self,
808        x: &ArrayView2<'_, Float>,
809        y: &Option<&ArrayView1<'_, Float>>,
810    ) -> SklResult<Self::Fitted> {
811        let mut mapper = self
812            .mapper
813            .ok_or_else(|| SklearsError::InvalidInput("No mapper provided".to_string()))?;
814
815        let mut reducer = self
816            .reducer
817            .ok_or_else(|| SklearsError::InvalidInput("No reducer provided".to_string()))?;
818
819        // Fit mapper and reducer on a sample of data
820        mapper.fit(x, y.as_ref().copied())?;
821        reducer.fit(x, y.as_ref().copied())?;
822
823        Ok(MapReducePipeline {
824            state: MapReducePipelineTrained {
825                fitted_mapper: mapper,
826                fitted_reducer: reducer,
827                cluster_manager: self.cluster_manager,
828                partitioning_strategy: self.partitioning_strategy,
829                n_features_in: x.ncols(),
830                feature_names_in: None,
831            },
832            mapper: None,
833            reducer: None,
834            cluster_manager: Arc::new(ClusterManager::new(ClusterConfig::default())),
835            partitioning_strategy: PartitioningStrategy::EqualSize {
836                partition_size: 1000,
837            },
838            map_tasks: Vec::new(),
839            reduce_tasks: Vec::new(),
840        })
841    }
842}
843
844impl MapReducePipeline<MapReducePipelineTrained> {
845    /// Execute `MapReduce` operation
846    pub fn map_reduce(&mut self, x: &ArrayView2<'_, Float>) -> SklResult<Array2<f64>> {
847        // Phase 1: Partition data
848        let partitions = self.partition_data(x)?;
849
850        // Phase 2: Submit map tasks
851        let mut map_task_ids = Vec::new();
852        for (i, partition) in partitions.into_iter().enumerate() {
853            let map_task = DistributedTask {
854                id: format!("map_task_{i}"),
855                name: format!("Map Task {i}"),
856                component: self.state.fitted_mapper.clone_step(),
857                input_shards: vec![partition],
858                dependencies: Vec::new(),
859                resource_requirements: ResourceRequirements {
860                    cpu_cores: 1,
861                    memory_mb: 512,
862                    disk_mb: 100,
863                    gpu_required: false,
864                    estimated_duration: Duration::from_secs(60),
865                    priority: TaskPriority::Normal,
866                },
867                config: TaskConfig {
868                    max_retries: 3,
869                    timeout: Duration::from_secs(300),
870                    failure_tolerance: FailureTolerance::RetryOnNode { max_retries: 2 },
871                    checkpoint_interval: None,
872                    persist_results: true,
873                },
874                metadata: HashMap::new(),
875            };
876
877            let task_id = self.state.cluster_manager.submit_task(map_task)?;
878            map_task_ids.push(task_id);
879        }
880
881        // Phase 3: Wait for map tasks to complete and collect results
882        let map_results = self.wait_for_tasks(&map_task_ids)?;
883
884        // Phase 4: Submit reduce task
885        let reduce_shard = DataShard {
886            id: "reduce_input".to_string(),
887            data: self.combine_map_results(map_results)?,
888            targets: None,
889            metadata: HashMap::new(),
890            source_node: None,
891        };
892
893        let reduce_task = DistributedTask {
894            id: "reduce_task".to_string(),
895            name: "Reduce Task".to_string(),
896            component: self.state.fitted_reducer.clone_step(),
897            input_shards: vec![reduce_shard],
898            dependencies: map_task_ids,
899            resource_requirements: ResourceRequirements {
900                cpu_cores: 2,
901                memory_mb: 1024,
902                disk_mb: 200,
903                gpu_required: false,
904                estimated_duration: Duration::from_secs(120),
905                priority: TaskPriority::High,
906            },
907            config: TaskConfig {
908                max_retries: 3,
909                timeout: Duration::from_secs(600),
910                failure_tolerance: FailureTolerance::RetryOnNode { max_retries: 2 },
911                checkpoint_interval: None,
912                persist_results: true,
913            },
914            metadata: HashMap::new(),
915        };
916
917        let reduce_task_id = self.state.cluster_manager.submit_task(reduce_task)?;
918
919        // Phase 5: Wait for reduce task and return result
920        let reduce_results = self.wait_for_tasks(&[reduce_task_id])?;
921
922        if let Some(result) = reduce_results.into_iter().next() {
923            Ok(result)
924        } else {
925            Err(SklearsError::InvalidData {
926                reason: "Reduce task produced no result".to_string(),
927            })
928        }
929    }
930
931    /// Partition input data
932    fn partition_data(&self, x: &ArrayView2<'_, Float>) -> SklResult<Vec<DataShard>> {
933        match &self.state.partitioning_strategy {
934            PartitioningStrategy::EqualSize { partition_size } => {
935                let mut partitions = Vec::new();
936                let n_rows = x.nrows();
937
938                for (i, chunk_start) in (0..n_rows).step_by(*partition_size).enumerate() {
939                    let chunk_end = std::cmp::min(chunk_start + partition_size, n_rows);
940                    let chunk = x.slice(s![chunk_start..chunk_end, ..]).to_owned();
941
942                    let shard = DataShard {
943                        id: format!("partition_{i}"),
944                        data: chunk.mapv(|v| v),
945                        targets: None,
946                        metadata: HashMap::new(),
947                        source_node: None,
948                    };
949
950                    partitions.push(shard);
951                }
952
953                Ok(partitions)
954            }
955            PartitioningStrategy::HashBased { num_partitions } => {
956                // Simplified hash-based partitioning
957                let mut partitions: Vec<Vec<usize>> = vec![Vec::new(); *num_partitions];
958
959                for i in 0..x.nrows() {
960                    let hash = i % num_partitions; // Simplified hash
961                    partitions[hash].push(i);
962                }
963
964                let mut shards = Vec::new();
965                for (partition_idx, indices) in partitions.into_iter().enumerate() {
966                    if !indices.is_empty() {
967                        let mut partition_data = Array2::zeros((indices.len(), x.ncols()));
968                        for (row_idx, &original_idx) in indices.iter().enumerate() {
969                            partition_data
970                                .row_mut(row_idx)
971                                .assign(&x.row(original_idx).mapv(|v| v));
972                        }
973
974                        let shard = DataShard {
975                            id: format!("hash_partition_{partition_idx}"),
976                            data: partition_data,
977                            targets: None,
978                            metadata: HashMap::new(),
979                            source_node: None,
980                        };
981
982                        shards.push(shard);
983                    }
984                }
985
986                Ok(shards)
987            }
988            PartitioningStrategy::RangeBased { ranges } => {
989                // Simplified range-based partitioning on first feature
990                let mut shards = Vec::new();
991
992                for (range_idx, (min_val, max_val)) in ranges.iter().enumerate() {
993                    let mut selected_rows = Vec::new();
994
995                    for i in 0..x.nrows() {
996                        let feature_val = x[[i, 0]];
997                        if feature_val >= *min_val && feature_val < *max_val {
998                            selected_rows.push(i);
999                        }
1000                    }
1001
1002                    if !selected_rows.is_empty() {
1003                        let mut partition_data = Array2::zeros((selected_rows.len(), x.ncols()));
1004                        for (row_idx, &original_idx) in selected_rows.iter().enumerate() {
1005                            partition_data
1006                                .row_mut(row_idx)
1007                                .assign(&x.row(original_idx).mapv(|v| v));
1008                        }
1009
1010                        let shard = DataShard {
1011                            id: format!("range_partition_{range_idx}"),
1012                            data: partition_data,
1013                            targets: None,
1014                            metadata: HashMap::new(),
1015                            source_node: None,
1016                        };
1017
1018                        shards.push(shard);
1019                    }
1020                }
1021
1022                Ok(shards)
1023            }
1024            PartitioningStrategy::Custom { partition_fn } => Ok(partition_fn(&x.mapv(|v| v))),
1025        }
1026    }
1027
1028    /// Wait for tasks to complete and collect results
1029    fn wait_for_tasks(&self, task_ids: &[TaskId]) -> SklResult<Vec<Array2<f64>>> {
1030        let mut results = Vec::new();
1031
1032        for task_id in task_ids {
1033            // Poll for task completion (simplified)
1034            let mut attempts = 0;
1035            const MAX_ATTEMPTS: usize = 100;
1036
1037            loop {
1038                if let Some(task_result) = self.state.cluster_manager.get_task_result(task_id) {
1039                    match task_result.status {
1040                        TaskStatus::Completed => {
1041                            if let Some(result) = task_result.result {
1042                                results.push(result);
1043                            }
1044                            break;
1045                        }
1046                        TaskStatus::Failed => {
1047                            return Err(task_result.error.unwrap_or_else(|| {
1048                                SklearsError::InvalidData {
1049                                    reason: format!("Task {task_id} failed"),
1050                                }
1051                            }));
1052                        }
1053                        _ => {
1054                            // Task still running
1055                        }
1056                    }
1057                }
1058
1059                attempts += 1;
1060                if attempts >= MAX_ATTEMPTS {
1061                    return Err(SklearsError::InvalidData {
1062                        reason: format!("Task {task_id} timed out"),
1063                    });
1064                }
1065
1066                thread::sleep(Duration::from_millis(100));
1067            }
1068        }
1069
1070        Ok(results)
1071    }
1072
1073    /// Combine map results for reduce phase
1074    fn combine_map_results(&self, results: Vec<Array2<f64>>) -> SklResult<Array2<f64>> {
1075        if results.is_empty() {
1076            return Ok(Array2::zeros((0, 0)));
1077        }
1078
1079        let total_rows: usize = results
1080            .iter()
1081            .map(scirs2_core::ndarray::ArrayBase::nrows)
1082            .sum();
1083        let n_cols = results[0].ncols();
1084
1085        let mut combined = Array2::zeros((total_rows, n_cols));
1086        let mut row_idx = 0;
1087
1088        for result in results {
1089            let end_idx = row_idx + result.nrows();
1090            combined.slice_mut(s![row_idx..end_idx, ..]).assign(&result);
1091            row_idx = end_idx;
1092        }
1093
1094        Ok(combined)
1095    }
1096
1097    /// Get cluster manager
1098    #[must_use]
1099    pub fn cluster_manager(&self) -> &Arc<ClusterManager> {
1100        &self.state.cluster_manager
1101    }
1102}
1103
1104#[allow(non_snake_case)]
1105#[cfg(test)]
1106mod tests {
1107    use super::*;
1108    use crate::MockTransformer;
1109    use scirs2_core::ndarray::array;
1110    use std::net::{IpAddr, Ipv4Addr};
1111
1112    #[test]
1113    fn test_cluster_node_creation() {
1114        let node = ClusterNode {
1115            id: "node1".to_string(),
1116            address: SocketAddr::new(IpAddr::V4(Ipv4Addr::new(127, 0, 0, 1)), 8080),
1117            status: NodeStatus::Healthy,
1118            resources: NodeResources {
1119                cpu_cores: 4,
1120                memory_mb: 8192,
1121                disk_mb: 100000,
1122                gpu_count: 1,
1123                network_bandwidth: 1000,
1124            },
1125            load: NodeLoad::default(),
1126            last_heartbeat: SystemTime::now(),
1127            metadata: HashMap::new(),
1128        };
1129
1130        assert_eq!(node.id, "node1");
1131        assert_eq!(node.status, NodeStatus::Healthy);
1132        assert_eq!(node.resources.cpu_cores, 4);
1133    }
1134
1135    #[test]
1136    fn test_load_balancer_round_robin() {
1137        let balancer = LoadBalancer::new(LoadBalancingStrategy::RoundRobin);
1138
1139        let nodes = vec![
1140            /// ClusterNode
1141            ClusterNode {
1142                id: "node1".to_string(),
1143                address: SocketAddr::new(IpAddr::V4(Ipv4Addr::new(127, 0, 0, 1)), 8080),
1144                status: NodeStatus::Healthy,
1145                resources: NodeResources {
1146                    cpu_cores: 4,
1147                    memory_mb: 8192,
1148                    disk_mb: 100000,
1149                    gpu_count: 0,
1150                    network_bandwidth: 1000,
1151                },
1152                load: NodeLoad::default(),
1153                last_heartbeat: SystemTime::now(),
1154                metadata: HashMap::new(),
1155            },
1156            /// ClusterNode
1157            ClusterNode {
1158                id: "node2".to_string(),
1159                address: SocketAddr::new(IpAddr::V4(Ipv4Addr::new(127, 0, 0, 1)), 8081),
1160                status: NodeStatus::Healthy,
1161                resources: NodeResources {
1162                    cpu_cores: 4,
1163                    memory_mb: 8192,
1164                    disk_mb: 100000,
1165                    gpu_count: 0,
1166                    network_bandwidth: 1000,
1167                },
1168                load: NodeLoad::default(),
1169                last_heartbeat: SystemTime::now(),
1170                metadata: HashMap::new(),
1171            },
1172        ];
1173
1174        let requirements = ResourceRequirements {
1175            cpu_cores: 1,
1176            memory_mb: 1024,
1177            disk_mb: 1000,
1178            gpu_required: false,
1179            estimated_duration: Duration::from_secs(60),
1180            priority: TaskPriority::Normal,
1181        };
1182
1183        let selected1 = balancer.select_node(&nodes, &requirements).unwrap();
1184        let selected2 = balancer.select_node(&nodes, &requirements).unwrap();
1185
1186        assert_ne!(selected1, selected2); // Round robin should alternate
1187    }
1188
1189    #[test]
1190    fn test_cluster_manager() {
1191        let config = ClusterConfig::default();
1192        let manager = ClusterManager::new(config);
1193
1194        let node = ClusterNode {
1195            id: "test_node".to_string(),
1196            address: SocketAddr::new(IpAddr::V4(Ipv4Addr::new(127, 0, 0, 1)), 8080),
1197            status: NodeStatus::Healthy,
1198            resources: NodeResources {
1199                cpu_cores: 4,
1200                memory_mb: 8192,
1201                disk_mb: 100000,
1202                gpu_count: 0,
1203                network_bandwidth: 1000,
1204            },
1205            load: NodeLoad::default(),
1206            last_heartbeat: SystemTime::now(),
1207            metadata: HashMap::new(),
1208        };
1209
1210        manager.add_node(node).unwrap();
1211
1212        let status = manager.cluster_status();
1213        assert_eq!(status.total_nodes, 1);
1214        assert_eq!(status.healthy_nodes, 1);
1215    }
1216
1217    #[test]
1218    fn test_data_shard_creation() {
1219        let data = array![[1.0, 2.0], [3.0, 4.0]];
1220        let targets = array![1.0, 0.0];
1221
1222        let shard = DataShard {
1223            id: "test_shard".to_string(),
1224            data: data.clone(),
1225            targets: Some(targets.clone()),
1226            metadata: HashMap::new(),
1227            source_node: None,
1228        };
1229
1230        assert_eq!(shard.id, "test_shard");
1231        assert_eq!(shard.data, data);
1232        assert_eq!(shard.targets, Some(targets));
1233    }
1234
1235    #[test]
1236    fn test_mapreduce_pipeline_creation() {
1237        let mapper = Box::new(MockTransformer::new());
1238        let reducer = Box::new(MockTransformer::new());
1239        let cluster_manager = Arc::new(ClusterManager::new(ClusterConfig::default()));
1240
1241        let pipeline = MapReducePipeline::new(mapper, reducer, cluster_manager);
1242
1243        assert!(matches!(
1244            pipeline.partitioning_strategy,
1245            PartitioningStrategy::EqualSize {
1246                partition_size: 1000
1247            }
1248        ));
1249    }
1250
1251    #[test]
1252    fn test_fault_detector() {
1253        let detector = FaultDetector::new();
1254
1255        let node = ClusterNode {
1256            id: "test_node".to_string(),
1257            address: SocketAddr::new(IpAddr::V4(Ipv4Addr::new(127, 0, 0, 1)), 8080),
1258            status: NodeStatus::Healthy,
1259            resources: NodeResources {
1260                cpu_cores: 4,
1261                memory_mb: 8192,
1262                disk_mb: 100000,
1263                gpu_count: 0,
1264                network_bandwidth: 1000,
1265            },
1266            load: NodeLoad::default(),
1267            last_heartbeat: SystemTime::now() - Duration::from_secs(60),
1268            metadata: HashMap::new(),
1269        };
1270
1271        let is_failed = detector.detect_node_failure(&node, Duration::from_secs(30));
1272        assert!(is_failed);
1273
1274        detector.record_failure(&node.id);
1275
1276        let strategy = detector.get_recovery_strategy("node_failure");
1277        assert!(matches!(strategy, Some(RecoveryStrategy::MigrateTask)));
1278    }
1279}
sklears_compose/distributed.rs

sklears_compose/
distributed.rs
