sklears_utils/distributed_computing/

types.rs

//! Auto-generated module
//!
//! 🤖 Generated with [SplitRS](https://github.com/cool-japan/splitrs)
//!
//! # GPU-fields scope note (2026-07-06 oxicuda honesty audit)
//!
//! The `gpu_count`/`gpu_usage`/`min_gpu_count`/`gpu_time`/`total_gpu_count`
//! fields on [`NodeCapabilities`], [`LoadMetrics`], [`ResourceUsage`],
//! [`ResourceRequirements`], [`ResourceAllocation`], and the cluster-summary
//! type in this module are pure scheduling/capacity metadata (job requests,
//! node advertised capacity, load-balancer bookkeeping): none of them call
//! any GPU driver/runtime API, so they are out of scope for the
//! scirs2-core-GPU-excision / oxicuda-migration audit and should not be
//! re-flagged by future passes.

use std::collections::{HashMap, HashSet};
use std::hash::Hash;
use std::net::SocketAddr;
use std::sync::{Arc, Mutex, RwLock};
use std::thread;
use std::time::{Duration, Instant};

/// Type alias for message handler function
pub type MessageHandlerFn =
    Box<dyn Fn(&DistributedMessage) -> Result<MessageResponse, DistributedError> + Send + Sync>;

#[derive(Debug, Clone)]
pub struct ResourceReservation {
    pub id: String,
    pub node_id: String,
    pub start_time: Instant,
    pub duration: Duration,
    pub resources: ResourceAllocation,
}
#[derive(Debug, Clone, PartialEq)]
pub enum ConsensusState {
    Follower,
    Candidate,
    Leader,
}
/// Cluster configuration
#[derive(Debug, Clone)]
pub struct ClusterConfig {
    pub heartbeat_interval: Duration,
    pub node_timeout: Duration,
    pub job_timeout: Duration,
    pub max_retries: u32,
    pub load_threshold: f64,
    pub replication_factor: u32,
}
#[derive(Debug, Clone)]
pub enum MessagePriority {
    Low,
    Normal,
    High,
    Critical,
}
#[derive(Debug, Clone)]
pub struct MessageResponse {
    pub message_id: String,
    pub success: bool,
    pub data: Vec<u8>,
    pub error: Option<String>,
}
/// Job priority
#[derive(Debug, Clone, PartialEq, Eq, PartialOrd, Ord)]
pub enum JobPriority {
    Low,
    Normal,
    High,
    Critical,
}
/// Job status
#[derive(Debug, Clone, PartialEq)]
pub enum JobStatus {
    Pending,
    Running,
    Completed,
    Failed,
    Cancelled,
    Timeout,
}
#[derive(Debug, Clone)]
pub struct SchedulingDecision {
    pub job_id: String,
    pub node_id: String,
    pub estimated_start_time: Instant,
    pub resource_allocation: ResourceAllocation,
}
/// Distributed computing errors
#[derive(Debug, thiserror::Error)]
pub enum DistributedError {
    #[error("Node not found")]
    NodeNotFound,
    #[error("Job not found")]
    JobNotFound,
    #[error("Insufficient resources")]
    InsufficientResources,
    #[error("Node unreachable")]
    NodeUnreachable,
    #[error("Job timeout")]
    JobTimeout,
    #[error("Scheduling error: {0}")]
    SchedulingError(String),
    #[error("Communication error: {0}")]
    CommunicationError(String),
}
#[derive(Debug, Clone)]
pub struct VoteRequest {
    pub term: u64,
    pub candidate_id: String,
    pub last_log_index: usize,
    pub last_log_term: u64,
}
#[derive(Debug, Clone)]
pub struct VoteResponse {
    pub term: u64,
    pub vote_granted: bool,
}
/// Advanced distributed computing features
/// Message passing system for inter-node communication
#[allow(dead_code)]
pub struct MessagePassingSystem {
    node_id: String,
    message_handlers: HashMap<String, MessageHandler>,
    pending_messages: Arc<Mutex<Vec<DistributedMessage>>>,
    pub(crate) message_queue: Arc<Mutex<Vec<DistributedMessage>>>,
    pub(crate) routing_table: Arc<RwLock<HashMap<String, SocketAddr>>>,
}
impl MessagePassingSystem {
    /// Create new message passing system
    pub fn new(node_id: String) -> Self {
        Self {
            node_id,
            message_handlers: HashMap::new(),
            pending_messages: Arc::new(Mutex::new(Vec::new())),
            message_queue: Arc::new(Mutex::new(Vec::new())),
            routing_table: Arc::new(RwLock::new(HashMap::new())),
        }
    }
    /// Send message to another node
    pub fn send_message(&self, message: DistributedMessage) -> Result<(), DistributedError> {
        let routing_table = self.routing_table.read().expect("operation should succeed");
        if let Some(_address) = routing_table.get(&message.destination) {
            self.message_queue
                .lock()
                .expect("operation should succeed")
                .push(message);
            Ok(())
        } else {
            Err(DistributedError::NodeUnreachable)
        }
    }
    /// Broadcast message to all nodes
    pub fn broadcast_message(
        &self,
        message_type: MessageType,
        data: Vec<u8>,
    ) -> Result<(), DistributedError> {
        let routing_table = self.routing_table.read().expect("operation should succeed");
        for node_id in routing_table.keys() {
            if node_id != &self.node_id {
                let message = DistributedMessage {
                    id: format!("{}_{}", self.node_id, Instant::now().elapsed().as_millis()),
                    source: self.node_id.clone(),
                    destination: node_id.clone(),
                    message_type: message_type.clone(),
                    data: data.clone(),
                    timestamp: Instant::now(),
                    priority: MessagePriority::Normal,
                };
                self.send_message(message)?;
            }
        }
        Ok(())
    }
    /// Register message handler
    pub fn register_handler(&mut self, message_type: String, handler: MessageHandler) {
        self.message_handlers.insert(message_type, handler);
    }
    /// Process incoming messages
    pub fn process_messages(&self) -> Result<Vec<MessageResponse>, DistributedError> {
        let mut responses = Vec::new();
        let mut queue = self.message_queue.lock().expect("operation should succeed");
        for message in queue.drain(..) {
            if let Some(handler) = self
                .message_handlers
                .get(&format!("{}", message.message_type))
            {
                let response = handler.handle(&message)?;
                responses.push(response);
            }
        }
        Ok(responses)
    }
}
#[derive(Debug, Clone)]
pub struct PeerInfo {
    pub id: String,
    pub next_index: usize,
    pub match_index: usize,
    pub last_response: Instant,
}
/// Advanced job scheduler with gang scheduling
#[allow(dead_code)]
pub struct AdvancedJobScheduler {
    scheduling_policies: Vec<SchedulingPolicy>,
    pub(crate) resource_reservations: HashMap<String, ResourceReservation>,
    job_dependencies: HashMap<String, Vec<String>>,
    priority_queues: HashMap<JobPriority, Vec<DistributedJob>>,
    backfill_enabled: bool,
}
impl AdvancedJobScheduler {
    /// Create new advanced scheduler
    pub fn new() -> Self {
        Self {
            scheduling_policies: vec![
                SchedulingPolicy::FIFO,
                SchedulingPolicy::ShortestJobFirst,
                SchedulingPolicy::GangScheduling,
            ],
            resource_reservations: HashMap::new(),
            job_dependencies: HashMap::new(),
            priority_queues: HashMap::new(),
            backfill_enabled: true,
        }
    }
    /// Schedule jobs with gang scheduling
    pub fn gang_schedule(
        &mut self,
        jobs: &[DistributedJob],
        nodes: &HashMap<String, ClusterNode>,
    ) -> Result<Vec<SchedulingDecision>, DistributedError> {
        let mut decisions = Vec::new();
        let job_groups = self.group_related_jobs(jobs);
        for group in job_groups {
            if let Some(node_assignment) = self.find_gang_assignment(&group, nodes) {
                for (job, node_id) in group.iter().zip(node_assignment.iter()) {
                    decisions.push(SchedulingDecision {
                        job_id: job.id.clone(),
                        node_id: node_id.clone(),
                        estimated_start_time: Instant::now(),
                        resource_allocation: self
                            .calculate_resource_allocation(job, node_id, nodes),
                    });
                }
            }
        }
        Ok(decisions)
    }
    /// Implement backfill scheduling
    pub fn backfill_schedule(
        &mut self,
        waiting_jobs: &[DistributedJob],
        nodes: &HashMap<String, ClusterNode>,
    ) -> Result<Vec<SchedulingDecision>, DistributedError> {
        let mut decisions = Vec::new();
        if !self.backfill_enabled {
            return Ok(decisions);
        }
        for job in waiting_jobs {
            for (node_id, node) in nodes {
                if self.can_backfill_job(job, node) {
                    decisions.push(SchedulingDecision {
                        job_id: job.id.clone(),
                        node_id: node_id.clone(),
                        estimated_start_time: Instant::now(),
                        resource_allocation: self
                            .calculate_resource_allocation(job, node_id, nodes),
                    });
                    break;
                }
            }
        }
        Ok(decisions)
    }
    /// Reserve resources for future jobs
    pub fn reserve_resources(
        &mut self,
        reservation: ResourceReservation,
    ) -> Result<(), DistributedError> {
        self.resource_reservations
            .insert(reservation.id.clone(), reservation);
        Ok(())
    }
    fn group_related_jobs(&self, jobs: &[DistributedJob]) -> Vec<Vec<DistributedJob>> {
        vec![jobs.to_vec()]
    }
    fn find_gang_assignment(
        &self,
        job_group: &[DistributedJob],
        nodes: &HashMap<String, ClusterNode>,
    ) -> Option<Vec<String>> {
        if job_group.len() <= nodes.len() {
            Some(nodes.keys().take(job_group.len()).cloned().collect())
        } else {
            None
        }
    }
    fn can_backfill_job(&self, _job: &DistributedJob, _node: &ClusterNode) -> bool {
        true
    }
    fn calculate_resource_allocation(
        &self,
        job: &DistributedJob,
        _node_id: &str,
        _nodes: &HashMap<String, ClusterNode>,
    ) -> ResourceAllocation {
        ResourceAllocation {
            cpu_cores: job.requirements.min_cpu_cores,
            memory_gb: job.requirements.min_memory_gb,
            gpu_count: job.requirements.min_gpu_count,
            storage_gb: job.requirements.min_storage_gb,
            network_bandwidth: 100,
        }
    }
}
#[derive(Debug, Clone)]
pub struct PartitionMove {
    pub partition: usize,
    pub from_node: String,
    pub to_node: String,
}
#[derive(Debug, Clone)]
pub struct CheckpointStats {
    pub total_checkpoints: usize,
    pub total_size_bytes: u64,
    pub compressed_checkpoints: usize,
    pub compression_ratio: f64,
}
/// Job scheduler
pub struct JobScheduler {
    scheduling_strategy: SchedulingStrategy,
}
impl JobScheduler {
    /// Create new job scheduler
    pub fn new() -> Self {
        Self {
            scheduling_strategy: SchedulingStrategy::LeastLoaded,
        }
    }
    /// Find suitable node for job
    pub fn find_suitable_node(
        &self,
        job: &DistributedJob,
        nodes: &HashMap<String, ClusterNode>,
    ) -> Option<String> {
        let suitable_nodes: Vec<_> = nodes
            .values()
            .filter(|node| self.can_run_job(node, job))
            .collect();
        if suitable_nodes.is_empty() {
            return None;
        }
        match self.scheduling_strategy {
            SchedulingStrategy::LeastLoaded => suitable_nodes
                .iter()
                .min_by(|a, b| {
                    let load_a = a.load_metrics.cpu_usage + a.load_metrics.memory_usage;
                    let load_b = b.load_metrics.cpu_usage + b.load_metrics.memory_usage;
                    load_a
                        .partial_cmp(&load_b)
                        .unwrap_or(std::cmp::Ordering::Equal)
                })
                .map(|node| node.id.clone()),
            SchedulingStrategy::RoundRobin => suitable_nodes.first().map(|node| node.id.clone()),
            SchedulingStrategy::HighestCapacity => suitable_nodes
                .iter()
                .max_by_key(|node| node.capabilities.cpu_cores * node.capabilities.memory_gb)
                .map(|node| node.id.clone()),
        }
    }
    /// Check if node can run job
    fn can_run_job(&self, node: &ClusterNode, job: &DistributedJob) -> bool {
        node.status == NodeStatus::Available
            && node.capabilities.cpu_cores >= job.requirements.min_cpu_cores
            && node.capabilities.memory_gb >= job.requirements.min_memory_gb
            && node.capabilities.gpu_count >= job.requirements.min_gpu_count
            && node.capabilities.storage_gb >= job.requirements.min_storage_gb
    }
}
/// Checkpointing and recovery system
pub struct CheckpointManager {
    pub(crate) checkpoint_storage: HashMap<String, Checkpoint>,
    #[allow(dead_code)]
    checkpoint_interval: Duration,
    compression_enabled: bool,
}
impl CheckpointManager {
    /// Create new checkpoint manager
    pub fn new(checkpoint_interval: Duration) -> Self {
        Self {
            checkpoint_storage: HashMap::new(),
            checkpoint_interval,
            compression_enabled: true,
        }
    }
    /// Create checkpoint for job
    pub fn create_checkpoint(
        &mut self,
        job_id: &str,
        state: JobState,
    ) -> Result<String, DistributedError> {
        let checkpoint_id = format!("{job_id}_{}", Instant::now().elapsed().as_millis());
        let checkpoint = Checkpoint {
            id: checkpoint_id.clone(),
            job_id: job_id.to_string(),
            state,
            created_at: Instant::now(),
            size_bytes: 1024,
            compressed: self.compression_enabled,
        };
        self.checkpoint_storage
            .insert(checkpoint_id.clone(), checkpoint);
        Ok(checkpoint_id)
    }
    /// Restore job from checkpoint
    pub fn restore_checkpoint(&self, checkpoint_id: &str) -> Result<JobState, DistributedError> {
        self.checkpoint_storage
            .get(checkpoint_id)
            .map(|checkpoint| checkpoint.state.clone())
            .ok_or(DistributedError::JobNotFound)
    }
    /// Clean up old checkpoints
    pub fn cleanup_old_checkpoints(&mut self, retention_period: Duration) {
        let cutoff = Instant::now() - retention_period;
        self.checkpoint_storage
            .retain(|_, checkpoint| checkpoint.created_at > cutoff);
    }
    /// Get checkpoint statistics
    pub fn get_checkpoint_stats(&self) -> CheckpointStats {
        let total_checkpoints = self.checkpoint_storage.len();
        let total_size: u64 = self.checkpoint_storage.values().map(|c| c.size_bytes).sum();
        let compressed_checkpoints = self
            .checkpoint_storage
            .values()
            .filter(|c| c.compressed)
            .count();
        CheckpointStats {
            total_checkpoints,
            total_size_bytes: total_size,
            compressed_checkpoints,
            compression_ratio: if total_checkpoints > 0 {
                compressed_checkpoints as f64 / total_checkpoints as f64
            } else {
                0.0
            },
        }
    }
}
/// Node information in distributed cluster
#[derive(Debug, Clone)]
pub struct ClusterNode {
    pub id: String,
    pub address: SocketAddr,
    pub capabilities: NodeCapabilities,
    pub status: NodeStatus,
    pub last_heartbeat: Instant,
    pub load_metrics: LoadMetrics,
    pub job_history: Vec<JobExecution>,
}
#[derive(Debug, Clone)]
pub struct LogEntry {
    pub term: u64,
    pub index: usize,
    pub command: String,
    pub data: Vec<u8>,
}
#[derive(Debug, Clone)]
pub struct DistributedMessage {
    pub id: String,
    pub source: String,
    pub destination: String,
    pub message_type: MessageType,
    pub data: Vec<u8>,
    pub timestamp: Instant,
    pub priority: MessagePriority,
}
#[derive(Debug, Clone)]
pub struct JobState {
    pub progress: f64,
    pub intermediate_results: HashMap<String, Vec<u8>>,
    pub runtime_state: Vec<u8>,
}
/// Data partitioning and sharding system
pub struct DataPartitioner {
    partitioning_strategy: PartitioningStrategy,
    partition_count: usize,
    node_assignments: HashMap<usize, String>,
    replication_factor: usize,
}
impl DataPartitioner {
    /// Create new data partitioner
    pub fn new(
        strategy: PartitioningStrategy,
        partition_count: usize,
        replication_factor: usize,
    ) -> Self {
        Self {
            partitioning_strategy: strategy,
            partition_count,
            node_assignments: HashMap::new(),
            replication_factor,
        }
    }
    /// Determine partition for data key
    pub fn get_partition(&self, key: &str) -> usize {
        match self.partitioning_strategy {
            PartitioningStrategy::Hash => {
                use std::collections::hash_map::DefaultHasher;
                use std::hash::Hasher;
                let mut hasher = DefaultHasher::new();
                key.hash(&mut hasher);
                (hasher.finish() as usize) % self.partition_count
            }
            PartitioningStrategy::Range => key.len() % self.partition_count,
            PartitioningStrategy::Random => key.len() % self.partition_count,
        }
    }
    /// Get nodes responsible for partition
    pub fn get_partition_nodes(&self, partition: usize) -> Vec<String> {
        let mut nodes = Vec::new();
        if let Some(primary_node) = self.node_assignments.get(&partition) {
            nodes.push(primary_node.clone());
            for i in 1..self.replication_factor {
                let replica_partition = (partition + i) % self.partition_count;
                if let Some(replica_node) = self.node_assignments.get(&replica_partition) {
                    if !nodes.contains(replica_node) {
                        nodes.push(replica_node.clone());
                    }
                }
            }
        }
        nodes
    }
    /// Assign partition to node
    pub fn assign_partition(&mut self, partition: usize, node_id: String) {
        self.node_assignments.insert(partition, node_id);
    }
    /// Rebalance partitions across nodes
    pub fn rebalance_partitions(&mut self, available_nodes: &[String]) -> PartitioningResult {
        let mut assignments_changed = 0;
        let mut partitions_moved = Vec::new();
        for partition in 0..self.partition_count {
            let optimal_node = &available_nodes[partition % available_nodes.len()];
            if let Some(current_node) = self.node_assignments.get(&partition) {
                if current_node != optimal_node {
                    partitions_moved.push(PartitionMove {
                        partition,
                        from_node: current_node.clone(),
                        to_node: optimal_node.clone(),
                    });
                    self.node_assignments
                        .insert(partition, optimal_node.clone());
                    assignments_changed += 1;
                }
            } else {
                self.node_assignments
                    .insert(partition, optimal_node.clone());
                assignments_changed += 1;
            }
        }
        PartitioningResult {
            assignments_changed,
            partitions_moved,
            rebalance_time: Instant::now(),
        }
    }
}
/// Cluster statistics
#[derive(Debug, Clone)]
pub struct ClusterStats {
    pub total_nodes: usize,
    pub available_nodes: usize,
    pub busy_nodes: usize,
    pub overloaded_nodes: usize,
    pub unreachable_nodes: usize,
    pub total_jobs: usize,
    pub running_jobs: usize,
    pub completed_jobs: usize,
    pub failed_jobs: usize,
    pub queued_jobs: usize,
    pub total_cpu_cores: u32,
    pub total_memory_gb: u32,
    pub total_gpu_count: u32,
    pub avg_cpu_usage: f64,
    pub avg_memory_usage: f64,
}
pub struct MessageHandler {
    pub handler_fn: MessageHandlerFn,
}
impl MessageHandler {
    pub fn new<F>(f: F) -> Self
    where
        F: Fn(&DistributedMessage) -> Result<MessageResponse, DistributedError>
            + Send
            + Sync
            + 'static,
    {
        Self {
            handler_fn: Box::new(f),
        }
    }
    pub fn handle(
        &self,
        message: &DistributedMessage,
    ) -> Result<MessageResponse, DistributedError> {
        (self.handler_fn)(message)
    }
}
/// Fault detector
pub struct FaultDetector {
    failure_history: HashMap<String, Vec<Instant>>,
}
impl FaultDetector {
    /// Create new fault detector
    pub fn new() -> Self {
        Self {
            failure_history: HashMap::new(),
        }
    }
    /// Handle node failure
    pub fn handle_failure(&mut self, node_id: &str) -> Result<(), DistributedError> {
        let failures = self.failure_history.entry(node_id.to_string()).or_default();
        failures.push(Instant::now());
        let cutoff = Instant::now() - Duration::from_secs(3600);
        failures.retain(|&failure_time| failure_time > cutoff);
        if failures.len() > 3 {
            println!("Node {node_id} has too many failures, marking as problematic");
        }
        Ok(())
    }
    /// Check if node is problematic
    pub fn is_problematic(&self, node_id: &str) -> bool {
        self.failure_history
            .get(node_id)
            .map(|failures| failures.len() > 3)
            .unwrap_or(false)
    }
}
#[derive(Debug, Clone)]
pub enum MessageType {
    JobSubmission,
    JobResult,
    Heartbeat,
    ResourceUpdate,
    ConsensusRequest,
    DataPartition,
    Custom(String),
}
/// Load balancer
pub struct LoadBalancer {
    rebalance_threshold: f64,
}
impl LoadBalancer {
    /// Create new load balancer
    pub fn new() -> Self {
        Self {
            rebalance_threshold: 0.8,
        }
    }
    /// Rebalance workload across nodes
    pub fn rebalance(&self, nodes: &HashMap<String, ClusterNode>) -> Result<(), DistributedError> {
        let overloaded_nodes: Vec<_> = nodes
            .values()
            .filter(|node| {
                let total_load = node.load_metrics.cpu_usage + node.load_metrics.memory_usage;
                total_load > self.rebalance_threshold * 2.0
            })
            .collect();
        let underloaded_nodes: Vec<_> = nodes
            .values()
            .filter(|node| {
                let total_load = node.load_metrics.cpu_usage + node.load_metrics.memory_usage;
                total_load < self.rebalance_threshold
            })
            .collect();
        println!(
            "Rebalancing: {} overloaded nodes, {} underloaded nodes",
            overloaded_nodes.len(),
            underloaded_nodes.len()
        );
        Ok(())
    }
}
/// Node status
#[derive(Debug, Clone, PartialEq)]
pub enum NodeStatus {
    Available,
    Busy,
    Overloaded,
    Unreachable,
    Maintenance,
}
/// Job type
#[derive(Debug, Clone, PartialEq)]
pub enum JobType {
    Training,
    Inference,
    DataProcessing,
    ModelEvaluation,
    Hyperparameter,
    Custom(String),
}
#[derive(Debug, Clone)]
pub struct Checkpoint {
    pub id: String,
    pub job_id: String,
    pub state: JobState,
    pub created_at: Instant,
    pub size_bytes: u64,
    pub compressed: bool,
}
/// Node load metrics
#[derive(Debug, Clone)]
pub struct LoadMetrics {
    pub cpu_usage: f64,
    pub memory_usage: f64,
    pub gpu_usage: f64,
    pub network_io: f64,
    pub disk_io: f64,
    pub active_jobs: u32,
    pub queue_size: u32,
}
/// Distributed job information
#[derive(Debug, Clone)]
pub struct DistributedJob {
    pub id: String,
    pub name: String,
    pub job_type: JobType,
    pub priority: JobPriority,
    pub requirements: ResourceRequirements,
    pub created_at: Instant,
    pub timeout: Duration,
    pub retry_count: u32,
    pub dependencies: Vec<String>,
    pub metadata: HashMap<String, String>,
}
/// Scheduling strategy
#[derive(Debug, Clone)]
pub enum SchedulingStrategy {
    LeastLoaded,
    RoundRobin,
    HighestCapacity,
}
/// Resource usage during job execution
#[derive(Debug, Clone)]
pub struct ResourceUsage {
    pub cpu_time: Duration,
    pub memory_peak: u64,
    pub gpu_time: Duration,
    pub network_bytes: u64,
    pub disk_bytes: u64,
}
/// Node capabilities
#[derive(Debug, Clone)]
pub struct NodeCapabilities {
    pub cpu_cores: u32,
    pub memory_gb: u32,
    pub gpu_count: u32,
    pub storage_gb: u32,
    pub network_bandwidth_mbps: u32,
    pub supported_tasks: HashSet<String>,
}
/// Consensus algorithm implementation (simplified Raft)
#[allow(dead_code)]
pub struct ConsensusManager {
    node_id: String,
    pub(crate) state: ConsensusState,
    term: u64,
    voted_for: Option<String>,
    pub(crate) log: Vec<LogEntry>,
    commit_index: usize,
    last_applied: usize,
    peers: HashMap<String, PeerInfo>,
}
impl ConsensusManager {
    /// Create new consensus manager
    pub fn new(node_id: String, peers: Vec<String>) -> Self {
        let mut peer_map = HashMap::new();
        for peer in peers {
            peer_map.insert(
                peer.clone(),
                PeerInfo {
                    id: peer,
                    next_index: 0,
                    match_index: 0,
                    last_response: Instant::now(),
                },
            );
        }
        Self {
            node_id,
            state: ConsensusState::Follower,
            term: 0,
            voted_for: None,
            log: Vec::new(),
            commit_index: 0,
            last_applied: 0,
            peers: peer_map,
        }
    }
    /// Start leader election
    pub fn start_election(&mut self) -> Result<(), DistributedError> {
        self.state = ConsensusState::Candidate;
        self.term += 1;
        self.voted_for = Some(self.node_id.clone());
        println!(
            "Node {} starting election for term {}",
            self.node_id, self.term
        );
        Ok(())
    }
    /// Handle vote request
    pub fn handle_vote_request(&mut self, request: VoteRequest) -> VoteResponse {
        let grant_vote = if request.term > self.term {
            self.term = request.term;
            self.voted_for = None;
            self.state = ConsensusState::Follower;
            true
        } else if request.term == self.term
            && (self.voted_for.is_none() || self.voted_for.as_ref() == Some(&request.candidate_id))
        {
            self.voted_for = Some(request.candidate_id.clone());
            true
        } else {
            false
        };
        VoteResponse {
            term: self.term,
            vote_granted: grant_vote,
        }
    }
    /// Append log entry
    pub fn append_entry(&mut self, entry: LogEntry) -> Result<(), DistributedError> {
        if self.state != ConsensusState::Leader {
            return Err(DistributedError::SchedulingError("Not leader".to_string()));
        }
        self.log.push(entry);
        Ok(())
    }
    /// Get current state
    pub fn get_state(&self) -> (ConsensusState, u64) {
        (self.state.clone(), self.term)
    }
}
#[derive(Debug, Clone)]
pub struct PartitioningResult {
    pub assignments_changed: usize,
    pub partitions_moved: Vec<PartitionMove>,
    pub rebalance_time: Instant,
}
#[derive(Debug, Clone)]
pub enum PartitioningStrategy {
    Hash,
    Range,
    Random,
}
#[derive(Debug, Clone)]
pub enum SchedulingPolicy {
    FIFO,
    ShortestJobFirst,
    GangScheduling,
    Backfill,
    PriorityBased,
}
/// Distributed computing cluster manager
pub struct DistributedCluster {
    nodes: Arc<RwLock<HashMap<String, ClusterNode>>>,
    jobs: Arc<RwLock<HashMap<String, DistributedJob>>>,
    executions: Arc<RwLock<HashMap<String, JobExecution>>>,
    pub(crate) job_queue: Arc<Mutex<Vec<DistributedJob>>>,
    scheduler: Arc<Mutex<JobScheduler>>,
    load_balancer: Arc<Mutex<LoadBalancer>>,
    fault_detector: Arc<Mutex<FaultDetector>>,
    config: ClusterConfig,
}
impl DistributedCluster {
    /// Create new distributed cluster
    pub fn new(config: ClusterConfig) -> Self {
        Self {
            nodes: Arc::new(RwLock::new(HashMap::new())),
            jobs: Arc::new(RwLock::new(HashMap::new())),
            executions: Arc::new(RwLock::new(HashMap::new())),
            job_queue: Arc::new(Mutex::new(Vec::new())),
            scheduler: Arc::new(Mutex::new(JobScheduler::new())),
            load_balancer: Arc::new(Mutex::new(LoadBalancer::new())),
            fault_detector: Arc::new(Mutex::new(FaultDetector::new())),
            config,
        }
    }
    /// Register a node in the cluster
    pub fn register_node(&self, node: ClusterNode) -> Result<(), DistributedError> {
        let mut nodes = self.nodes.write().expect("operation should succeed");
        nodes.insert(node.id.clone(), node);
        Ok(())
    }
    /// Remove a node from the cluster
    pub fn remove_node(&self, node_id: &str) -> Result<(), DistributedError> {
        let mut nodes = self.nodes.write().expect("operation should succeed");
        nodes
            .remove(node_id)
            .ok_or(DistributedError::NodeNotFound)?;
        Ok(())
    }
    /// Get all nodes in the cluster
    pub fn get_nodes(&self) -> Vec<ClusterNode> {
        self.nodes
            .read()
            .expect("operation should succeed")
            .values()
            .cloned()
            .collect()
    }
    /// Get available nodes
    pub fn get_available_nodes(&self) -> Vec<ClusterNode> {
        self.nodes
            .read()
            .expect("operation should succeed")
            .values()
            .filter(|node| node.status == NodeStatus::Available)
            .cloned()
            .collect()
    }
    /// Submit a job to the cluster
    pub fn submit_job(&self, job: DistributedJob) -> Result<String, DistributedError> {
        let job_id = job.id.clone();
        self.jobs
            .write()
            .expect("operation should succeed")
            .insert(job_id.clone(), job.clone());
        self.job_queue
            .lock()
            .expect("operation should succeed")
            .push(job);
        self.schedule_jobs()?;
        Ok(job_id)
    }
    /// Schedule jobs in the queue
    pub fn schedule_jobs(&self) -> Result<(), DistributedError> {
        let scheduler = self.scheduler.lock().expect("operation should succeed");
        let mut queue = self.job_queue.lock().expect("operation should succeed");
        let nodes = self.nodes.read().expect("operation should succeed");
        queue.sort_by(|a, b| {
            b.priority
                .cmp(&a.priority)
                .then_with(|| a.created_at.cmp(&b.created_at))
        });
        let mut scheduled_jobs = Vec::new();
        for job in queue.iter() {
            if let Some(node_id) = scheduler.find_suitable_node(job, &nodes) {
                let execution = JobExecution {
                    job_id: job.id.clone(),
                    node_id: node_id.clone(),
                    start_time: Instant::now(),
                    end_time: None,
                    status: JobStatus::Running,
                    progress: 0.0,
                    result: None,
                    error: None,
                    resource_usage: None,
                };
                self.executions
                    .write()
                    .expect("operation should succeed")
                    .insert(job.id.clone(), execution);
                scheduled_jobs.push(job.id.clone());
            }
        }
        queue.retain(|job| !scheduled_jobs.contains(&job.id));
        Ok(())
    }
    /// Get job status
    pub fn get_job_status(&self, job_id: &str) -> Option<JobStatus> {
        self.executions
            .read()
            .expect("operation should succeed")
            .get(job_id)
            .map(|exec| exec.status.clone())
    }
    /// Get job execution info
    pub fn get_job_execution(&self, job_id: &str) -> Option<JobExecution> {
        self.executions
            .read()
            .expect("operation should succeed")
            .get(job_id)
            .cloned()
    }
    /// Cancel a job
    pub fn cancel_job(&self, job_id: &str) -> Result<(), DistributedError> {
        let mut executions = self.executions.write().expect("operation should succeed");
        if let Some(execution) = executions.get_mut(job_id) {
            execution.status = JobStatus::Cancelled;
            execution.end_time = Some(Instant::now());
            Ok(())
        } else {
            Err(DistributedError::JobNotFound)
        }
    }
    /// Update node heartbeat
    pub fn update_heartbeat(
        &self,
        node_id: &str,
        load_metrics: LoadMetrics,
    ) -> Result<(), DistributedError> {
        let mut nodes = self.nodes.write().expect("operation should succeed");
        if let Some(node) = nodes.get_mut(node_id) {
            node.last_heartbeat = Instant::now();
            node.load_metrics = load_metrics;
            node.status = self.determine_node_status(&node.load_metrics);
            Ok(())
        } else {
            Err(DistributedError::NodeNotFound)
        }
    }
    /// Determine node status based on load metrics
    fn determine_node_status(&self, metrics: &LoadMetrics) -> NodeStatus {
        if metrics.cpu_usage > 0.9 || metrics.memory_usage > 0.9 {
            NodeStatus::Overloaded
        } else if metrics.cpu_usage > 0.7 || metrics.memory_usage > 0.7 {
            NodeStatus::Busy
        } else {
            NodeStatus::Available
        }
    }
    /// Get cluster statistics
    pub fn get_cluster_stats(&self) -> ClusterStats {
        let nodes = self.nodes.read().expect("operation should succeed");
        let jobs = self.jobs.read().expect("operation should succeed");
        let executions = self.executions.read().expect("operation should succeed");
        let total_nodes = nodes.len();
        let available_nodes = nodes
            .values()
            .filter(|n| n.status == NodeStatus::Available)
            .count();
        let busy_nodes = nodes
            .values()
            .filter(|n| n.status == NodeStatus::Busy)
            .count();
        let overloaded_nodes = nodes
            .values()
            .filter(|n| n.status == NodeStatus::Overloaded)
            .count();
        let total_jobs = jobs.len();
        let running_jobs = executions
            .values()
            .filter(|e| e.status == JobStatus::Running)
            .count();
        let completed_jobs = executions
            .values()
            .filter(|e| e.status == JobStatus::Completed)
            .count();
        let failed_jobs = executions
            .values()
            .filter(|e| e.status == JobStatus::Failed)
            .count();
        let total_cpu_cores: u32 = nodes.values().map(|n| n.capabilities.cpu_cores).sum();
        let total_memory_gb: u32 = nodes.values().map(|n| n.capabilities.memory_gb).sum();
        let total_gpu_count: u32 = nodes.values().map(|n| n.capabilities.gpu_count).sum();
        let avg_cpu_usage = if !nodes.is_empty() {
            nodes
                .values()
                .map(|n| n.load_metrics.cpu_usage)
                .sum::<f64>()
                / nodes.len() as f64
        } else {
            0.0
        };
        let avg_memory_usage = if !nodes.is_empty() {
            nodes
                .values()
                .map(|n| n.load_metrics.memory_usage)
                .sum::<f64>()
                / nodes.len() as f64
        } else {
            0.0
        };
        ClusterStats {
            total_nodes,
            available_nodes,
            busy_nodes,
            overloaded_nodes,
            unreachable_nodes: total_nodes - available_nodes - busy_nodes - overloaded_nodes,
            total_jobs,
            running_jobs,
            completed_jobs,
            failed_jobs,
            queued_jobs: self
                .job_queue
                .lock()
                .expect("operation should succeed")
                .len(),
            total_cpu_cores,
            total_memory_gb,
            total_gpu_count,
            avg_cpu_usage,
            avg_memory_usage,
        }
    }
    /// Start cluster monitoring
    pub fn start_monitoring(&self) -> Result<(), DistributedError> {
        let nodes = Arc::clone(&self.nodes);
        let executions = Arc::clone(&self.executions);
        let config = self.config.clone();
        thread::spawn(move || loop {
            let now = Instant::now();
            let mut nodes_guard = nodes.write().expect("operation should succeed");
            for node in nodes_guard.values_mut() {
                if now.duration_since(node.last_heartbeat) > config.node_timeout {
                    node.status = NodeStatus::Unreachable;
                }
            }
            let mut executions_guard = executions.write().expect("operation should succeed");
            for execution in executions_guard.values_mut() {
                if execution.status == JobStatus::Running
                    && now.duration_since(execution.start_time) > config.job_timeout
                {
                    execution.status = JobStatus::Timeout;
                    execution.end_time = Some(now);
                }
            }
            drop(nodes_guard);
            drop(executions_guard);
            thread::sleep(config.heartbeat_interval);
        });
        Ok(())
    }
    /// Rebalance workload across nodes
    pub fn rebalance_workload(&self) -> Result<(), DistributedError> {
        let load_balancer = self.load_balancer.lock().expect("operation should succeed");
        let nodes = self.nodes.read().expect("operation should succeed");
        load_balancer.rebalance(&nodes)?;
        Ok(())
    }
    /// Handle node failure
    pub fn handle_node_failure(&self, node_id: &str) -> Result<(), DistributedError> {
        let mut fault_detector = self
            .fault_detector
            .lock()
            .expect("operation should succeed");
        let mut executions = self.executions.write().expect("operation should succeed");
        for execution in executions.values_mut() {
            if execution.node_id == node_id && execution.status == JobStatus::Running {
                execution.status = JobStatus::Failed;
                execution.end_time = Some(Instant::now());
                execution.error = Some("Node failure".to_string());
            }
        }
        fault_detector.handle_failure(node_id)?;
        Ok(())
    }
}
#[derive(Debug, Clone)]
pub struct ResourceAllocation {
    pub cpu_cores: u32,
    pub memory_gb: u32,
    pub gpu_count: u32,
    pub storage_gb: u32,
    pub network_bandwidth: u32,
}
/// Job execution information
#[derive(Debug, Clone)]
pub struct JobExecution {
    pub job_id: String,
    pub node_id: String,
    pub start_time: Instant,
    pub end_time: Option<Instant>,
    pub status: JobStatus,
    pub progress: f64,
    pub result: Option<String>,
    pub error: Option<String>,
    pub resource_usage: Option<ResourceUsage>,
}
/// Resource requirements
#[derive(Debug, Clone)]
pub struct ResourceRequirements {
    pub min_cpu_cores: u32,
    pub min_memory_gb: u32,
    pub min_gpu_count: u32,
    pub min_storage_gb: u32,
    pub preferred_node_tags: HashSet<String>,
    pub exclusive_access: bool,
}