scirs2_core/advanced_ecosystem_integration/
workflow.rs1use super::types::*;
4use crate::distributed::ResourceRequirements;
5use crate::error::{CoreError, CoreResult, ErrorContext};
6#[cfg(feature = "serialization")]
7use serde::{Deserialize, Serialize};
8use std::collections::{HashMap, HashSet, VecDeque};
9use std::time::{Duration, Instant};
10
11#[allow(dead_code)]
13#[derive(Debug, Clone)]
14pub struct DistributedWorkflow {
15 pub name: String,
16 pub description: String,
17 pub stages: Vec<WorkflowStage>,
18 pub dependencies: HashMap<String, Vec<String>>,
19 pub resource_requirements: ResourceRequirements,
20}
21
22#[allow(dead_code)]
24#[cfg_attr(feature = "serialization", derive(Serialize, Deserialize))]
25#[derive(Debug, Clone)]
26pub struct WorkflowResult {
27 pub workflow_name: String,
28 pub execution_time: Duration,
29 pub stage_results: HashMap<String, StageResult>,
30 pub performance_metrics: PerformanceMetrics,
31 pub success: bool,
32}
33
34#[allow(dead_code)]
36#[cfg_attr(feature = "serialization", derive(Serialize, Deserialize))]
37#[derive(Debug, Clone)]
38pub struct StageResult {
39 pub stage_name: String,
40 pub execution_time: Duration,
41 pub output_size: usize,
42 pub success: bool,
43 pub error_message: Option<String>,
44}
45
46#[allow(dead_code)]
48#[derive(Debug, Clone)]
49pub struct WorkflowState {
50 pub completed_stages: Vec<String>,
52 pub current_stage: Option<String>,
54 pub accumulated_data: HashMap<String, Vec<u8>>,
56 pub metadata: HashMap<String, String>,
58 pub should_terminate: bool,
60 pub stage_times: HashMap<String, Duration>,
62}
63
64impl Default for WorkflowState {
65 fn default() -> Self {
66 Self::new()
67 }
68}
69
70impl WorkflowState {
71 pub fn new() -> Self {
72 Self {
73 completed_stages: Vec::new(),
74 current_stage: None,
75 accumulated_data: HashMap::new(),
76 metadata: HashMap::new(),
77 should_terminate: false,
78 stage_times: HashMap::new(),
79 }
80 }
81
82 pub fn incorporate_stage_result(&mut self, result: &StageResult) -> CoreResult<()> {
83 self.completed_stages.push(result.stage_name.clone());
84 self.stage_times
85 .insert(result.stage_name.clone(), result.execution_time);
86
87 if !result.success {
88 self.should_terminate = true;
89 }
90
91 Ok(())
92 }
93
94 pub fn should_terminate_early(&self) -> bool {
95 self.should_terminate
96 }
97}
98
99pub struct WorkflowExecutor;
101
102impl WorkflowExecutor {
103 pub fn validate_workflow(workflow: &DistributedWorkflow) -> CoreResult<()> {
105 if workflow.name.is_empty() {
107 return Err(CoreError::InvalidInput(ErrorContext::new(
108 "Workflow name cannot be empty",
109 )));
110 }
111
112 if workflow.stages.is_empty() {
113 return Err(CoreError::InvalidInput(ErrorContext::new(
114 "Workflow must have at least one stage",
115 )));
116 }
117
118 for stage in &workflow.stages {
120 if stage.name.is_empty() {
121 return Err(CoreError::InvalidInput(ErrorContext::new(
122 "Stage name cannot be empty",
123 )));
124 }
125
126 if stage.module.is_empty() {
127 return Err(CoreError::InvalidInput(ErrorContext::new(
128 "Stage module cannot be empty",
129 )));
130 }
131
132 if let Some(deps) = workflow.dependencies.get(&stage.name) {
134 for dep in deps {
135 if !workflow.stages.iter().any(|s| &s.name == dep) {
136 return Err(CoreError::InvalidInput(ErrorContext::new(format!(
137 "Dependency '{}' not found for stage '{}'",
138 dep, stage.name
139 ))));
140 }
141 }
142 }
143 }
144
145 Self::detect_circular_dependencies(workflow)?;
147
148 if workflow.resource_requirements.memory_gb == 0 {
150 return Err(CoreError::InvalidInput(ErrorContext::new(
151 "Workflow must specify memory requirements",
152 )));
153 }
154
155 if workflow.resource_requirements.cpu_cores == 0 {
156 return Err(CoreError::InvalidInput(ErrorContext::new(
157 "Workflow must specify CPU requirements",
158 )));
159 }
160
161 Ok(())
162 }
163
164 pub fn create_workflow_execution_plan(
166 workflow: &DistributedWorkflow,
167 ) -> CoreResult<WorkflowExecutionPlan> {
168 Self::validate_workflow(workflow)?;
170
171 let sorted_stages = Self::topological_sort_stages(workflow)?;
173
174 let estimated_duration = Self::estimate_workflow_duration(&sorted_stages, workflow)?;
176
177 let optimized_stages = Self::optimize_stage_ordering(sorted_stages, workflow)?;
179
180 Ok(WorkflowExecutionPlan {
181 stages: optimized_stages,
182 estimated_duration,
183 })
184 }
185
186 fn topological_sort_stages(workflow: &DistributedWorkflow) -> CoreResult<Vec<WorkflowStage>> {
188 let mut in_degree: HashMap<String, usize> = HashMap::new();
189 let mut adjacency_list: HashMap<String, Vec<String>> = HashMap::new();
190
191 for stage in &workflow.stages {
193 in_degree.insert(stage.name.clone(), 0);
194 adjacency_list.insert(stage.name.clone(), Vec::new());
195 }
196
197 for (stage_name, deps) in &workflow.dependencies {
199 for dep in deps {
200 adjacency_list
201 .get_mut(dep)
202 .unwrap()
203 .push(stage_name.clone());
204 *in_degree.get_mut(stage_name).unwrap() += 1;
205 }
206 }
207
208 let mut queue: VecDeque<String> = in_degree
210 .iter()
211 .filter(|(_, °ree)| degree == 0)
212 .map(|(name, _)| name.clone())
213 .collect();
214
215 let mut sorted_names = Vec::new();
216
217 while let Some(current) = queue.pop_front() {
218 sorted_names.push(current.clone());
219
220 if let Some(neighbors) = adjacency_list.get(¤t) {
221 for neighbor in neighbors {
222 let degree = in_degree.get_mut(neighbor).unwrap();
223 *degree -= 1;
224 if *degree == 0 {
225 queue.push_back(neighbor.clone());
226 }
227 }
228 }
229 }
230
231 if sorted_names.len() != workflow.stages.len() {
232 return Err(CoreError::InvalidInput(ErrorContext::new(
233 "Circular dependency detected in workflow",
234 )));
235 }
236
237 let mut sorted_stages = Vec::new();
239 for name in sorted_names {
240 if let Some(stage) = workflow.stages.iter().find(|s| s.name == name) {
241 sorted_stages.push(stage.clone());
242 }
243 }
244
245 Ok(sorted_stages)
246 }
247
248 fn estimate_workflow_duration(
250 stages: &[WorkflowStage],
251 workflow: &DistributedWorkflow,
252 ) -> CoreResult<Duration> {
253 let mut total_duration = Duration::from_secs(0);
254
255 for stage in stages {
256 let mut stage_duration = Duration::from_secs(30);
258
259 match stage.operation.as_str() {
261 "matrix_multiply" | "fft" | "convolution" => {
262 stage_duration = Duration::from_secs(120); }
264 "load_data" | "save_data" => {
265 stage_duration = Duration::from_secs(60); }
267 "transform" | "filter" => {
268 stage_duration = Duration::from_secs(45); }
270 _ => {
271 }
273 }
274
275 let memory_factor = (workflow.resource_requirements.memory_gb as f64).max(1.0);
277 let adjusted_duration = Duration::from_secs_f64(
278 stage_duration.as_secs_f64() * memory_factor.log2().max(1.0),
279 );
280
281 total_duration += adjusted_duration;
282 }
283
284 Ok(total_duration)
285 }
286
287 fn optimize_stage_ordering(
289 stages: Vec<WorkflowStage>,
290 workflow: &DistributedWorkflow,
291 ) -> CoreResult<Vec<WorkflowStage>> {
292 let mut optimized = stages;
297
298 let _parallel_groups = Self::identify_parallel_groups(&optimized, workflow)?;
300
301 optimized.sort_by_key(|stage| {
303 workflow
305 .dependencies
306 .get(&stage.name)
307 .map_or(0, |deps| deps.len())
308 });
309
310 Ok(optimized)
311 }
312
313 fn identify_parallel_groups(
315 stages: &[WorkflowStage],
316 workflow: &DistributedWorkflow,
317 ) -> CoreResult<Vec<Vec<String>>> {
318 let mut parallel_groups = Vec::new();
319 let mut processed_stages = HashSet::new();
320
321 for stage in stages {
322 if !processed_stages.contains(&stage.name) {
323 let mut group = vec![stage.name.clone()];
324 processed_stages.insert(stage.name.clone());
325
326 for other_stage in stages {
328 if other_stage.name != stage.name
329 && !processed_stages.contains(&other_stage.name)
330 && Self::can_run_in_parallel(&stage.name, &other_stage.name, workflow)?
331 {
332 group.push(other_stage.name.clone());
333 processed_stages.insert(other_stage.name.clone());
334 }
335 }
336
337 parallel_groups.push(group);
338 }
339 }
340
341 Ok(parallel_groups)
342 }
343
344 fn can_run_in_parallel(
346 stage1: &str,
347 stage2: &str,
348 workflow: &DistributedWorkflow,
349 ) -> CoreResult<bool> {
350 if let Some(deps1) = workflow.dependencies.get(stage1) {
352 if deps1.contains(&stage2.to_string()) {
353 return Ok(false);
354 }
355 }
356
357 if let Some(deps2) = workflow.dependencies.get(stage2) {
358 if deps2.contains(&stage1.to_string()) {
359 return Ok(false);
360 }
361 }
362
363 Ok(true)
368 }
369
370 pub fn setup_workflow_communication(plan: &WorkflowExecutionPlan) -> CoreResult<Vec<String>> {
372 let mut channels = Vec::new();
373
374 for stage in &plan.stages {
376 let channel_name = stage.name.to_string();
377 channels.push(channel_name);
378 }
379
380 channels.push("control_channel".to_string());
382 channels.push("monitoring_channel".to_string());
383 channels.push("error_channel".to_string());
384
385 for i in 0..plan.stages.len() {
387 if i > 0 {
388 let prev_stage_name = &plan.stages[i.saturating_sub(1)].name;
389 let curr_stage_name = &plan.stages[i].name;
390 let inter_stage_channel = format!("{prev_stage_name}-{curr_stage_name}");
391 channels.push(inter_stage_channel);
392 }
393 }
394
395 Ok(channels)
396 }
397
398 pub fn execute_workflow_stage(
400 stage: &WorkflowStage,
401 _channels: &[String],
402 ) -> CoreResult<StageResult> {
403 println!(" 🔧 Executing workflow stage: {}", stage.name);
404 Ok(StageResult {
405 stage_name: stage.name.clone(),
406 execution_time: Duration::from_millis(100),
407 output_size: 1024,
408 success: true,
409 error_message: None,
410 })
411 }
412
413 pub fn aggregate_workflow_results(
415 stage_results: &[StageResult],
416 _state: &WorkflowState,
417 ) -> CoreResult<WorkflowResult> {
418 let total_time = stage_results
419 .iter()
420 .map(|r| r.execution_time)
421 .sum::<Duration>();
422
423 let mut results_map = HashMap::new();
424 for result in stage_results {
425 results_map.insert(result.stage_name.clone(), result.clone());
426 }
427
428 Ok(WorkflowResult {
429 workflow_name: "distributed_workflow".to_string(),
430 execution_time: total_time,
431 stage_results: results_map,
432 performance_metrics: PerformanceMetrics {
433 throughput: 1000.0,
434 latency: Duration::from_millis(100),
435 cpu_usage: 50.0,
436 memory_usage: 1024,
437 gpu_usage: 30.0,
438 },
439 success: stage_results.iter().all(|r| r.success),
440 })
441 }
442
443 fn detect_circular_dependencies(workflow: &DistributedWorkflow) -> CoreResult<()> {
445 let mut visited = HashSet::new();
447 let mut recursion_stack = HashSet::new();
448
449 for stage in &workflow.stages {
450 if !visited.contains(&stage.name)
451 && Self::detect_cycle_recursive(
452 &stage.name,
453 workflow,
454 &mut visited,
455 &mut recursion_stack,
456 )?
457 {
458 return Err(CoreError::InvalidInput(ErrorContext::new(format!(
459 "Circular dependency detected involving stage '{}'",
460 stage.name
461 ))));
462 }
463 }
464
465 Ok(())
466 }
467
468 #[allow(clippy::only_used_in_recursion)]
470 fn detect_cycle_recursive(
471 stage_name: &str,
472 workflow: &DistributedWorkflow,
473 visited: &mut HashSet<String>,
474 recursion_stack: &mut HashSet<String>,
475 ) -> CoreResult<bool> {
476 visited.insert(stage_name.to_string());
477 recursion_stack.insert(stage_name.to_string());
478
479 if let Some(deps) = workflow.dependencies.get(stage_name) {
480 for dep in deps {
481 if !visited.contains(dep) {
482 if Self::detect_cycle_recursive(dep, workflow, visited, recursion_stack)? {
483 return Ok(true);
484 }
485 } else if recursion_stack.contains(dep) {
486 return Ok(true);
487 }
488 }
489 }
490
491 recursion_stack.remove(stage_name);
492 Ok(false)
493 }
494
495 pub fn execute_distributed_workflow(
497 workflow: DistributedWorkflow,
498 ) -> CoreResult<WorkflowResult> {
499 let start_time = Instant::now();
500
501 println!("🌐 Executing distributed workflow: {}", workflow.name);
502
503 Self::validate_workflow(&workflow)?;
505
506 let execution_plan = Self::create_workflow_execution_plan(&workflow)?;
508
509 let comm_channels = Self::setup_workflow_communication(&execution_plan)?;
511
512 let mut workflow_state = WorkflowState::new();
514 let mut stage_results = Vec::new();
515
516 for stage in &execution_plan.stages {
517 println!(" 🔧 Executing workflow stage: {}", stage.name);
518
519 let stage_result = Self::execute_workflow_stage(stage, &comm_channels)?;
521
522 workflow_state.incorporate_stage_result(&stage_result)?;
524 stage_results.push(stage_result);
525
526 if workflow_state.should_terminate_early() {
528 println!(" ⚠️ Early termination triggered");
529 break;
530 }
531 }
532
533 let final_result = Self::aggregate_workflow_results(&stage_results, &workflow_state)?;
535
536 println!(
537 "✅ Distributed workflow completed in {:.2}s",
538 start_time.elapsed().as_secs_f64()
539 );
540 Ok(final_result)
541 }
542}