GH-141565: Add async code awareness to Tachyon

Lib/profiling/sampling/cli.py

@@ -195,6 +195,11 @@ def _add_sampling_options(parser):
         dest="gc",
         help='Don\'t include artificial "<GC>" frames to denote active garbage collection',
     )
+    sampling_group.add_argument(
+        "--async-aware",
+        action="store_true",
+        help="Enable async-aware profiling (uses task-based stack reconstruction)",
+    )
 
 
 def _add_mode_options(parser):
@@ -205,7 +210,14 @@ def _add_mode_options(parser):
         choices=["wall", "cpu", "gil"],
         default="wall",
         help="Sampling mode: wall (all samples), cpu (only samples when thread is on CPU), "
-        "gil (only samples when thread holds the GIL)",
+        "gil (only samples when thread holds the GIL). Incompatible with --async-aware",
+    )
+    mode_group.add_argument(
+        "--async-mode",
+        choices=["running", "all"],
+        default="running",
+        help='Async profiling mode: "running" (only running task) '
+        'or "all" (all tasks including waiting). Requires --async-aware',
     )
 
 
@@ -382,6 +394,27 @@ def _validate_args(args, parser):
             "Live mode requires the curses module, which is not available."
         )
 
+    # Async-aware mode is incompatible with --native, --no-gc, --mode, and --all-threads
+    if args.async_aware:
+        issues = []
+        if args.native:
+            issues.append("--native")
+        if not args.gc:
+            issues.append("--no-gc")
+        if hasattr(args, 'mode') and args.mode != "wall":
+            issues.append(f"--mode={args.mode}")
+        if hasattr(args, 'all_threads') and args.all_threads:
+            issues.append("--all-threads")
+        if issues:
+            parser.error(
+                f"Options {', '.join(issues)} are incompatible with --async-aware. "
+                "Async-aware profiling uses task-based stack reconstruction."
+            )
+
+    # --async-mode requires --async-aware
+    if hasattr(args, 'async_mode') and args.async_mode != "running" and not args.async_aware:
+        parser.error("--async-mode requires --async-aware to be enabled.")
+
     # Live mode is incompatible with format options
     if hasattr(args, 'live') and args.live:
         if args.format != "pstats":
@@ -570,6 +603,7 @@ def _handle_attach(args):
         all_threads=args.all_threads,
         realtime_stats=args.realtime_stats,
         mode=mode,
+        async_aware=args.async_mode if args.async_aware else None,
         native=args.native,
         gc=args.gc,
     )
@@ -618,6 +652,7 @@ def _handle_run(args):
             all_threads=args.all_threads,
             realtime_stats=args.realtime_stats,
             mode=mode,
+            async_aware=args.async_mode if args.async_aware else None,
             native=args.native,
             gc=args.gc,
         )
@@ -650,6 +685,7 @@ def _handle_live_attach(args, pid):
         limit=20,  # Default limit
         pid=pid,
         mode=mode,
+        async_aware=args.async_mode if args.async_aware else None,
     )
 
     # Sample in live mode
@@ -660,6 +696,7 @@ def _handle_live_attach(args, pid):
         all_threads=args.all_threads,
         realtime_stats=args.realtime_stats,
         mode=mode,
+        async_aware=args.async_mode if args.async_aware else None,
         native=args.native,
         gc=args.gc,
     )
@@ -689,6 +726,7 @@ def _handle_live_run(args):
         limit=20,  # Default limit
         pid=process.pid,
         mode=mode,
+        async_aware=args.async_mode if args.async_aware else None,
     )
 
     # Profile the subprocess in live mode
@@ -700,6 +738,7 @@ def _handle_live_run(args):
             all_threads=args.all_threads,
             realtime_stats=args.realtime_stats,
             mode=mode,
+            async_aware=args.async_mode if args.async_aware else None,
             native=args.native,
             gc=args.gc,
         )

Lib/profiling/sampling/collector.py

@@ -2,10 +2,16 @@
 from .constants import (
     THREAD_STATUS_HAS_GIL,
     THREAD_STATUS_ON_CPU,
-    THREAD_STATUS_UNKNOWN,
     THREAD_STATUS_GIL_REQUESTED,
+    THREAD_STATUS_UNKNOWN,
 )
 
+try:
+    from _remote_debugging import FrameInfo
+except ImportError:
+    # Fallback definition if _remote_debugging is not available
+    FrameInfo = None
+
 class Collector(ABC):
     @abstractmethod
     def collect(self, stack_frames):
@@ -33,6 +39,95 @@ def _iter_all_frames(self, stack_frames, skip_idle=False):
                 if frames:
                     yield frames, thread_info.thread_id
 
+    def _iter_async_frames(self, awaited_info_list):
+        # Phase 1: Index tasks and build parent relationships with pre-computed selection
+        task_map, child_to_parent, all_task_ids, all_parent_ids = self._build_task_graph(awaited_info_list)
+
+        # Phase 2: Find leaf tasks (tasks not awaited by anyone)
+        leaf_task_ids = self._find_leaf_tasks(all_task_ids, all_parent_ids)
+
+        # Phase 3: Build linear stacks from each leaf to root (optimized - no sorting!)
+        yield from self._build_linear_stacks(leaf_task_ids, task_map, child_to_parent)
+
+    def _build_task_graph(self, awaited_info_list):
+        task_map = {}
+        child_to_parent = {}  # Maps child_id -> (selected_parent_id, parent_count)
+        all_task_ids = set()
+        all_parent_ids = set()  # Track ALL parent IDs for leaf detection
+
+        for awaited_info in awaited_info_list:
+            thread_id = awaited_info.thread_id
+            for task_info in awaited_info.awaited_by:
+                task_id = task_info.task_id
+                task_map[task_id] = (task_info, thread_id)
+                all_task_ids.add(task_id)
+
+                # Pre-compute selected parent and count for optimization
+                if task_info.awaited_by:
+                    parent_ids = [p.task_name for p in task_info.awaited_by]
+                    parent_count = len(parent_ids)
+                    # Track ALL parents for leaf detection
+                    all_parent_ids.update(parent_ids)
+                    # Use min() for O(n) instead of sorted()[0] which is O(n log n)
+                    selected_parent = min(parent_ids) if parent_count > 1 else parent_ids[0]
+                    child_to_parent[task_id] = (selected_parent, parent_count)
+
+        return task_map, child_to_parent, all_task_ids, all_parent_ids
+
+    def _find_leaf_tasks(self, all_task_ids, all_parent_ids):
+        # Leaves are tasks that are not parents of any other task
+        return all_task_ids - all_parent_ids
+
+    def _build_linear_stacks(self, leaf_task_ids, task_map, child_to_parent):
+        for leaf_id in leaf_task_ids:
+            frames = []
+            visited = set()
+            current_id = leaf_id
+            thread_id = None
+
+            # Follow the single parent chain from leaf to root
+            while current_id is not None:
+                # Cycle detection
+                if current_id in visited:
+                    break
+                visited.add(current_id)
+
+                # Check if task exists in task_map
+                if current_id not in task_map:
+                    break
+
+                task_info, tid = task_map[current_id]
+
+                # Set thread_id from first task
+                if thread_id is None:
+                    thread_id = tid
+
+                # Add all frames from all coroutines in this task
+                if task_info.coroutine_stack:
+                    for coro_info in task_info.coroutine_stack:
+                        for frame in coro_info.call_stack:
+                            frames.append(frame)
+
+                # Get pre-computed parent info (no sorting needed!)
+                parent_info = child_to_parent.get(current_id)
+
+                # Add task boundary marker with parent count annotation if multiple parents
+                task_name = task_info.task_name or "Task-" + str(task_info.task_id)
+                if parent_info:
+                    selected_parent, parent_count = parent_info
+                    if parent_count > 1:
+                        task_name = f"{task_name} ({parent_count} parents)"
+                    frames.append(FrameInfo(("<task>", 0, task_name)))
+                    current_id = selected_parent
+                else:
+                    # Root task - no parent
+                    frames.append(FrameInfo(("<task>", 0, task_name)))
+                    current_id = None
+
+            # Yield the complete stack if we collected any frames
+            if frames and thread_id is not None:
+                yield frames, thread_id, leaf_id
+
     def _is_gc_frame(self, frame):
         if isinstance(frame, tuple):
             funcname = frame[2] if len(frame) >= 3 else ""

Lib/profiling/sampling/live_collector/collector.py

@@ -103,6 +103,7 @@ def __init__(
         pid=None,
         display=None,
         mode=None,
+        async_aware=None,
     ):
         """
         Initialize the live stats collector.
@@ -115,6 +116,7 @@ def __init__(
             pid: Process ID being profiled
             display: DisplayInterface implementation (None means curses will be used)
             mode: Profiling mode ('cpu', 'gil', etc.) - affects what stats are shown
+            async_aware: Async tracing mode - None (sync only), "all" or "running"
         """
         self.result = collections.defaultdict(
             lambda: dict(total_rec_calls=0, direct_calls=0, cumulative_calls=0)
@@ -133,6 +135,9 @@ def __init__(
         self.running = True
         self.pid = pid
         self.mode = mode  # Profiling mode
+        self.async_aware = async_aware  # Async tracing mode
+        # Pre-select frame iterator method to avoid per-call dispatch overhead
+        self._get_frame_iterator = self._get_async_frame_iterator if async_aware else self._get_sync_frame_iterator
         self._saved_stdout = None
         self._saved_stderr = None
         self._devnull = None
@@ -294,6 +299,15 @@ def process_frames(self, frames, thread_id=None):
         if thread_data:
             thread_data.result[top_location]["direct_calls"] += 1
 
+    def _get_sync_frame_iterator(self, stack_frames):
+        """Iterator for sync frames."""
+        return self._iter_all_frames(stack_frames, skip_idle=self.skip_idle)
+
+    def _get_async_frame_iterator(self, stack_frames):
+        """Iterator for async frames, yielding (frames, thread_id) tuples."""
+        for frames, thread_id, task_id in self._iter_async_frames(stack_frames):
+            yield frames, thread_id
+
     def collect_failed_sample(self):
         self.failed_samples += 1
         self.total_samples += 1
@@ -304,78 +318,40 @@ def collect(self, stack_frames):
             self.start_time = time.perf_counter()
             self._last_display_update = self.start_time
 
-        # Thread status counts for this sample
-        temp_status_counts = {
-            "has_gil": 0,
-            "on_cpu": 0,
-            "gil_requested": 0,
-            "unknown": 0,
-            "total": 0,
-        }
         has_gc_frame = False
 
-        # Always collect data, even when paused
-        # Track thread status flags and GC frames
-        for interpreter_info in stack_frames:
-            threads = getattr(interpreter_info, "threads", [])
-            for thread_info in threads:
-                temp_status_counts["total"] += 1
-
-                # Track thread status using bit flags
-                status_flags = getattr(thread_info, "status", 0)
-                thread_id = getattr(thread_info, "thread_id", None)
-
-                # Update aggregated counts
-                if status_flags & THREAD_STATUS_HAS_GIL:
-                    temp_status_counts["has_gil"] += 1
-                if status_flags & THREAD_STATUS_ON_CPU:
-                    temp_status_counts["on_cpu"] += 1
-                if status_flags & THREAD_STATUS_GIL_REQUESTED:
-                    temp_status_counts["gil_requested"] += 1
-                if status_flags & THREAD_STATUS_UNKNOWN:
-                    temp_status_counts["unknown"] += 1
-
-                # Update per-thread status counts
-                if thread_id is not None:
-                    thread_data = self._get_or_create_thread_data(thread_id)
-                    thread_data.increment_status_flag(status_flags)
-
-                # Process frames (respecting skip_idle)
-                if self.skip_idle:
-                    has_gil = bool(status_flags & THREAD_STATUS_HAS_GIL)
-                    on_cpu = bool(status_flags & THREAD_STATUS_ON_CPU)
-                    if not (has_gil or on_cpu):
-                        continue
-
-                frames = getattr(thread_info, "frame_info", None)
-                if frames:
-                    self.process_frames(frames, thread_id=thread_id)
-
-                    # Track thread IDs only for threads that actually have samples
-                    if (
-                        thread_id is not None
-                        and thread_id not in self.thread_ids
-                    ):
-                        self.thread_ids.append(thread_id)
-
-                    # Increment per-thread sample count and check for GC frames
-                    thread_has_gc_frame = False
-                    for frame in frames:
-                        funcname = getattr(frame, "funcname", "")
-                        if "<GC>" in funcname or "gc_collect" in funcname:
-                            has_gc_frame = True
-                            thread_has_gc_frame = True
-                            break
-
-                    if thread_id is not None:
-                        thread_data = self._get_or_create_thread_data(thread_id)
-                        thread_data.sample_count += 1
-                        if thread_has_gc_frame:
-                            thread_data.gc_frame_samples += 1
-
-        # Update cumulative thread status counts
-        for key, count in temp_status_counts.items():
-            self.thread_status_counts[key] += count
+        # Collect thread status stats (only available in sync mode)
+        if not self.async_aware:
+            status_counts, sample_has_gc, per_thread_stats = self._collect_thread_status_stats(stack_frames)
+            for key, count in status_counts.items():
+                self.thread_status_counts[key] += count
+            if sample_has_gc:
+                has_gc_frame = True
+
+            for thread_id, stats in per_thread_stats.items():
+                thread_data = self._get_or_create_thread_data(thread_id)
+                thread_data.has_gil += stats.get("has_gil", 0)
+                thread_data.on_cpu += stats.get("on_cpu", 0)
+                thread_data.gil_requested += stats.get("gil_requested", 0)
+                thread_data.unknown += stats.get("unknown", 0)
+                thread_data.total += stats.get("total", 0)
+                if stats.get("gc_samples", 0):
+                    thread_data.gc_frame_samples += stats["gc_samples"]
+
+        # Process frames using pre-selected iterator
+        for frames, thread_id in self._get_frame_iterator(stack_frames):
+            if not frames:
+                continue
+
+            self.process_frames(frames, thread_id=thread_id)
+
+            # Track thread IDs
+            if thread_id is not None and thread_id not in self.thread_ids:
+                self.thread_ids.append(thread_id)
+
+            if thread_id is not None:
+                thread_data = self._get_or_create_thread_data(thread_id)
+                thread_data.sample_count += 1
 
         if has_gc_frame:
             self.gc_frame_samples += 1

Lib/profiling/sampling/pstats_collector.py

@@ -42,8 +42,14 @@ def _process_frames(self, frames):
             self.callers[callee][caller] += 1
 
     def collect(self, stack_frames):
-        for frames, thread_id in self._iter_all_frames(stack_frames, skip_idle=self.skip_idle):
-            self._process_frames(frames)
+        if stack_frames and hasattr(stack_frames[0], "awaited_by"):
+            # Async frame processing
+            for frames, thread_id, task_id in self._iter_async_frames(stack_frames):
+                self._process_frames(frames)
+        else:
+            # Regular frame processing
+            for frames, thread_id in self._iter_all_frames(stack_frames, skip_idle=self.skip_idle):
+                self._process_frames(frames)
 
     def export(self, filename):
         self.create_stats()