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feat(auto-annotation): add batch progress updates to reduce DB write pressure
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Throttle progress updates to reduce database write operations during large dataset processing. Key features: - Add PROGRESS_UPDATE_INTERVAL config (default 2.0s, configurable via AUTO_ANNOTATION_PROGRESS_INTERVAL env) - Conditional progress updates: Only write to DB when (now - last_update) >= interval - Use time.monotonic() for timing (immune to system clock adjustments) - Final status updates (completed/stopped/failed) always execute (not throttled) Implementation: - Initialize last_progress_update timestamp before as_completed() loop - Replace unconditional _update_task_status() with conditional call based on time interval - Update docstring to reflect throttling capability Performance impact (T=2s): - 1,000 files / 100s processing: DB writes reduced from 1,000 to ~50 (95% reduction) - 10,000 files / 500s processing: DB writes reduced from 10,000 to ~250 (97.5% reduction) - Small datasets (10 files): Minimal difference Backward compatibility: - PROGRESS_UPDATE_INTERVAL=0: Updates every file (identical to previous behavior) - Heartbeat mechanism unaffected (2s interval << 300s timeout) - Stop check mechanism independent of progress updates - Final status updates always execute Testing: - 14 unit tests all passed (11 existing + 3 new): * Fast processing with throttling * PROGRESS_UPDATE_INTERVAL=0 updates every file * Slow processing (per-file > T) updates every file - py_compile syntax check passed Edge cases handled: - Single file task: Works normally - Very slow processing: Degrades to per-file updates - Concurrent FILE_WORKERS > 1: Counters accurate (lock-protected), DB reflects with max T seconds delay
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@@ -320,5 +320,71 @@ class TestWorkerLoopSimplified(unittest.TestCase):
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mock_recover.assert_not_called()
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class TestProgressThrottling(unittest.TestCase):
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"""Test time-based progress update throttling (improvement #5)."""
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def test_progress_updates_throttled(self):
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"""With PROGRESS_UPDATE_INTERVAL>0, rapid completions should batch DB writes."""
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update_calls: List[float] = []
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lock = threading.Lock()
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def mock_update(*args, **kwargs):
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with lock:
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update_calls.append(time.monotonic())
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interval = 0.05 # 50ms throttle interval
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processed = 0
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# Initialize in the past so the first file triggers an update
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last_progress_update = time.monotonic() - interval
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total_files = 50
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# Simulate the throttled update loop from _process_single_task
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for i in range(total_files):
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processed += 1
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now = time.monotonic()
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if interval <= 0 or (now - last_progress_update) >= interval:
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mock_update(processed=processed, total=total_files)
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last_progress_update = now
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# Simulate very fast file processing (~1ms)
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time.sleep(0.001)
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# With 50 files at ~1ms each (~50ms total) and 50ms interval,
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# should get far fewer updates than total_files
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self.assertLess(len(update_calls), total_files)
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self.assertGreater(len(update_calls), 0)
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def test_progress_interval_zero_updates_every_file(self):
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"""PROGRESS_UPDATE_INTERVAL=0 should update on every file completion."""
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update_count = 0
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interval = 0.0
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total_files = 20
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last_progress_update = time.monotonic()
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for i in range(total_files):
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now = time.monotonic()
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if interval <= 0 or (now - last_progress_update) >= interval:
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update_count += 1
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last_progress_update = now
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self.assertEqual(update_count, total_files)
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def test_progress_throttle_with_slow_processing(self):
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"""When each file takes longer than the interval, every file triggers an update."""
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update_count = 0
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interval = 0.01 # 10ms interval
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total_files = 5
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last_progress_update = time.monotonic() - 1.0 # Start in the past
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for i in range(total_files):
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time.sleep(0.02) # 20ms per file > 10ms interval
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now = time.monotonic()
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if interval <= 0 or (now - last_progress_update) >= interval:
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update_count += 1
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last_progress_update = now
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# Every file should trigger an update since processing time > interval
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self.assertEqual(update_count, total_files)
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if __name__ == "__main__":
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unittest.main()
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