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Performance Monitoring: Track query times, memory usage, and system metrics
Provides real-time performance statistics and benchmarking
"""
import time
import psutil
import os
from functools import wraps
from typing import Dict, List, Callable
from collections import defaultdict, deque
import threading
import logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)
class PerformanceMonitor:
"""
Centralized performance monitoring system
Tracks query response times, memory usage, and system health
"""
def __init__(self, history_size: int = 1000):
"""
Initialize performance monitor
Args:
history_size: Number of recent queries to keep in history
"""
self.history_size = history_size
# Query performance tracking
self.query_times: deque = deque(maxlen=history_size)
self.query_counts = defaultdict(int)
self.query_types = defaultdict(list)
# Memory tracking
self.process = psutil.Process(os.getpid())
self.initial_memory = self.get_memory_usage()
# System statistics
self.total_queries = 0
self.failed_queries = 0
self.cache_hits = 0
self.cache_misses = 0
# Performance requirements tracking
self.single_word_times = deque(maxlen=100)
self.multi_word_times = defaultdict(lambda: deque(maxlen=100))
# Thread lock for concurrent access
self.lock = threading.Lock()
logger.info("Performance monitor initialized")
def get_memory_usage(self) -> dict:
"""Get current memory usage in MB"""
memory_info = self.process.memory_info()
return {
'rss_mb': memory_info.rss / (1024 * 1024), # Resident Set Size
'vms_mb': memory_info.vms / (1024 * 1024), # Virtual Memory Size
'percent': self.process.memory_percent()
}
def record_query(self, query: str, response_time: float,
result_count: int, query_type: str = 'unknown',
success: bool = True):
"""
Record a query's performance metrics
Args:
query: Search query text
response_time: Time taken in milliseconds
result_count: Number of results returned
query_type: Type of query (single_word, multi_word, semantic, etc.)
success: Whether query succeeded
"""
with self.lock:
# Record query time
self.query_times.append({
'query': query,
'time_ms': response_time,
'results': result_count,
'type': query_type,
'timestamp': time.time(),
'success': success
})
# Update counters
self.total_queries += 1
if not success:
self.failed_queries += 1
self.query_counts[query_type] += 1
self.query_types[query_type].append(response_time)
# Track by word count for requirement compliance
word_count = len(query.split())
if word_count == 1:
self.single_word_times.append(response_time)
else:
self.multi_word_times[word_count].append(response_time)
def get_statistics(self) -> dict:
"""Get comprehensive performance statistics"""
with self.lock:
# Calculate averages
if self.query_times:
recent_times = [q['time_ms'] for q in self.query_times]
avg_time = sum(recent_times) / len(recent_times)
max_time = max(recent_times)
min_time = min(recent_times)
else:
avg_time = max_time = min_time = 0
# Memory stats
current_memory = self.get_memory_usage()
memory_delta = current_memory['rss_mb'] - self.initial_memory['rss_mb']
# Requirement compliance
compliance = self._check_compliance()
return {
'total_queries': self.total_queries,
'failed_queries': self.failed_queries,
'success_rate': (
(self.total_queries - self.failed_queries) / self.total_queries * 100
if self.total_queries > 0 else 100
),
'average_response_time_ms': round(avg_time, 2),
'max_response_time_ms': round(max_time, 2),
'min_response_time_ms': round(min_time, 2),
'memory_usage_mb': round(current_memory['rss_mb'], 2),
'memory_delta_mb': round(memory_delta, 2),
'memory_percent': round(current_memory['percent'], 2),
'query_types': dict(self.query_counts),
'recent_queries': list(self.query_times)[-10:], # Last 10 queries
'compliance': compliance,
'cache_hit_rate': (
self.cache_hits / (self.cache_hits + self.cache_misses) * 100
if (self.cache_hits + self.cache_misses) > 0 else 0
)
}
def _check_compliance(self) -> dict:
"""Check compliance with performance requirements"""
compliance = {
'single_word_query': {
'requirement': '< 500ms',
'current_avg': 0,
'passing': False,
'sample_size': 0
},
'five_word_query': {
'requirement': '< 1500ms',
'current_avg': 0,
'passing': False,
'sample_size': 0
},
'memory_usage': {
'requirement': ' 2GB (datasets < 100k docs)',
'current_mb': 0,
'passing': False
}
}
# Single word queries
if self.single_word_times:
avg_single = sum(self.single_word_times) / len(self.single_word_times)
compliance['single_word_query']['current_avg'] = round(avg_single, 2)
compliance['single_word_query']['passing'] = avg_single < 500
compliance['single_word_query']['sample_size'] = len(self.single_word_times)
# Five word queries
if 5 in self.multi_word_times and self.multi_word_times[5]:
avg_five = sum(self.multi_word_times[5]) / len(self.multi_word_times[5])
compliance['five_word_query']['current_avg'] = round(avg_five, 2)
compliance['five_word_query']['passing'] = avg_five < 1500
compliance['five_word_query']['sample_size'] = len(self.multi_word_times[5])
# Memory usage
current_memory = self.get_memory_usage()
compliance['memory_usage']['current_mb'] = round(current_memory['rss_mb'], 2)
compliance['memory_usage']['passing'] = current_memory['rss_mb'] <= 2048
return compliance
def get_performance_report(self) -> str:
"""Generate human-readable performance report"""
stats = self.get_statistics()
report = []
report.append("=" * 60)
report.append("PERFORMANCE REPORT")
report.append("=" * 60)
report.append(f"\nQUERY STATISTICS:")
report.append(f" Total Queries: {stats['total_queries']:,}")
report.append(f" Failed Queries: {stats['failed_queries']}")
report.append(f" Success Rate: {stats['success_rate']:.2f}%")
report.append(f"\nRESPONSE TIMES:")
report.append(f" Average: {stats['average_response_time_ms']}ms")
report.append(f" Max: {stats['max_response_time_ms']}ms")
report.append(f" Min: {stats['min_response_time_ms']}ms")
report.append(f"\nMEMORY USAGE:")
report.append(f" Current: {stats['memory_usage_mb']}MB")
report.append(f" Delta from Start: {stats['memory_delta_mb']:+.2f}MB")
report.append(f" Percent: {stats['memory_percent']:.2f}%")
report.append(f"\nREQUIREMENT COMPLIANCE:")
for req_name, req_data in stats['compliance'].items():
status = " PASS" if req_data['passing'] else " FAIL"
report.append(f" {req_name}: {status}")
report.append(f" Requirement: {req_data['requirement']}")
if 'current_avg' in req_data:
report.append(f" Current Avg: {req_data['current_avg']}ms")
report.append(f" Sample Size: {req_data['sample_size']}")
elif 'current_mb' in req_data:
report.append(f" Current: {req_data['current_mb']}MB")
report.append("=" * 60)
return "\n".join(report)
def performance_tracked(query_type: str = 'unknown'):
"""
Decorator to track function performance
Usage:
@performance_tracked('text_search')
def search_function(query):
...
"""
def decorator(func: Callable) -> Callable:
@wraps(func)
def wrapper(*args, **kwargs):
start_time = time.time()
success = True
result_count = 0
query = ""
try:
result = func(*args, **kwargs)
# Extract query and result count
if args and isinstance(args[0], str):
query = args[0]
elif 'query' in kwargs:
query = kwargs['query']
if isinstance(result, dict) and 'results' in result:
result_count = len(result['results'])
elif isinstance(result, list):
result_count = len(result)
return result
except Exception as e:
success = False
raise
finally:
end_time = time.time()
response_time = (end_time - start_time) * 1000 # Convert to ms
# Record in global monitor
if hasattr(wrapper, 'monitor'):
wrapper.monitor.record_query(
query=query,
response_time=response_time,
result_count=result_count,
query_type=query_type,
success=success
)
return wrapper
return decorator
# Global performance monitor instance
performance_monitor: PerformanceMonitor = PerformanceMonitor()
def track_query(query: str, response_time: float, result_count: int,
query_type: str = 'unknown', success: bool = True):
"""
Manually track a query's performance
Args:
query: Search query
response_time: Response time in milliseconds
result_count: Number of results
query_type: Type of query
success: Whether successful
"""
performance_monitor.record_query(
query=query,
response_time=response_time,
result_count=result_count,
query_type=query_type,
success=success
)
def get_performance_stats() -> dict:
"""Get current performance statistics"""
return performance_monitor.get_statistics()
def get_performance_report() -> str:
"""Get formatted performance report"""
return performance_monitor.get_performance_report()
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