Function demo_performance_comparison

python/examples/range_queries.py:182–235

Show performance advantages of range queries.

()

def demo_performance_comparison():
    """Show performance advantages of range queries."""
    print("\n=== Performance Advantages ===\n")

    tree = BPlusTreeMap(capacity=32)

    # Create larger dataset
    print("Setting up performance test with 10,000 items...")
    for i in range(10000):
        tree[i] = f"item_{i:05d}"

    import time

    # Test 1: Get range of 100 items from middle
    start_time = time.time()
    range_items = list(tree.range(5000, 5100))
    range_time = time.time() - start_time

    print(f"   Range query (100 items): {range_time:.6f} seconds")
    print(f"   Retrieved {len(range_items)} items efficiently")

    # Test 2: Compare with dictionary approach (simulated)
    dict_data = {i: f"item_{i:05d}" for i in range(10000)}

    start_time = time.time()
    dict_range = [(k, v) for k, v in dict_data.items() if 5000 <= k < 5100]
    dict_time = time.time() - start_time

    print(f"   Dictionary scan (100 items): {dict_time:.6f} seconds")
    print(f"   B+ Tree is {dict_time/range_time:.1f}x faster for this range query!")

    # Test 3: Early termination advantage
    print("\n   Early termination test (find first 5 items > 7500):")

    start_time = time.time()
    tree_early = []
    for key, value in tree.range(7500, None):
        tree_early.append((key, value))
        if len(tree_early) >= 5:
            break
    tree_early_time = time.time() - start_time

    start_time = time.time()
    dict_early = []
    for k, v in sorted(dict_data.items()):
        if k >= 7500:
            dict_early.append((k, v))
            if len(dict_early) >= 5:
                break
    dict_early_time = time.time() - start_time

    print(f"     B+ Tree: {tree_early_time:.6f} seconds")
    print(f"     Dict scan: {dict_early_time:.6f} seconds")
    print(f"     B+ Tree is {dict_early_time/tree_early_time:.1f}x faster!")


def main():