[BENCH] Real-world query performance comparison

`examples/ctable/real_world.py` exists but is a fairly raw script. There is no self-contained example that clearly shows what performance gain SUMMARY indexes provide over a full scan, or how block size affects that gain — which is the most common question users will have after enabling auto-indexing.

Suggested work: Write `bench/ctable/summary_index_perf.py` that:
- Generates a synthetic CTable with a few million rows and numeric columns
- Runs the same where() query three ways: no index, SUMMARY at chunk granularity, SUMMARY at block granularity
- Prints a clean results table (rows scanned, time, speedup)
- Includes comments explaining the trade-offs

Ideally, it should work without any external dataset so it can be run immediately after install, but using an accessible dataset is also an option.

Lee primero examples/ctable/real_world.py y luego crea bench/ctable/summary_index_perf.py. Ejecuta el benchmark autocontenido después de instalar el proyecto y compara la misma consulta where() sin índice, SUMMARY con granularidad de chunk y SUMMARY con granularidad de bloque. Se considera terminado cuando una tabla clara muestra las filas escaneadas, el tiempo y la aceleración, con comentarios que expliquen las ventajas y desventajas.

Escrito por el modelo de indexación a partir del texto del issue.