[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.

Read examples/ctable/real_world.py first, then create bench/ctable/summary_index_perf.py. Run the self-contained benchmark after installing the project and compare the same where() query with no index, SUMMARY at chunk granularity, and SUMMARY at block granularity. Done means a clean table reports rows scanned, time, and speedup, with comments explaining the trade-offs.

Vom Indexierungsmodell aus dem Issue-Text verfasst.