This example demonstrates point clustering on a map using CartoDB.js, Google Maps, and a custom SQL template. It visualizes tornado data, grouping nearby points into hexagonal clusters of varying sizes based on a user-adjustable "cluster size" slider. The clustering algorithm runs through a SQL query that creates three levels of hexagon grids (large, medium, small) to aggregate points, with each cluster's size and opacity reflecting the number of points it contains. Clicking a cluster reveals details about the original points it represents. The side panel includes a range input to dynamically adjust the cluster radius, which updates the visualization via CartoDB's SQL and CartoCSS templating.