Geospatial Indexing Fundamentals | Dataford Interview Questions

Lots and lots of low-level geospatial indexing questions

Implement a static spatial index for latitude-longitude points using quantization, Morton/Z-order codes, recursive cell decomposition, and binary search over sorted code ranges. Return matching point IDs in their original input order after exact coordinate filtering.

Function signature: def range_query(points, south, west, north, east, bits):. points is a list of [id, latitude, longitude]; return IDs inside the inclusive rectangle. Coordinates satisfy -90 <= latitude <= 90 and -180 <= longitude <= 180, with south <= north and west <= east.

Constraints

1 <= len(points) <= 5000
1 <= bits <= 15
Each point is [unique_id, latitude, longitude]
-90 <= latitude <= 90
-180 <= longitude <= 180
south <= north and west <= east
Point IDs are JSON-compatible values and are unique

Function Signature

def range_query(points, south, west, north, east, bits):

Your question is Geospatial Indexing Fundamentals. Start with the requirements in the Question tab.

Run and submit as often as you like. When you're ready, talk me through your approach or go straight to the code.

Problem

Lots and lots of low-level geospatial indexing questions

Constraints

1 <= len(points) <= 5000
1 <= bits <= 15
Each point is [unique_id, latitude, longitude]
-90 <= latitude <= 90
-180 <= longitude <= 180
south <= north and west <= east
Point IDs are JSON-compatible values and are unique

Function Signature

def range_query(points, south, west, north, east, bits):

Your question is Geospatial Indexing Fundamentals. Start with the requirements in the Question tab.

Run and submit as often as you like. When you're ready, talk me through your approach or go straight to the code.