Big Data
Indexing Strategies for Search & Filter
NoSQL is fast only if your indexes are right. This lesson covers Compound and Geospatial indexes for apps like Uber or Airbnb.
Level: IntermediateBig Data
What You'll Learn
Single-field vs compound index design
Index selectivity and cardinality rules
Geospatial indexing with 2dsphere
Text search indexes for full-text queries
Covered queries for zero-document-fetch reads
'Find nearby stores' query implementation
Index analysis with explain() and execution stats
What's Included
🧭AI Tutor🔒
Interactive learning path with AI-generated lessons read aloud by your personal tutor
🧪Practice Lab🔒
Step-by-step lab instructions with AI guidance — run in your own IDE or sandbox.
🎙️Mock Interviews🔒
AI interviewer asks tailored questions, gives real-time feedback and a score report
📝Evaluation🔒
MCQ questions (theory, practical, code) to test your knowledge and earn a badge
⚔️Challenge AI🔒
Compete head-to-head against AI on real production problems — judged on correctness, performance, scalability, code quality, and edge cases
Course Syllabus
Module 1: Index Fundamentals
- •How B-tree indexes work under the hood
- •Single-field vs compound index trade-offs
- •Index selectivity, cardinality, and prefix rules
- •The ESR rule: Equality → Sort → Range
- •Using explain() to audit query plans
Module 2: Geospatial Indexes
- •GeoJSON point, polygon, and LineString types
- •Creating a 2dsphere index for location data
- •$near and $geoWithin operators
- •Distance-based radius queries
- •'Find nearby stores' implementation walkthrough
Module 3: Advanced Indexing Patterns
- •Text indexes for full-text search
- •Covered queries: reading from index only
- •Partial and sparse indexes
- •Compound geospatial + filter indexes (Uber / Airbnb pattern)
- •Capstone: location-aware search with compound 2dsphere index
You're all set
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✓Practice Lab
✓Mock Interviews
✓Evaluation
✓Challenge AI