Day16
60-day SSE plan
Cache (LRU) • Uber-style Ride Hailing • Two Pointers • Tech: Solr
Algorithm
DSA
Two Pointers — Trapping Rain Water (LC 42)
Compute trapped water using two-pointer approach.
Example
Input: [0,1,0,2,1,0,1,3,2,1,2,1] → Output: 6
Where it shows up
Resource aggregation, elevation maps, histogram problems.
References
Low-level design
LLD
Cache (LRU)
Requirements
- Put/get with capacity; LRU eviction policy.
Expectations
- Classes for LRUCache using LinkedHashMap or custom DLL+HashMap.
- Complexity guarantees O(1) operations.
Where it shows up
Databases, OS page cache, web caching layers.
References
High-level design
HLD
Uber-style Ride Hailing
Requirements
- Driver/rider match by proximity; live location; trip lifecycle; pricing.
Expectations
- Geo-indexing (geohash), matching service, WS gateway, storage model.
- Regional partitions, degradation strategies.
Where it shows up
Mobility platforms, logistics dispatch.
References
Today's deep-dive
Tech
Solr
Run Solr in Docker; create a core; index sample JSON; test analyzers & facets.
Where it shows up
Search engines, e-commerce product search, log analytics, and any system requiring fast, flexible text search and faceting.
References