Week 10 · Day 2 · 2026-09-29 TUE · CORE · all deep dives + Bad/Good/Great

Uber deep dives: geo index, freshness, driver reservation, durable dispatch

08:50-10:55 system design14:30-16:15 Intervals20:30-21:15 recall/mock

今日目标

Cover every Uber deep dive and defend correctness when GPS, push notifications, or matcher workers are stale.

08:50-09:00Set target
State the dispatch invariant before reading: one driver can hold at most one live offer.
09:00-10:05Hello Interview deep dives
Read all Uber deep dives and level expectations.
10:05-10:45Failure walk
Airport hot zone, stale driver point, double offer, dropped request, no-response timeout, geo-shard split.
10:45-10:55Spoken close
Bad/Good/Great plus failure/recovery/metrics without notes.
14:30-16:15NeetCode Tag · Intervals
Exactly three contiguous slots; each slot is 30m solve + 5m evidence.
20:30-21:15Recall / Mock
20:30-21:15 Staff Q&A on stale location, dispatch race, fairness, and safe recovery.

Live canonical source anchors

Daily anchors retain the original Hello Interview heading text.

ProjectExact canonical source headingDispositionUse
UberPotential Deep Divesdeep diveenter location and dispatch correctness
Uber1) How do we handle frequent driver location updates and efficient proximity searches on location data?deep divegeospatial index, in-memory geo store, hot-cell write path
Uber2) How can we manage system overload from frequent driver location updates while ensuring location accuracy?deep diveadaptive update interval, freshness, confidence
Uber3) How do we prevent multiple ride requests from being sent to the same driver simultaneously?deep divedriver reservation, TTL, idempotent assignment
Uber4) How can we ensure no ride requests are dropped during peak demand periods?deep divedurable queue, dynamic scaling, safe retry
Uber5) What happens if a driver fails to respond in a timely manner?deep divetimeout, cancellation race, durable execution
Uber6) How can you further scale the system to reduce latency and improve throughput?deep divegeo-sharding, read replicas, regional routing
UberWhat is Expected at Each Level?level expectationcalibrate Senior+/Staff answer
UberMid-levellevel expectationfunctional HLD and basic spatial index
UberSeniorlevel expectationtwo deep dives with trade-offs
UberStaff+level expectationthree-plus deep dives with operating semantics

DDIA decision links

Week 10 decisionExact DDIA subsectionDesign consequence
How do airport/event zones avoid becoming one overloaded shard?Ch7 - 倾斜的工作负载与缓解热点Detect hot cells, sub-split by ring/driver bucket, and move only overload, not the whole region.
How does a request find the right geo shard after rebalancing?Ch7 - 请求路由A routing layer maps geocell and rideId to current owners with epoch/fencing, not hard-coded client routing.
What does stale location mean in the matching contract?Ch9 - 带置信区间的时钟读数Every driver candidate carries observedAt, source, and confidence; old points lower score or are excluded.
How does a paused matcher avoid assigning a stale driver reservation?Ch9 - 隔离僵尸进程和延迟请求Offer/reservation writes include an assignment epoch; stale owners cannot accept or release current offers.

Algorithm block

SlotProblemPatternInvariantBug riskTimeSpace
4Insert Interval
NEW · 30m solve + 5m evidence
ordered mergeAppend all intervals ending before new, merge overlaps, append rest.Touching endpoints and empty input.O(n)O(n) output
5Merge Intervals
NEW · 30m solve + 5m evidence
sort and foldResult intervals are disjoint and sorted by start.Sort by end instead of start.O(n log n)O(n)
6Non Overlapping Intervals
NEW · 30m solve + 5m evidence
greedy by endKeep earliest end to maximize future capacity.Counting kept vs removed backwards.O(n log n)O(1) extra

Output and repair

DeliverableUber deep-dive matrix with geospatial indexing, hot zones, freshness/confidence, driver reservation TTL, idempotent assignment, cancellation races, SLIs.
Repair ruleIf the answer says only 'use Redis lock', add versioned DriverOffer, idempotency key, fencing token, timeout event, and compensation path.
ArtifactsUber Chinese deep script Uber Chinese audio Uber English recall Uber recall PDF
English recallEnglish recall: defend freshness, reservation, race recovery, fairness, and observability without reading notes.
Local study materials
Detailed lecture notes, audio, recall scripts, PDFs, Staff Q&A, and mock packs are archived locally and are intentionally not published on this site.