Week 10 · Day 4 · 2026-10-01 THU · FULL · follow-up + DDIA decision
Tinder deep dives: atomic mutual match, feed generation, stale cache, Bloom filter
今日目标
Complete Tinder full coverage and map concurrent swipes to unique match creation.
| 08:50-09:00 | Set target Name the race: A and B both swipe right before either inverse read sees the other. |
|---|---|
| 09:00-10:05 | Hello Interview deep dives Read Tinder deep dives, Final Design, and level expectations. |
| 10:05-10:45 | Decision note Choose pairId uniqueness/CAS, stale feed TTL, active-user warming, and Bloom filter no-reshow. |
| 10:45-10:55 | Spoken close Explain immediate match vs reconciliation trade-off. |
| 14:30-16:15 | NeetCode Tag · Intervals Exactly three contiguous slots; each slot is 30m solve + 5m evidence. |
| 20:30-21:15 | Recall / Mock 20:30-21:15 No frontier reading; use slot for Tinder Staff follow-ups because no AI source changes Week 10 decisions. |
Live canonical source anchors
Daily anchors retain the original Hello Interview heading text.
| Project | Exact canonical source heading | Disposition | Use |
|---|---|---|---|
| Tinder | Potential Deep Dives | deep dive | consistency, feed latency, no reshow |
| Tinder | 1) How can we ensure that swiping is consistent and low latency? | deep dive | atomic mutual match under concurrent swipes |
| Tinder | 2) How can we ensure low latency for feed/stack generation? | deep dive | precompute + indexed DB + stale feed controls |
| Tinder | 3) How can the system avoid showing user profiles that the user has previously swiped on? | deep dive | cache, DB check, Bloom filter |
| Tinder | Final Design | required reading | full coverage closure |
| Tinder | What is Expected at Each Level? | level expectation | calibrate full-coverage bar |
| Tinder | Mid-level | level expectation | functional feed/swipe/match |
| Tinder | Senior | level expectation | geo filters, no reshow, swipe consistency |
| Tinder | Staff+ | level expectation | operating parameters and race recovery |
DDIA decision links
| Week 10 decision | Exact DDIA subsection | Design consequence |
|---|---|---|
| Why must mutual match creation be unique under concurrent right swipes? | Ch10 - 约束与唯一性保证 | Normalize pairId=min(userA,userB)#max(userA,userB); create one Match row with conditional uniqueness. |
| How can a swipe or driver offer perform one atomic transition? | Ch10 - 比较并设置作为共识 | Use CAS/conditional write on pair or driver state to turn read-check-write races into accepted/rejected transitions. |
Algorithm block
| Slot | Problem | Pattern | Invariant | Bug risk | Time | Space |
|---|---|---|---|---|---|---|
| 10 | Meeting Rooms III NEW · 30m solve + 5m evidence | resource heap + delay | A meeting either takes a free room or delays to earliest end. | Tie-breaking smallest room id. | O(n log n) | O(n) |
| 11 | Divide Intervals Into Minimum Number of Groups NEW · 30m solve + 5m evidence | max overlap | Minimum groups equals maximum concurrent intervals. | Inclusive endpoints require end < start to free. | O(n log n) | O(n) |
| 12 | Remove Covered Intervals NEW · 30m solve + 5m evidence | sort by start asc/end desc | A covered interval has end <= maxEnd seen. | Wrong tie sort counts duplicate starts. | O(n log n) | O(1) |
Output and repair
| Deliverable | Tinder follow-up sheet: consistency/latency/feed/no-reshow, with failure and metrics. |
|---|---|
| Repair rule | If mutual match can be missed, add unique pair write and replay notification reconciliation. |
| Artifacts | Tinder Chinese explainer Tinder Chinese audio Tinder English recall |
| English recall | English recall: defend freshness, reservation, race recovery, fairness, and observability without reading notes. |
Detailed lecture notes, audio, recall scripts, PDFs, Staff Q&A, and mock packs are archived locally and are intentionally not published on this site.