Problems / Caching, hard

Nearby search at lunchtime

Asked at Yelp, Google (Maps) and Uber Eats. Every “near me” search runs a PostGIS radius query, as do place pages and reviews, on one database with read replicas. At 8 s lunchtime doubles traffic for 10 seconds.

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Your goals

Success ≥ 99.5%, p99 ≤ 600 ms and Apdex ≥ 0.90, for at most $18,000 a month.

Test cases

Like a coding problem, a solution has to pass every case, not just the one it was built for. Submit in the lab runs all 4; 1 of them are hidden until then.

  1. As given. The problem’s own traffic, scheduled failures and seed.
  2. A slow dependency. The main data store or model answers twice as slowly for part of the run.
  3. A server dies. One replica of the service with the most replicas is killed for part of the run.

The traffic

20,000 requests a second for 20 seconds: 85% nearby (reads), 10% place (reads), 5% review (writes).

The system

What each component does in this design, and what calls it. The simulator mimics each one from these settings.

ComponentIts job hereSettings
Load balancerLoad balancerTraffic enters here.Calls Places API.Layer 4 balancers route by IP and port; layer 7 balancers read HTTP and can route by path or header.–
Places APIApp serviceLoad balancer forwards to it.Calls Places and reviews (PostGIS radius queries).Little's law: throughput ≈ concurrency ÷ latency. 200 slots at 50 ms serve about 4,000 req/s.16 replicas × 100 slots · timeout 1.0 s
Places and reviews (PostGIS radius queries)SQL databasePlaces API calls it.Postgres runs one process per connection, which is why poolers like PgBouncer sit in front of busy databases.32 vCPU · 800 connections · 2 read replicas

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