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Reservoir Sampling for a Privacy-Preserving Telemetry Pipeline

FreeVerified credential3 weeksAdvanced

Overview

What this challenge is about.

Implement Vitter’s Algorithm R in Rust for reservoir sampling from an 18B-event stream, then earn a verifiable certificate.

The scenario

The company (around USD 22M ARR, open-core licensing) is privacy-first by reputation — sampling must be defensibly unbiased so analytics conclusions hold up under public scrutiny.

CredentialBlockchain-anchored
ShareableLinkedIn-ready
LanguageEnglish
PaceSelf-paced

The Brief

What you'll do, and what you'll demonstrate.

Build a reservoir-sampling pipeline that produces a uniform 0.5 percent sample from an 18B-event/day stream with per-key stratification and provable uniformity.

Earning criteria — what you'll demonstrate

  • Implement Vitter's Algorithm R and reason about its uniformity guarantee
  • Apply A-Res (Efraimidis-Spirakis) for weighted/stratified reservoir sampling
  • Verify sampling uniformity with chi-square goodness-of-fit
  • Engineer a streaming sampler that respects backpressure and memory bounds

Program Fit

Where this fits in your program.

Sharpens the same skills your degree expects you to demonstrate.

Aligned coursework coming soon.

One more thing

You can put a credential on your CV by Friday.