Design a service to compute each user's Top 10 songs from streaming/listening events. Cover event ingestion, deduplication, sessionization, counters/windows (e.g., last 7/30 days), ranking per user, batch vs. streaming pipelines, storage choices (hot cache vs. warehouse), freshness SLAs, APIs for retrieval, personalization signals, privacy/PII handling, and backfill/replay strategy.

This question evaluates a candidate's ability to design scalable, real-time streaming and batch data pipelines that support per-user ranking, sessionization, deduplication, privacy-preserving storage, and backfill/replay for a high-throughput music service.

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Design user top-10 songs service | Meta Interview Question

Design a Service to Compute Each User's Top 10 Songs

Context

You are designing a backend service for a large-scale music streaming platform to compute and serve each user's Top 10 songs from listening events. The system must support both real-time freshness and offline accuracy/reproducibility.

Assume: hundreds of millions of MAUs, peak 1–2M events/sec globally, multi-region deployment, and clients that can buffer and upload events late or out of order.

Requirements

Functional

Ingest streaming listening events from clients (mobile/web/TV), handle duplicates, out-of-order and late arrivals, and occasional replays.
Define “listen” eligibility (e.g., listened ≥ N seconds, not muted/seek-skipped) and support sessionization (e.g., 30-min gap) for downstream features.
Maintain per-user ranking for windows: last 7 days and last 30 days (Top 10 songs). Consider also all-time if helpful.
Provide both streaming (low-latency) updates and batch recomputation/backfill for correctness.
Serve results via APIs with configurable window, limit, and as-of freshness.

Non-Functional

Freshness SLA: P95 end-to-end under ~1–2 minutes for streaming updates; daily correctness reconciliation.
High availability and horizontal scalability.
Privacy: minimize PII, secure transit/at-rest, support deletion/retention policies and access control.
Backfill and replay: ability to recompute windows for past dates and correct bad data.

Scope to Cover

Event ingestion, deduplication, sessionization.
Counters/windows for last 7/30 days.
Per-user ranking and tie-breaking.
Batch vs. streaming trade-offs.
Storage: hot cache vs. warehouse/lake.
Freshness SLAs and data quality.
APIs for retrieval.
Personalization signals/weights.
Privacy/PII handling.
Backfill/replay strategy.

Context

Assume: hundreds of millions of MAUs, peak 1–2M events/sec globally, multi-region deployment, and clients that can buffer and upload events late or out of order.

Requirements

Functional

Ingest streaming listening events from clients (mobile/web/TV), handle duplicates, out-of-order and late arrivals, and occasional replays.

Define “listen” eligibility (e.g., listened ≥ N seconds, not muted/seek-skipped) and support sessionization (e.g., 30-min gap) for downstream features.

Maintain per-user ranking for windows: last 7 days and last 30 days (Top 10 songs). Consider also all-time if helpful.

Provide both streaming (low-latency) updates and batch recomputation/backfill for correctness.

Serve results via APIs with configurable window, limit, and as-of freshness.

Non-Functional

Freshness SLA: P95 end-to-end under ~1–2 minutes for streaming updates; daily correctness reconciliation.

High availability and horizontal scalability.

Privacy: minimize PII, secure transit/at-rest, support deletion/retention policies and access control.

Backfill and replay: ability to recompute windows for past dates and correct bad data.

Scope to Cover

Event ingestion, deduplication, sessionization.

Counters/windows for last 7/30 days.

Per-user ranking and tie-breaking.

Batch vs. streaming trade-offs.

Storage: hot cache vs. warehouse/lake.

Freshness SLAs and data quality.

APIs for retrieval.

Personalization signals/weights.

Privacy/PII handling.

Backfill/replay strategy.

Design user top-10 songs service

Quick Overview

Design a Service to Compute Each User's Top 10 Songs

Context

Requirements

Functional

Non-Functional

Scope to Cover

Solution

Submit Your Answer to Earn 20XP

Design user top-10 songs service

Quick Overview

Design a Service to Compute Each User's Top 10 Songs

Context

Requirements

Functional

Non-Functional

Scope to Cover

Solution

Submit Your Answer to Earn 20XP