Chapter 10 — Stream Processing System (Flink-like)
Chapter of Distributed Systems Fundamentals, part of System Design.
Purpose
Watermarks, windowing, stateful operators, exactly-once.
[stub: stream-processing-system]— fill this in. Greppable doc-debt marker.
Metadata
| Dimension | Detail |
|---|---|
| Author | Amit Singh |
| Scope | MAANG interview preparation — not production documentation |
Local graph
Linked from 2 notes
Data Engineering
A book-shaped table of contents for data engineering: foundations and lifecycle, data modeling, storage systems, ingestion and CDC, distributed processing (Spark/Flink), SQL mastery, workflow orchestration, data quality, platform and cloud architecture, pipeline observability, security and governance, performance engineering, system design, and MAANG interview preparation through capstone builds — cross-linking the existing observability book instead of duplicating it.
System Design
Principal/Staff-level system design reference collection for MAANG interview preparation — observability pipelines, distributed systems, reliability engineering, and beyond.
Related notes
Chapter 8 — Distributed Message Queue (Kafka-like)
Partitioning, consumer groups, at-least-once vs. exactly-once.
Chapter 11 — Rate Limiter (Distributed)
Token bucket, leaky bucket, sliding window, Redis-backed global limiter.
Chapter 12 — Consensus & Leader Election
Raft/Paxos, split-brain prevention, fencing tokens.
Chapter 9 — Distributed Key-Value Store (DynamoDB-like)
Consistent hashing, replication, read/write quorum.