Code Room
System designHard
Question
Design the storage layer for a data lake holding petabytes of analytical data as columnar (Parquet) files on object storage, queried by Spark/Presto-style engines. Workloads are append-heavy ingestion plus large analytical scans that read a few columns across billions of rows, with occasional row-level updates/deletes (GDPR erasure). How do you organize files, make queries fast, and support mutation on an immutable object store?
What a strong answer looks like
Clarify scale and constraints first. Propose a clean component breakdown, then go deep on the hard parts — data model, bottlenecks, consistency, failure modes — and name the trade-offs you are making.
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