The Materialization Storm
A hard ai_coding interview practice problem on DataDriven. Write and execute real ai_coding code with instant grading.
- Domain
- ai_coding
- Difficulty
- hard
- Seniority
- L6
Problem
We added a new dataset to our Dagster repo last week. It declared 50 dynamic-partition assets that depend on shared upstream assets. Dagster scheduler CPU pegged at 100% within an hour and we're now seeing 12,000 materialization runs per hour for what should be ~50. Run tests/test_no_runaway_runs.py to reproduce. Find the cycle/fanout pattern in dagster_repo/assets.py and fix it so the partition fan-out is bounded and the run count is sane. Be ready to defend the trade-off your fix makes.
Summary
The graph started eating itself.
Practice This Problem
Solve this ai_coding problem with real code execution. DataDriven runs your solution and grades it automatically.