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Lesson plan 31: Distributed query execution
Follow distributed scans, joins, exchanges, and partial aggregation through data movement.
Placement: Part 6: Scaling execution and state delivery.
Prerequisites: Lesson 30: Distributed transactions, plus the earlier dependency chain.
Learning outcomes
- Follow distributed scans, joins, exchanges, and partial aggregation through data movement.
- Calculate broadcast and repartition costs and handle weighted aggregate state correctly.
- Explain partition pruning, skew, stragglers, and the difference between transactional and analytical priorities.
- Separate a general mechanism, a documented implementation choice, and an illustrative numerical assumption.
Teaching sequence
- Establish the motivating situation: A global join moves far more bytes than its final result contains.
- Introduce the vocabulary and the correctness obligation before an optimization. Define partition pruning, distributed joins, shuffle.
- Develop the mechanism: Compare broadcast, repartition, and colocated joins; push partial aggregation without changing semantics.
- Follow the complete worked example: Broadcasting a 20 MB dimension to 50 workers moves about 1 GB before protocol overhead. Explain the assumptions, intermediate units, and limiting interpretation.
- Extend the scenario to changed load, skew, or failure, explaining aggregation, stragglers, OLAP priorities.
- Connect the mechanism to a documented implementation and an alternative with a different workload fit. Close by stating the remaining cost and the next lesson dependency.
Required chapter material
Use a complete execution trace or worked calculation, supported by an annotated static diagram or table. Include language-neutral pseudocode or labeled SQL when it clarifies the mechanism. State preconditions, ownership, visibility, and failure boundaries for algorithms. Describe operational costs as well as the normal path. All questions raised in the narrative must be resolved in the text.
Visual explanation
A distributed-plan graph labels local operators and network exchanges; a weighted-average trace carries sum and count instead of averaging averages. The accompanying prose explains the arrows, state changes, or table entries so the lesson remains understandable in a plain Markdown reader.
Editorial checks
Confirm that the numerical example agrees with its units and assumptions. Check that a faster path preserves the stated contract, or explicitly identify the changed guarantee. Keep hypothetical figures separate from product measurements. Explain both an appropriate use and a limitation of the case design. Check terminology against the glossary and links against the course index.