AdvancedTechnical
5 min
Data Partitioning Strategies
DatabasesPartitioningScalability
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Interview Question
How would you design data partitioning for a system that must handle billions of records with fast queries?
Key Points to Cover
- Choose partition keys that evenly distribute load
- Apply range, hash, or composite partitioning
- Design secondary indexes for query efficiency
- Handle partition rebalancing and hotspot prevention
Evaluation Rubric
Chooses effective partition keys30% weight
Explains partitioning strategies30% weight
Handles partition rebalancing20% weight
Optimizes query performance20% weight
Hints
- 💡Think DynamoDB partition key design.
Common Pitfalls to Avoid
- ⚠️Choosing a partition key with low cardinality, leading to uneven data distribution.
- ⚠️Ignoring query patterns and partitioning based solely on data volume, resulting in slow queries.
- ⚠️Over-partitioning, which can increase management overhead and query planning complexity without significant performance gains.
- ⚠️Under-partitioning, leading to massive partitions that are slow to scan and manage.
- ⚠️Neglecting the impact of secondary indexes on partition performance and maintenance, especially with global indexes on heavily partitioned tables.
Potential Follow-up Questions
- ❓How do you detect partition hotspots?
- ❓What about multi-tenant data?
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