What are the common pitfalls in data partitioning?
An example of an AI chatbot conversation about data partitioning pitfalls and how to avoid them.
What are the common pitfalls in data partitioning?
Common pitfalls include uneven data distribution, over-partitioning, and ignoring query patterns.
How can uneven data distribution affect performance?
Uneven distribution can lead to hotspots, where some partitions are overloaded while others are underutilized.
What is over-partitioning and why is it a problem?
Over-partitioning creates too many partitions, which can increase management overhead and slow down queries.
Can you give examples of ignoring query patterns?
Ignoring query patterns can lead to inefficient partitioning strategies, causing slow query performance.
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