What are the main challenges in data partitioning?

What are the main challenges in data partitioning?

Data partitioning can face several challenges, including data skew, maintaining consistency, and managing complexity.

Can you explain what data skew is?

Data skew occurs when data is unevenly distributed across partitions, leading to some partitions being overloaded while others are underutilized.

How can I mitigate data skew?

You can mitigate data skew by using techniques like data sampling, partitioning based on range or hash, and monitoring data distribution.

What about consistency issues?

Consistency issues arise when updates to data are not reflected across all partitions, which can lead to stale or conflicting data.

What strategies can help maintain consistency?

To maintain consistency, you can implement distributed transactions, use consensus algorithms, or adopt eventual consistency models.