Snowflake Certification Practice Test

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What does data skew refer to in database partitions?

The ideal size of all partitions
Having equal volume of data across partitions
Partitions being disproportionately-sized
The presence of micro-partitions only

The correct answer is: Partitions being disproportionately-sized

Data skew in the context of database partitions refers to the situation where partitions are not evenly distributed in terms of data volume. When there is data skew, some partitions contain a significantly larger amount of data compared to others, which can lead to performance issues such as unbalanced workloads. This imbalance can cause certain nodes in a distributed system to work harder than others, resulting in longer processing times for queries and inefficient resource utilization. Understanding data skew is crucial for optimizing performance in database systems, especially in scenarios involving parallel processing. When partitions are disproportionately sized, it can affect the speed and efficiency of data retrieval and processing tasks. Identifying and managing data skew involves monitoring the distribution of data across partitions and implementing strategies to rebalance or resize partitions as needed. This can help ensure more evenly distributed workloads and improve overall performance.