Imagine you're sorting a large dataset stored on disk using Quick Sort. How would you mitigate the risk of running out of memory during the sorting process?
- Employ an external sorting algorithm such as Merge Sort
- Increase the size of available memory
- Split the dataset into smaller chunks and sort them individually
- Use an in-memory caching mechanism to reduce disk I/O operations
When sorting large datasets stored on disk, mitigating the risk of running out of memory involves using an in-memory caching mechanism. This mechanism allows frequently accessed data to be stored in memory, reducing disk I/O operations and minimizing the chance of memory exhaustion.
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