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You have to sort 1 GB of data with only 100 MB of available main memory. Which sorting technique will be most appropriate?
- a)Heap sort
- b)Merge sort
- c)Quick sort
- d)Insertion sort
Correct answer is option 'B'. Can you explain this answer?
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Verified Answer
You have to sort 1 GB of data with only 100 MB of available main memor...
The data can be sorted using external sorting which uses merging technique. This can be done as follows:
1. Divide the data into 10 groups each of size 100.
2. Sort each group and write them to disk.
3. Load 10 items from each group into main memory.
4. Output the smallest item from the main memory to disk. Load the next item from the group whose item was chosen.
5. Loop step #4 until all items are not outputted. The step 3-5 is called as merging technique.
Most Upvoted Answer
You have to sort 1 GB of data with only 100 MB of available main memor...
The data can be sorted using external sorting which uses merging technique. This can be done as follows:
1. Divide the data into 10 groups each of size 100.
2. Sort each group and write them to disk.
3. Load 10 items from each group into main memory.
4. Output the smallest item from the main memory to disk. Load the next item from the group whose item was chosen.
5. Loop step #4 until all items are not outputted. The step 3-5 is called as merging technique.
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You have to sort 1 GB of data with only 100 MB of available main memor...
Merge Sort
Merge sort is the most appropriate sorting technique for sorting 1 GB of data with only 100 MB of available main memory because it is an efficient external sorting algorithm that can handle large amounts of data with limited memory.
Explanation:
- Divide and Conquer: Merge sort follows the divide-and-conquer approach, where it divides the data into smaller chunks, sorts them individually, and then merges them back together. This allows it to efficiently handle large datasets.
- Memory Efficiency: In merge sort, the data is divided into smaller chunks that can fit into the available memory. This makes it suitable for situations where the entire dataset cannot be loaded into memory at once.
- External Sorting: Merge sort is commonly used for external sorting, where data is too large to fit into main memory. It efficiently utilizes disk I/O operations to merge sorted sublists.
- Stable Sorting: Merge sort is a stable sorting algorithm, meaning that it preserves the relative order of equal elements. This is important when dealing with large datasets where data integrity is crucial.
Therefore, when sorting 1 GB of data with only 100 MB of available main memory, merge sort is the most appropriate choice due to its efficiency, memory handling capabilities, and stability.
Merge sort is the most appropriate sorting technique for sorting 1 GB of data with only 100 MB of available main memory because it is an efficient external sorting algorithm that can handle large amounts of data with limited memory.
Explanation:
- Divide and Conquer: Merge sort follows the divide-and-conquer approach, where it divides the data into smaller chunks, sorts them individually, and then merges them back together. This allows it to efficiently handle large datasets.
- Memory Efficiency: In merge sort, the data is divided into smaller chunks that can fit into the available memory. This makes it suitable for situations where the entire dataset cannot be loaded into memory at once.
- External Sorting: Merge sort is commonly used for external sorting, where data is too large to fit into main memory. It efficiently utilizes disk I/O operations to merge sorted sublists.
- Stable Sorting: Merge sort is a stable sorting algorithm, meaning that it preserves the relative order of equal elements. This is important when dealing with large datasets where data integrity is crucial.
Therefore, when sorting 1 GB of data with only 100 MB of available main memory, merge sort is the most appropriate choice due to its efficiency, memory handling capabilities, and stability.
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You have to sort 1 GB of data with only 100 MB of available main memory. Which sorting technique will be most appropriate?a)Heap sortb)Merge sortc)Quick sortd)Insertion sortCorrect answer is option 'B'. Can you explain this answer?
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