Merge sort data can be sorted using external sorting which usses merge sort..

Sorting 1 GB of data with only 100 MB of available main memory

Sorting is a process of arranging data in a particular order. It is a fundamental operation in computer science and is used in various applications. However, sorting large amounts of data can be challenging when the available memory is limited. In this scenario, we have to sort 1 GB of data with only 100 MB of available main memory.

Sorting techniques

There are various sorting techniques available, each with its advantages and disadvantages. Some of the common sorting techniques are:

1. Bubble Sort
2. Insertion Sort
3. Selection Sort
4. Merge Sort
5. Quick Sort
6. Heap Sort
7. Radix Sort
8. Counting Sort

Which sorting technique will be most appropriate?

Among all the sorting techniques, the most appropriate one for sorting 1 GB of data with only 100 MB of available main memory is Merge Sort.

Why Merge Sort?

Merge Sort is a divide and conquer algorithm that recursively divides an array into two halves until each sub-array contains only one element. It then merges the sub-arrays by comparing and arranging the elements in the correct order.

The following are the reasons why Merge Sort is the most appropriate sorting technique:

1. Merge Sort has a stable time complexity of O(n log n), which is efficient for large datasets.
2. Merge Sort is a comparison-based sorting algorithm that does not require random access to the data. Therefore, it is suitable for sorting data that is stored on external devices with slow access times.
3. Merge Sort is a stable sorting algorithm, which means that it preserves the relative order of the equal elements in the input array.
4. Merge Sort can be easily implemented to sort data that is too large to fit into memory by dividing the data into smaller chunks and sorting them individually.

Conclusion

In conclusion, Merge Sort is the most appropriate sorting technique for sorting 1 GB of data with only 100 MB of available main memory. It has a stable time complexity, is suitable for sorting data on external devices, is stable, and can be easily implemented to sort large datasets.