Differentiate between internal sorting and external sorting.

Internal Sorting

• Occurs entirely in main memory.
• Utilizes a wide variety of sorting algorithms, including:
  • Bubble sort
  • Selection sort
  • Insertion sort
  • Merge sort
  • Quick sort
  • Heap sort
• Suitable for small to medium-sized datasets that fit entirely in main memory.
• Efficient for datasets that are small enough to be processed in a single pass.
• Requires additional overhead for copying data into and out of main memory.
• Generally faster than external sorting due to the higher speed of main memory compared to secondary storage.

External Sorting

• Used for sorting large datasets that cannot fit entirely in main memory.
• Employs a divide-and-conquer approach:
  • The dataset is divided into smaller chunks that can be sorted individually in main memory.
  • The sorted chunks are merged together to obtain the final sorted dataset.
• Common external sorting algorithms include:
  • Merge sort
  • Quicksort
  • Heapsort
• Suitable for large datasets that exceed the capacity of main memory.
• Requires multiple passes over the dataset, which can be time-consuming.
• Utilizes secondary storage (e.g., hard disk) to store intermediate results and sorted chunks.
• Generally slower than internal sorting due to the involvement of slower secondary storage devices.

Comparison

Feature	Internal Sorting	External Sorting
Location	Main memory	Main memory and secondary storage
Suitable for	Small to medium-sized datasets	Large datasets that exceed main memory capacity
Efficiency	Faster for small datasets	Slower for large datasets
Overhead	Requires additional overhead for copying data into and out of main memory	Utilizes secondary storage, which can be slower than main memory
Algorithms	Utilizes a wide variety of sorting algorithms	Commonly employs merge sort, quicksort, or heapsort
Number of passes	Single pass	Multiple passes