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- 1. Types of Sortingin Database Structure and Algorithms Sorting algorithms are fundamental in computer science, organizing data efficiently. They play a crucial role in database management and data processing. Understanding various sorting techniques is essential for optimizing performance in diverse applications. by Arya M
- 2. Introduction to Sorting Algorithms 1Definition Sorting algorithms arrange data elements in a specific order, typically ascending or descending. 2 Importance They enhance data retrieval efficiency and are fundamental to many computer science applications. 3 Categories Sorting algorithms are broadly classified into comparison- based and non-comparison-based techniques.
- 3. Comparison-Based Sorting Algorithms 1 KeyConcept These algorithms compare elements to determine their relative order in the sorted output. 2 Time Complexity Most comparison-based sorts have an average time complexity of O(n log n). 3 Common Examples Bubble Sort, Selection Sort, Insertion Sort, Quick Sort, and Merge Sort.
- 4. Bubble Sort 1 Compare Adjacent BubbleSort repeatedly steps through the list, comparing adjacent elements and swapping them. 2 Bubble Up Larger elements "bubble up" to the end of the list with each iteration. 3 Repeat The process is repeated until no more swaps are needed, indicating the list is sorted.
- 5. Selection Sort 1 FindMinimum Selection Sort finds the minimum element in the unsorted portion of the array. 2 Swap It swaps this minimum element with the first unsorted element. 3 Repeat The process continues until the entire array is sorted in ascending order.
- 6. Insertion Sort Start Insertion Sortbegins with the second element, considering the first as sorted. Compare It compares the current element with previous elements, shifting them if necessary. Insert The current element is then inserted into its correct position in the sorted portion. Repeat This process continues until all elements are in their proper sorted positions.
- 7. Quick Sort Divide Quick Sortselects a pivot element and partitions the array around it. Conquer It recursively sorts the sub-arrays on either side of the pivot. Combine The sorted sub-arrays are combined to produce the final sorted array.
- 8. Merge Sort 1 Divide MergeSort divides the unsorted list into n sublists, each containing one element. 2 Conquer It repeatedly merges sublists to produce new sorted sublists until there is only one. 3 Combine The final merged sublist is the sorted list, combining efficiency with stability.
- 9. Non-Comparison-Based Sorting Algorithms 1 KeyConcept These algorithms don't compare elements directly, often using numerical properties for sorting. 2 Time Complexity They can achieve linear time complexity, outperforming comparison-based sorts in specific scenarios. 3 Examples Counting Sort, Bucket Sort, and Radix Sort are common non- comparison-based algorithms.
- 10. Radix Sort 1 Least SignificantDigit Radix Sort starts by sorting elements based on their least significant digit. 2 Iterate It continues sorting based on each digit, moving towards the most significant. 3 Final Sort After processing all digits, the list is completely sorted in linear time.