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MYSQL DATABASE MYSQL DATABASEquick-sort.pptx
1. QuickSort:
QuickSort is a divide-and-conquer algorithm that chooses a pivot
element and partitions the array into two subarrays, one containing
elements less than the pivot and the other containing elements greater
than the pivot. It then recursively sorts these subarrays.
2. Introduction to Sorting and Its Importance
Sorting is the process of arranging elements in a specific
order, which can be ascending or descending based on a
defined key or criteria. The importance of sorting cannot
be overstated, as it underpins numerous data processing
tasks, enabling efficient data retrieval, searching, and
analysis.
3. Advantages of QuickSort
QuickSort offers several advantages that make it a preferred choice for sorting
data:
Speed: QuickSort is exceptionally fast, often outperforming other sorting
algorithms like Bubble Sort or Insertion Sort.
In-Place Sorting: QuickSort requires minimal additional memory, as it sorts the
elements in the original array, making it an in-place sorting algorithm.
Versatility: QuickSort can be easily adapted for various data types, including
integers, floating-point numbers, and strings.
4. Consider: arr[] = {10, 80, 30, 90, 40}.
Compare 10 with the pivot and as it is less than pivot arrange it accrodingly.
5. Compare 80 with the pivot. It is greater than pivot.
Partition in QuickSort: Compare pivot with 80
6. Compare 30 with pivot. It is less than pivot so arrange it accordingly.
9. Heap sort - is a comparison-based sorting technique
based on Binary Heap data structure. It is similar to the
selection sort where we first find the minimum element
and place the minimum element at the beginning. Repeat
the same process for the remaining elements.
10. Advantages of Heap Sort
Efficient insertion and deletion: The heap data structure allows efficient
insertion and deletion of elements. When a new element is added to the
heap, it is placed at the bottom of the heap and moved up to its correct
position using the heapify operation. Similarly, when an element is
removed from the heap, it is replaced by the bottom element, and the
heap is restructured using the heapify operation.
Efficient priority queue: The heap data structure is commonly used to
implement a priority queue, where the highest priority element is
always at the top of the heap. The heap allows constant-time access to
the highest priority element, making it an efficient data structure for
implementing priority queues.
11. Disadvantages of Heap Data Structure:
Lack of flexibility: The heap data structure is not very flexible, as
it is designed to maintain a specific order of elements. This
means that it may not be suitable for some applications that
require more flexible data structures.
Not ideal for searching: While the heap data structure allows
efficient access to the top element, it is not ideal for searching
for a specific element in the heap. Searching for an element in a
heap requires traversing the entire tree, which has a time
complexity
