Partitioning Logic
Partitioning logic refers to algorithms that divide a problem or data structure into smaller partitions to enable parallel or more efficient processing.
Some examples include:
 Divide and conquer algorithms
 Hash partitioning in distributed systems
 Partitioning for parallel mapreduce
 Database sharding and partitioning
Java  Array quicksort partitioning:


C++  Graph partitioning for distribution:


Python  Database sharding:


Partitioning decomposes problems into independently solvable chunks, enabling parallelism. Useful across domains.
Quick Select and Quick Sort algorithms use a partitioning logic where an element is placed at its correct position in the sorted array, and all elements smaller than it are placed to its left, and all larger elements to its right. This is done through a partition function.
Here are some LeetCode problems that can be solved using this partitioning logic:
Find the kth largest (or smallest) element in an unsorted array:
 Kth Largest Element in an Array. This problem can be solved using Quick Select algorithm, which is an efficient inplace variation of Quick Sort that is used to select the kth largest element.
Sort an array:
 Sort an Array. This is a basic application of the Quick Sort algorithm.
Color Sort:
 Sort Colors. This problem is a variation of the Dutch national flag problem, which can be solved using a threeway partitioning algorithm, a variant of Quick Sort partitioning.
Find the kth smallest element in a sorted matrix:
 Kth Smallest Element in a Sorted Matrix. This problem uses a binary search approach, but the partitioning logic is similar to Quick Select.
Wiggle Sort:
 Wiggle Sort II. This problem can be solved using a variant of Quick Select to find the median and then partition the array.
While these problems can be solved using partitioning logic, there may be other efficient algorithms and approaches to solve them depending on the constraints and requirements of the problem.
Code
Here’s a simple example of the partitioning logic of Quick Select / Quick Sort in Python:


The partition
function takes an array arr
and two indexes low
and high
, and rearranges the array such that all elements less than arr[high]
(the pivot) are to the left of it, and all elements greater than arr[high]
are to the right. It then returns the index of the pivot element.
This is a simple, inplace implementation of the partitioning logic. You could use it as a building block for more complex problems that require partitioning, such as the LeetCode problems mentioned in the previous response.
In Quick Select or Quick Sort, you would typically follow up this partitioning step with recursive calls to process the two partitions.