Understanding the quickselect algorithm

When designing large-scale software systems that process large volumes of data, software engineers often need to balance efficiency and scalability. These systems may process millions of records to rank search results, surface top recommendations, or find the kth-best item. In most of these cases, a perfectly ordered dataset isn’t required, and only some partial ordering of a subset of the dataset can solve the problem. However, sorting-based solutions sort the entire dataset, which becomes a bottleneck.

The quickselect is an algorithm designed to efficiently solve them at scale. It finds the top k or bottom k items in an unsorted dataset without sorting the dataset, where the definition of top or bottom is problem dependent.