Common Hashing Patterns
Explore common hashing patterns in JavaScript coding interviews, focusing on frequency counting and prefix sum techniques. Learn to identify when to apply each pattern, optimize performance with Maps, and avoid common pitfalls, enabling you to solve typical hash table problems confidently.
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Recognizing a hash table as the right data structure is only the first step. In JavaScript, that usually means reaching for a Map. The next step is knowing which pattern to apply. This lesson covers the two most important hashing patterns in coding interviews: frequency counting and prefix sum with hashing. Together, they cover the majority of hash table-based interview problems.
Interview lens: Both patterns share a common signal: repeated lookup or counting over a sequence. Any problem that requires us to know how many times something appeared, or whether a subarray with a given sum exists, is almost certainly one of these two patterns. Spotting that signal early and reaching for a hash table, usually a JavaScript Map, is the reflex this lesson builds.
Frequency counting
The frequency counting pattern uses a hash table to count how many times each element appears in a collection during a single pass. We map each unique element to its count, incrementing the count each time we encounter the element. Once the pass is complete, the hash table gives us
This pattern eliminates the need for nested loops. Without a hash table, counting occurrences of every element requires an