ALGORITHM READING NOTE

Hash Table

A hash table maps keys to bucket locations using a hash function. It aims for very fast average lookup, insertion and deletion.

TYPEData structureCATEGORYData StructuresDEPTHBeginnerTYPICAL COMPLEXITYavg O(1), worst O(n)

SHORT INTERVIEW ANSWER

Start with this mental model

A hash table maps keys to bucket locations using a hash function. It aims for very fast average lookup, insertion and deletion.

SIMPLE EXPLANATION

How it works, without unnecessary jargon

The hash function converts a key into an index-like value.

Different keys may collide, so the implementation needs a collision strategy such as chaining or open addressing.

EXECUTION

Read the algorithm as a sequence of decisions

Hash the key.

Map the hash to a bucket.

Resolve collisions and compare actual keys.

A small example to keep in mind

A user id can be hashed to a bucket; the bucket then stores or finds the actual user entry.

READABLE JAVASCRIPT IMPLEMENTATIONJavaScript

class HashTable {
  constructor(size = 16) {
    this.buckets = Array.from({ length: size }, () => []);
  }
  hash(key) {
    let h = 0;
    for (const ch of String(key)) h = (h * 31 + ch.charCodeAt(0)) >>> 0;
    return h % this.buckets.length;
  }
}

How to read this code

Do not memorize the syntax. Follow the state that changes on each line and connect it to the invariant described above.

COMPLEXITY

avg O(1), worst O(n)

Do not quote this complexity mechanically. Ask which operation or input dimension it describes, then derive the cost from the loops, recursion depth, data-structure operations and any preprocessing assumptions.

WHEN TO USE IT

Good fit

Choose it when its dominant operations match your workload.
Compare memory overhead as well as Big-O.

COMMON MISTAKES

What usually goes wrong

Calling average O(1) a guaranteed worst-case O(1).
Ignoring key equality and collision handling.

HOW TO EXPLAIN IT IN AN INTERVIEW

A professional answer shape

Explain average O(1), collisions, load factor and resizing. Those details distinguish a strong answer from 'it is just a key-value map'.

Problem→Core idea→Invariant / state→Big-O→Trade-off

QUICK INTERVIEW CHECK

What problem does Hash Table solve?

A hash table maps keys to bucket locations using a hash function. It aims for very fast average lookup, insertion and deletion.

What should I mention about complexity?

Its typical cost here is avg O(1), worst O(n), but a complete answer should connect that cost to the representation, input constraints and the dominant operations.

What is the most common mistake?

Calling average O(1) a guaranteed worst-case O(1).

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class HashTable { constructor(size = 16) { this.buckets = Array.from({ length: size }, () => []); } hash(key) { let h = 0; for (const ch of String(key)) h = (h * 31 + ch.charCodeAt(0)) >>> 0; return h % this.buckets.length; } }