Hash Map vs Array vs Linked List for Lookup in DSA Go - Visual Comparison

Concept Flow - Hash Map vs Array vs Linked List for Lookup

Start Lookup

↓

Choose Data Structure

↓

Array

↓

Check Index

↓

Compare Value

↓

Found?

No→Not Found

↓

Return Value

↓

End Lookup

Lookup starts by choosing the data structure, then uses index, traversal, or hashing to find the value.

Execution Sample

DSA Go

array := []int{10, 20, 30}
linkedList := 10 -> 20 -> 30
hashMap := map[int]bool{10: true, 20: true, 30: true}
lookup(20)

Lookup for value 20 in array, linked list, and hash map.

Execution Table

Step	Data Structure	Operation	Details	Result	Visual State
1	Array	Check index 0	array[0] == 10	No match	[10, 20, 30]
2	Array	Check index 1	array[1] == 20	Match found	[10, 20, 30]
3	Linked List	Check node 1	node.value == 10	No match	10 -> 20 -> 30 -> null
4	Linked List	Check node 2	node.value == 20	Match found	10 -> 20 -> 30 -> null
5	Hash Map	Compute hash	hash(20) -> bucket	Access bucket	{10:true,20:true,30:true}
6	Hash Map	Check bucket	bucket contains 20	Match found	{10:true,20:true,30:true}
7	All	Return result	Value found in all	Success	Array: [10,20,30], LinkedList: 10->20->30, HashMap: {10:true,20:true,30:true}
8	Array	Check index 3	array[3] out of range	Stop	[10, 20, 30]
9	Linked List	Check node 4	node == null	Stop	10 -> 20 -> 30 -> null
10	Hash Map	Check bucket	bucket empty	Stop	{10:true,20:true,30:true}

💡 Lookup stops when value is found or all elements checked.

Variable Tracker

Variable	Start	After Step 1	After Step 2	After Step 3	After Step 4	After Step 5	After Step 6	Final
Array Index	0	1	1 (found)	-	-	-	-	1 (found)
Linked List Node	head (10)	10	10	20	-	-	-	20 (found)
Hash Map Bucket	-	-	-	-	-	bucket for 20	bucket contains 20	bucket contains 20

Key Moments - 3 Insights

Why does array lookup stop after checking index 1?

Because at step 2 in execution_table, array[1] matches the value 20, so lookup stops early.

Why does linked list lookup need to check nodes one by one?

As shown in steps 3 and 4, linked list nodes are checked sequentially because there is no direct index access.

How does hash map find the value so quickly?

At steps 5 and 6, hash map computes a hash to directly access the bucket, avoiding traversal.

Visual Quiz - 3 Questions

Look at the execution_table, at which step does the array find the value 20?

A Step 2

B Step 1

C Step 3

D Step 4

💡 Hint

Check the 'Result' column for 'Match found' under 'Array' data structure.

According to variable_tracker, what is the linked list node value after step 3?

A 30

B 20

C 10

D null

💡 Hint

Look at 'Linked List Node' row after 'After Step 3' column.

If the hash map did not contain 20, which step in execution_table would show 'Stop' due to empty bucket?

A Step 6

B Step 10

C Step 7

D Step 9

💡 Hint

Check the 'Details' and 'Result' columns for hash map stopping conditions.

Concept Snapshot

Lookup in Array: Check elements by index until found or end.
Lookup in Linked List: Traverse nodes one by one until found or end.
Lookup in Hash Map: Compute hash to access bucket directly.
Hash Map is fastest for lookup, Array is fast if index known, Linked List is slowest.
Stop lookup when value found or all checked.

Full Transcript

This visual execution compares lookup in three data structures: array, linked list, and hash map. Lookup starts by choosing the data structure. For array, it checks elements by index one by one until it finds the value or reaches the end. For linked list, it traverses nodes sequentially checking each value. For hash map, it computes a hash to directly access the bucket where the value might be stored, making lookup faster. The execution table shows each step, operation, and the current state of the data structure. Variable tracker shows how indexes or nodes move during lookup. Key moments clarify why array stops early when value is found, why linked list needs traversal, and how hash map uses hashing for quick access. The quiz tests understanding of these steps. The snapshot summarizes lookup behavior and speed differences among these data structures.

Practice

1. Which data structure provides the fastest average lookup time for finding an element by key?

easy

A. Stack

B. Hash Map

C. Linked List

D. Array

Solution

1. Step 1: Understand lookup times for each data structure

   Hash Map uses hashing to find keys quickly, usually in constant time O(1). Arrays require scanning or index access, O(1) if index known but O(n) if searching by value. Linked Lists require scanning all nodes, O(n).

2. Step 2: Compare average lookup times

   Hash Map is fastest on average for key lookup because it directly computes the position. Arrays and Linked Lists are slower for searching by value.

3. Final Answer:

   Hash Map -> Option B

4. Quick Check:

   Fastest lookup by key = Hash Map [OK]

Hint: Hash Map uses keys for O(1) lookup, arrays and lists do not [OK]

Common Mistakes:

• Confusing array index access with searching by value
• Assuming linked list lookup is fast
• Thinking stack is a lookup structure

2. Which of the following is the correct way to declare a hash map in Go for string keys and integer values?

easy

A. var m map[string]int = make(map[string]int)

B. var m = [string]int{}

C. var m = []int{}

D. var m map[int]string = make(map[int]string)

Solution

1. Step 1: Identify correct Go syntax for hash map declaration

   In Go, maps are declared with 'map[keyType]valueType' and initialized with make(). var m map[string]int = make(map[string]int) uses 'map[string]int' and make(), which is correct.

2. Step 2: Check other options for errors

   var m = [string]int{} uses array syntax incorrectly. var m = []int{} is a slice, not a map. var m map[int]string = make(map[int]string) has reversed key and value types compared to question.

3. Final Answer:

   var m map[string]int = make(map[string]int) -> Option A

4. Quick Check:

   Go map syntax = var m map[string]int = make(map[string]int) [OK]

Hint: Use make(map[keyType]valueType) to create Go maps [OK]

Common Mistakes:

• Using array or slice syntax instead of map
• Not initializing map with make()
• Swapping key and value types

3. You have a large dataset of unique user IDs and want to check membership efficiently. Which data structure should you choose and why? A hash map, an array, or a linked list?

easy

A. Array, because it stores elements contiguously for fast access

B. Linked List, because it uses less memory and is easy to insert

C. None, use a stack for membership checking

D. Hash Map, because it provides average O(1) lookup time for membership checks

Solution

1. Step 1: Understand membership check requirements

   Membership check means quickly finding if an element exists. For large datasets, speed matters.

2. Step 2: Compare data structures for membership check

   Array requires scanning O(n), linked list also O(n). Hash Map uses hashing for average O(1) lookup, best for membership.

3. Final Answer:

   Hash Map, because it provides average O(1) lookup time for membership checks -> Option D

4. Quick Check:

   Membership check fastest = Hash Map [OK]

Hint: Use hash map for fast membership checks in large data [OK]

Common Mistakes:

• Choosing array or list for fast membership
• Ignoring hash map average O(1) lookup
• Confusing stack with membership structure

4. What will be the output of the following Go code snippet?

package main
import "fmt"
func main() {
  arr := []int{10, 20, 30, 40}
  m := make(map[int]int)
  for i, v := range arr {
    m[v] = i
  }
  fmt.Println(m[30])
}

medium

A. 2

B. 30

C. 0

D. Compilation error

Solution

1. Step 1: Understand the loop and map assignment

   The loop iterates over array elements with index i and value v. It sets m[v] = i, so key is element value, value is index.

2. Step 2: Find the value for key 30 in map

   For element 30, index is 2, so m[30] = 2. Printing m[30] outputs 2.

3. Final Answer:

   2 -> Option A

4. Quick Check:

   m[30] = index 2 [OK]

Hint: Map keys are array values, values are indices [OK]

Common Mistakes:

• Confusing key and value in map
• Expecting output 30 instead of index
• Thinking code has error

5. Identify the error in the following Go code that tries to find if a value exists in a linked list:

package main
import "fmt"

type Node struct {
  val int
  next *Node
}

func contains(head *Node, target int) bool {
  for head != nil {
    if head.val == target {
      return true
    }
    head = head.next
  }
  return false
}

func main() {
  var head *Node
  head.val = 10
  head.next = nil
  fmt.Println(contains(head, 10))
}

medium

A. Loop condition should be head.next != nil

B. Function contains has wrong return type

C. head is nil, so accessing head.val causes runtime panic

D. Missing import for fmt package

Solution

1. Step 1: Analyze initialization of head pointer

   head is declared as nil pointer. Accessing head.val without allocating Node causes runtime panic (nil pointer dereference).

2. Step 2: Check function and loop correctness

   Function contains is correct. Loop condition is correct.

3. Final Answer:

   head is nil, so accessing head.val causes runtime panic -> Option C

4. Quick Check:

   Nil pointer access causes panic [OK]

Hint: Initialize nodes before accessing fields to avoid nil panic [OK]

Common Mistakes:

• Ignoring nil pointer dereference
• Thinking loop condition is wrong
• Missing import is not main error