Computer Science
Grade 9
20 min
Hash Tables Basics
Hash Tables Basics
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1
Introduction & Learning Objectives
Learning Objectives
Explain what a hash collision is and why it occurs.
Describe and visually trace the 'Separate Chaining' method for collision resolution.
Describe and visually trace the 'Linear Probing' method for collision resolution.
Define 'Load Factor' and calculate it for a given hash table.
Explain how a high load factor impacts hash table performance.
Compare the advantages and disadvantages of separate chaining and linear probing.
Ever tried to put a book on a library shelf, only to find it's already full? 📚💥 Hash tables face a similar problem called a 'collision'. Let's learn how they cleverly solve this!
In this lesson, we'll explore what happens when a hash table isn't perfect. We will learn about &...
2
Key Concepts & Vocabulary
TermDefinitionExample
Hash CollisionAn event that occurs when two different keys are processed by a hash function and produce the exact same hash value (i.e., they are assigned to the same bucket/index in the array).If our hash function is `hash(key) = key % 10`, both the number `12` and `22` would cause a collision because `12 % 10 = 2` and `22 % 10 = 2`. Both want to go to index 2.
Collision ResolutionThe set of strategies or algorithms used to handle hash collisions and ensure all data can still be stored and retrieved correctly.Two common strategies are Separate Chaining (making a list at the collision spot) and Linear Probing (finding the next empty spot).
Separate ChainingA collision resolution technique where each bucket in the hash table is a pointer to another data structure, lik...
3
Core Syntax & Patterns
Load Factor Formula
α = n / k
Use this to measure how full a hash table is. 'n' is the number of items stored, and 'k' is the number of buckets (the size of the array). Programmers monitor this value to decide when to resize (rehash) the table, typically when α is around 0.7.
Separate Chaining Insertion Algorithm
1. Calculate index = hash(key). 2. Go to the list at that index. 3. Add the new key-value pair to the end of the list.
This is the step-by-step process for adding an item to a hash table that uses separate chaining. It's simple because you never have to look for an alternative spot.
Linear Probing Insertion Algorithm
1. Calculate initial index = hash(key). 2. Check if the bucket at the index is empty. 3. If it's empty, place the i...
4 more steps in this tutorial
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Challenging
A hash table of size 5 uses Linear Probing and `hash(key) = key % 5`. The final state is `[10, 11, 6, null, 14]`. Which of the following insertion sequences is IMPOSSIBLE to produce this final state?
A.10, 14, 11, 6
B.14, 10, 11, 6
C.10, 6, 14, 11
D.10, 11, 14, 6
Challenging
When comparing memory usage, under which condition is Separate Chaining most likely to use significantly MORE memory than a Linear Probing table of the same size (k) and with the same number of elements (n)?
A.When the table is sparsely populated (low load factor) and has many small linked lists.
B.When the table is nearly full (high load factor).
C.When all keys hash to the same bucket.
D.When the number of items is exactly equal to the number of buckets.
Challenging
A developer complains, 'My hash table is really slow. I should switch from Linear Probing to Separate Chaining to fix it.' What is the most likely underlying problem that this change alone will NOT fix?
A.The load factor is too high, and the table needs rehashing.
B.The keys being used are all integers.
C.The computer's memory is too slow.
D.poor hash function that causes an excessive number of collisions.
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