Swift Algorithm Club: Hash Tables
Learn how to implement a hash table data structure in Swift, in this step-by-step tutorial from the Swift Algorithm Club. By Kelvin Lau.
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Contents
Swift Algorithm Club: Hash Tables
20 mins
Resizing the Hash Table
This version of the hash table always uses an array of fixed size or capacity. If you have many items to store in the hash table, choose a prime number greater than the maximum number of items.
The load factor of a hash table is the percentage of the capacity that is currently used. If there are 3 items in a hash table with 5 buckets, then the load factor is 3/5 = 60%
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If the hash table is small, and the chains are long, the load factor can become greater than 1, which is a sign of bad performance. One way to avoid this is to resize the hash table. Adding the code for this condition is left as an exercise for the reader. Keep in mind that making the buckets array larger will change the array indices that the keys map to! This requires you to insert all the elements again after resizing the array.
Where to Go From Here?
I hope you enjoyed this tutorial on implementing a Swift hash table!
Here is a playground with the above code. You can also find the original implementation here.
This was just one of the many algorithms in the Swift Algorithm Club repository. If you're interested in more, check out the repo.
It's in your best interest to know about algorithms and data structures - they're solutions to many real-world problems, and are frequently asked as interview questions. Plus it's fun!
So stay tuned for many more tutorials from the Swift Algorithm club in the future. In the meantime, if you have any questions on implementing trees in Swift, please join the forum discussion below.
If you enjoyed what you learned in this tutorial, why not check out our Data Structures and Algorithms in Swift book, available on our store?
In Data Structures and Algorithms in Swift, you’ll learn how to implement the most popular and useful data structures and when and why you should use one particular datastructure or algorithm over another. This set of basic data structures and algorithms will serve as an excellent foundation for building more complex and special-purpose constructs.
As well, the high-level expressiveness of Swift makes it an ideal choice for learning these core concepts without sacrificing performance.
- You’ll start with the fundamental structures of linked lists, queues and stacks, and see how to implement them in a highly Swift-like way.
- Move on to working with various types of trees, including general purpose trees, binary trees, AVL trees, binary search trees and tries.
- Go beyond bubble and insertion sort with better-performing algorithms, including mergesort, radix sort, heap sort and quicksort.
- Learn how to construct directed, non-directed and weighted graphs to represent many real-world models, and traverse graphs and trees efficiently with breadth-first, depth-first, Dijkstra’s and Prim’s algorithms to solve problems such as finding the shortest path or lowest cost in a network.
- And much, much more!
By the end of this book, you’ll have hands-on experience solving common issues with data structures and algorithms — and you’ll be well on your way to developing your own efficient and useful implementations.