Hashtables

What is a hash table

A hash table is a data structure that holds key value pairs within it.

Hash tables are also known as hash maps.

Hash table uses a hash function to compute an index, also called a hash code, into an array of buckets or slots, from which the desired value can be found.

imagine you have a big toy box, and you want to remember where you put each of your toys. Now, instead of remembering the exact spot for each toy, you decide to use some special stickers.

Here's how it works:

Getting a Sticker (Hashing): Whenever you get a new toy, you put a special sticker on it. This sticker is like a magical code that helps you remember where to find the toy.

Finding the Toy (Indexing): Your toy box has many sections, like drawers. Each section is numbered. When you get a new toy, you look at its sticker (magical code) and decide which section (drawer) to put it in. You put the toy in that section.

Finding Toys Later (Lookup): When you want to play with a specific toy, you look at its sticker (magical code) again. This time, instead of searching through the entire toy box, you go directly to the section (drawer) that matches the sticker. That way, you find your toy quickly!

Sharing the Toy Box (Collisions): Sometimes, two toys might get the same sticker (magical code). It's like giving two toys the same special sticker by mistake. When that happens, you put both toys in the same section (drawer). So, when you look for a toy later, you might find a few toys in one section, but that's okay.

Cleaning Up (Deletion): If you decide you don't want a toy anymore, you can take it out of the section (drawer) by looking at its sticker. This way, you can keep your toy box neat and tidy.

a hash table is like your toy box with stickers. The stickers help you remember where to find your toys quickly, and even if a few toys end up in the same section, it's still easy to find them. That's how a hash table helps you organize and find things fast!

In python hash tables are implemented via a built in data structure called a dictionary.

Hash table explainers

Hash table questions

Duplicate detection

Problem: Given an array of integers, find if the array contains any duplicates.

Solution Approach: Use a hash table to store the seen elements. While iterating through the array, check if the current element is already in the hash table.

Word Frequency Counter:

Problem: Given a text document, count the frequency of each word.

Solution Approach: Use a hash table to store word frequencies. Tokenize the text into words, and for each word, update its count in the hash table.

Anagram Detection:

Problem: Given two strings, check if they are anagrams of each other.

Solution Approach: Use a hash table to count the occurrences of each character in both strings. If the counts are the same for each character, the strings are anagrams.

Collaborative Filtering:

Problem: Implement a simple collaborative filtering recommendation system. Given a dataset of user-item interactions, recommend items for a specific user.

Solution Approach: Use a hash table to store user-item interactions. For recommending items to a user, find similar users based on their interactions and suggest items that those users have interacted with but the current user hasn't.

Caching:

Problem: Implement a cache with a maximum capacity. When the capacity is exceeded, remove the least recently used item.

Solution Approach: Use a combination of a hash table and a doubly linked list. The hash table stores key-value pairs, and the linked list keeps track of the order of access. When accessing or inserting an item, update its position in the linked list. When the capacity is exceeded, remove the tail of the linked list.

Find the first non-repeating character in a string:

Write a Python function that takes a string as input and returns the first non-repeating character. You can use a hash table to track the count of each character in the string and then iterate over the string to find the first character with a count of 1.

Count the frequency of elements in a list:

Write a Python function that takes a list of elements as input and returns a dictionary with the frequency of each element. You can use a hash table to store the element as the key and its count as the value while iterating over the list.

Find the intersection of two lists:

Write a Python function that takes two lists as input and returns a list of their common elements (intersection). You can use hash tables to store the elements of one list and then iterate over the second list to find the common elements.

Check if two strings are anagrams:

Write a Python function that takes two strings as input and returns True if they are anagrams (contain the same characters in a different order), and False otherwise. You can use hash tables to store the count of characters in each string and compare the counts.

Remove duplicates from a list:

Write a Python function that takes a list as input and returns a new list with duplicates removed. You can use a hash table to track the elements seen so far and only add unique elements to the new list.

Design a system to store and retrieve user information from a database.

The system should allow users to search for other users based on their name or email address. How would you design the schema of the database? What algorithms and data structures would you use to optimize the search functionality?

Product similarity

Given a large dataset containing information about various products sold online, how would you implement an algorithm to find the most similar products to a given product? You may assume that the similarity between two products is determined by the number of common attributes they share.

Implement a cache mechanism for a web server.

When a client requests a resource, your program should check if it exists in the cache before fetching it from the origin server. If it does exist in the cache, return the cached version; otherwise, fetch it from the origin server and add it to the cache. Use a suitable data structure (e.g., hash table) to keep track of which resources have been cached.

Write a function to compute the frequency distribution of words in a text document.

Your function should take as input a string representing the contents of the file and output a dictionary mapping each word to its frequency count. For example, if the input string were "hello world hello", the output dictionary might look like {"hello": 2, "world": 1}.

is target the sum of two numbers?

Given a list of integers, write a function to determine whether there exists a pair of numbers whose sum equals a target value. For example, if the input list were [1, 2, 3, 4, 5], and the target value were 7, then the function should return True because 2 + 5 = 7.