Numerical-Algo

Problem Given a stream of elements too large to store in memory, pick a random element from the stream with uniform probability. Solution This is a classic problem known as Reservoir Sampling. The goal is to randomly select an element from a large stream of data with uniform probability, even when the entire stream cannot be stored in memory. Introduction to Problem Reservoir sampling, often referred to as Algorithm R as described by Jeffrey Vitter in Random Sampling with a Reservoir, is a widely used technique in data processing. It allows for the random selection of k samples from a set S containing n items, where n is very large or unknown. Each of the chosen k items forms a “reservoir,” ensuring that every item is selected with an equal probability of 1/n. ...

Problem Given an integer num, repeatedly add all its digits until the result has only one digit, and return it. Examples Example 1: Input: num = 38 Output: 2 Explanation: The process is 38 --> 3 + 8 --> 11 11 --> 1 + 1 --> 2 Since 2 has only one digit, return it. ...