Big Data Modeling, MapReduce, Spark, PySpark @ Santa Clara University

❄Implement the common subgraph isomorphism algorithms (i.e. Ullmann, VF2) based on MapReduce on Hadoop

HAPOD - Hierarchical Approximate Proper Orthogonal Decomposition

Naive Implementation of Machine Learning Algorithms in distributed frameworks MapReduce and Spark

Map Reduce implementation using golang

Lightweight and extensible library to execute MapReduce-like jobs in Python

Word co-occurrence and Matrix Multiplication using MapReduce

A full-stack Search Engine built for a Big Data course project. It scrapes over 200K articles, stores them in HDFS, and builds an inverted index using MapReduce. Designed to demonstrate scalable data processing, distributed storage, and basic information retrieval over large datasets.

Designing and implementing MapReduce algorithms for a variety of common data processing tasks

Mapreduce Presentation

Parallel mapreduce for Julia

K-means clustering algorithm using MapReduce.

A MapReduce framework implemented from scratch to perform K-mean clustering

Design and implementation of different MapReduce jobs used to analyze a dataset on Covid-19 disease created by Our World In Data

Counts the word occurrences in a file

Cross Correlation Algorithm.

Website that allows working with a spells database

Text analysis: find a pattern in the text by using MapReduce algorithm and thread tools in C#

MIT Distributed System Lab 1

A MapReduce implementation in python in a docker simulated distributed system