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

Map Reduce implementation using golang

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

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.

Word co-occurrence and Matrix Multiplication using MapReduce

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

Mapreduce Presentation

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

K-means clustering algorithm using MapReduce.

Parallel mapreduce for Julia

Cross Correlation Algorithm.

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

A MapReduce implementation in python in a docker simulated distributed system

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

Counts the word occurrences in a file

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

Scalable MapReduce System on Google Cloud with FaaS (Function as a Service).

HW for the Big Data Computation course. Use Apache Spark and MapReduce algorithm to extract information from a dataset.