Slice and map utilities based on generics and additional collection implementations like ordered map, set

Kubernetes-native platform to run massively parallel data/streaming jobs

Fast & furious GroupBy operations for dask.array

Efficient transducers for Julia

Web Application Message Async Server and WAMP/MQTT bridge

Iterable Java8 style Streams for Python

Simple map reduce LLM chain pattern demo using Ollama and Langchain

Parallelized Base functions

Fast, efficient, and scalable distributed map/reduce system, DAG execution, in memory or on disk, written in pure Go, runs standalone or distributedly.

Array.map but for objects with good TypeScript support. A small and simple integration.

K-means clustering algorithm using MapReduce.

A small hobby implementation of MapReduce that I hacked together at 2am.

MapReduce-MPI Library

Comparative Big Data Processing with Hadoop and Spark on User Query Logs

Terraform module to provision an Elastic MapReduce (EMR) cluster on AWS using a Spotinst AWS MrScaler resource

A mobile application that serves as the user interface for the Activity Tracker system, allowing users to add and track their activities.

A Java Stochastic Dynamic Programming Library

This project implements a distributed K-means clustering algorithm using a custom-built MapReduce framework. It is designed to handle potentially large datasets by distributing the clustering workload across multiple processes or machines. Uses gRPC for the communication between mapper, reducer, master

This repository presents a Python-powered analysis tool using MRJob and MongoDB to identify top-selling music artists by decade. With a focus on big data processing, it serves as a valuable resource for understanding historical and current musical trends, providing a streamlined solution for music industry analytics.

Perform a single-pass map-reduce operation against each element in an array while iterating from right to left and return the accumulated result.