Kubernetes-native platform to run massively parallel data/streaming jobs
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Updated
Jun 6, 2024 - Go
Kubernetes-native platform to run massively parallel data/streaming jobs
Array.map but for objects with good TypeScript support. A small and simple integration.
Slice and map utilities based on generics and additional collection implementations like ordered map, set
K-means clustering algorithm using MapReduce.
Efficient transducers for Julia
A small hobby implementation of MapReduce that I hacked together at 2am.
Comparative Big Data Processing with Hadoop and Spark on User Query Logs
Parallelized Base functions
Terraform module to provision an Elastic MapReduce (EMR) cluster on AWS using a Spotinst AWS MrScaler resource
Web Application Message Async Server and WAMP/MQTT bridge
A Java Stochastic Dynamic Programming Library
Fast, efficient, and scalable distributed map/reduce system, DAG execution, in memory or on disk, written in pure Go, runs standalone or distributedly.
Iterable Java8 style Streams for Python
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
Perform a single-pass map-reduce operation against each element in an array while iterating from right to left and return the accumulated result.
Perform a single-pass map-reduce operation against each element in an array and return the accumulated result.
MIT Distributed Systems CS 6.824/CS 6.5840
I have 5 Million articles of Wikipedia Articles , i have preprocessed my data using pandas , after that i have used Hadoop map reduce technology to make a search engine.
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