Apache Spark is an open source distributed general-purpose cluster-computing framework. It provides an interface for programming entire clusters with implicit data parallelism and fault tolerance.
Using Apache Spark for marketing analytics
This repository you are browsing contains intermediate level piece of codes which are useful for cleaning, exploratory analysis, handling of missing data points, outlier detection and different visualization techniques using graphics, ggplot2, tidycharts, ggExtra packages. Also in particular part of the script you can get basic information about…
Projects created using R
A tutorial showing how to use Apache Spark, Apache Sedona, and Delta Lake for big data analysis in R.
R workloads running at scale on Google Cloud
A sparklyr extension to analyze genome datasets
Mirror of https://gitlab.com/zero323/dlt
Enable spatial functions in Spark through the `sparklyr` package
Sparklyr extension making Flint time series library functionalities (https://github.com/twosigma/flint) easily accessible through R
R interface to Spark TensorFlow Connector
Old repo for R interface for GraphFrames
R interface for XGBoost on Spark
bring sf to spark in production
R interface for Apache Spark
Created by Matei Zaharia
Released May 26, 2014