Mosaic on R; sparkrMosaic and sparklyrMosaic

Mosaic offers APIs for both of the R Spark interfaces, SparkR and sparklyr.

sparkrMosaic and sparklyrMosaic are lightweight extensions of their respective Spark APIs to expose Mosaic's large scale geospatial data processing functions.

Getting started

Requirements

The only requirement to start using Mosaic is a Databricks cluster running Databricks Runtime 10.0 (or later) with the Mosaic Scala JAR attached and the relevant R mosaic package installed.

It is recommended to install the Scala JAR suffixed "with-dependencies" for the easiest installation experience.

The R Mosaic packages and JAR can be found in the 'Releases' section of the Mosaic GitHub repository.

Instructions for how to attach JARs to a Databricks cluster can be found here.

Installing the R package requires a manual installation via install.packages(). This is most easily achieved by moving the R package into DBFS from Github.

The following code block illustrates an installation;

# SparkR is preinstalled on Databricks
library(SparkR)

sparkr_mosaic_package_path = '/Users/<my-user-name>/sparkrMosaic.tar.gz'
install.packages(sparkr_mosaic_package_path, repos=NULL)
library(sparkrMosaic)

# sparklyr is preinstalled on Databricks
library(sparklyr)

sparklyr_mosaic_package_path = '/Users/<my-user-name>/sparklyrMosaic.tar.gz'
install.packages(sparklyr_mosaic_package_path, repos=NULL)
library(sparklyrMosaic)

Example notebooks

This repository contains several example notebooks in notebooks/examples. There are example notebooks for both sparkrMosaic and sparklyrMosaic. You can import them into your Databricks workspace using the instructions here.

Contributing to the R bindings for Mosaic

See the contributing section.