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README.Rmd
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---
output: github_document
---
<!-- README.md is generated from README.Rmd. Please edit that file -->
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
```
# pysparklyr
<!-- badges: start -->
[![R-CMD-check](https://github.com/mlverse/pysparklyr/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/mlverse/pysparklyr/actions/workflows/R-CMD-check.yaml)
[![Spark-Connect](https://github.com/mlverse/pysparklyr/actions/workflows/spark-tests.yaml/badge.svg)](https://github.com/mlverse/pysparklyr/actions/workflows/spark-tests.yaml)
[![codecov](https://codecov.io/gh/mlverse/pysparklyr/graph/badge.svg?token=O1N9qPabpF)](https://app.codecov.io/gh/mlverse/pysparklyr)
[![CRAN status](https://www.r-pkg.org/badges/version/pysparklyr)](https://CRAN.R-project.org/package=pysparklyr)
<!-- badges: end -->
Integrates `sparklyr` with PySpark and Databricks. The main reason of this
package is because the new Spark and Databricks Connect connection method does
not work with standard `sparklyr` integration.
## Installing
To install the version in CRAN use:
```r
install.packages("pysparklyr")
```
To get the development version from GitHub use:
```r
remotes::install_github("mlverse/pysparklyr")
```
## Using
To learn how to use, please visit the Spark / Databricks Connect article,
available in the official `sparklyr` website: [Spark Connect, and Databricks Connect v2
](https://spark.posit.co/deployment/databricks-connect.html)