In javierluraschi/sparklyudf: sparklyudf: Scala UDF from R - Example

sparklyudf demonstrates how to build a sparklyr extension package that uses custom Scala code which is compiled, deployed to Apache Spark and registered as an UDF that can be used in SQL and dplyr.

Building

First build this package, then build its Spark 2.0 jars by running:

spec <- sparklyr::spark_default_compilation_spec()
spec <- Filter(function(e) e$spark_version >= "2.0.0", spec)
sparklyr::compile_package_jars()

then build the R package as usual.

This package contains an Scala-based UDF defined as:

```{scala eval=FALSE} object Main { def register_hello(spark: SparkSession) = { spark.udf.register("hello", (name: String) => { "Hello, " + name + "! - From Scala" }) } }

## Getting Started

Connect and test this package as follows:

```r
library(sparklyudf)
library(sparklyr)
library(dplyr)

sc <- spark_connect(master = "local")

sparklyudf_register(sc)

Now the Scala UDF hello() is registered and can be used as follows:

data.frame(name = "Javier") %>%
  copy_to(sc, .) %>%
  mutate(hello = hello(name))

spark_disconnect_all()

javierluraschi/sparklyudf documentation built on May 30, 2019, 3:09 p.m.