Greenplum PL/R Language Extension

This chapter contains the following information:

Parent topic: Greenplum Database Reference Guide

About Greenplum Database PL/R

PL/R is a procedural language. With the Greenplum Database PL/R extension you can write database functions in the R programming language and use R packages that contain R functions and data sets.

For information about supported PL/R versions, see the Greenplum Database Release Notes.

Installing PL/R

The PL/R extension is available as a package. Download the package from VMware Tanzu Network and install it with the Greenplum Package Manager (gppkg).

The gppkg utility installs Greenplum Database extensions, along with any dependencies, on all hosts across a cluster. It also automatically installs extensions on new hosts in the case of system expansion and segment recovery.

For information about gppkg, see the Greenplum Database Utility Guide.

Installing the Extension Package

Before you install the PL/R extension, make sure that your Greenplum Database is running, you have sourced, and that the $MASTER_DATA_DIRECTORY and $GPHOME variables are set.

  1. Download the PL/R extension package from VMware Tanzu Network.
  2. Follow the instructions in Verifying the Greenplum Database Software Download to verify the integrity of the Greenplum Procedural Languages PL/R software.
  3. Copy the PL/R package to the Greenplum Database master host.
  4. Install the software extension package by running the gppkg command. This example installs the PL/R extension on a Linux system:

    $ gppkg -i plr-2.3.1-gp5-rhel6-x86_64.gppkg
  5. Source the file $GPHOME/

  6. Restart the database.

    $ gpstop -r

The extension and the R environment is installed in this directory:


Note: The version of some shared libraries installed with the operating system might not be compatible with the Greenplum Database PL/R extension.

If a shared library is not compatible, edit the file $GPHOME/ in all Greenplum Database master and segment hosts and set environment variable LD_LIBRARY_PATH to specify the location that is installed with the PL/R extension.

export *LD\_LIBRARY\_PATH= 

Enabling PL/R Language Support

For each database that requires its use, register the PL/R language with the SQL command CREATE EXTENSION. Because PL/R is an untrusted language, only superusers can register PL/R with a database. For example, run this command as the gpadmin user to register the language with the database named testdb:

$ psql -d testdb -c 'CREATE EXTENSION plr;'

PL/R is registered as an untrusted language.

Uninstalling PL/R

When you remove PL/R language support from a database, the PL/R routines that you created in the database will no longer work.

Remove PL/R Support for a Database

For a database that no longer requires the PL/R language, remove support for PL/R with the SQL command DROP EXTENSION. Because PL/R is an untrusted language, only superusers can remove support for the PL/R language from a database. For example, run this command as the gpadmin user to remove support for PL/R from the database named testdb:

$ psql -d testdb -c 'DROP EXTENSION plr;'

The default command fails if any existing objects (such as functions) depend on the language. Specify the CASCADE option to also drop all dependent objects, including functions that you created with PL/R.

Uninstall the Extension Package

If no databases have PL/R as a registered language, uninstall the Greenplum PL/R extension with the gppkg utility. This example uninstalls PL/R package version 2.3.1

$ gppkg -r plr-2.3.1

You can run the gppkg utility with the options -q --all to list the installed extensions and their versions.

Restart the database.

$ gpstop -r


The following are simple PL/R examples.

Example 1: Using PL/R for single row operators

This function generates an array of numbers with a normal distribution using the R function rnorm().

CREATE OR REPLACE FUNCTION r_norm(n integer, mean float8, 
  std_dev float8) RETURNS float8[ ] AS

The following CREATE TABLE command uses the r_norm function to populate the table. The r_norm function creates an array of 10 numbers.

CREATE TABLE test_norm_var
  AS SELECT id, r_norm(10,0,1) as x
  FROM (SELECT generate_series(1,30:: bigint) AS ID) foo

Example 2: Returning PL/R data.frames in Tabular Form

Assuming your PL/R function returns an R data.frame as its output, unless you want to use arrays of arrays, some work is required to see your data.frame from PL/R as a simple SQL table:

  • Create a TYPE in a Greenplum database with the same dimensions as your R data.frame:

    CREATE TYPE t1 AS ...
  • Use this TYPE when defining your PL/R function

    ... RETURNS SET OF t1 AS ...

Sample SQL for this is given in the next example.

Example 3: Hierarchical Regression using PL/R

The SQL below defines a TYPE and runs hierarchical regression using PL/R:

--Create TYPE to store model results
CREATE TYPE wj_model_results AS (
  cs text, coefext float, ci_95_lower float, ci_95_upper float, 
  ci_90_lower, float, ci_90_upper float, ci_80_lower, 
  float, ci_80_upper float);

--Create PL/R function to run model in R
DROP FUNCTION wj.plr.RE(response float [ ], cs text [ ])
RETURNS SETOF wj_model_results AS
  y<- log(response)
  cs<- cs
  d_temp<- data.frame(y,cs)
  m0 <- lmer (y ~ 1 + (1 | cs), data=d_temp)
  cs_unique<- sort(unique(cs))
  n_cs_unique<- length(cs_unique)
  temp_m0<- data.frame(matrix0,n_cs_unique, 7))
  for (i in 1:n_cs_unique){temp_m0[i,]<-
    c(exp(coef(m0)$cs[i,1] + c(0,-1.96,1.96,-1.65,1.65
  names(temp_m0)<- c("Coefest", "CI_95_Lower",
    "CI_95_Upper", "CI_90_Lower", "CI_90_Upper",
   "CI_80_Lower", "CI_80_Upper")
  temp_m0_v2<- data.frames(cs_unique, temp_m0)

--Run modeling plr function and store model results in a 
DROP TABLE IF EXISTS wj_model_results_roi;
CREATE TABLE wj_model_results_roi AS SELECT * 
  FROM wj.plr_RE((SELECT wj.droi2_array), 
  (SELECT cs FROM wj.droi2_array));

Downloading and Installing R Packages

R packages are modules that contain R functions and data sets. You can install R packages to extend R and PL/R functionality in Greenplum Database.

Greenplum Database provides a collection of data science-related R libraries that can be used with the Greenplum Database PL/R language. You can download these libraries in .gppkg format from VMware Tanzu Network. For information about the libraries, see R Data Science Library Package.

Note: If you expand Greenplum Database and add segment hosts, you must install the R packages in the R installation of the new hosts.

  1. For an R package, identify all dependent R packages and each package web URL. The information can be found by selecting the given package from the following navigation page:

    As an example, the page for the R package arm indicates that the package requires the following R libraries: Matrix, lattice, lme4, R2WinBUGS, coda, abind, foreign, and MASS.

    You can also try installing the package with R CMD INSTALL command to determine the dependent packages.

    For the R installation included with the Greenplum Database PL/R extension, the required R packages are installed with the PL/R extension. However, the Matrix package requires a newer version.

  2. From the command line, use the wget utility to download the tar.gz files for the arm package to the Greenplum Database master host:

  3. Use the gpscp utility and the hosts_all file to copy the tar.gz files to the same directory on all nodes of the Greenplum Database cluster. The hosts_all file contains a list of all the Greenplum Database segment hosts. You might require root access to do this.

    gpscp -f hosts_all Matrix_0.9996875-1.tar.gz =:/home/gpadmin 
    gpscp -f /hosts_all arm_1.5-03.tar.gz =:/home/gpadmin
  4. Use the gpssh utility in interactive mode to log into each Greenplum Database segment host (gpssh -f all_hosts). Install the packages from the command prompt using the R CMD INSTALL command. Note that this may require root access. For example, this R install command installs the packages for the arm package.

    $R_HOME/bin/R CMD INSTALL Matrix_0.9996875-1.tar.gz   arm_1.5-03.tar.gz
  5. Ensure that the package is installed in the $R_HOME/library directory on all the segments (the gpssh can be use to install the package). For example, this gpssh command list the contents of the R library directory.

    gpssh -s -f all_hosts "ls $R_HOME/library"

    The gpssh option -s sources the file before running commands on the remote hosts.

  6. Test if the R package can be loaded.

    This function performs a simple test to if an R package can be loaded:

    CREATE OR REPLACE FUNCTION R_test_require(fname text)
    RETURNS boolean AS
    LANGUAGE 'plr';

    This SQL command checks if the R package arm can be loaded:

    SELECT R_test_require('arm');

Displaying R Library Information

You can use the R command line to display information about the installed libraries and functions on the Greenplum Database host. You can also add and remove libraries from the R installation. To start the R command line on the host, log into the host as the gadmin user and run the script R from the directory $GPHOME/ext/R-3.3.3/bin.

This R function lists the available R packages from the R command line:

> library()

Display the documentation for a particular R package

> library(help="<package_name>")
> help(package="<package_name>")

Display the help file for an R function:

> help("<function_name>")
> ?<function_name>

To see what packages are installed, use the R command installed.packages(). This will return a matrix with a row for each package that has been installed. Below, we look at the first 5 rows of this matrix.

> installed.packages()

Any package that does not appear in the installed packages matrix must be installed and loaded before its functions can be used.

An R package can be installed with install.packages():

> install.packages("<package_name>") 
> install.packages("mypkg", dependencies = TRUE, type="source")

Load a package from the R command line.

> library(" <package_name> ") 

An R package can be removed with remove.packages

> remove.packages("<package_name>")

You can use the R command -e option to run functions from the command line. For example, this command displays help on the R package MASS.

$ R -e 'help("MASS")'

References - The R Project home page - The home page for PivotalR, a package that provides an R interface to operate on Greenplum Database tables and views that is similar to the R data.frame. PivotalR also supports using the machine learning package MADlib directly from R.

R documentation is installed with the Greenplum R package:


R Functions and Arguments

Passing Data Values in R

Aggregate Functions in R

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