Using PL/R in HAWQ
PL/R is a procedural language. With the HAWQ PL/R extension, you can write database functions in the R programming language and use R packages that contain R functions and data sets.
Note: To use PL/R in HAWQ, R must be installed on each node in your HAWQ cluster. Additionally, you must install the PL/R package on an existing HAWQ deployment or have specified PL/R as a build option when compiling HAWQ.
This section contains simple PL/R examples.
This function generates an array of numbers with a normal distribution using the R function
CREATE OR REPLACE FUNCTION r_norm(n integer, mean float8, std_dev float8) RETURNS float8[ ] AS $$ x<-rnorm(n,mean,std_dev) return(x) $$ LANGUAGE 'plr';
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 DISTRIBUTED BY (id);
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 in order for HAWQ to see your PL/R
data.frame as a simple SQL table:
Create a TYPE in HAWQ with the same dimensions as your R
CREATE TYPE t1 AS ...
Use this TYPE when defining your PL/R function:
... RETURNS SET OF t1 AS ...
Sample SQL for this situation is provided in the next example.
The SQL below defines a TYPE and a function to process employee information with
data.frame using PL/R:
-- Create type to store employee information DROP TYPE IF EXISTS emp_type CASCADE; CREATE TYPE emp_type AS (name text, age int, salary numeric(10,2)); -- Create function to process employee information and return data.frame DROP FUNCTION IF EXISTS get_emps(); CREATE OR REPLACE FUNCTION get_emps() RETURNS SETOF emp_type AS ' names <- c("Joe","Jim","Jon") ages <- c(41,25,35) salaries <- c(250000,120000,50000) df <- data.frame(name = names, age = ages, salary = salaries) return(df) ' LANGUAGE 'plr'; -- Call the function SELECT * FROM get_emps();
R packages are modules that contain R functions and data sets. You can install R packages to extend R and PL/R functionality in HAWQ.
Note: If you expand HAWQ and add segment hosts, you must install the R packages in the R installation of each of the new hosts.
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
armindicates that the package requires the following R libraries:
You can also try installing the package with
R CMD INSTALLcommand to determine the dependent packages.
For the R installation included with the HAWQ PL/R extension, the required R packages are installed with the PL/R extension. However, the Matrix package requires a newer version.
From the command line, use the
wgetutility to download the tar.gz files for the
armpackage to the HAWQ master host:
$ wget http://cran.r-project.org/src/contrib/Archive/arm/arm_1.5-03.tar.gz $ wget http://cran.r-project.org/src/contrib/Archive/Matrix/Matrix_0.9996875-1.tar.gz
hawq scputility and the
hawq_hostsfile to copy the tar.gz files to the same directory on all nodes of the HAWQ cluster. The
hawq_hostsfile contains a list of all of the HAWQ segment hosts. You might require root access to do this.
$ hawq scp -f hosts_all Matrix_0.9996875-1.tar.gz =:/home/gpadmin $ hawq scp -f hawq_hosts arm_1.5-03.tar.gz =:/home/gpadmin
hawq sshutility in interactive mode to log into each HAWQ segment host (
hawq ssh -f hawq_hosts). Install the packages from the command prompt using the
R CMD INSTALLcommand. Note that this may require root access. For example, this R install command installs the packages for the
$ R CMD INSTALL Matrix_0.9996875-1.tar.gz arm_1.5-03.tar.gz
Note: Some packages require compilation. Refer to the package documentation for possible build requirements.
Ensure that the R package was installed in the
/usr/lib64/R/librarydirectory on all the segments (
hawq sshcan be used to install the package). For example, this
hawq sshcommand lists the contents of the R library directory.
$ hawq ssh -f hawq_hosts "ls /usr/lib64/R/library"
Verify the R package can be loaded.
This function performs a simple test to determine if an R package can be loaded:
CREATE OR REPLACE FUNCTION R_test_require(fname text) RETURNS boolean AS $BODY$ return(require(fname,character.only=T)) $BODY$ LANGUAGE 'plr';
This SQL command calls the previous function to determine if the R package
armcan be loaded:
You can use the R command line to display information about the installed libraries and functions on the HAWQ host. You can also add and remove libraries from the R installation. To start the R command line on the host, log in to the host as the
gpadmin user and run the script R.
This R function lists the available R packages from the R command line:
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.
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("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
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 named
$ R -e 'help("MASS")'
http://www.r-project.org/ - The R Project home page
https://github.com/pivotalsoftware/gp-r - GitHub repository that contains information about using R.
https://github.com/pivotalsoftware/PivotalR - GitHub repository for PivotalR, a package that provides an R interface to operate on HAWQ 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 R package:
where N.N.N corresponds to the version of R installed.