Introduction to Resources

The resourcer package is meant to access resources identified by a URL in a uniform way whether it references a dataset (stored in a file, a SQL table, a MongoDB collection etc.) or a computation unit (system commands, web services etc.). Usually some credentials will be defined, and an additional data format information can be provided to help dataset coercing to a data.frame object.

The main concepts are:

File Resources

These are resources describing a file. If the file is in a remote location, it must be downloaded before being read. The data format specification of the resource helps to find the appropriate file reader.

File Getter

The file locations supported by default are:

This can be easily applied to other file locations by extending the FileResourceGetter class. An instance of the new file resource getter is to be registered so that the FileResourceResolver can operate as expected.

File Data Format

The data format specified within the Resource object, helps at finding the appropriate file reader. Currently supported data formats are:

Usage example that reads a local SPSS file:

To support other file data format, extend the FileResourceClient class with the new data format reader implementation. Associate factory class, an extension of the ResourceResolver class is also to be implemented and registered.

Database Resources

DBI Connectors

DBI is a set of virtual classes that are are used to abstract the SQL database connections and operations within R. Then any DBI implementation can be used to access to a SQL table. Which DBI connector to be used is an information that can be extracted from the scheme part of the resource’s URL. For instance a resource URL starting with postgres:// will require the RPostgres driver. To separate the DBI connector instanciation from the DBI interface interactions in the SQLResourceClient, a DBIResourceConnector registry is to be populated. The currently supported SQL database connectors are:

To support another SQL database having a DBI driver, extend the DBIResourceConnector class and register it:

Use dplyr

Having the data stored in the database allows to handle large (common SQL databases) to big (PrestoDB, Spark) datasets using dplyr which will delegate as much as possible operations to the database.

Document Databases

NoSQL databases can be described by a resource. The nodbi can be used here. Currently only connection to MongoDB database is supported using URL scheme mongodb or mongodb+srv.

Computation Resources

Computation resources are resources on which tasks/commands can be triggerred and from which resulting data can be retrieved.

Example of computation resource that connects to a server through SSH:

# make an application resource on a ssh server
res <- resourcer::newResource(
  name = "supercomp1",
  url = "ssh://server1.example.org/work/dir?exec=plink,ls",
  identity = "sshaccountid",
  secret = "sshaccountpwd"
)

# get ssh client from resource object
client <- resourcer::newResourceClient(res) # does a ssh::ssh_connect()

# execute commands
files <- client$exec("ls") # exec 'cd /work/dir && ls'

# release connection
client$close() # does ssh::ssh_disconnect(session)

Extending Resources

There are several ways to extend the Resources handling. These are based on different R6 classes having a isFor(resource) function:

The design of the URL that will describe your new resource should not overlap an existing one, otherwise the different registries will return the first instance for which the isFor(resource) is TRUE. In order to distinguish resource locations, the URL’s scheme can be extended, for instance the scheme for accessing a file in a Opal server is opal+https so that the credentials be applied as needed by Opal.