Analyze Vimeo Data in R via ODBC

Access Vimeo data with pure R script and standard SQL. You can use the CData ODBC Driver for Vimeo and the RODBC package to work with remote Vimeo data in R. By using the CData Driver, you are leveraging a driver written for industry-proven standards to access your data in the popular, open-source R language. This article shows how to use the driver to execute SQL queries to Vimeo data and visualize Vimeo data in R.

Install R

You can complement the driver's performance gains from multi-threading and managed code by running the multithreaded Microsoft R Open or by running R linked with the BLAS/LAPACK libraries. This article uses Microsoft R Open (MRO).

Connect to Vimeo as an ODBC Data Source

Information for connecting to Vimeo follows, along with different instructions for configuring a DSN in Windows and Linux environments.

Vimeo is a professional video hosting platform. The Vimeo API uses personal access tokens (bearer tokens) to enable secure access to video metadata, user information, channels, groups, categories, and related resources.

Using API Key Authentication

To authenticate to the Vimeo API, you will need to provide a personal access token. To obtain your access token:

1. Log in to your Vimeo account at https://vimeo.com
2. Navigate to https://developer.vimeo.com/apps
3. Create a new app or select an existing app
4. Under "Personal Access Tokens", click "Generate" to create a new token
5. Select the required scopes: public and private for read access
6. Copy the generated token

After obtaining your access token, set the following connection properties:

• AuthScheme: Set this to APIKey.
• APIKey: Set this to your Vimeo personal access token.

Example connection string

Profile=C:\profiles\Vimeo.apip;ProfileSettings='APIKey=your_personal_access_token';

When you configure the DSN, you may also want to set the Max Rows connection property. This will limit the number of rows returned, which is especially helpful for improving performance when designing reports and visualizations.

Windows

If you have not already, first specify connection properties in an ODBC DSN (data source name). This is the last step of the driver installation. You can use the Microsoft ODBC Data Source Administrator to create and configure ODBC DSNs.

Linux

If you are installing the CData ODBC Driver for Vimeo in a Linux environment, the driver installation predefines a system DSN. You can modify the DSN by editing the system data sources file (/etc/odbc.ini) and defining the required connection properties.

/etc/odbc.ini

[CData API Source]
Driver = CData ODBC Driver for Vimeo
Description = My Description
Profile = C:\profiles\Vimeo.apip
ProfileSettings = 'APIKey = your_personal_access_token'

For specific information on using these configuration files, please refer to the help documentation (installed and found online).

Load the RODBC Package

To use the driver, download the RODBC package. In RStudio, click Tools -> Install Packages and enter RODBC in the Packages box.

After installing the RODBC package, the following line loads the package:

library(RODBC)

Note: This article uses RODBC version 1.3-12. Using Microsoft R Open, you can test with the same version, using the checkpoint capabilities of Microsoft's MRAN repository. The checkpoint command enables you to install packages from a snapshot of the CRAN repository, hosted on the MRAN repository. The snapshot taken Jan. 1, 2016 contains version 1.3-12.

library(checkpoint)
checkpoint("2016-01-01")

Connect to Vimeo Data as an ODBC Data Source

You can connect to a DSN in R with the following line:

conn <- odbcConnect("CData API Source")

Schema Discovery

The driver models Vimeo APIs as relational tables, views, and stored procedures. Use the following line to retrieve the list of tables:

sqlTables(conn)

Execute SQL Queries

Use the sqlQuery function to execute any SQL query supported by the Vimeo API.

videos <- sqlQuery(conn, "SELECT ,  FROM Videos WHERE UserUri = '/users/12345678'", believeNRows=FALSE, rows_at_time=1)

You can view the results in a data viewer window with the following command:

View(videos)

Plot Vimeo Data

You can now analyze Vimeo data with any of the data visualization packages available in the CRAN repository. You can create simple bar plots with the built-in bar plot function:

par(las=2,ps=10,mar=c(5,15,4,2))
barplot(videos$, main="Vimeo Videos", names.arg = videos$, horiz=TRUE)