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The JSON ODBC Driver is a powerful tool that allows you to connect with live JSON web services, directly from any applications that support ODBC connectivity.

Access JSON services like you would any standard database - read, write, and update etc. through a standard ODBC Driver interface.

Analyze JSON Services in R



Create data visualizations and use high-performance statistical functions to analyze JSON services in Microsoft R Open.

Access JSON services with pure R script and standard SQL. You can use the CData ODBC Driver for JSON and the RODBC package to work with remote JSON services 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 JSON services and visualize JSON services 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 JSON as an ODBC Data Source

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

See the Getting Started chapter in the data provider documentation to authenticate to your data source: The data provider models JSON APIs as bidirectional database tables and JSON files as read-only views (local files, files stored on popular cloud services, and FTP servers). The major authentication schemes are supported, including HTTP Basic, Digest, NTLM, OAuth, and FTP. See the Getting Started chapter in the data provider documentation for authentication guides.

After setting the URI and providing any authentication values, set DataModel to more closely match the data representation to the structure of your data.

The DataModel property is the controlling property over how your data is represented into tables and toggles the following basic configurations.

  • Document (default): Model a top-level, document view of your JSON data. The data provider returns nested elements as aggregates of data.
  • FlattenedDocuments: Implicitly join nested documents and their parents into a single table.
  • Relational: Return individual, related tables from hierarchical data. The tables contain a primary key and a foreign key that links to the parent document.

See the Modeling JSON Data chapter for more information on configuring the relational representation. You will also find the sample data used in the following examples. The data includes entries for people, the cars they own, and various maintenance services performed on those cars.

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 JSON 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 JSON Source] Driver = CData ODBC Driver for JSON Description = My Description URI = C:/people.json DataModel = Relational

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 JSON Services as an ODBC Data Source

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

conn <- odbcConnect("CData JSON Source")

Schema Discovery

The driver models JSON 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 JSON API.

people <- sqlQuery(conn, "SELECT [people].[personal.age] AS age, [people].[personal.gender] AS gender, [people].[personal.name.first] AS first_name, [people].[personal.name.last] AS last_name, [vehicles].[model], FROM [people] JOIN [vehicles] ON [people].[_id] = [vehicles].[people_id]", believeNRows=FALSE, rows_at_time=1)

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

View(people)

Plot JSON Services

You can now analyze JSON services 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(people$[ personal.name.last ], main="JSON people", names.arg = people$[ personal.name.first ], horiz=TRUE)