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URL: https://www.cdata.com/kb/tech/databricks-jdbc-r.rst

⇱ Analyze Databricks Data in R via JDBC

Analyze Databricks Data in R via JDBC

👁 Jerod Johnson
Jerod Johnson
Director, Technology Evangelism
Use standard R functions and the development environment of your choice to analyze Databricks data with the CData JDBC Driver for Databricks.

Access Databricks data with pure R script and standard SQL on any machine where R and Java can be installed. You can use the CData JDBC Driver for Databricks and the RJDBC package to work with remote Databricks 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 Databricks and visualize Databricks data by calling standard R functions.

About Databricks Data Integration

Accessing and integrating live data from Databricks has never been easier with CData. Customers rely on CData connectivity to:

  • Access all versions of Databricks from Runtime Versions 9.1 - 13.X to both the Pro and Classic Databricks SQL versions.
  • Leave Databricks in their preferred environment thanks to compatibility with any hosting solution.
  • Secure authenticate in a variety of ways, including personal access token, Azure Service Principal, and Azure AD.
  • Upload data to Databricks using Databricks File System, Azure Blog Storage, and AWS S3 Storage.

While many customers are using CData's solutions to migrate data from different systems into their Databricks data lakehouse, several customers use our live connectivity solutions to federate connectivity between their databases and Databricks. These customers are using SQL Server Linked Servers or Polybase to get live access to Databricks from within their existing RDBMs.

Read more about common Databricks use-cases and how CData's solutions help solve data problems in our blog: What is Databricks Used For? 6 Use Cases.


Getting Started


Install R

You can match the driver's performance gains from multi-threading and managed code by running the multithreaded Microsoft R Open or by running open R linked with the BLAS/LAPACK libraries. This article uses Microsoft R Open 3.2.3, which is preconfigured to install packages from the Jan. 1, 2016 snapshot of the CRAN repository. This snapshot ensures reproducibility.

Load the RJDBC Package

To use the driver, download the RJDBC package. After installing the RJDBC package, the following line loads the package: 

library(RJDBC)

Connect to Databricks as a JDBC Data Source

You will need the following information to connect to Databricks as a JDBC data source:

  • Driver Class: Set this to cdata.jdbc.databricks.DatabricksDriver
  • Classpath: Set this to the location of the driver JAR. By default this is the lib subfolder of the installation folder.

The DBI functions, such as dbConnect and dbSendQuery, provide a unified interface for writing data access code in R. Use the following line to initialize a DBI driver that can make JDBC requests to the CData JDBC Driver for Databricks: 

driver <- JDBC(driverClass = "cdata.jdbc.databricks.DatabricksDriver", classPath = "MyInstallationDir\lib\cdata.jdbc.databricks.jar", identifier.quote = "'")

You can now use DBI functions to connect to Databricks and execute SQL queries. Initialize the JDBC connection with the dbConnect function.

To connect to a Databricks cluster, set the properties as described below.

Note: The needed values can be found in your Databricks instance by navigating to Clusters, and selecting the desired cluster, and selecting the JDBC/ODBC tab under Advanced Options.

  • Server: Set to the Server Hostname of your Databricks cluster.
  • HTTPPath: Set to the HTTP Path of your Databricks cluster.
  • Token: Set to your personal access token (this value can be obtained by navigating to the User Settings page of your Databricks instance and selecting the Access Tokens tab).

Built-in Connection String Designer

For assistance in constructing the JDBC URL, use the connection string designer built into the Databricks JDBC Driver. Either double-click the JAR file or execute the jar file from the command-line.

java -jar cdata.jdbc.databricks.jar

Fill in the connection properties and copy the connection string to the clipboard.

👁 Using the built-in connection string designer to generate a JDBC URL (Salesforce is shown.)

Below is a sample dbConnect call, including a typical JDBC connection string:

conn <- dbConnect(driver,"jdbc:databricks:Server=127.0.0.1;Port=443;TransportMode=HTTP;HTTPPath=MyHTTPPath;UseSSL=True;User=MyUser;Password=MyPassword;")

Schema Discovery

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

dbListTables(conn)

Execute SQL Queries

You can use the dbGetQuery function to execute any SQL query supported by the Databricks API: 

customers <- dbGetQuery(conn,"SELECT City, CompanyName FROM Customers WHERE Country = 'US'")

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

View(customers)

Plot Databricks Data

You can now analyze Databricks 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(customers$CompanyName, main="Databricks Customers", names.arg = customers$City, horiz=TRUE)
👁 A basic bar plot. (Salesforce is shown.)