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Access Databricks data with pure R script and standard SQL. You can use the CData ODBC Driver for Databricks and the RODBC 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 data and visualize Databricks data in R.
Accessing and integrating live data from Databricks has never been easier with CData. Customers rely on CData connectivity to:
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.
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).
Information for connecting to Databricks follows, along with different instructions for configuring a DSN in Windows and Linux environments.
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.
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.
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.
If you are installing the CData ODBC Driver for Databricks 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.
[CData Databricks Source] Driver = CData ODBC Driver for Databricks Description = My Description Server = 127.0.0.1 Port = 443 TransportMode = HTTP HTTPPath = MyHTTPPath UseSSL = True User = MyUser Password = MyPassword
For specific information on using these configuration files, please refer to the help documentation (installed and found online).
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")
You can connect to a DSN in R with the following line:
conn <- odbcConnect("CData Databricks Source")
The driver models Databricks APIs as relational tables, views, and stored procedures. Use the following line to retrieve the list of tables:
sqlTables(conn)
Use the sqlQuery function to execute any SQL query supported by the Databricks API.
customers <- sqlQuery(conn, "SELECT City, CompanyName FROM Customers WHERE Country = 'US'", believeNRows=FALSE, rows_at_time=1)
You can view the results in a data viewer window with the following command:
View(customers)
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.)
Download a free trial of the Databricks ODBC Driver to get started:
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👁 Databricks IconThe Databricks ODBC Driver is a powerful tool that allows you to connect with live data from Databricks, directly from any applications that support ODBC connectivity.
Access Databricks data like you would a database - read, write, and update through a standard ODBC Driver interface.