Process & Analyze Open Exchange Rates Data in Azure Databricks

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Open Exchange Rates JDBC Driver

Build fully-integrated Java/J2EE apps with access to live Currency and economic data. Enables live access to real-time currency exchange data.



Host the CData JDBC Driver for Open Exchange Rates in Azure and use Databricks to perform data engineering and data science on live Open Exchange Rates data.

Databricks is a cloud-based service that provides data processing capabilities through Apache Spark. When paired with the CData JDBC Driver, customers can use Databricks to perform data engineering and data science on live Open Exchange Rates data. This article walks through hosting the CData JDBC Driver in Azure, as well as connecting to and processing live Open Exchange Rates data in Databricks.

With built-in optimized data processing, the CData JDBC Driver offers unmatched performance for interacting with live Open Exchange Rates data. When you issue complex SQL queries to Open Exchange Rates, the driver pushes supported SQL operations, like filters and aggregations, directly to Open Exchange Rates and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations). Its built-in dynamic metadata querying allows you to work with and analyze Open Exchange Rates data using native data types.

Install the CData JDBC Driver in Azure

To work with live Open Exchange Rates data in Databricks, install the driver on your Azure cluster.

  1. Navigate to your Databricks administration screen and select the target cluster.
  2. On the Libraries tab, click "Install New."
  3. Select "Upload" as the Library Source and "Jar" as the Library Type.
  4. Upload the JDBC JAR file (cdata.jdbc.openexchangerates.jar) from the installation location (typically C:\Program Files\CData\CData JDBC Driver for Open Exchange Rates\lib).

Connect to Open Exchange Rates from Databricks

With the JAR file installed, we are ready to work with live Open Exchange Rates data in Databricks. Start by creating a new notebook in your workspace. Name the notebook, select Python as the language (though Scala is available as well), and choose the cluster where you installed the JDBC driver. When the notebook launches, we can configure the connection, query Open Exchange Rates, and create a basic report.

Configure the Connection to Open Exchange Rates

Connect to Open Exchange Rates by referencing the class for the JDBC Driver and constructing a connection string to use in the JDBC URL. Additionally, you will need to set the RTK property in the JDBC URL (unless you are using a Beta driver). You can view the licensing file included in the installation for information on how to set this property.

driver = "cdata.jdbc.openexchangerates.OpenExchangeRatesDriver"
url = "jdbc:openexchangerates:RTK=5246...;AppId=abc1234;"

Built-in Connection String Designer

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

java -jar cdata.jdbc.openexchangerates.jar

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

The Open Exchange Rates API supports basic authentication with an App Id. After you register, your App Id is displayed in your account dashboard. Set this to the AppId connection property.

Load Open Exchange Rates Data

Once the connection is configured, you can load Open Exchange Rates data as a dataframe using the CData JDBC Driver and the connection information.

remote_table = spark.read.format ( "jdbc" ) \
	.option ( "driver" , driver) \
	.option ( "url" , url) \
	.option ( "dbtable" , "Projects") \
	.load ()

Display Open Exchange Rates Data

Check the loaded Open Exchange Rates data by calling the display function.

display (remote_table.select ("Id"))

Analyze Open Exchange Rates Data in Azure Databricks

If you want to process data with Databricks SparkSQL, register the loaded data as a Temp View.

remote_table.createOrReplaceTempView ( "SAMPLE_VIEW" )

The SparkSQL below retrieves the Open Exchange Rates data for analysis.

% sql

SELECT Id, Statistics_ViewCount FROM Projects

The data from Open Exchange Rates is only available in the target notebook. If you want to use it with other users, save it as a table.

remote_table.write.format ( "parquet" ) .saveAsTable ( "SAMPLE_TABLE" )

Download a free, 30-day trial of the CData JDBC Driver for Open Exchange Rates and start working with your live Open Exchange Rates data in Apache NiFi. Reach out to our Support Team if you have any questions.