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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 xBase data. This article explains how to host the CData JDBC Driver in AWS, as well as connect to and process live xBase data in Databricks.
With built-in optimized data processing, the CData JDBC Driver offers unmatched performance for interacting with live xBase data. When you issue complex SQL queries to xBase, the driver pushes supported SQL operations, like filters and aggregations, directly to xBase 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 xBase data using native data types.
To work with live xBase data in Databricks, install the driver on your Databricks cluster.
With the JAR file installed, we are ready to work with live xBase 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 xBase, and create a basic report.
Connect to xBase by referencing the JDBC Driver class and constructing a connection string to use in the JDBC URL. Additionally, you will need to set the 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.xbase.xBaseDriver" url = "jdbc:xbase:RTK=5246...;DataSource=MyDBFFilesFolder;"
For assistance in constructing the JDBC URL, use the connection string designer built into the xBase JDBC Driver. Either double-click the JAR file or execute the jar file from the command-line.
java -jar cdata.jdbc.xbase.jar
Fill in the connection properties and copy the connection string to the clipboard.
The DataSource property must be set to the name of the folder that contains the .dbf files. Specify the IncludeFiles property to work with xBase table files having extensions that differ from .dbf. Specify multiple extensions in a comma-separated list.
๐ Using the built-in connection string designer to generate a JDBC URL (Salesforce is shown.)Once you configure the connection, you can load xBase 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" , "Invoices") \ .load ()
Check the loaded xBase data by calling the display function.
display (remote_table.select ("Company"))
๐ Displaying xBase DataIf you want to process data with Databricks SparkSQL, register the loaded data as a Temp View.
remote_table.createOrReplaceTempView ( "SAMPLE_VIEW" )
With the Temp View created, you can use SparkSQL to retrieve the xBase data for reporting, visualization, and analysis.
% sql SELECT Company, Total FROM SAMPLE_VIEW ORDER BY Total DESC LIMIT 5๐ Displaying xBase Data
The data from xBase 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 xBase and start working with your live xBase data in Databricks. Reach out to our Support Team if you have any questions.
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๐ xBase-Compatible Databases IconRapidly create and deploy powerful Java applications that integrate with xBase-compatible database engines like FoxPro & Clipper (.dbf, .ndx, .ntx, .dbt, etc).