How to work with Xero Data in Apache Spark using SQL

Apache Spark is a fast and general engine for large-scale data processing. When paired with the CData JDBC Driver for Xero, Spark can work with live Xero data. This article describes how to connect to and query Xero data from a Spark shell.

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

Getting Started

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Install the CData JDBC Driver for Xero

Download the CData JDBC Driver for Xero installer, unzip the package, and run the JAR file to install the driver.

Start a Spark Shell and Connect to Xero Data

1. Open a terminal and start the Spark shell with the CData JDBC Driver for Xero JAR file as the jars parameter:

   $ spark-shell --jars /CData/CData JDBC Driver for Xero/lib/cdata.jdbc.xero.jar
   

2. With the shell running, you can connect to Xero with a JDBC URL and use the SQL Context load() function to read a table.

   To connect, set the Schema connection property in addition to any authentication values. Xero offers authentication for private applications, public applications, and partner applications. Set the XeroAppAuthentication property to PUBLIC, PRIVATE, or PARTNER, depending on the type of application configured. To connect from a private application, you will additionally need to set the OAuthAccessToken, OAuthClientId, OAuthClientSecret, CertificateStoreType, CertificateStore, and CertificateStorePassword.

   To connect from a public or partner application, you can use the embedded OAuthClientId, OAuthClientSecret, and CallbackURL, or you can register an app to obtain your own OAuth values.

   See the "Getting Started" chapter of the help documentation for a guide to authenticating to Xero.

   Built-in Connection String Designer

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

   java -jar cdata.jdbc.xero.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.)
   

   Configure the connection to Xero, using the connection string generated above.

   scala> val xero_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:xero:InitiateOAuth=GETANDREFRESH;").option("dbtable","Items").option("driver","cdata.jdbc.xero.XeroDriver").load()
   

3. Once you connect and the data is loaded you will see the table schema displayed.

4. Register the Xero data as a temporary table:

   scala> xero_df.registerTable("items")

5. Perform custom SQL queries against the Data using commands like the one below:

   scala> xero_df.sqlContext.sql("SELECT Name, QuantityOnHand FROM Items WHERE Name = Golf balls - white single").collect.foreach(println)

   You will see the results displayed in the console, similar to the following:

   👁 Data in Apache Spark (Salesforce is shown)
   

Using the CData JDBC Driver for Xero in Apache Spark, you are able to perform fast and complex analytics on Xero data, combining the power and utility of Spark with your data. Download a free, 30 day trial of any of the hundreds of CData JDBC Drivers and get started today.