How to work with Sage Cloud Accounting 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 Sage Cloud Accounting, Spark can work with live Sage Cloud Accounting data. This article describes how to connect to and query Sage Cloud Accounting data from a Spark shell.

The CData JDBC Driver offers unmatched performance for interacting with live Sage Cloud Accounting data due to optimized data processing built into the driver. When you issue complex SQL queries to Sage Cloud Accounting, the driver pushes supported SQL operations, like filters and aggregations, directly to Sage Cloud Accounting 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 Sage Cloud Accounting data using native data types.

Install the CData JDBC Driver for Sage Cloud Accounting

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

Start a Spark Shell and Connect to Sage Cloud Accounting Data

1. Open a terminal and start the Spark shell with the CData JDBC Driver for Sage Cloud Accounting JAR file as the jars parameter: $ spark-shell --jars /CData/CData JDBC Driver for Sage Cloud Accounting/lib/cdata.jdbc.sagebcaccounting.jar
2. With the shell running, you can connect to Sage Cloud Accounting with a JDBC URL and use the SQL Context load() function to read a table.

   You can connect to Sage Business Cloud Accounting using the embedded OAuth connectivity. When you connect, the OAuth endpoint opens in your browser. Log in and grant permissions to complete the OAuth process. See the OAuth section in the online Help documentation for more information on other OAuth authentication flows.

   Built-in Connection String Designer

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

   java -jar cdata.jdbc.sagebcaccounting.jar

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

   Configure the connection to Sage Cloud Accounting, using the connection string generated above.

   scala> val sagebcaccounting_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:sagebcaccounting:").option("dbtable","SalesInvoices").option("driver","cdata.jdbc.sagebcaccounting.SageBCAccountingDriver").load()
3. Once you connect and the data is loaded you will see the table schema displayed.

4. Register the Sage Cloud Accounting data as a temporary table:

   scala> sagebcaccounting_df.registerTable("salesinvoices")

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

   scala> sagebcaccounting_df.sqlContext.sql("SELECT contact_name, total_amount FROM SalesInvoices WHERE sent = TRUE").collect.foreach(println)

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

Using the CData JDBC Driver for Sage Cloud Accounting in Apache Spark, you are able to perform fast and complex analytics on Sage Cloud Accounting data, combining the power and utility of Spark with your data. Download a free, 30 day trial of any of the 200+ CData JDBC Drivers and get started today.