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Work with QuickBooks POS Data in Apache Spark Using SQL

Access and process QuickBooks POS Data in Apache Spark using the CData JDBC Driver.

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

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

Install the CData JDBC Driver for QuickBooks POS

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

Start a Spark Shell and Connect to QuickBooks POS Data

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

    When you are connecting to a local QuickBooks instance, you do not need to set any connection properties.

    Requests are made to QuickBooks POS through the Remote Connector. The Remote Connector runs on the same machine as QuickBooks POS and accepts connections through a lightweight, embedded Web server. The server supports SSL/TLS, enabling users to connect securely from remote machines.

    The first time you connect, you will need to authorize the Remote Connector with QuickBooks POS. See the "Getting Started" chapter of the help documentation for a guide.

    Built-in Connection String Designer

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

    java -jar cdata.jdbc.quickbookspos.jar

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

    scala> val quickbookspos_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:quickbookspos:").option("dbtable","Customers").option("driver","cdata.jdbc.quickbookspos.QuickBooksPOSDriver").load()
  3. Once you connect and the data is loaded you will see the table schema displayed.
  4. Register the QuickBooks POS data as a temporary table:

    scala> quickbookspos_df.registerTable("customers")
  5. Perform custom SQL queries against the Data using commands like the one below:

    scala> quickbookspos_df.sqlContext.sql("SELECT ListId, AccountLimit FROM Customers WHERE LastName = Cook").collect.foreach(println)

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

Using the CData JDBC Driver for QuickBooks POS in Apache Spark, you are able to perform fast and complex analytics on QuickBooks POS data, combining the power and utility of Spark with your data. Download a free, 30 day trial of any of the 160+ CData JDBC Drivers and get started today.