How to work with Halo Service Desk 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 Halo Service Desk, Spark can work with live Halo Service Desk data. This article describes how to connect to and query Halo Service Desk data from a Spark shell.

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

Install the CData JDBC Driver for Halo Service Desk

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

Start a Spark Shell and Connect to Halo Service Desk Data

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

   
   $ spark-shell --jars /CData/CData JDBC Driver for Halo Service Desk/lib/cdata.jdbc.api.jar
   

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

   Start by setting the Profile connection property to the location of the HaloServiceDesk Profile on disk (e.g. C:\profiles\HaloServiceDesk.apip). Next, set the ProfileSettings connection property to the connection string for HaloServiceDesk (see below).

   HaloServiceDesk API Profile Settings

   HaloServiceDesk uses API key authentication. You can find or create API keys in HaloServiceDesk under Administration > Integrations > Halo API.

   Set the following connection properties to connect:

   • AuthScheme: Set this to APIKey.
   • APIKey: Set this to the API key from your HaloServiceDesk account.
   • Domain: Set this to the hostname of your HaloServiceDesk instance (e.g. yourcompany.haloservicedesk.com).

   Built-in Connection String Designer

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

   
   java -jar cdata.jdbc.api.jar
   

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

   

   Configure the connection to Halo Service Desk, using the connection string generated above.

   
   scala> val api_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:api:Profile=C:\profiles\HaloServiceDesk.apip;AuthScheme=APIKey;ProfileSettings='APIKey=your_api_key;Domain=yourcompany.haloservicedesk.com';").option("dbtable","Assets").option("driver","cdata.jdbc.api.APIDriver").load()
   

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

4. Register the Halo Service Desk data as a temporary table:

   scala> api_df.registerTable("assets")

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

   scala> api_df.sqlContext.sql("SELECT Id, InventoryNumber FROM Assets WHERE ClientId = 1").collect.foreach(println)

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

   

Using the CData JDBC Driver for Halo Service Desk in Apache Spark, you are able to perform fast and complex analytics on Halo Service Desk 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.