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

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

Install the CData JDBC Driver for TimeCamp

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

Start a Spark Shell and Connect to TimeCamp Data

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

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

2. With the shell running, you can connect to TimeCamp 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 TimeCamp Profile on disk (e.g. C:\profiles\TimeCamp.apip). Next, set the ProfileSettings connection property to the connection string for TimeCamp (see below).

   TimeCamp API Profile Settings

   TimeCamp uses token-based authentication. To obtain an API Token:

   1. Log in to your TimeCamp account at https://app.timecamp.com
   2. Click your profile avatar in the top-right corner
   3. Select Profile Settings
   4. Copy the API token shown at the bottom of the page

   After obtaining your API Token, set the following connection properties:

   • AuthScheme: Set this to APIKey.

   Set the following in the ProfileSettings connection property:

   • APIKey: Set this to your TimeCamp API token.

   Built-in Connection String Designer

   For assistance in constructing the JDBC URL, use the connection string designer built into the TimeCamp 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 TimeCamp, using the connection string generated above.

   
   scala> val api_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:api:Profile=C:\profiles\TimeCamp.apip;AuthScheme=APIKey;ProfileSettings='APIKey=your_api_token';").option("dbtable","GroupUsers").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 TimeCamp data as a temporary table:

   scala> api_df.registerTable("groupusers")

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

   scala> api_df.sqlContext.sql("SELECT UserId, Email FROM GroupUsers WHERE GroupId = 12345").collect.foreach(println)

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

   

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