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Work with Basecamp Data in Apache Spark Using SQL

Access and process Basecamp 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 Basecamp, Spark can work with live Basecamp data. This article describes how to connect to and query Basecamp data from a Spark shell.

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

Install the CData JDBC Driver for Basecamp

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

Start a Spark Shell and Connect to Basecamp Data

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

    Basecamp uses basic or OAuth 2.0 authentication. To use basic authentication you will need the user and password that you use for logging in to Basecamp. To authenticate to Basecamp via OAuth 2.0, you will need to obtain the OAuthClientId, OAuthClientSecret, and CallbackURL connection properties by registering an app with Basecamp.

    See the Getting Started section in the help documentation for a connection guide.

    Additionally, you will need to specify the AccountId connection property. This can be copied from the URL after you log in.

    Built-in Connection String Designer

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

    java -jar cdata.jdbc.basecamp.jar

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

    scala> val basecamp_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:basecamp:User=test@northwind.db;Password=test123;").option("dbtable","Projects").option("driver","cdata.jdbc.basecamp.BasecampDriver").load()
  3. Once you connect and the data is loaded you will see the table schema displayed.
  4. Register the Basecamp data as a temporary table:

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

    scala> basecamp_df.sqlContext.sql("SELECT Name, DocumentsCount FROM Projects WHERE Drafts = True").collect.foreach(println)

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

Using the CData JDBC Driver for Basecamp in Apache Spark, you are able to perform fast and complex analytics on Basecamp data, combining the power and utility of Spark with your data. Download a free, 30 day trial of any of the 150+ CData JDBC Drivers and get started today.