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

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

Install the CData JDBC Driver for Vercel

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

Start a Spark Shell and Connect to Vercel Data

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

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

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

   Using API Key Authentication

   Vercel uses Bearer token authentication. You can use either a personal access token or an OAuth access token as the API key.

   To obtain a personal access token:

   1. Log into your Vercel account at https://vercel.com/
   2. Navigate to Account Settings > Tokens.
   3. Click Create Token, enter a name and expiration, and click Create.
   4. Copy the generated token (it will only be shown once).

   After obtaining your token, set the following connection properties:

   • AuthScheme: Set this to APIKey.
   • APIKey: Set this to your Vercel personal access token or OAuth access token.

   Example Connection String

   Profile=C:\profiles\Vercel.apip;AuthScheme=APIKey;APIKey=your_access_token;
   

   Working with Teams

   Many Vercel resources are scoped to a team. To scope all requests to a specific team, set the TeamId connection property to your team's ID. You can find your team ID by querying the Teams table or from the Vercel dashboard. Alternatively, you can specify TeamId in your SQL queries using the WHERE clause where supported.

   Connecting to Vercel

   Once the authentication is configured, you can connect to Vercel and query data from any of the available tables such as Projects, Deployments, Teams, and Domains.

   Built-in Connection String Designer

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

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

   scala> api_df.registerTable("user")

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

   scala> api_df.sqlContext.sql("SELECT ,  FROM User WHERE  = ").collect.foreach(println)

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

   

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