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

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

Install the CData JDBC Driver for SpaceX

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

Start a Spark Shell and Connect to SpaceX Data

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

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

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

   SpaceX API Profile Settings

   No authentication is required to access SpaceX data — the SpaceX API is publicly available. Simply set the Profile connection property to the path of the SpaceX profile file.

   Built-in Connection String Designer

   For assistance in constructing the JDBC URL, use the connection string designer built into the SpaceX 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.

   👁 Using the built-in connection string designer to generate a JDBC URL (Salesforce is shown.)
   

   Configure the connection to SpaceX, using the connection string generated above.

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

   scala> api_df.registerTable("capsules")

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

   scala> api_df.sqlContext.sql("SELECT CapsuleSerial, CapsuleId FROM Capsules WHERE Status = active").collect.foreach(println)

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

   👁 Data in Apache Spark (Salesforce is shown)
   

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