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

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

Install the CData JDBC Driver for Nuclia

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

Start a Spark Shell and Connect to Nuclia Data

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

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

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

   Using API Key Authentication

   Nuclia uses API key authentication for accessing Knowledge Box data. To obtain an API key:

   1. Log in to the Nuclia Cloud Dashboard at https://nuclia.cloud
   2. Navigate to your Knowledge Box settings
   3. Go to the Service Accounts section
   4. Create a new service account or copy an existing API key

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

   • AuthScheme: Set this to APIKey.
   • APIKey: Set this to your Nuclia service account API key.
   • KbId: Set this to your Knowledge Box UUID.
   • Zone: Set this to your Nuclia deployment zone (e.g., aws-us-east-2-1).

   Example Connection String

   Profile=C:\profiles\Nuclia.apip;AuthScheme=APIKey;APIKey=your_service_account_key;KbId=your_kb_uuid;Zone=aws-us-east-2-1;
   

   Connecting to Nuclia

   Once the authentication is configured, you can connect to Nuclia and query data from any of the available tables such as Resources, KnowledgeBox, LabelSets, and ProcessingStatus.

   Built-in Connection String Designer

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

   scala> val api_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:api:Profile=C:\profiles\Nuclia.apip;AuthScheme=APIKey;APIKey=your_service_account_key;KbId=your_kb_uuid;Zone=aws-us-east-2-1;").option("dbtable","KnowledgeBox").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 Nuclia data as a temporary table:

   scala> api_df.registerTable("knowledgebox")

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

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

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

   

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