Connect to Spark Data in HULFT Integrate

HULFT Integrate is a modern data integration platform that provides a drag-and-drop user interface to create cooperation flows, data conversion, and processing so that complex data connections are easier than ever to execute. When paired with the CData JDBC Driver for Apache Spark, HULFT Integrate can work with live Spark data. This article walks through connecting to Spark and moving the data into a CSV file.

With built-in optimized data processing, the CData JDBC Driver offers unmatched performance for interacting with live Spark data. When you issue complex SQL queries to Spark, the driver pushes supported SQL operations, like filters and aggregations, directly to Spark and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations). Its built-in dynamic metadata querying allows you to work with and analyze Spark data using native data types.

Enable Access to Spark

To enable access to Spark data from HULFT Integrate projects:

1. Copy the CData JDBC Driver JAR file (and license file if it exists), cdata.jdbc.sparksql.jar (and cdata.jdbc.sparksql.lic), to the jdbc_adapter subfolder for the Integrate Server
2. Restart the HULFT Integrate Server and launch HULFT Integrate Studio

Build a Project with Access to Spark Data

Once you copy the JAR files, you can create a project with access to Spark data. Start by opening Integrate Studio and creating a new project.

1. Name the project
2. Ensure the "Create script" checkbox is checked
3. Click Next
4. Name the script (e.g.: SparkSQLtoCSV)

Once you create the project, add components to the script to copy Spark data to a CSV file.

Configure an Execute Select SQL Component

Drag an "Execute Select SQL" component from the Tool Palette (Database -> JDBC) into the Script workspace.

1. In the "Required settings" tab for the Destination, click "Add" to create a new connection for Spark. Set the following properties:
   • Name: Spark Connection Settings
   • Driver class name: cdata.jdbc.sparksql.SparkSQLDriver
   • URL: jdbc:sparksql:Server=127.0.0.1;
     
     

     Built-in Connection String Designer

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

     java -jar cdata.jdbc.sparksql.jar

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

     Set the Server, Database, User, and Password connection properties to connect to SparkSQL.

2. Write your SQL statement. For example:

   SELECT City, Balance FROM Customers

3. Click "Extraction test" to ensure the connection and query are configured properly
4. Click "Execute SQL statement and set output schema"
5. Click "Finish"

Configure a Write CSV File Component

Drag a "Write CSV File" component from the Tool Palette (File -> CSV) onto the workspace.

1. Set a file to write the query results to (e.g. Customers.csv)
2. Set "Input data" to the "Select SQL" component
3. Add columns for each field selected in the SQL query
4. In the "Write settings" tab, check the checkbox to "Insert column names into first row"
5. Click "Finish"

Map Spark Fields to the CSV Columns

Map each column from the "Select" component to the corresponding column for the "CSV" component.

Finish the Script

Drag the "Start" component onto the "Select" component and the "CSV" component onto the "End" component. Build the script and run the script to move Spark data into a CSV file.

Download a free, 30-day trial of the CData JDBC Driver for Apache Spark and start working with your live Spark data in HULFT Integrate. Reach out to our Support Team if you have any questions.