Connect to Parquet 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 Parquet, HULFT Integrate can work with live Parquet data. This article explains how to connect to Parquet and move the data into a CSV file.

With built-in optimized data processing, the CData JDBC driver offers unmatched performance for interacting with live Parquet data. When you issue complex SQL queries to Parquet, the driver pushes supported SQL operations, like filters and aggregations, directly to Parquet 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 Parquet data using native data types.

Enable Access to Parquet

To enable access to Parquet data from HULFT Integrate projects:

1. Copy the CData JDBC Driver JAR file (and license file if it exists), cdata.jdbc.parquet.jar (and cdata.jdbc.parquet.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 Parquet Data

Once you copy the JAR files, you can create a project with access to Parquet 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 👁 Creating a new project.
   
4. Name the script (e.g.: ParquettoCSV)

Once you create the project, add components to the script to copy Parquet 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 Parquet. Set the following properties:
   • Name: Parquet Connection Settings
   • Driver class name: cdata.jdbc.parquet.ParquetDriver
   • URL: jdbc:parquet:URI=C:/folder/table.parquet;
     
     👁 JDBC connection settings (Salesforce is shown).
     

     Built-in Connection String Designer

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

     		java -jar cdata.jdbc.parquet.jar
     		

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

     Connect to your local Parquet file(s) by setting the URI connection property to the location of the Parquet file.

     👁 Using the built-in connection string designer to generate a JDBC URL (Salesforce is shown.)
     
2. Write your SQL statement. For example:

   SELECT Id, Column1 FROM SampleTable_1

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" 👁 Configuring the Execute Select SQL operation
   

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. SampleTable_1.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 Parquet 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 Parquet data into a CSV file.

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