Access Live Parquet Data in AWS Lambda

AWS Lambda is a compute service that lets you build applications that respond quickly to new information and events. AWS Lambda functions can work with live Parquet data when paired with the CData JDBC Driver for Parquet. This article describes how to connect to and query Parquet data from an AWS Lambda function built in Eclipse.

At the time this article was written (June 2022), Eclipse version 2019-12 and Java 8 were the highest versions supported by the AWS Toolkit for Eclipse.

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). In addition, its built-in dynamic metadata querying allows you to work with and analyze Parquet data using native data types.

Gather Connection Properties and Build a Connection String

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

NOTE: To use the JDBC driver in an AWS Lambda function, you will need a license (full or trial) and a Runtime Key (RTK). For more information on obtaining this license (or a trial), contact our sales team.

Built-in Connection String Designer

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

Fill in the connection properties (including the RTK) and copy the connection string to the clipboard.

Create an AWS Lambda Function

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

2. Create a new AWS Lambda Java Project in Eclipse using the AWS Toolkit for Eclipse. You can follow the tutorial from AWS (amazon.com).

   For this article, set the Input Type for the project to "Custom" so we can enter a table name as the input.

3. Add the CData JDBC Driver for Parquet JAR file (cdata.jdbc.parquet.jar) to the build path. The file is found in INSTALL_PATH\lib\.
4. Add the following import statements to the Java class: import java.sql.Connection; import java.sql.DriverManager; import java.sql.ResultSet; import java.sql.ResultSetMetaData; import java.sql.SQLException; import java.sql.Statement;

5. Replace the body of the handleRequest method with the code below. Be sure to fill in the connection string in the DriverManager.getConnection method call.

   String query = "SELECT * FROM " + input; try { Class.forName("cdata.jdbc.parquet.ParquetDriver"); } catch (ClassNotFoundException ex) { context.getLogger().log("Error: class not found"); } Connection connection = null; try { connection = DriverManager.getConnection("jdbc:cdata:parquet:RTK=52465...;URI=C:/folder/table.parquet;"); } catch (SQLException ex) { context.getLogger().log("Error getting connection: " + ex.getMessage()); } catch (Exception ex) { context.getLogger().log("Error: " + ex.getMessage()); } if(connection != null) { context.getLogger().log("Connected Successfully!\n"); } ResultSet resultSet = null; try { //executing query Statement stmt = connection.createStatement(); resultSet = stmt.executeQuery(query); ResultSetMetaData metaData = resultSet.getMetaData(); int numCols = metaData.getColumnCount(); //printing the results while(resultSet.next()) { for(int i = 1; i <= numCols; i++) { System.out.printf("%-25s", (resultSet.getObject(i) != null) ? resultSet.getObject(i).toString().replaceAll("\n", "") : null ); } System.out.print("\n"); } } catch (SQLException ex) { System.out.println("SQL Exception: " + ex.getMessage()); } catch (Exception ex) { System.out.println("General exception: " + ex.getMessage()); } String output = "query: " + query + " complete"; return output;

Deploy and Run the Lambda Function

Once you build the function in Eclipse, you are ready to upload and run the function. In this article, the output is written to the AWS logs, but you can use this is a template to implement you own custom business logic to work with Parquet data in AWS Lambda functions.

1. Right-click the Package and select Amazon Web Services -> Upload function to AWS Lamba.
2. Name the function, select an IAM role, and set the timeout value to a high enough value to ensure the function completes (depending on the result size of your query).
3. Right-click the Package and select Amazon Web Services -> Run function on AWS Lambda and set the input to the name of the Parquet object you wish to query (i.e. "SampleTable_1").
4. After the job runs, you can view the output in the CloudWatch logs.

Free Trial & More Information

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