Discover how a bimodal integration strategy can address the major data management challenges facing your organization today.
Get the Report →Access Live Elasticsearch Data in AWS Lambda
Connect to live Elasticsearch data in AWS Lambda using the CData JDBC Driver.
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 Elasticsearch data when paired with the CData JDBC Driver for Elasticsearch. This article describes how to connect to and query Elasticsearch 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 Elasticsearch data. When you issue complex SQL queries to Elasticsearch, the driver pushes supported SQL operations, like filters and aggregations, directly to Elasticsearch 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 Elasticsearch data using native data types.
About Elasticsearch Data Integration
Accessing and integrating live data from Elasticsearch has never been easier with CData. Customers rely on CData connectivity to:
- Access both the SQL endpoints and REST endpoints, optimizing connectivity and offering more options when it comes to reading and writing Elasticsearch data.
- Connect to virtually every Elasticsearch instance starting with v2.2 and Open Source Elasticsearch subscriptions.
- Always receive a relevance score for the query results without explicitly requiring the SCORE() function, simplifying access from 3rd party tools and easily seeing how the query results rank in text relevance.
- Search through multiple indices, relying on Elasticsearch to manage and process the query and results instead of the client machine.
Users frequently integrate Elasticsearch data with analytics tools such as Crystal Reports, Power BI, and Excel, and leverage our tools to enable a single, federated access layer to all of their data sources, including Elasticsearch.
For more information on CData's Elasticsearch solutions, check out our Knowledge Base article: CData Elasticsearch Driver Features & Differentiators.
Getting Started
Gather Connection Properties and Build a Connection String
Set the Server and Port connection properties to connect. To authenticate, set the User and Password properties, PKI (public key infrastructure) properties, or both. To use PKI, set the SSLClientCert, SSLClientCertType, SSLClientCertSubject, and SSLClientCertPassword properties.
The data provider uses X-Pack Security for TLS/SSL and authentication. To connect over TLS/SSL, prefix the Server value with 'https://'. Note: TLS/SSL and client authentication must be enabled on X-Pack to use PKI.
Once the data provider is connected, X-Pack will then perform user authentication and grant role permissions based on the realms you have configured.
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 Elasticsearch JDBC Driver. Double-click the JAR file or execute the jar file from the command line.
java -jar cdata.jdbc.elasticsearch.jar
Fill in the connection properties (including the RTK) and copy the connection string to the clipboard.
Create an AWS Lambda Function
- Download the CData JDBC Driver for Elasticsearch installer, unzip the package, and run the JAR file to install the driver.
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.
- Add the CData JDBC Driver for Elasticsearch JAR file (cdata.jdbc.elasticsearch.jar) to the build path. The file is found in INSTALL_PATH\lib\.
- 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;
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.elasticsearch.ElasticsearchDriver"); } catch (ClassNotFoundException ex) { context.getLogger().log("Error: class not found"); } Connection connection = null; try { connection = DriverManager.getConnection("jdbc:cdata:elasticsearch:RTK=52465...;Server=127.0.0.1;Port=9200;User=admin;Password=123456;"); } 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 Elasticsearch data in AWS Lambda functions.
- Right-click the Package and select Amazon Web Services -> Upload function to AWS Lamba.
- 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).
- Right-click the Package and select Amazon Web Services -> Run function on AWS Lambda and set the input to the name of the Elasticsearch object you wish to query (i.e. "Orders").
- 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 Elasticsearch and start working with your live Elasticsearch data in AWS Lambda. Reach out to our Support Team if you have any questions.