How to load Lakebase data into Elasticsearch via Logstash

Elasticsearch is a popular distributed full-text search engine. By centrally storing data, you can perform ultra-fast searches, fine-tuning relevance, and powerful analytics with ease. Elasticsearch has a pipeline tool for loading data called "Logstash". You can use CData JDBC Drivers to easily import data from any data source into Elasticsearch for search and analysis.

This article explains how to use the CData JDBC Driver for Lakebase to load data from Lakebase into Elasticsearch via Logstash.

Using CData JDBC Driver for Lakebase with Elasticsearch Logstash

• Install the CData JDBC Driver for Lakebase on the machine where Logstash is running.
• The JDBC Driver will be installed at the following path (the year part, e.g. 20XX, will vary depending on the product version you are using). You will use this path later. Place this .jar file (and the .lic file if it's a licensed version) in Logstash.
  C:\Program Files\CData\CData JDBC Driver for Lakebase 20XX\lib\cdata.jdbc.lakebase.jar
  
• Next, install the JDBC Input Plugin, which connects Logstash to the CData JDBC driver. The JDBC Plugin comes by default with the latest version of Logstash, but depending on the version, you may need to add it.
  https://www.elastic.co/guide/en/logstash/5.4/plugins-inputs-jdbc.html
• Move the CData JDBC Driver’s .jar file and .lic file to Logstash's "/logstash-core/lib/jars/".

Sending Lakebase data to Elasticsearch with Logstash

Now, let's create a configuration file for Logstash to transfer Lakebase data to Elasticsearch.

• Write the process to retrieve Lakebase data in the logstash.conf file, which defines data processing in Logstash. The input will be JDBC, and the output will be Elasticsearch. The data loading job is set to run at 30-second intervals.
• Set the CData JDBC Driver's .jar file as the JDBC driver library, configure the class name, and set the connection properties to Lakebase in the form of a JDBC URL. The JDBC URL allows detailed configuration, so please refer to the product documentation for more specifics.
To connect to Databricks Lakebase, start by setting the following properties:
• DatabricksInstance: The Databricks instance or server hostname, provided in the format instance-abcdef12-3456-7890-abcd-abcdef123456.database.cloud.databricks.com.
• Server: The host name or IP address of the server hosting the Lakebase database.
• Port (optional): The port of the server hosting the Lakebase database, set to 5432 by default.
• Database (optional): The database to connect to after authenticating to the Lakebase Server, set to the authenticating user's default database by default.

OAuth Client Authentication

To authenicate using OAuth client credentials, you need to configure an OAuth client in your service principal. In short, you need to do the following:

1. Create and configure a new service principal
2. Assign permissions to the service principal
3. Create an OAuth secret for the service principal

For more information, refer to the Setting Up OAuthClient Authentication section in the Help documentation.

OAuth PKCE Authentication

To authenticate using the OAuth code type with PKCE (Proof Key for Code Exchange), set the following properties:

• AuthScheme: OAuthPKCE.
• User: The authenticating user's user ID.

For more information, refer to the Help documentation.

Executing data movement with Logstash

Now let's run Logstash using the created "logstash.conf" file.

 logstash-7.8.0\bin\logstash -f logstash.conf

A log indicating success will appear. This means the Lakebase data has been loaded into Elasticsearch.

For example, let's view the data transferred to Elasticsearch in Kibana.

 GET lakebase_table/_search
 {
 "query": {
 "match_all": {}
 }
 }

We have confirmed that the data is stored in Elasticsearch.

By using the CData JDBC Driver for Lakebase with Logstash, it functions as a Lakebase connector, making it easy to load data into Elasticsearch. Please try the 30-day free trial.