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Get the Report →How to load Google Data Catalog data into Elasticsearch via Logstash
Introducing a simple method to load Google Data Catalog data using the ETL module Logstash of the full-text search service Elasticsearch and the CData JDBC driver.
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 Google Data Catalog to load data from Google Data Catalog into Elasticsearch via Logstash.
Using CData JDBC Driver for Google Data Catalog with Elasticsearch Logstash
- Install the CData JDBC Driver for Google Data Catalog on the machine where Logstash is running.
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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 GoogleDataCatalog 20XX\lib\cdata.jdbc.googledatacatalog.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 Google Data Catalog data to Elasticsearch with Logstash
Now, let's create a configuration file for Logstash to transfer Google Data Catalog data to Elasticsearch.
- Write the process to retrieve Google Data Catalog 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 Google Data Catalog in the form of a JDBC URL. The JDBC URL allows detailed configuration, so please refer to the product documentation for more specifics.
- OrganizationId: The ID associated with the Google Cloud Platform organization resource you would like to connect to. Find this by navigating to the cloud console.
Click the project selection drop-down, and select your organization from the list. Then, click More -> Settings. The organization ID is displayed on this page.
- ProjectId: The ID associated with the Google Cloud Platform project resource you would like to connect to.
Find this by navigating to the cloud console dashboard and selecting your project from the Select from drop-down. The project ID will be present in the Project info card.
Google Data Catalog uses the OAuth authentication standard. Authorize access to Google APIs on behalf on individual users or on behalf of users in a domain.
Before connecting, specify the following to identify the organization and project you would like to connect to:
When you connect, the OAuth endpoint opens in your default browser. Log in and grant permissions to the application to completes the OAuth process. For more information, refer to the OAuth section in 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 Google Data Catalog data has been loaded into Elasticsearch.
For example, let's view the data transferred to Elasticsearch in Kibana.
GET googledatacatalog_table/_search { "query": { "match_all": {} } }
We have confirmed that the data is stored in Elasticsearch.
By using the CData JDBC Driver for Google Data Catalog with Logstash, it functions as a Google Data Catalog connector, making it easy to load data into Elasticsearch. Please try the 30-day free trial.