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Get the Report →How to load BigQuery data into Elasticsearch via Logstash
Introducing a simple method to load BigQuery 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 BigQuery to load data from BigQuery into Elasticsearch via Logstash.
Using CData JDBC Driver for BigQuery with Elasticsearch Logstash
- Install the CData JDBC Driver for BigQuery 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 GoogleBigQuery 20XX\lib\cdata.jdbc.googlebigquery.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 BigQuery data to Elasticsearch with Logstash
Now, let's create a configuration file for Logstash to transfer BigQuery data to Elasticsearch.
- Write the process to retrieve BigQuery 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 BigQuery in the form of a JDBC URL. The JDBC URL allows detailed configuration, so please refer to the product documentation for more specifics.
Google uses the OAuth authentication standard. To access Google APIs on behalf of individual users, you can use the embedded credentials or you can register your own OAuth app.
OAuth also enables you to use a service account to connect on behalf of users in a Google Apps domain. To authenticate with a service account, you will need to register an application to obtain the OAuth JWT values.
In addition to the OAuth values, you will need to specify the DatasetId and ProjectId. See the "Getting Started" chapter of the help documentation for a guide to using OAuth.
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 BigQuery data has been loaded into Elasticsearch.
For example, let's view the data transferred to Elasticsearch in Kibana.
GET googlebigquery_table/_search { "query": { "match_all": {} } }
We have confirmed that the data is stored in Elasticsearch.
By using the CData JDBC Driver for BigQuery with Logstash, it functions as a BigQuery connector, making it easy to load data into Elasticsearch. Please try the 30-day free trial.