How to load Azure Table 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 Azure Table to load data from Azure Table into Elasticsearch via Logstash.

Using CData JDBC Driver for Azure Table with Elasticsearch Logstash

• Install the CData JDBC Driver for Azure Table 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 AzureTables 20XX\lib\cdata.jdbc.azuretables.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 Azure Table data to Elasticsearch with Logstash

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

• Write the process to retrieve Azure Table 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 Azure Table in the form of a JDBC URL. The JDBC URL allows detailed configuration, so please refer to the product documentation for more specifics.

Specify your AccessKey and your Account to connect. Set the Account property to the Storage Account Name and set AccessKey to one of the Access Keys. Either the Primary or Secondary Access Keys can be used. To obtain these values, navigate to the Storage Accounts blade in the Azure portal. You can obtain the access key by selecting your account and clicking Access Keys in the Settings section.

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 Azure Table data has been loaded into Elasticsearch.

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

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

We have confirmed that the data is stored in Elasticsearch.

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