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Get the Report →How to load JSON data into Elasticsearch via Logstash
Introducing a simple method to load JSON 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 JSON to load data from JSON into Elasticsearch via Logstash.
Using CData JDBC Driver for JSON with Elasticsearch Logstash
- Install the CData JDBC Driver for JSON 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 JSON 20XX\lib\cdata.jdbc.json.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 JSON data to Elasticsearch with Logstash
Now, let's create a configuration file for Logstash to transfer JSON data to Elasticsearch.
- Write the process to retrieve JSON 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 JSON in the form of a JDBC URL. The JDBC URL allows detailed configuration, so please refer to the product documentation for more specifics.
- Document (default): Model a top-level, document view of your JSON data. The data provider returns nested elements as aggregates of data.
- FlattenedDocuments: Implicitly join nested documents and their parents into a single table.
- Relational: Return individual, related tables from hierarchical data. The tables contain a primary key and a foreign key that links to the parent document.
See the Getting Started chapter in the data provider documentation to authenticate to your data source: The data provider models JSON APIs as bidirectional database tables and JSON files as read-only views (local files, files stored on popular cloud services, and FTP servers). The major authentication schemes are supported, including HTTP Basic, Digest, NTLM, OAuth, and FTP. See the Getting Started chapter in the data provider documentation for authentication guides.
After setting the URI and providing any authentication values, set DataModel to more closely match the data representation to the structure of your data.
The DataModel property is the controlling property over how your data is represented into tables and toggles the following basic configurations.
See the Modeling JSON Data chapter for more information on configuring the relational representation. You will also find the sample data used in the following examples. The data includes entries for people, the cars they own, and various maintenance services performed on those cars.
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 JSON data has been loaded into Elasticsearch.
For example, let's view the data transferred to Elasticsearch in Kibana.
GET json_table/_search { "query": { "match_all": {} } }
We have confirmed that the data is stored in Elasticsearch.
By using the CData JDBC Driver for JSON with Logstash, it functions as a JSON connector, making it easy to load data into Elasticsearch. Please try the 30-day free trial.