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Elasticsearch is a search engine based on the Lucene library. It provides a distributed, multitenant-capable, full-text search engine with an HTTP web interface and schema-free JSON documents.

Below is the process for exporting data in a View in Mammoth to the Elasticsearch on a remote server:

  1. Go to Exports and Share > Export to database > Already existing database > Elasticsearch;
  1. Enter your credentials - Host, Username, Password, Batch Size (the number of rows from the View exported in a single POST request), Index name and Connection type (HTTP/HTTPS);
  2. Tick the checkbox "Keep at the end of the pipeline" to keep the export task at the end of the pipeline. Any task performed will be added to the Pipeline before the export task;
  3. Tick the checkbox “include hidden columns” to export the hidden columns;
  4. Validate the credentials;
  5. Once it is validated, click on Apply.

An index will then be created with the type as ”Mammoth” and for each row a document will be created with an ID auto-generated by Elasticsearch.

The export will also be recorded as a Task in the pipeline.