Elasticsearch Connector
Enabling Easy Access to Elasticsearch API
Overview
The Elasticsearch connector enables access to the Elasticsearch REST API through the Anypoint platform.
Elasticsearch is a distributed, open-source search and analytics engine, designed for horizontal scalability, reliability, and easy management.
The connector exposes Elasticsearch operations by executing their API calls as per configuration. It supports HTTP and HTTPS connections to Elasticsearch instances.
Technical Specifications
Published on – 3rd September, 2018
Version – 1.0.0
Compatible with – MuleSoft Runtime version 4.1.1+
Available at Anypoint Exchange
Diving Deeper into the World of Elasticsearch
The real value of the Elasticsearch connector is in the way it can be used at design time in conjunction with other functional features available in MuleSoft.
The Elasticsearch connector functions within a Mule application. Using the connector, applications can perform several operations that Elasticsearch exposes via APIs. When building an application that connects with Elasticsearch, there is no need to custom code (or secure!) a connection. Rather, a connector can just be dropped into the flow and the connection details configured to have the application running on Elasticsearch.
Data Sense
DataSense extracts metadata for Elasticsearch standard response to automatically determine the data type and format that applications must deliver to, or can expect from, Elasticsearch. Mule does the heavy lifting of discovering the type of data that must be sent to or received from Elasticsearch.
Transform Message Component
This component’s integrated scripting language called DataWeave can automatically extract response metadata that can be used to visually map and/or transform to a different data format or structure. Essentially, DataWeave lets the user control mappings between data types. For example, if an Elasticsearch connector is configured in an application, and then a Transform Message component dropped after the connector, the component uses DataWeave to gather information that DataSense extracted to pre-populate input values for mapping. In other words, DataSense makes sure that DataWeave knows the data format and structure it must work with, so that it doesn’t have to be figured out manually.
