In order to do that, we need to make use of a templating engine (a tool for dynamically rendering HTML using server data). If we want to simply send HTML back we can use ndFile, but since we are using server-side templates, we will be using a method called render.

So far we have only seen how to respond by sending text, but when building server-side applications, we usually want to send back HTML or JSON / XML (if we're building an RESTful API). Now move your search function from nestedQuery.js into functions.js.By the end of this chapter, you should be able to: var client = require ('./connection.js') Add the following lines to connect to Elasticsearch and use the get-json library. Start by creating a new file and call it functions.js. This will set us up nicely for when we are putting our application together since it will allow us to keep our functions separate from our logic. We'll also move the search query into a separate file which we'll call from nestedQuery.js. We'll need the get-json library for this so install it before you start. To get an idea of what you'll have by the end of this article, check out our own Petitioneering app.īefore we get to that we'll add in the postcode lookup we promised at the end of the last article. In this article - the last in the series - we're going to turn our existing code into a fully-fledged app and deploy it using IBM Bluemix. In the previous article we ran some queries on the nested fields in our petitions data. In the final step of the series, we create a web application to access the Elasticsearch managed data and show how to host the web app on IBM's Bluemix. Getting started with Elasticsearch and Node.js - Part 5 tutorial elasticsearch bluemix Free 30 Day Trial

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