Mobile GeoLocation App in 30 minutes ā€“ Part 3: Deploying to OpenShift


In the previous two parts, you saw how to create a Node.js application and store JSON data in MongoDB (Part 1). You also saw how to present this data in a mobile Web application using Sencha Touch complete with Google Maps and geospatial searching (Part 2). Now, we are going to take both of these two pieces and deploy them on a Platform as a Service (PaaS). I looked at three different provides in this space: OpenShift, Heroku and Nodejitsu. The latter is Node.js specific while the other two you can deploy other types of applications (Java EE, Ruby, PHP, Python, etc.). I really liked RedHat’s OpenShift model. It has several nice dev features that I thought worked well which I will go over in this post. Nodejitsu worked well too but didn’t use Git (a distributed SCM tool) to manage changes. Heroku required a credit card at the point I wanted to introduce MongoDB, so I opted not to continue with Heroku. It doesn’t hurt to experiment with multiple vendors since you can sign-up for free accounts on the respective sites.

One of the main motivations to use a PaaS is that it wouldn’t be very maintainable or production worthy SSH’ing to a server and running your node process every time you wanted to launch your app. Moreover, even if you run your process, it eventually will shutdown when you close your SSH session. There is an npm package forever that can keep this from happening, but I think running Node on a PaaS is ideal.

Using OpenShift to create a Node App

The first thing you’ll want to do is create a free OpenShift account here. Once you have an account created, you can create the application directly from the website (very convenient) or you can install Ruby and the RHC gem (sudo gem install rhc) that allows you to do the same thing from command line. The website is pretty intuitive so I won’t cover this and should you want to use the CLI, the set-up is sufficiently covered here. Note that there are a few prerequisites to use the CLI, namely installed Ruby and Msysgit. Be sure to have those installed as per the provided link before continuing.

For the purposes of deploying the app we created in Part 1, you would do the following after you’ve established your OpenShift domain and added your SSH public keys to commit code from Git:

First, we create “dogtag” as a nodejs app:

$ rhc app create -a dogtag -t nodejs-0.6

Second, we add the MongoDB cartridge:

$ rhc app cartridge add -a myMongo -c mongodb-2.0

Last, we add the RockMongo cartridge to administer MongoDB from the browser (context URI: /rockmongo from your domain)

$ rhc app cartridge add -a myMongo -c rockmongo-1.1

Working with your application in OpenShift

After you have created the app, the next part is copy the DogTag Node.js code to the “dogtag” directory that was created by OpenShift. Since Git is used to manage changes, you can run the following commands to push the code to the server:

$ git add .

$ git commit -am ‘Initial check-in’

$ git push

What will happen then is that the code changes will push to the server, stop the node.js instance, deploy your code and restart the server…very cool! It will pick-up any NPM packages you need as long as you define them in the package.json file (in our case, we need express and mongoose). After that you can go to the provided URL from OpenShift and test the various URL routes we defined in Part 1 (e.g., You’ll notice that there is no data, so I created a JSON file that you can import into MongoDB to have some initial data. To do the import, you need to run the following command when you SSH to your server’s node:

$ mongoimport –host $OPENSHIFT_NOSQL_DB_HOST –port $OPENSHIFT_NOSQL_DB_PORT –username $OPENSHIFT_NOSQL_DB_USERNAME –password $OPENSHIFT_NOSQL_DB_PASSWORD –db dogtag –collection dogtags –file dogs.json –jsonArray

Note the $OPENSHIFT* provided constants so that you don’t have to figure out the actual host, port, username and password you are on which is especially helpful in a cloud environment running on multiple nodes. Once you import, you can check the files and add a geospatial index, which is required for the geospatial queries as follows:

$ mongo
> use dogtag
> db.dogtags.find() //will return results
> db.dogtags.find().forEach( function (e) { e.coords = [ e.longitude, e.latitude ];; }); //will add the required format for a coordinates field to index
> db.dogtags.ensureIndex( { coords : “2d” } ) //indexes the coords field for geospatial queries
> exit

Now, if you go to the URL again you will have JSON data returned in a JSONP callback. You can change the callback simply by adding &callback=[your callback name]. This is necessary to prevent cross-site scripting issues and required when using the JSONP proxy in Sencha Touch.

Deploying the Mobile App

Since the Mobile App was created with Sencha Touch, I just used a “DIY” (Do it yourself) app from OpenShift to deploy my app there. The process is very similar:

$ rhc app create -a dogtags -t diy-0.1

This creates a very basic Web app. You can cd to the “diy” directory that is created and copy the code from the Mobile app there. It will prompt you to replace index.html, which is fine. There is one thing you need to do in the existing code; you will need to update the store’s proxy to point to your “dogtag” node.js app you created in the previous section as well as the Pettracker controller which also has these references. To do that, simply update the URL with the one OpenShift provides and append “dogtag” on the end to get the list as follows:

 proxy: {  
       type: 'jsonp',  
       url: '',  
       reader: {  
           type: 'json',  
           idProperty: '_id',  
           rootProperty: 'records',  
           useSimpleAccessors: true  

Lastly, use git to push the updates to the server. It will deploy the new code and restart the server. Launch your app from a Webkit browser or from your mobile device and you should be in business similar to what you see here.

Once the app is deployed to OpenShift, you can tail the logs by running the following:

$ rhc app tail -a <app-name>

You can also start and stop the server as follows:

$ rhc app [start | stop ] -a <app-name>

And to snapshot a particular revision and go back to it you run the following:

$ rhc app snapshot save -a <app-name>

$ rhc app restore -a <app-name> -f <path to snapshot file>


I hope you found this three part series useful. In addition to creating a Node.js app and front-ending it with a Mobile application, you saw how easy it is to deploy such an application to the cloud.


Mobile GeoLocation App in 30 minutes – Part 1: Node.js and MongoDB


Are you interested in learning how to use Node.js with a NoSQL database like MongoDB to create REST services? Would you like to know how to create a mobile app with Google Maps that can perform geospatial queries with ease? Do you want to see how you can deploy all this to a PaaS with the click of a few buttons and a rudimentary understanding of Git? The answers to this and more are part of my three part series where I will cover the details on how you can create a “Pettracker” like application using Node.js, MongoDB, and Sencha Touch hosted on OpenShift. In this first part I will discuss how to build the middle tier and data store with Node.js and MongoDB.

What is Node.js and MongoDB?

Node.js is a JavaScript framework (API to a C library) for creating highly scaling, non-blocking IO applications that does not create multiple process threads for each invocation incurring a lot less O/S overhead under load. This is accomplished using an event-driven programming model that executes an IO bound call but does not block; it continues to the next line of code. It uses a callback mechanism to conclude the operation with the response once the event is complete. JavaScript is perfect to accommplish this because its native support for closures. Node by itself isn’t that interesting, but akin to Maven in the Java world, Node has npm so that you can add modules to it and expand its functionality further to all sorts of different use cases. In this article you’ll see how I leverage npm for working with MongoDB and creating a Web server router. Finally, Node together with Socket.IO can be used to create real-time Web applications (more on this in the future).

MongoDB is a highly scalable, high performance, open source NoSQL database that stores documents (rows in SQL parlance) into collections (tables in SQL) and is maximized for performance using in-memory cache, replica sets and sharding. It has a very nice query API and supports map/reduce functionality found in Hadoop/HBase. One of the pecular things with NoSQL DB’s is that there is no schema defined ahead of time. So other than installing MongoDB, there isn’t much else that you need to do. Given the fact that there’s no schema it doesn’t mean that we don’t have structure to our data. NoSQL allows for a very flexible schemas that can change easily as your application needs changing. Finally, MongoDB has built-in geospatial querying to support “near” and polygon searches. We’ll explore this in detail.

The DogTag Application

As you may be aware, Pettracker (aka Tagg) is a Qualcomm device/application that can be used to track lost Pets. I work for Qualcomm but I didn’t work on this project;however, I thought it would be interesting to see how I could replicate this application using Node.js and MongoDB, since it would be the perfect use case for something that would require high throughput and geospatial searching. Node.js will provide the middleware both to consume the JSON data from the emitters (i.e., the dog tag transponder) and it will provide the REST interface so that the mobile device can locate the dogs or perform geospatial queries of what’s near the user.

The first step to do all this is to create a Node.js application. I used the Express and Mongoose Node modules to allow me to create a website and to interface with MongoDB. You can add these modules using npm to your node install or add them to your package.json. I’ll talk more about this later in Part 3. Also, you can download the code from my GitHub account here.

Let’s take a look at the model.js code:

var mongoose = require('mongoose')
  , Schema = mongoose.Schema;

var dtSchema = new Schema({
    date: {type: Date, default:},
    longitude: Number,
    latitude: Number,
    coords: [Number, Number]

module.exports = mongoose.model('DogTag', dtSchema);

Mongoose is a nice Node module that allows me to work with MongoDB data in JavaScript, so in the code above you can see that I am defining “DogTag” schema (a document in Mongo) and setting fields for what should be stored. Mongoose will take care of the unmarshalling/marshalling the JSON data to MongoDB. Next, I need to define the api for the operations I wish to perform shown as follows:

var DogTag = require('../model/dogtag.js'); = function(req, res) {
    var dogtag = new DogTag({name:, description: req.params.descr,
        longitude: req.params.longitude, latitude: req.params.latitude}); (err) {
        if (err) throw err;
        console.log('Dogtag saved.');

        res.send('Dogtag saved.');

exports.list = function(req, res) {
    DogTag.find(function(err, dogtag) {
          res.setHeader('Content-Type', 'text/javascript;charset=UTF-8');
        res.send(req.query["callback"] + '({"records":' +  JSON.stringify(dogtag) + '});');
} = (function(req, res) {
    DogTag.findOne({name:}, function(error, dogtag) {
        res.send([{Dog: dogtag}]);

// first locates a dog by its name = (function(req, res) {
    DogTag.findOne({name:}, function(error, dogtag) {
        res.send([{Dog: dogtag}]);

exports.near = function(req, res) {
    DogTag.find({coords : { $near : [req.params.lon,], $maxDistance : req.params.dist/68.91}}, 
      function (error, dogtag) {    
        res.setHeader('Content-Type', 'text/javascript;charset=UTF-8');
        res.send(req.query["callback"] +'({"records":' + JSON.stringify(dogtag) + '});');

This code provides the CRUD operations to work with MongoDB. I used the schema I created previously to create dogtag objects and I use their save method to persist them into MongoDB. It’s that simple! If I need to find all the dogs, I use find(), or to find one dog by name, I use show(petname). Now, the last API, “near”, is doing a geospatial query using $near and $maxDistance against my “coords” field in the database. One thing to note is that you have to tell MongoDB to index fields that contain lat/lon. For details on this, see here, but all you really do is run this command from a mongo prompt: db.[collection_name].ensureIndex({ [field_name]: "2d" }).

One more thing to note is that I need to return JSONP back to the client by providing a callback name. To do that, I need the client to pass my a queryParameter (called “callback”) that will be the name of the callback method in the JSONP that is returned. I also need to call the built-in JavaScript function JSON.stringify to convert the schema object to JSON. You can see this put to use on lines 17 and 38.

The last piece is do build the node server. Yes, that’s right…you’re actually going to create the HTTP server that will respond to the request. Let’s take a look to see how:

var express = require('express');
var mongoose = require('mongoose');
var app = express();

var ipaddr  = '';
var port    =  8081;


app.configure(function () {

// set up the REST API handler methods are defined in api.js
var api = require('./controller/api.js');'/dogtag',;
app.get('/dogtag/near/:lon/:lat/:dist?', api.near);
app.get('/dogtag', api.list);

//  And start the app on that interface (and port).
app.listen(port, ipaddr, function() {
   console.log('%s: Dogtag server started on %s:%d ...', Date( ),
               ipaddr, port);

As described earlier, I need to tell node that I’m going to use express and mongoose in my application. One line 3, I simply create the HTTP server. On lines 6-9, I use mongoose to connect to the database. On lines 18-23, I configure URL routing to the controller api’s from the previous example. Note how I use colons to express parameters on the URL and then bind them to a given api. Finally, I tell the server to listen on a certain port and host spit out a start message if everything went successful.

So that’s really all there is to create the necessary middleware to support our DogTag application. It takes in JSON data from the emitters to store in MongoDB and then uses the Express framework to create a router to respond to requests for finding dogs whether by name or through geospatial searching. In the next part I’ll explore how we can use Sencha Touch to create a mobile application that will help a user locate their dog. For a little preview of that application, you can go here to experiment with it here.