In this section, we will learn which server software we require to support the Geolocation API, which server software we require to support the application we will build in this book, and how to set up your server software to support the application.
In this book, we're going to build a simple application that creates a KML (Keyhole Markup Language) feed of the user's movements that can be imported into mapping applications such as Google Maps and Google Earth. In order to do this, we need to capture the user's geolocation coordinates, save them into a database, and then export the saved coordinates into a data feed.
There are four core actions that will need to be supported:
Displaying the page containing the Geolocation API code
Capturing the user's location
Storing the user's location
Displaying the user's history of locations as a KML feed
For the purposes of this book, we will support them in turn with:
Apache Web Server
A MySQL database and the PHP scripting language
A simple feed script written in PHP
Note that you could use any web browser, any web scripting language, and virtually any database, to perform these tasks. I hope that the examples here are generalized enough to allow you to translate them into the languages and server software of your choice. For example, if PHP isn't to your taste, these examples should be relatively easy to translate into Ruby or Python.
We will assume that you are running a recent copy of Apache Web Server, configured to allow scripting using PHP 5.3 or later.
Create the following files in a new location on your web server:
index.php: The main page that retrieves the user's location
feed.php: The script that will echo the KML feed
lib.php: A common file to handle the database connection and any other configuration
live.php: A version of the main page that continuously retrieves the user's location
livepath.php: A version of the main page that continuously retrieves the user's location and displays his/her route as a path
Create a new MySQL database table (and, if you like, a new database to house it in) for this example. This will store our retrieved geolocation coordinates, with a timestamp and an identifier for the user.
There are a number of different ways we could store the location information. Geolocation coordinates are returned as longitude and latitude; an angle on the surface of the Earth east and west of the Prime Meridian, and an angle north and south of the Equator, respectively. Recall the example data in the Understanding the geolocation API (Simple) recipe, the angles were returned to 14 decimal places. The more accurately we can store these numbers, the more accurately we can retrieve the user's location.
For the purposes of this tutorial, we are going to store our coordinates as a set of floating point numbers. This is because we're not performing any comparisons on the geographic data; we're simply storing and retrieving it.
All we need, then, is decimal point latitudes and longitudes with the required level of accuracy, as well as an integer identifier for the user, and another for the timestamp. As we'll be searching by user and timestamp, it's a good idea to maintain an index for each of these fields.
We'll call our database table
-- Table structure for table 'points' -- CREATE TABLE IF NOT EXISTS 'points' ( 'id' int(11) NOT NULL AUTO_INCREMENT COMMENT 'Our primary index field', 'latitude' float NOT NULL COMMENT 'Our latitude coordinate', 'longitude' float NOT NULL COMMENT 'Our longitude coordinate', 'user_id' int(11) NOT NULL COMMENT 'The unique ID of the user', 'time' int(11) NOT NULL COMMENT 'The UNIX timestamp of the time when the point was recorded', PRIMARY KEY ('id'), KEY 'user_id' ('user_id'), KEY 'time' ('time') ) ENGINE=InnoDB;
Downloading the example code
You can download the example code files for all Packt books you have purchased from your account at http://www.PacktPub.com. If you purchased this book elsewhere, you can visit http://www.PacktPub.com/support and register to have the files e-mailed directly to you.
Note that I've also included a unique identifier for each row in the database, for ease of access later.
One of the problems with geographic data is that it's very easy to store a huge amount of it, which can cause databases to slow down if you're not careful—particularly, if you're doing a lot of proximity queries, for example, to discover stored geographic points within a certain radius of a location. The mathematics behind this functionality, while not massively complicated, can become expensive in aggregate.
MySQL has a spatial support extension, which allows you to store, retrieve, and compare extensions based on an optimized geographic engine. This uses a standard set from the OpenGIS project to store sets of geographic data. It's often installed by default, and is worth getting to know for more sophisticated geo-aware applications.