Build a RESTful Webservice in less than 5 minutes

There are quite some tutorials around about building and exposing a RESTful Webservice, but some of them are outdated and make you wade through complex dependencies and tinkering with deployment descriptors and web.xml files. But using RESTeasy, the JBoss implementation that is fully compliant with the JAX-RS 2.0 JCP specification, and Eclipse you can build a simple webservice (“hello world”) with less than 10 lines of sourceode with annotations and no web.xml used in a few minutes and run it on Wildfly.

Lets build a webservice that creates random numbers.

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Exploring a SQLite Database on Android

or “How to read SQLite DB from a desktop”

SQLite is the relational, embedded, ACID compliant database that comes with Android. Due to this fact it is certainly the most deployed DB engine on this planet. In case your application need to have CRUD features for local persisted data and the complexity level is beyond a simple text file, you have to consider it.

A challenge is to look into the (raw) DB from your desktop (if you dont want to build and integrate a DB viewer into your app). As Android apps store databases into their respective /data subfolder and if you don’t have a rooted phone, you cant look inside this folder.

I am not aware of any tool that can open a connection to the DB remotely, so the best way is to copy the DB file into the accessible SD card (or whatever the phone and its manufacturer considers as SD card, even the internal memory mounted as SD card), download it to your desktop and open it with a tool like the SQLite DB Browser.

Let’s put some sourcecode here as reference

Create a simple demo DB

No bells and whistles, no helper classes, etc. just the most simple way to create DB and a table.

    private void createDB() {
        SQLiteDatabase sampleDB = this.openOrCreateDatabase("MYDEMODB", MODE_PRIVATE, null);
        sampleDB.execSQL("INSERT INTO MYTABLE Values ('Smith','John','CEO');");
        sampleDB.execSQL("INSERT INTO MYTABLE Values ('Thomson','Allan','CTO');");

Copy the DB to your SD card

    private void exportDB() {
        File mySd = Environment.getExternalStorageDirectory();
        File myData = Environment.getDataDirectory();

        FileChannel src = null;
        FileChannel des = null;
        String currentDBPath = "/data/" + getApplicationContext().getPackageName() + "/databases/MYDEMODB";
        String exportDBPath = "MYDEMODB";

        File currentDB = new File(myData, currentDBPath);
        File backupDB = new File(mySd, exportDBPath);
        try {
            src = new FileInputStream(currentDB).getChannel();
            des = new FileOutputStream(backupDB).getChannel();
            des.transferFrom(src, 0, src.size());
        } catch (IOException e) {

After download to your local drive you can use the SQLite Browser to open the file. Very useful data debugging or for apps that collect data and you can’t implement an upload of the data to a server via the internet connection.

SQLite DB Browser

SQLite DB Browser (Structure View)


SQLite DB Browser

SQLite DB Browser (Data View)

D3.js Getting started (again..)

The same questions as some years back: How to get started with it ?

The learning curve for beginners is certainly a bit steep if you dont have a basic background in at least HTML, CSS and JavaScript, in this case you rather go for a visualization tool like Tableau if you look for fast results.
The good news: There is plenty of material out there about D3, books, websites, tutorials. I purchased a couple of books from Packt Books and O’Reilly as PDF version, I think they have the most books, though most of them based on earlier D3 versions.

Packt Books

Packt Books

O'Reilly Books

O’Reilly Books

I wont recommend a specific one, most follow the same principles, a short intro to the DOM, explain the D3 basics followed by more or less complex samples. As with any other technology or programming language you learn most hands-on, there so many examples and good tutorials available. I never attempted to understand everything, understand the concepts, dissect existing visualizations and get creative !

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d3.js – From tree to cluster and radial projection

Some visualizations seem to be more sophisticated (to implement) than they actual are, specifically the radial projections. Starting from a tree representation with nodes and links it is quite easy to get to the radial version.
Remark: Of course there are more challenging radial diagrams like the bundle, but lets get started with something simple first !

“Standard” Tree
(I added few more nodes to make the visual difference more obvious)

Tree Visualization

We change 1 line of our sourcecode (see previous tutorial for complete code):

var tree = d3.layout.tree().size([300,300]);
var tree = d3.layout.cluster().size([300,300]);

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d3.js – Most simple stack layout with bars

In order to understand the physics of various visualizations I walk through the samples and gists I find, dissect them and strip them down to the bare minimum. From there I explore my own variations. I took Mike’s sample for a stacked bar chart and changed it to chart reading from a matrix instead of the csv file.

Stacked Bar Chart

The matrix object

            var matrix = [
                [ 1,  5871, 8916, 2868],
                [ 2, 10048, 2060, 6171],
                [ 3, 16145, 8090, 8045],
                [ 4,   990,  940, 6907],
                [ 5,   450,  430, 5000]

The stack layout expects an object with an array of objects, each member of the array represents the values of one value group (eg. “all dark blue values”), and each object contains x and y value. It will process theis array amnd a y0 value (the offset to the baseline).
You can see this if you run the below code with the console.log output.


<!DOCTYPE html>
        <title>Simple Stack</title>
        <script type="text/javascript" src="libnew/d3.v2.min.js"></script>
            svg {
                border: solid 1px #ccc;
                font: 10px sans-serif;
                shape-rendering: crispEdges;

        <div id="viz"></div>

        <script type="text/javascript">

            var w = 960,
            h = 500

            // create canvas
            var svg ="#viz").append("svg:svg")
            .attr("class", "chart")
            .attr("width", w)
            .attr("height", h )
            .attr("transform", "translate(10,470)");

            x = d3.scale.ordinal().rangeRoundBands([0, w-50])
            y = d3.scale.linear().range([0, h-50])
            z = d3.scale.ordinal().range(["darkblue", "blue", "lightblue"])

            console.log("RAW MATRIX---------------------------");
	    // 4 columns: ID,c1,c2,c3
            var matrix = [
                [ 1,  5871, 8916, 2868],
                [ 2, 10048, 2060, 6171],
                [ 3, 16145, 8090, 8045],
                [ 4,   990,  940, 6907],
                [ 5,   450,  430, 5000]

            var remapped =["c1","c2","c3"].map(function(dat,i){
                    return {x: ii, y: d[i+1] };

            var stacked = d3.layout.stack()(remapped)

            x.domain(stacked[0].map(function(d) { return d.x; }));
            y.domain([0, d3.max(stacked[stacked.length - 1], function(d) { return d.y0 + d.y; })]);

            // show the domains of the scales
            console.log("x.domain(): " + x.domain())
            console.log("y.domain(): " + y.domain())

            // Add a group for each column.
            var valgroup = svg.selectAll("g.valgroup")
            .attr("class", "valgroup")
            .style("fill", function(d, i) { return z(i); })
            .style("stroke", function(d, i) { return d3.rgb(z(i)).darker(); });

            // Add a rect for each date.
            var rect = valgroup.selectAll("rect")
            .data(function(d){return d;})
            .attr("x", function(d) { return x(d.x); })
            .attr("y", function(d) { return -y(d.y0) - y(d.y); })
            .attr("height", function(d) { return y(d.y); })
            .attr("width", x.rangeBand());


My gist:

d3.js Playing with Selections

One should have a good understanding of selections, it is worth playing with a sandbox and explore the various options you have. I adopted the tutorial from Mike here.

Lets assume we have a simple HTML table:

<!DOCTYPE html>
        <script type="text/javascript" src="lib/d3.v2.min.js"></script>
                <tr><td>  A</td><td>  B</td><td>  C</td><td>  D</td></tr>
                <tr><td>  0</td><td>  1</td><td>  2</td><td>  3</td></tr>
                <tr><td>  4</td><td>  5</td><td>  6</td><td>  7</td></tr>
                <tr><td>  8</td><td>  9</td><td> 10</td><td> 11</td></tr>
                <tr><td> 12</td><td> 13</td><td> 14</td><td> 15</td></tr>
        <script type="text/javascript">
           //nothing yet

HTML table

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d3.js with Dynamic Data II

A slightly adopted version using SVG. A form to control radius of randomly drawn circles.

<!DOCTYPE html>
        <title>Hello, data!</title>
        <script type="text/javascript" src="lib/d3.js"></script>

        <form name="myform" onSubmit="return handleClick()">
            <input name="Submit"  type="submit" value="Radius" />
            <input type="text" id="myRadius"/>

        <div id="viz"></div>

        <script type="text/javascript">

            var mySVG ="#viz")
            .attr("width", 600)
            .attr("height", 400);

            function handleClick(event){
                return false;

            function draw(rad){
                .style("stroke", "black")
                .style("fill", "grey")
                .attr("r", rad)
                .attr("cx", Math.round(Math.random()*600))
                .attr("cy", Math.round(Math.random()*400))


SVG circles