yousry.de/blog

Java applets were originally introduced to provide interactive features for web applications (Wikipedia). With javascript based libraries (jquery, yui), proprietary plugins (flash, silverlight or javaFX) and the oncoming HTML5 this intended purpose disappeared, but java applets remain useful for following reasons:

• Scala/Java is type safe: You can find errors early.
• You can use the same language like you used for your web application.
• The Implementation is browser independent.

Example: Distributed Computation of Perfect Numbers

Definition: Perfect Number (Wikipedia)

Testing numbers for perfection is a simple but process-time consuming task. It isn’t complicated to distribute the calculation on several computers.  You can easily think of other domains where similar types of computations could be useful.

Application Overview

Instead of a javascript a java applet is used to factorize numbers. With the typical features of the lift framework, the application looks as follows:

PerfectNumbers Overview

Details: Server -> Client Communication

The snippet: You can deploy your java/scala applet with your web application.

You can invoke your applet method like a javascript function:

// OnLoad(JsRaw("findFactors('"+ c.toJson +"');"))
   OnLoad(JsRaw(c.toJsCall))

Update your case class:

case class JobPackage(ticket: Int,
                   start: Long,
                   end: Long,
                   master: Long) {
  import net.liftweb.json._
  import net.liftweb.json.JsonDSL._
  def toJson = {
    val json = ("ticket" -> ticket) ~
      ("start" -> start) ~
      ("end"-> end) ~
      ("master" -> master)

    compact(JsonAST.render(json))
  }

  def toJsCall = "$('#some-div').html($('#clientEngine').get(0).doCalc(" + ticket
  + ", " + start + ", "+ end +", " + master +"));"

Client -> Server Communication

Add your ajax call to your applet:

JSONObject serverPackage = new JSONObject();
...
private void sendResult() {
		try {
			String sps = serverPackage.toString();
			getAppletContext().showDocument(
					new URL("javascript:replyResult('replyResult', '" + sps + "')"));
		} catch (MalformedURLException e) {
			errorText = "Error: " + e.getMessage();
		}
	}

and dispatch the result:

  def PMCall(s: String) = { 

    logger.info("PMCall "  + s)

    val cResJs = net.liftweb.json.JsonParser.parse(s)
    val ticket  = (cResJs \\ "ticket").extract[Int]

    // With 2.8: facs.extract[List[Long]]
    val facs = for{
      JInt(fac) <- cResJs \\ "factors"
    } yield fac.extract[Long]

    PerfectNumberMaster ! PerfectNumberMaster.CalcDone(ticket , facs)
    Empty
  }

Download and run the example

The Sourcecode is available here.
Type: mvn jetty:run and open the url http://localhost:8080

With the 73th version of the Kungle trend engine it is now possible to track a meaningful trend again.

It was difficult to rebuild a functional trend prediction after the decision to remove the search engine results from my calculations.

Cause of the decision:

The search terms got more and more insignificant. For Example on Sep. 29 (The Tsunami Day)  the highest ranked search phrase was “pink toed tarantula”.  Other examples were “who is mysterion” or “out of memory at line 130″ !

The Trend Analysis is now extremely fast. The response time is about  30 minutes after an occurrence. In contrary, searchengine results are delayed up to four hours!

I’m now using microblogs, blogs, and newsfeeds as datasource.

The Trend Score is calculated by following factors:

• Time of publication
• Frequency of occurrence
• Subject significance (by Dictionary)
• Subject insignificance (by Dictionary)
• Registration Date
• Publisher significance

Votes:

I have added a voting mechanism to compare the trend results with my readers opinions. To offer an incentive I have added a Trend bonus for every vote.

Next Steps:

Dependent on the success of Kungle.de and the related earnings:

1. Switch to bigger hardware.
2. Improve the topic identification.
3. Deep text analysis.
4. Global Impact calculation

Improved user interaction:

Kungle.de is a Scala/Lift Project based on HTML and Ajax.  Next Steps would require to build Restful Web Service and a Rich Internet Application. for a better user experience.

Null Pointer Exceptions (NPEs) are most common runtime errors in Java (more than 500.000 results in Google). Most Java libraries are interspersed with methods returning null if the computation could not be finished. Invoking method calls on null raises Null Pointer Exceptions.

The best practice in Java to avoid such errors is a test against null.

if(aObject == null) {...

or pass the null test to another function.

For example, Instead of writing:

if(aResultString.equals(“literal”)) {
...

you write:

if(“literal”.equals(aResultString)) {
...

More than eleven years ago (beginning with the java era) a data type existed, avoiding the NPE problem:

data  Maybe a =  Nothing | Just a deriving (Eq, Ord, Read, Show)

A Haskell one-liner ported to Java could have prevented thousands of errors.

Why?

You cannot forget to test against None (unlike the null check) because this would raise a compile time error. Based on Haskells Maybe-Type, Scala defines the Some and None Type with:

final case class Some[+A](x: A) extends Option[A]
...

and

case object None extends Option[Nothing]
...

To test an Option Type against None you write:

val result =  a getOrElse b..

If a is Some(_) than result is _. If result is None, than result is b. The value of result is therefore always defined!

Runtime Errors on my News Page Kungle.de so far

To Keep it short:
None

Scala is a modern, statically typed language. Its bytecode is Java-VM compatible and the design is influenced by languages like Haskell or Erlang.

Lift is a Web Framework written in Scala. Lift applications follow the View First pattern. The View First pattern defines a complete separation of presentation and logic.

Although with long experience in business, writing my first web application in Scala/Lift wasn’t an easy task. The combination of functional and object-oriented programming paradigms enables a wide range of new possibilities to compose your source code. It may take a while to understand wiki examples or library documentation, but writing your application in Scala has crucial advantages.

• Less code:
  The elegant Type System and the modern Control Flow Structures reduce your code size dramatically.
• A manageable toolchain:
  Every new tool in your development environment means a new dependency in your application. Every update can cause trouble. To configure these tools you often implant new plugins in your ide which in turn complicates the build process. Typically you stop updating your development environment at a certain project stage.
  In contrary, you can build your Lift applications with vi. In less than 100 lines of code you can create a complete web application!

The result is a fast and flexible development cycle.

You can visit my site at kungle.de. It is an application to identify relevant news. The news rating is statistically calculated by an adaptive network and updated every 30 minutes.

References:
Scala homepage: http://www.scala-lang.org/
Lift homepage: http://liftweb.net/
Introduction “View First Pattern”: http://wiki.liftweb.net/index.php/Lift_View_First