An insight into sonar plugin development

In the recent months, I've been involved in developing a language plugin for sonar that displays different metrics for a specified language. I am writing this post as there is not much content available for this topic even when sonar is a widely popular tool.

Below are tips to avoid some of the common pitfalls in developing sonar:

• Read the official documentation carefully, even when there isn't much of it.
• Download the sources of all the open source plugins and try looking their code for proper understanding into plugin development.
• Do read books available on the topic in addition to the blogs for proper understanding.
• Use maven, this is a real lifesaver and focus on TDD while coding - as you cannot hope to debug the process otherwise.

If you've followed these steps diligently,  you'd have a basic understanding on the innards of sonar plugin development.
In very brief words, a sonar plugin comprises of a java based program that performs the heavy duty work of loading/populating the code metrics and a ruby based UI (embedded ruby pages(erb)) that helps in displaying of this data, in a nice manner and also uses view helpers to create eye-catching widgets that display these data. There is another provision for a complete rails based application to be created in place of this, but that's a different idea altogether.

In my case, I needed to Populate the data from a database , so in a class implementing Sensor interface, following method was present

  public void analyse(Project project, SensorContext sensorContext)
Inside this method, I can use Project object to read from project properties,etc as inputs to my process and SensorContext object as output in the form of  measures;

sensorContext.saveMeasure(new Measure(MyMetricAnalysisClass.MetricName, Double.valueOf(metricVal)));

One of the nice features of working with erb templates in the UI for widgets is that you can use a lot of helper methods to create slick effects with your data. One such example is a piechart:
<%= piechart( 'Field1 = '+var1.to_s+'; Field2 = '+var2.to_s+';'  , { :size => "500x200"}) -%>

One caveat present while transferring the data from server to views is that only text data works well, the information about using data structures is sketchy at best so we are left with using the data delimimted with ';' (See the first argument in piechart helper method above). Surprisingly, other data cause widgets to fail with no descriptive error messages. For larger data, it is more intuitive to use a GWT page instead of a widget as the users can focus more on the details provided in the page as opposed to the concise totals present on the widgets.
Hope this post helps the users developing plugins on this platform something to get started with.

Going to classes, the online way

Recently, there have been a lot of announcements regarding free online classrooms for instructor-led E-learning. I was a bit skeptical of it at first, but now am glad that I enrolled myself into it.

Some of the advantages that online courses offer over conventional courses:

• All the comforts of an online\distance learning course for free.
• Vibrant discussion forums that help erase doubts.
• High quality material: These courses are taught as-is in the real classes in top universities.
• Hands-on learning: The learner gets to create programs and solve practical problems related with the topic.
• Stay focused on a specific topic - working as a professional developer, it is natural to get stuck with the mundane aspects of programming and forget the big picture as there is the excitement into hacking into different topics without much time constraints, like in college. 

I am currently enrolled in two courses at coursera.org and one at edx.
My first course is a 10 week course about Big Data, which I had an inking that it would be related with hadoop and other high level aspects of it, but what surprised me was that the first three weeks of this course have passed and the instructor is tirelessly helping us understand the basics/theory of the importance of big data and its key challenges. This being an IIT post graduate level course, further lends credibility to its undivided concentration over the background aspects of  big data (and intelligently breaking it down to look, listen, learn, connect, predict, correct).
Another course that has just started is Programming in Scala by none other than its inventor itself, Martin Odensky. What is pleasant about the course is that right from day one, the course uses test driven development and sbt for building & submitting programming excercises.
I also have high hopes for the upcoming SAAS course offered by MIT that seems promising and offers me to create a cloud based solution after a long time.

These myriad courses do take up time, especially the after work hours, but is a better use to put my time rather than just browsing around. So, lot of efforts and headaches are induced into this process, but is worth a try - whether you are a student, a developer or a curious bystander who happens to have some of these type of subjects affecting them in one way or another.

Problem with as/400 jdbc driver

While iterating over the resultset obtained from an as/400 datasource today, I was constantly getting this error:

descriptor index not valid

Upon searching for this error, I found its solution that should better be shared with everyone.
The jdbc driver starts the columns from 1 instead of 0 index, so when calling some data from the ResultSet object, such as resultSet.getString(1), the column fetched is the first column, and not the second column as it seems.
It could be nice if the error message explained this problem in a non-cryptic manner. This problem is one of those nagging problems that repeat from time to time(as this api doesn't seem to conform to java conventions in this case).

Book Review: Hadoop: The Definitive Guide, Second Edition by Tom White

Anyone interested in big data management today has at least a passing familiarity with Hadoop, an open source map-reduce algorithm implementation. Here's my review of the second edition of one of the most comprehensive books on the topic.
As a longtime hadoop enthusiast, I already had read the first book, I was interested in finding out what this second edition has in store for the readers.

The book builds over its predecessor and apart from addition of Hive and Sqoop, a case study covering graph visualization in social networks has been added. The hadoop version has been updated, as a developer, I'd recommend latest stable release of hadoop as it is an active project. However, as Tom White is himself a committer in this project, various project insights are added along the way as in the original edition.

From the first time hadoop adopter's point of view too, this text is an easy to adapt and the learning curve of hadoop is lessened to a great extent.
The book starts by building the context, presenting the history and ecosystem of hadoop and gives its user a high level overview. The underpinings of hadoop, or the mapreduce algorithm and its implementation in hadoop is covered in the next few chapters. This contains practical aspects of running any hadoop application including HDFS file manipulation and map reduce operation in detail. An exhaustive list of mapreduce techniques alongwith their examples are then covered that come up in everyday development while using hadoop api to interface with big data.
Another highlight of this book is the comprehensiveness of running and deploying hadoop in various configurations. Also, closely knit data management tools in the hadoop ecosystem or its sub-projects such as pig, hive, hbase, zookeeper and sqoop have been covered.
This is followed by various case studies that make an interesting read. It was disheartening to see no major updates in the case studies compared to the previous edition .

From a person already having the original edition of this book, the second edition does not have much to cover, but for a person not having read any previous editions, this is a comprehensive book.
Note: This book has been provided to me for reviewing under the Oreilly Blogger Review Program.

VM management with Vagrant

Setting up a virtualized environment on your own machine is always a headache inducing and risky setup. However, with virtualbox, one can use the vms without changing the OS internals (such as in Xen). The chief disadvantage of using virtualbox directly is that the virtual machine quickly escalates to a huge scale, and if you are cloning/ distributing your virtual machine, it easily becomes a hassle involving both the VM and its virtual hard disk.

However, with Vagrant, one can quickly create, configure and delete virtual machines, similar to a professional cloud environment like Amazon.
According to their documentation; ' Vagrant gives you the tools to build unique development environments for each project once and then easily tear them down and rebuild them only when they’re needed so you can save time and frustration.'. The documentation starts with a 5 minute tutorial that demonstrates how easy it is to setup, connect and configure different VM instances.

The configuration is handled by a vargant file, which is a ruby DSL.For the GUI inclined people, Vagrant can also be configured by different provisioners like Puppet or Chef. Thus, developers and project managers can quickly configure and setup environments for different projects.

By easily enabling the developer to directly configure the VM, the development process can be streamlined, in principle with the DevOpts movement.