Just as the Japanese, Spanish and French languages are uniquely different, programming languages also have their variations, some more popular and easier to use than others. With the recent introduction of some new ones, there is a 'war' of modern day languages. What's easier and faster to use is not always the best option.

The graphic includes stats like:

• Usability ratings
• Popularity in the TIOBE index
• How much it's discussed (from the IEEE Spectrum, IRC)
• The number of open job postings
• Average run time/lines of code

Check out the full post for more interesting data.

The results are pretty interesting, and it clearly shows that a small number of ISPs are definitely doing something right, which is causing many consumers to vote with their dollars in those ISPs favor. As usual the information is shown in graph form, to filter down the data to just the large providers I've set a minimum at 100,000 domains, leaving me with just 122 ISPs. The image [below] shows the break-down of the Top 25.

He's created a pie graph that breaks down the ISP list with GoDaddy once again coming in top of the list and The Planet coming in second. The numbers behind the graph are also included with other things like IP, country, region and city for each. He also mentions other major breakdowns like the top ranking IP addresses and the total number of around 80,000 IPs that have over 100 domains resolving to them.

I am making available two additional geographic chats that breakdown the domain distribution by top world cities. The first chart a preview of which can been below (click to see full, browse-able/zoomable version) shows the Top 150 cities, by domain distribution. These cities represent a total 91.3% of some 102 million domains that could be resolved to a city level.

The top ranking city falls in the US in Scottsdale, Arizona (because of the large domain provider GoDaddy being based there) with the second place spot going to San Francisco, California. He's created both a interactive map you can use to see the numbers for different parts of the world and a concentration view of the same results making it a bit easier to digest.

The first step of the process has been resolving all of these domains, which is now complete. The next step is fetching the server information, which began, but will take some time to finish. However, even from the domain revolving data there is a lot of useful data to be gleamed, which is what I am now publishing. My first focus was on the world-wide distribution on these TLDs, which at least for me held a few surprises.

He includes a few graphs of the results he's found showing things like:

• The US has the most domains hosted followed with less than half by Germany
• The overwhelming majority of the PHP domains are in the .com area
• In the US, the state with the highest number of PHP-powered domains was Arizona with Clifornia coming in second

If you'd like something more interactive, he's also come up with a clickable world map of the results for you to click around on.

Recently I installed a Ruby gem called buildhawk which allows to measure and display the build times of Rake driven builds. As I like the idea behind this tool a lot but mostly use Phing for build orchestration, it was time to explore the possibility to interconnect them both. In this blog post I'll show an implementation of an apposite Phing Logger gathering the buildhawk compatible build times via git note(s) and how to put the interplay between those two tools to work.

He includes the script you'll need to get his example set up - a new logger for Phing that works directly with Buildhawk and stores the information directly into a git note. He includes an example of running the phing build with it enabled and some of the results as exported as an HTML document.

Since I'm using WordPress.com Stats, I would like to use the rankings generated by this service or plugin. Searching Google, I found some widget called "WordPress.com Stats: Top Posts Widget" which works out of the box (if like to use a widget). In my case I have a custom sidebar with different custom sections using custom code. The following example explains how-to use that code on your website.

WordPress, by default, doesn't track any statistic information about the posts on your site, so you'll need something like the WordPress Stats plugin to get that part working. Once that's there, you can use his code to pull out the posts from the last few days (configurable) and show the most popular of the list.

We all know that Joomla is a tremendously popular CMS. In the past several attempts have been made to estimate the number of websites using Joomla. While these attempts were worthy contributions to the discussion, all of them were using their own methods and therefore had their own shortcomings. Several of the earlier attempts will be discussed and a new method for estimating the number of websites that use Joomla will be presented.

They look at the methods used by previous studies and how their method is different using this "new method". They've broken it down by number of sites, then number of domains, then total number of active domains based on publicly available statistics from other groups. In the end, out of the huge number of sites available on the web today, they came up with the number of around 1.5 to 2 million of them to be running Joomla.

As for any Open-Source community, it's not easy to find metrics that tell you what people use and how they use it. You can measure the number of tickets for a specific feature, count the number of people asking for help on Propel or Doctrine. But for the Propel vs Doctrine question, we have two more reliable metrics.

As is shown in this graph of the total Jobeet traffic in 2009, Doctrine is winning by a long shot. That's not to say that you can't still use Propel is that's what you and your application are using, this is just showing the overall popularity of each of the ORMs.

This is about twice as much as it was when I blogged about the 59 tuning screws for mysqlnd. While the basics have not not changed and the API calls for accessing the data remained the same (see previous posting) the new figures have never been described before.

Each of the items on the list is described and some include some sample use cases. Here's just a few:

• packets_sent, packets_received
• bytes_received_eof_packets, packets_received_eof
• bytes_received_rset_field_meta_packet, packets_received_rset_field_metabytes_received_change_user_packet, packets_received_change_user
• result_set_queries
• slow_queries
• flushed_normal_sets, flushed_ps_sets
• rows_fetched_from_client_ps_cursor
• connect_success, connect_failure
• in_middle_of_command_close
• command_buffer_too_small

• Since PHP 3.0.18 (released October 2000) (no, php.net doesn't keep release records before that for some reason) 60 PHP releases have been made.
• There have only been 2 releases in 2009 so far
• The 89th, 121st, 122nd, 194th, 228th, 241st and the 349th day of the year have had 2 releases each
• The 18th week of the year is most likely to have an release, whole 8 releases have been made in that week!
• 26 PHP releases have been on Thursdays

He also includes a snippet of code that can be used to pull together some of these stats yourself (with only a few errors thrown).