Speeding up Database Access with mod_perl

Continuing the discussion of mod_perl, Mr. Lerner tells us about the DBI specification and the Apache::DBI module.
How Fast is it?

Now that we have our test program, how can we actually test it? I wrote a short Perl program using Benchmark.pm, in Listing 3. The timethese function is imported by Benchmark.pm, which we bring in at the beginning of the program. We also bring in LWP::Simple, part of the “Library for WWW access in Perl” that makes it a snap to write a small web client. How simple? Well, the following one-liner returns the HTML contents at http://www.linuxjournal.com/:

perl -e 'use LWP::Simple;
print get "http://www.linuxjournal.com";'

Perl does not format the output for you. That's the difference between a web browser and a web client; the former is meant to retrieve information for humans, while the latter is meant to retrieve information for programs. In this particular case, we just want to simulate 100 retrievals of each of our programs via the web. Any timing differences will thus be due to the program on the server side—which, since they are identical, means that the differences will be due to mod_perl and Apache::DBI.

How much faster is the Apache::DBI version than its CGI counterpart? Here are the results I got running time-db.pl:

[1086] ~% ./time-db.pl
Benchmark: timing 100 iterations ...
Apache::DBI: 24 secs (1.77 usr 0.67 sys = 2.44 cpu)
Plain CGI: 394 secs (1.10 usr 0.61 sys = 1.71 cpu)

That's quite a difference. When I first ran this benchmark, I was convinced that the plain CGI program had somehow gotten stuck. Alas, that was not the case; the overhead associated with CGI was simply too great.

Here is a second run of the same benchmark, just for comparison.

[1099] ~% ./time-db.pl
Benchmark: timing 100 iterations ...
Apache::DBI: 28 secs (1.89 usr 0.61 sys = 2.50 cpu)
Plain CGI: 355 secs (1.15 usr 0.62 sys = 1.77 cpu)

Yes, it looks like CGI is indeed much slower. By the way, you can see that Apache::DBI used more CPU time than plain CGI—which means that the time was spent forking the new Perl process, rather than performing our program's computations.

What if we take out the Apache::DBI directive in srm.conf and restart the server? That would give us an indication of how much overhead was being used opening the database connection. As you can see, things do indeed slow down—although admittedly not by a huge amount:

[1104] ~% ./time-db.pl
Benchmark: timing 100 iterations ...
Apache::DBI: 34 secs (1.97 usr 0.63 sys = 2.60 cpu)
Plain CGI: 460 secs (1.19 usr 0.60 sys = 1.79 cpu)

The moral, then, seems to be that moving from CGI to mod_perl gives a huge performance boost, and that moving from DBI to Apache::DBI gives a moderate performance boost. The more database accesses your web applications do, the more useful these technologies will probably be in your work. Perl has always been known as a useful language, but rarely as one that can help you write fast software. Now, with mod_perl and Apache::DBI, you can write web applications quickly, and watch them run quickly as well.

Resources

Reuven M. Lerner is an Internet and Web consultant living in Haifa, Israel, who has been using the Web since early 1993. In his spare time, he cooks, reads and volunteers with educational projects in his community. You can reach him at reuven@netvision.net.il.

______________________

White Paper
Fabric-Based Computing Enables Optimized Hyperscale Data Centers

Today’s modular x86 servers are compute-centric, designed as a least common denominator to support a wide range of IT workloads. Those generic, virtualized IT workloads have much different resource optimization requirements than hyperscale and cloud applications. They have resulted in a “one size fits all” enterprise IT architecture that is not optimized for a specific set of IT workloads, and especially not emerging hyperscale workloads, such as web applications, big data, and object storage. In this report, you will learn how shifting the focus from traditional compute-centric IT architectures to an innovative disaggregated fabric-based architecture can optimize and scale your data center.

Learn More

Sponsored by AMD

White Paper
Red Hat White Paper: Using an Open Source Framework to Catch the Bad Guy

Built-in forensics, incident response, and security with Red Hat Enterprise Linux 6

Every security policy provides guidance and requirements for ensuring adequate protection of information and data, as well as high-level technical and administrative security requirements for a system in a given environment. Traditionally, providing security for a system focuses on the confidentiality of the information on it. However, protecting the data integrity and system and data availability is just as important. For example, when processing United States intelligence information, there are three attributes that require protection: confidentiality, integrity, and availability.

Learn more about catching the bad guy in this free white paper.

Learn More

Sponsored by DLT Solutions