Asynchronous Synchrony

Or, when is performing request-response communication over an asynchronous channel a good idea? When is it not?

If system A needs to ask system B a question and get some data as a response it could do so in a variety of ways, some awful, others less so.

  • Take a periodic database extract, transform and load
  • Query the other system’s database on the fly
  • Use RMI / Corba binary interop
  • Send a message and wait for a reply
  • Get some XML from a URL via HTTP

This list is not exhaustive, but represents a reasonable spread of mechanisms. Lets narrow it down to the two least awful.

First, any integration involving a database is right out. Coupling application databases together is extremely awful. Binary integration is bad for the same reason. These integration mechanisms are fragile and make the job of releasing both applications much harder, as well as making it hard to know if a change has broken the integration.

Moving on to the two remaining choices. Using messaging can work well if the requesting system can tolerate a large variation in latency and/or you need to scale by having multiple processes sending and receiving the messages. It is also very handy if you need to cope with one of the systems failing periodically as the messaging infrastructure can hold onto the messages when the systems are unavailable. The request-response semantics can be achieved by passing a correlation id around to track conversational state. The implementation is more complicated because you don’t really want the requestor sitting blocked waiting for a response that could take an unbounded amount of time to return (eg. if the responder is busy or down).

If the complexity of a message based approach is not justified then a simple web service (that is, XML and HTTP GET requests, no SOAP or other pointless nonsense) can work very well. As an added benefit, if some thought is put into how the URLs are designed it is a relatively simple matter to insert an HTTP proxy cache (such as Squid) into the flow. Sensible use of cache directives in the HTTP headers can allow even moderately fast changing data to be cached effectively without going stale. All without having to complexify the code that returns the XML.

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JDom, XPath and the saga of the invisible namespace

JDOM’s XPath implementation has (in my opinion)  big glaring bug with respect to its handling of the default namespace. That’s a namespace that looks a bit like this in the XML:

<?xml version="1.0" encoding="utf-8"?>
<myRootElement xmlns="https://darrenhobbs.com/some/namespace/2008/10/15"
               xmlns:foo="https://darrenhobbs.com/some/foo/namespace">
 <myChildElement>
  ... some stuff ...
 </myChildElement>
 <foo:aFooElement>
  ... some foo stuff ...
 </foo:aFooElement>
</myRootElement>

Note the ‘xmlns=…’, denoting the default namespace. As opposed to ‘xmlns:foo=’ which denotes the ‘foo’ namespace.

Let’s say I wanted to run an XPath query for: ‘//myChildElement’:

XPath xPath = XPath.newInstance("//myChildElement");
xPath.addNamespace(Namespace.getNamespace("https://darrenhobbs.com/some/namespace/2008/10/15"));
List nodes = xPath.selectNodes(aDocument);

This will never work. XPath does not play nicely with default namespaces. The solution is to register the same namespace URI against a made-up prefix and change the XPath like so:

XPath xPath = XPath.newInstance("//dh:myChildElement");
xPath.addNamespace("dh", "https://darrenhobbs.com/some/namespace/2008/10/15");

The query should then work.  This is not a new problem.

Chrome / V8 Javascript performance

According to http://code.google.com/apis/v8/run.html Chrome’s javascript engine is 10 times faster than Firefox 3.0. 1152 (Chrome) vs 110 (Firefox). Although they both take about 8 seconds to run on my machine. This is the danger of benchmarks. You can optimise for any benchmark but the real trick is in choosing which benchmarks to optimise for. And you ignore ‘user time’ at your peril. As a browsing human, I don’t really care how many milliseconds New and Improved Browser shaves off Brand X’s benchmarks. I care about how long I’m waiting for the hourglass to disappear or the spinny thing to stop spinning.

As a developer, of course I went off and found the webkit benchmark. Results below, in all their ugly unformatted glory:

TEST                   COMPARISON            FROM                 TO             DETAILS

=============================================================================

** TOTAL **:           2.28x as fast     5387.6ms +/- 0.6%   2358.2ms +/- 0.2%     significant

=============================================================================

  3d:                  3.69x as fast      621.6ms +/- 1.1%    168.6ms +/- 4.0%     significant
    cube:              5.35x as fast      229.0ms +/- 1.3%     42.8ms +/- 11.5%     significant
    morph:             2.88x as fast      205.4ms +/- 1.4%     71.2ms +/- 5.7%     significant
    raytrace:          3.43x as fast      187.2ms +/- 2.1%     54.6ms +/- 3.1%     significant

  access:              6.93x as fast      885.6ms +/- 0.9%    127.8ms +/- 4.3%     significant
    binary-trees:      13.7x as fast      112.6ms +/- 0.6%      8.2ms +/- 12.7%     significant
    fannkuch:          8.92x as fast      401.2ms +/- 0.1%     45.0ms +/- 2.0%     significant
    nbody:             4.86x as fast      210.8ms +/- 2.7%     43.4ms +/- 10.0%     significant
    nsieve:            5.16x as fast      161.0ms +/- 1.7%     31.2ms +/- 4.4%     significant

  bitops:              8.42x as fast      796.8ms +/- 0.2%     94.6ms +/- 5.3%     significant
    3bit-bits-in-byte: 26.6x as fast      154.2ms +/- 0.4%      5.8ms +/- 17.9%     significant
    bits-in-byte:      17.8x as fast      217.2ms +/- 0.5%     12.2ms +/- 8.5%     significant
    bitwise-and:       5.51x as fast      178.6ms +/- 0.9%     32.4ms +/- 4.4%     significant
    nsieve-bits:       5.58x as fast      246.8ms +/- 0.2%     44.2ms +/- 7.0%     significant

  controlflow:         28.3x as fast      113.2ms +/- 0.5%      4.0ms +/- 22.0%     significant
    recursive:         28.3x as fast      113.2ms +/- 0.5%      4.0ms +/- 22.0%     significant

  crypto:              5.29x as fast      405.0ms +/- 0.3%     76.6ms +/- 4.8%     significant
    aes:               4.97x as fast      153.2ms +/- 0.7%     30.8ms +/- 6.0%     significant
    md5:               5.27x as fast      126.6ms +/- 1.1%     24.0ms +/- 8.2%     significant
    sha1:              5.74x as fast      125.2ms +/- 0.8%     21.8ms +/- 2.6%     significant

  date:                1.07x as fast      416.2ms +/- 1.1%    389.6ms +/- 1.6%     significant
    format-tofte:      1.23x as fast      261.4ms +/- 1.3%    212.2ms +/- 2.0%     significant
    format-xparb:      *1.15x as slow*    154.8ms +/- 1.0%    177.4ms +/- 1.8%     significant

  math:                3.79x as fast      619.6ms +/- 1.1%    163.4ms +/- 5.6%     significant
    cordic:            3.24x as fast      294.2ms +/- 0.9%     90.8ms +/- 6.2%     significant
    partial-sums:      3.39x as fast      177.8ms +/- 2.9%     52.4ms +/- 11.3%     significant
    spectral-norm:     7.31x as fast      147.6ms +/- 0.5%     20.2ms +/- 2.8%     significant

  regexp:              *1.88x as slow*    305.8ms +/- 10.1%    573.6ms +/- 0.5%     significant
    dna:               *1.88x as slow*    305.8ms +/- 10.1%    573.6ms +/- 0.5%     significant

  string:              1.61x as fast     1223.8ms +/- 3.3%    760.0ms +/- 1.4%     significant
    base64:            1.81x as fast      154.8ms +/- 2.2%     85.6ms +/- 9.5%     significant
    fasta:             3.84x as fast      306.0ms +/- 2.1%     79.6ms +/- 2.6%     significant
    tagcloud:          -                  216.0ms +/- 3.5%    209.0ms +/- 1.5%
    unpack-code:       1.36x as fast      378.0ms +/- 10.1%    278.2ms +/- 2.3%     significant
    validate-input:    1.57x as fast      169.0ms +/- 2.9%    107.6ms +/- 2.4%     significant

That’s looking a bit more believable. On average Chrome/V8 seems to be twice as fast as Firefox/Spidermonkey, with results varying from 30 times faster to almost 2 times slower. It will be interesting to see how Tracemonkey compares, as it seems to be about 1.8 times faster than Spidermonkey.

Javascript is the next Ruby

Ruby is so, like, web 2.0. More than two graduating classes have, er, graduated since Ruby became the next big thing. That makes it nearly your grandad’s social networking application programming language, in these ‘internet speed’ times we live in. This would be the same community that has just realised that network connections that survive beyond a single request are actually quite useful. But that’s my XMPP / HTTP rant, not this one.

I’ve been of the opinion that Javascript is a much underrated and very powerful language that was only missing a key ingredient to become a ‘real’ language and escape the browser.  The ingredient being the backing of a big enough commercial entity. Popular programming languages generally have one of two things: either a charismatic and beneficent despot or a powerful company behind them.  Examples? Naturally.

  • Perl: Larry Wall
  • Python: Guido van Rossum
  • Ruby: Yukihiro Matsumoto
  • Java: Sun
  • .Net: Microsoft

And now…

  • Javascript: Google

Google are (at the time of writing) on the cusp of releasing their web browser, Chrome. While Chrome has many interesting and cool features, the most interesting is that they’ve written their own Javascript virtual machine, called V8. And the people they’ve got writing it are not short of experience in the realm of VM’s. Lars Bak has worked on Self, Strongtalk and the Hotspot Java VM and was (last I heard) working on a Smalltalk VM for embedded devices called OOVM before the company got bought by Esmertec.

Javascript (strictly speaking ECMAscript 4th edition) also seems to pass Steve’s NBL test and now it has a VM with large commercial organisation backing it, which was the thing it most obviously needed, in my view, to get traction beyond the browser.

Final piece of evidence? This year JAOO has a Javascript track. It’s time.