Showing posts with label software. Show all posts
Showing posts with label software. Show all posts

Monday, February 13, 2012

Debugging JavaScript

tl;dr: Firefox nightlies now ship with an experimental JavaScript debugger. It's not ready for end-users yet, but we are feverishly working on filling in the missing bits.

Debugging is always hard, especially when debugging other people's code. Adding a bunch of console.log() statements, becomes tedious after a while and that's assuming that you are familiar enough with the code in question to know where to place them. Tools like Firebug are a tremendous help in this case. Having the ability to pause the execution at any point or inspect variables and stack frames, provides valuable insights into the runtime behavior of a program.

Firebug depends on the traditional JSD API in SpiderMonkey to perform its magic, but nowadays JSD is limiting in a number of ways. In order to overcome these limitations, the new JSDBG2 API was designed and implemented by Jim Blandy and Jason Orendorff, and the first version of this work landed in Firefox 8. Jim, being the kind of guy that has forgotten more about debuggers than I will ever know, designed a remote debugging protocol to separate the debugger from the browser, allowing for debugging desktop browsers, mobile browsers, mail readers and even more exotic software in the future. Dave Camp got a great protocol implementation up and running, but was assigned managerial duties (poor sap!) before having a chance to finish the job, so Victor Porof, Mihai Șucan and yours truly lined up to carry the torch. The culmination of this work landed in mozilla-central last week, including the remote protocol implementation and a prototype UI (disabled by default). It is now available in nightlies for adventurous souls to play with.

Let me be clear about that last point: what's in there right now is not useful for day-to-day work, even for experienced developers. There is no UI to add breakpoints besides the experimental Graphical Command Line Interface (whose awesomeness deserves a separate post), no stepping, no variable inspection besides call parameters and 'this', and numerous other limitations. In short: it's not ready, yet. In the course of the next weeks we will be furiously working to add the missing bits and improve the UI, so that it becomes a worthy addition to our existing suite of developer tools.

If, however, you are the kind of person who doesn't take no for an answer, here is what you need to do to play with it: type about:config in the awesomebar and set the preference devtools.debugger.enabled to true. Also, set devtools.gcli.enable to true in order to be able to set breakpoints. Restart your browser and select Tools -> Web Developer -> Script Debugger to open it. You will need to reload the page for the debugger to become aware of the scripts in the page (see? It's not ready!). Browse through the source scripts to find a place where you would like to add a breakpoint, then open the web console and type break add line <url> <line>. Don't worry about memorizing it, GCLI will guide you along the way, suggesting among the available options at each step. When the code hits the breakpoint, the debugger will display the stack frames and the variables in scope (not all of them, it's not ready, remember?) for inspection.

If you have better things to do with your time than play with experimental, uninished debuggers, but would still like to take a peek into what's in store already, here is a short screencast that should give you a broad idea. Note that the stepping functionality in the demo is not in the nightlies yet, because, you guessed it, it's not quite ready.



Ready or not, we would love to have any feedback you might have. Drop by #devtools for a chat, or file bugs to torturehelp us get things fixed. Rest assured, when it's done, debugging web apps will never be the same again.

Tuesday, October 12, 2010

GSS/Pithos update: iPhone, Android, Mongo & getting to 2.0


It has been a while since my last post on GSS/Pithos, and there have been quite a few important announcements that I have not blogged about, only tweeted:
  • a shiny native iPhone client
  • a brand new Android client
  • a back-office application for statistics and admin tasks
  • public folders for hosting static web sites
  • a slew of performance, usability and bug fixes for the web & desktop clients
  • new user registration and quota upgrade workflows
And since the code base has been adopted by other European NRNs, we have also improved our release engineering process and documentation. This however was just the tip of the iceberg. What we are now close to completing, is nothing short of an almost complete rewrite of the core GSS server, aiming at even greater performance and scalability. We are about to release GSS 2.0.

The initial plan was far more modest. We had identified the PostgreSQL installation that stores all of the the system’s data besides the actual files, as a future bottleneck when user adoption would start to accelerate. In such an event there were a few low-to-medium-cost solutions that we could pursue, like replication and manual sharding, but since the problem seemed best suited for a NoSQL solution, we decided to bite the bullet and attempt a transition.

Our field search included lots of products, like Mongo, Couch, Cassandra, Riak, Redis, HBase, MemcacheDB and others. The basic requirements were high write throughput, sharding, replication and easy migration. Most of the products boasted high performance for writes and lots supported replication. In the end we discarded the ones that didn’t support sharding, which limited the options a lot, and we investigated the various APIs, trying to figure out what it would mean to rewrite GSS for one of these. In the end we chose Mongo for its rich query support, since it was the best fit for our problem at hand, making the transition of the existing code base easier. Although we’d love to have had the opportunity to try different ports for each of those datastores, it is most likely that we would have had to rewrite the entire server from scratch, which was not an option.

The initial plan was to try to isolate the changes to the data access layer, essentially building a new adapter for the middle tier that would appear almost identical to the existing code. This effort was fruitless however, since we could not find satisfactory solutions for various issues, like transactions, data mapping, entity lifecycle, etc. We came to the conclusion that even if we managed to build a not-too-leaky abstraction for Mongo, it would have probably killed the performance, making the switch from PostgreSQL pointless.

So we ditched JPA and container-managed transactions and decided to make a simpler POJO mapping to Mongo using Morphia, a Java data mapper for Mongo that takes care of the nitty-gritty details and repetitive coding, for only a minor performance hit. Since Mongo only supports atomicity for a single query, we reverted to manual transaction handling and decided to ditch the EJBs that formed the backbone of GSS altogether, since they didn’t buy us anything at that point. The new GSS server would be a set of servlets, service and domain objects, wired together via Google Guice. Since we could host the new server in a plain servlet container, we went from JBoss to Jetty, which vastly reduced the server startup time from 60 seconds down to 2. As a consequence, development round-trip times went down, and coding was fast again. Lots of object copying and conversions from entities to DTOs and back again were now unnecessary, since there was no more a transaction boundary at the session bean layer. This kept memory usage low, increased cache locality and boosted performance. There are lots of interesting details about our approach, but they would be better discussed in separate blog posts. If you are interested, you can already check out the code in the gss2 branch of the GSS repository.

The next generation GSS server is not production ready yet, but we'll be getting there soon, and so far it has been a great ride!

Friday, February 19, 2010

The Cloud Desktop


This was originally posted in the mynetworkfolders.com blog.

We live in a browser these days. E-mail, word-processing, spreadsheets, chat, are all occupying a browser window in front of me. Maybe not for everyone yet, but the trend is clear, and has been clear for quite some time now. This is a good thing. The Web of today bears little similarity to the Web of the millennium. It's fast, it's powerful and it's ubiquitous. A consequence of that evolution is the simplicity with which I can continue my work when leaving my Linux workstation at work and sit in front of my Mac at home. Since my applications are web-based, they are OS- and browser-agnostic. More importantly, my data are always there when I need them. Readily accessible from my desktop, laptop or mobile phone. I may keep local backups for archival purposes, but my master copies are always online.

Assuming this trend is indeed inescapable, one can't help but wonder: what are the applications that have not migrated to the cloud, yet? What kind of things would I like to do online, seamlessly, from every device I own? What are the barriers that make our current online experience less powerful than the desktop one?

One thing that we noticed was missing from the online desktop, was the... desktop! Yes, my spreadsheets are online. Sure, my pictures are online. Yes, I can upload arbitrary files in various storage services. But, I couldn't find a way to use a familiar file manager interface to work with my data in the cloud, as I do on my computer. This was the need we decided to fulfill with MyNetworkFolders.

MyNetworkFolders attempts to provide an answer to the question: how would my desktop look in the cloud? And even though we are nowhere near done yet, the results so far are exciting and very promising.

MyNetworkFolders offers a familiar file manager interface for my cloud storage needs, with advanced functionality and ease of use. Documents can be viewed, modified, searched or sent to the trash. They can be shared with other users or among the members of a group using flexible ACLs, or even be publicly accessible from the whole internet. They can be versioned for tracking changes more effectively. The service can be accessed from a variety of ways, including a web browser, a desktop client, a WebDAV network share or (really soon) a mobile phone. But most importantly, there is no vendor lock-in. There is a REST-like API available, battle-tested from all the above client implementations, giving everyone the opportunity to access his data in his own particular way. Or even get them out of our service altogether.

Oh, and one other thing. It's all based on open-source software. The core infrastructure, the various clients we have built, even API helpers in various programming languages, are all available for anyone and everyone to see, use and modify. Or maybe used to setup and run YourNetworkFolders, if you feel really ambitious.

If however you just want a true desktop environment, with unparalleled flexibility, and maybe also see how far the cloud desktop rabbit-hole goes, then come along. It's going to be an exciting ride.

Thursday, August 20, 2009

Spell-checking in JavaScript

I just heard of Atwood's Law a few days ago. Apparently Jeff Atwood first published his discovery a couple of years ago, which is like a century in Internet time, but I can't keep up with everything. The Law states that "any application that can be written in JavaScript, will eventually be written in JavaScript". As Atwood explains, it is based on Tim Berners-Lee's Principle Of Least Power:

Computer Science spent the last forty years making languages which were as powerful as possible. Nowadays we have to appreciate the reasons for picking not the most powerful solution but the least powerful. The less powerful the language, the more you can do with the data stored in that language.


I think there is a common theme between Atwood's Law, Zawinski's Law ("Every program attempts to expand until it can read mail. Those programs which cannot so expand are replaced by ones which can") and Greenspun's Tenth Rule ("Any sufficiently complicated C or Fortran program contains an ad hoc, informally-specified, bug-ridden, slow implementation of half of Common Lisp"). The inevitability of the specified outcome makes the world seem like a much simpler place. There is no need to argue. Believe and ye shall be redeemed.

I might have been in this state of mind, when I came across Peter Norvig's "How to Write a Spelling Corrector", because I knew instantly I had to port the algorithm to JavaScript. The algorithm is quite simple and has already been ported to many different languages, so I seized the opportunity to study the differences in expressiveness, performance and style, between these languages and my latest affection, JavaScript.

After a few night's work I have it working and free (as in beer and speech) for anyone to use. Check out the speller project on GitHub. If you want to understand how the algorithm works, you should go and read Norvig's article, although you might get some hints from the comments in my code. The modestly condensed version of the code is 53 lines:


var speller = {};
speller.train = function (text) {
var m;
while ((m = /[a-z]+/g.exec(text.toLowerCase()))) {
speller.nWords[m[0]] = speller.nWords.hasOwnProperty(m[0]) ? speller.nWords[m[0]] + 1 : 1;
}
};
speller.correct = function (word) {
if (speller.nWords.hasOwnProperty(word)) return word;
var candidates = {}, list = speller.edits(word);
list.forEach(function (edit) {
if (speller.nWords.hasOwnProperty(edit)) candidates[speller.nWords[edit]] = edit;
});
if (speller.countKeys(candidates) > 0) return candidates[speller.max(candidates)];
list.forEach(function (edit) {
speller.edits(edit).forEach(function (w) {
if (speller.nWords.hasOwnProperty(w)) candidates[speller.nWords[w]] = w;
});
});
return speller.countKeys(candidates) > 0 ? candidates[speller.max(candidates)] : word;
};
speller.nWords = {};
speller.countKeys = function (object) {
var attr, count = 0;
for (attr in object)
if (object.hasOwnProperty(attr))
count++;
return count;
};
speller.max = function (candidates) {
var candidate, arr = [];
for (candidate in candidates)
if (candidates.hasOwnProperty(candidate))
arr.push(candidate);
return Math.max.apply(null, arr);
};
speller.letters = "abcdefghijklmnopqrstuvwxyz".split("");
speller.edits = function (word) {
var i, results = [];
for (i=0; i < word.length; i++)
results.push(word.slice(0, i) + word.slice(i+1));
for (i=0; i < word.length-1; i++)
results.push(word.slice(0, i) + word.slice(i+1, i+2) + word.slice(i, i+1) + word.slice(i+2));
for (i=0; i < word.length; i++)
speller.letters.forEach(function (l) {
results.push(word.slice(0, i) + l + word.slice(i+1));
});
for (i=0; i <= word.length; i++)
speller.letters.forEach(function (l) {
results.push(word.slice(0, i) + l + word.slice(i));
});
return results;
};


It may not be as succinct as Norvig's Python version (21 lines), or the record-holding Awk and F# versions (15 lines), but is much better than C (184 lines), C++, Perl, PHP, Rebol and Erlang. There is even a Java version with 372 lines. It must contain some sort of spell-checking framework in there, or something. The condensed version above, although correct, has terrible performance in most JavaScript engines, however. For real-world use you should pick the regular version which may be slightly longer, but performs much better.

Since this was a toy project of mine, I wanted to play with ServerJS modules as well, in order to run it as a shell script. I turned the code into a securable module, so you can run it from the command line, using narwhal. I have a couple of scripts to that end. Of course since this is JavaScript, you can try it from your browser, by visiting the demo page, courtesy of GitHub Pages. Be sure to use a modern browser, like Firefox 3.5, Safari 4 or Chrome 3 (beta), otherwise you won't be able to run the test suite, since I used the brand-new Web Workers to make the long-running tasks run in the background.

Norvig's Python implementation took 16 seconds for test 1 and the best I got was 25 seconds with Safari 4 on my Mac. Narwhal is using Rhino by default, so it is definitely not competitive in such tests (139 seconds), but I'm planning to fix support for v8cgi and give that a try.

And it goes without saying that I'd love to hear about ways to improve the performance or the conciseness of the code. If you have any ideas, don't be shy, leave a comment or even better fork the code and send me a pull request on GitHub.

Tuesday, July 7, 2009

GSS authentication

As I've described before, the GSS API is a REST-like interface for interacting with a GSS-based service, like Pithos. Using regular HTTP commands a client can upload, download, browse and modify files and folders stored in the GSS server. These interactions have two important properties: they store no client state to the server and they are not encrypted. I have already mentioned the most important benefits from the stateless architecture of the GSS protocol, namely scalability and loose coupling along the client-server boundary. In the same line of thought, SSL/TLS encryption of the transport was avoided for scalability reasons. Consequently, these two properties of the communication protocol, lead to another requirement: message authentication for each API call.


Since no session state is stored in the server, the client must authenticate each request as if it were the first one. Traditional web applications use an initial authentication interaction between client and server, that creates a unique session ID, which is transmitted with each subsequent request in that same session. While using this ID, the client does not need to authenticate again to the server. Stateless protocols, like WebDAV for instance, cannot rely on such an ID and have to transmit authentication data in each call. Ultimately the tradeoff is a minor increase in the message payload, in return for a big boost in scalability. The HTTP specification defines an Authorization header for use in such cases and WebDAV uses the HTTP Digest Access Authentication scheme. The GSS API uses a slight variation in that theme, blended with some ideas from OAuth request signing.

Essentially the standard HTTP Authorization header is populated with a concatenation of the username (for identifying the user making the request) and a HMAC-SHA1 signature of the request. The request signature is obtained by applying a secret authentication token to a concatenated string of the HTTP method name, the date and time of the request and the actual requested path. The GSS API page has all the details. The inclusion of the date and time helps thwart replay attacks using a previously sniffed signature. Furthermore, a separate header with timestamp information, X-GSS-Date, is used to thwart replay attacks with a full copy of the payload. The authentication token is issued securely by the server to the client and is the time-limited secret that is shared between the client and server. Since it is not the user password that is used as a shared secret, were the authentication token to be compromised, any ill effects would have been limited to the time period the token was valid. There are two ways for client applications to obtain the user's authentication token, and they are both described in detail in the API documentation.

In my experience, protocol descriptions are one thing and working code is a totally different one. In that spirit, I'm closing this post with a few tested implementations of the GSS API signature calculation, for client applications in different languages. Here is the method for signing a GSS API request in Java (full code here):


public static String sign(String httpMethod, String timestamp,
String path, String token) {
String input = httpMethod + timestamp + path;
String signed = null;

try {
System.err.println("Token:" + token);
// Get an HMAC-SHA1 key from the authentication token.
System.err.println("Input: " + input);
SecretKeySpec signingKey = new SecretKeySpec(
Base64.decodeBase64(token.getBytes()), "HmacSHA1");

// Get an HMAC-SHA1 Mac instance and initialize with the signing key.
Mac hmac = Mac.getInstance("HmacSHA1");
hmac.init(signingKey);

// Compute the HMAC on the input data bytes.
byte[] rawMac = hmac.doFinal(input.getBytes());

// Do base 64 encoding.
signed = new String(Base64.encodeBase64(rawMac), "US-ASCII");

} catch (InvalidKeyException ikex) {
System.err.println("Fatal key exception: " + ikex.getMessage());
ikex.printStackTrace();
} catch (UnsupportedEncodingException ueex) {
System.err.println("Fatal encoding exception: "
+ ueex.getMessage());
} catch (NoSuchAlgorithmException nsaex) {
System.err.println("Fatal algorithm exception: "
+ nsaex.getMessage());
nsaex.printStackTrace();
}

if (signed == null)
System.exit(-1);
System.err.println("Signed: " + signed);
return signed;
}


Here is a method for signing GSS API requests in JavaScript, that uses the SHA-1 JavaScript implementation by Paul Johnston (full code here):


function sign(method, time, resource, token) {
var q = resource.indexOf('?');
var res = q == -1? resource: resource.substring(0, q);
var data = method + time + res;
// Use strict RFC compliance
b64pad = "=";
return b64_hmac_sha1(atob(token), data);
}

Here is a Tcl implementation by Alexios Zavras (full code here):


proc ::rest::_sign {id} {
variable $id
upvar 0 $id data
set str2sign ""
append str2sign $data(method)
append str2sign $data(date)
set idx [string first ? $data(path)]
if {$idx < 0} {
set str $data(path)
} else {
incr idx -1
set str [string range $data(path) 0 $idx]
}
# append str2sign [::util::url::encode $str]
append str2sign $str
puts "SIGN $str2sign"
set sig [::base64::encode [::sha1::hmac -bin -key $::GG(gsstoken) $str2sign]]
set data(signature) $sig
}

I'd love to show implementations of the signature calculation for other languages as well, but since my time is scarce these days, I could use some help here. If you've written one yourself and you'd like to share, leave a comment and I'll update this post, with proper attribution of course.

Wednesday, June 17, 2009

Retrying transactions with exponential backoff

The method I described in my previous post about retrying transactions could use some improvement. A deficiency that will only become relevant in highly congested servers is the constant retry interval. When two or more transactions try to commit at the same time and fail, with the code from the last post they will retry probably simultaneously again. Random runtime events (like process/thread scheduler decisions, JIT compiler invocations, etc.) might help avoid collisions, but in general the collided transactions may well collide again. And again. And then again, until the specified maximum number of retries is reached.


The general method to alleviate such problems is to randomize the retry intervals. The most well-known algorithm in this category is called exponential backoff. This is one way to implement it for the utility method in my previous post (full code in gss):


public T tryExecute(final Callable<T> command) throws Exception {
T returnValue = null;
// Schedule a Future task to call the command after delay milliseconds.
int delay = 0;
ScheduledExecutorService executor = Executors.newScheduledThreadPool(1);
for (int i = 0; i < TRANSACTION_RETRIES; i++) {
final int retry = i;
ScheduledFuture<T> future = executor.schedule(new Callable<T>() {

@Override
public T call() throws Exception {
return command.call();
}
}, delay, TimeUnit.MILLISECONDS);

try {
returnValue = future.get();
break;
} catch (ExecutionException e) {
Throwable cause = e.getCause();
if (!(cause instanceof EJBTransactionRolledbackException) ||
retry == TRANSACTION_RETRIES - 1) {
executor.shutdownNow();
throw new Exception(cause);
}
delay = MIN_TIMEOUT + (int) (MIN_TIMEOUT * Math.random() * (i + 1));
String origCause = cause.getCause() == null ?
cause.getClass().getName() :
cause.getCause().getClass().getName();
logger.info("Transaction retry #" + (i+1) + " scheduled in " + delay +
" msec due to " + origCause);
}

}
executor.shutdownNow();
return returnValue;
}
The notable changes in this version are the delayed invocations of the Callable and the retry interval calculation. The former is accomplished using a ScheduledFuture from the excellent utilities in java.util.concurrent, which gets executed after a random time period. The interval calculation is something that can be implemented in a number of ways, either with monotonically increasing intervals or not. I opted for the formula above since it provided the fastest collision elimination in my tests, much faster than the monotonically increasing interval formulas I tried. The MIN_TIMEOUT constant is more of a black art. It should be tuned to the particular hardware and network setup in order to attain maximum efficiency: the minimum number of retries with the minimum interval between retries.

Another issue raised in a comment in my previous post was that the exception I am using as guard, EJBTransactionRolledbackException, may be too generic for this purpose. This is definitely true, EJBTransactionRolledbackException just wraps an OptimisticLockException as one would expect for this case, which in turn wraps the Hibernate-specific StaleObjectStateException that is thrown initially. However, contention in a database table, index or row might not necessarily result in optimistic locking violations, but in deadlocks as well, when one transaction holds exclusive locks on resources that are needed by the other and vice versa. Deadlock detection is performed by the DBMS, which forces a rollback of both transactions. This time however the initial exception (at least in my testing, might be DBMS or JDBC driver-specific) is GenericJDBCException which gets wrapped in a PersistenceException, which in turn is put inside a EJBTransactionRolledbackException before being received by our call site. Therefore, the generic nature of the guard is not a problem in this case. On the contrary it covers more relevant cases and one might argue even that there is no better service that can be offered to the caller, than retrying in all such occasions.

Monday, June 15, 2009

Retrying transactions in Java

When building a web-based system, the most often encountered persistence solution is the use of a relational DBMS. This provides many benefits, but probably the most important one is that its behavior and usage are widely understood after so many decades of use. The simplicity of the ACID transactional model, coupled with the nice fit of the HTTP request/response protocol, make for a killer combination.

The simplicity starts to break down however, when the load on the DBMS server increases, causing transactions to start failing. The DBMS can guarantee that no data corruption will occur, but handling such cases is not that simple. The scalable Optimistic Locking model requires transactions to be resubmitted when failure occurs. Since this is supposed to be rather rare (otherwise optimistic locking should probably not be used), developers often cheat by not dealing with such errors, letting them bubble up to the user, who is then responsible for resubmitting the transaction. This leads to simple, elegant codebases and unhappy users.

Adding ORM to the mix only makes things worse. In JavaEE, the JPA API hides much of the complexity of dealing with relational databases, but corner cases become harder. Add the container-managed transaction boundaries provided by session EJBs and one might be tempted to raise his hands up in despair.

However a solution is not as hard as it sounds. Provided that session EJB methods are sufficiently free from side effects, one can replay a transaction for a number of times from the call site (external to the session bean) with a small amount of code and a small added complexity to the call sites. Since I seem to come up against this requirement quite often, I thought I should describe one way to do it. The following tryExecute() helper method, retries any action supplied in a standard Callable interface for a number of times, in the face of optimistic locking violations:


public T tryExecute(Callable<T> command) throws Exception {
T returnValue = null;
for (int i = 0; i < TRANSACTION_RETRIES; i++) {
try {
returnValue = command.call();
break;
} catch(EJBTransactionRolledbackException trbe) {
if (i == TRANSACTION_RETRIES - 1)
throw trbe;
} catch (Exception e) {
throw e;
}
logger.debug("Transaction retry: " + (i+1));
}
return returnValue;
}


By abstracting away the session bean method code in a parameterized class we can reuse this method in every place that needs to retry transactions. Using a Callable as a parameter lets us return any values received from the session bean. For supplying bean methods that do not return values, we could create Runnable instances and wrap them to Callable using Executors.callable(). You can see the original code here.

If you use the above code in a JavaSE environment without EJB, you should probably need to catch OptimisticLockException for JPA, or even StaleObjectStateException, if you don't mind depending on a Hibernate API. I use the above helper method like this in my code:


file = new TransactionHelper<FileHeaderDTO>().tryExecute(new Callable<FileHeaderDTO>() {
@Override
public FileHeaderDTO call() throws Exception {
return sessionBean.createFile(user.getId(), folder.getId(), name, mimeType, uploadedFile);
}
});


Java's verbosity makes this not that easy to understand at first sight, but what happens is very simple indeed: I wrap a one-liner call to the session bean method createFile(), in a Callable and supply it to tryExecute(). The result from the bean method is received in a local variable as usual. One thing to keep in mind though is that since Java doesn't have closures, the above anonymous function can only receive final variables as parameters. In my example user, folder, name, mimeType and uploadedFile are all final. You might have to resort to using temporary local variables for storing final values on some occasions.

Thursday, April 23, 2009

An introduction to the GSS API

Application Programming Interface or API design is one of my favorite topics in programming, probably because it is both a science and an art. It is a science because there are widely accepted principles about how to design an API, but at the same time applying these principles within the constraints of a given programming language, requires the finesse of an experienced practicioner. Therefore it is with great pleasure that I'll try to explain the ins and outs of the GSS REST-like API, as promised before. As I've already mentioned, GSS is both the name of the source code project in Google Code, as well as the GRNET-sponsored service for the Greek research and academic network (although, it's official name after leaving the beta stage will be Pithos). Since anyone can use the open-source code to setup a GSS service, in this post I'll use generic examples, so anyone writing a client for the GRNET service should modify them accordingly.

When developing an application in a particular programming language, we are used to thinking about the APIs presented to us by the various libraries, which are invariably specified in that same language. For instance, for communicating with an HTTP server from a Java program we might use the HttpClient library API. This library presents a set of Java classes, interfaces and methods for interacting with web servers. These classes hide the underlying complexity of making the low-level HTTP protocol operations, allowing our mental process to remain constantly in a Java world. We could however interact with a web server without such a library, opting to implement the HTTP protocol interactions ourselves instead. Unfortunately, there is no such higher-level library for GSS yet, wrapping the low-level HTTP communications. Therefore this post will present a low-level API, in the sense that one has to make direct HTTP calls in his chosen programming language. The good news is that the following discussion is useful for programmers with any background, since there is support for the ubiquitus HTTP protocol in every modern programming language.

A RESTful API models its entities as resources. Resources are identified by Uniform Resource Identifiers, or URIs. There are four kinds of resources in GSS: files, folders, users & groups. These resources have a number of properties that contain various attributes. The API models these entities and their properties in the JSON format. There is also a fifth entity that is not modeled as a resource, but is important enough to warrant special mention: permissions.

Users · Users are the entities that represent the actual users of the system. They are used to login to the service and separate namespaces of files and folders. User entities have attributes like full name, e-mail, username, authentication token, creation/modification times, groups, etc. The URI of a user with username paul would be:

http://host.domain/gss/rest/paul/
The JSON representation of this user would be something like this:
{
"name": "Paul Smith",
"username": "paul",
"email": "paul@gmail.com",
"files": "http://hostname.domain/gss/rest/paul/files",
"trash": "http://hostname.domain/gss/rest/paul/trash",
"shared": "http://hostname.domain/gss/rest/paul/shared",
"others": "http://hostname.domain/gss/rest/paul/others",
"tags": "http://hostname.domain/gss/rest/paul/tags",
"groups": "http://hostname.domain/gss/rest/paul/groups",
"creationDate": 1223372769275,
"modificationDate": 1223372769275,
"quota": {
"totalFiles": 7,
"totalBytes": 429330,
"bytesRemaining": 10736988910
}
}


Groups · Groups are entities used to organize users for easier sharing of files and folders among peers. They can be used to facilitate sharing files to multiple users at once. Groups belong to the user who created them and cannot be shared. The URI of a group named work created by the user with username paul would be:
http://host.domain/gss/rest/paul/groups/work
The JSON representation of this group would be something like this:

[
"http://hostname.domain/gss/rest/paul/groups/work/tom",
"http://hostname.domain/gss/rest/paul/groups/work/jim",
"http://hostname.domain/gss/rest/paul/groups/work/mary"
]


Files · Files are the most basic resources in GSS. They represent actual operating system files from the client's computer that have been augmented with extra metadata for storage, retrieval and sharing purposes. Familiar metadata from modern file systems are also maintained in GSS, like file name, creation/modification times, creator, modifier, tags, permissions, etc. Furthermore, files can be versioned in GSS. Updating versioned files retains the previous versions, while updating an unversioned file replaces irrevocably the old file contents. The URI of a file named doc.txt located in the root folder of the user with username paul would be:
http://host.domain/gss/rest/paul/files/doc.txt
The JSON representation of the metadata in this file would be something like this:

{
"name": "doc.txt",
"creationDate": 1232449958563,
"createdBy": "paul",
"readForAll": true,
"modifiedBy": "paul",
"owner": "paul",
"modificationDate": 1232449944444,
"deleted": false,
"versioned": true,
"version": 1,
"size": 802,
"content": "text/plain",
"uri": "http://hostname.domain/gss/rest/paul/files/doc.txt",
"folder": {
"uri": "http://hostname/gss/rest/aaitest@uth.gr/files/",
"name": "Paul Smith"
},
"path": "/",
"tags": [
"work",
"personal"
],
"permissions": [
{
"modifyACL": true,
"write": true,
"read": true,
"user": "paul"
},
{
"modifyACL": false,
"write": true,
"read": true,
"group": "work"
}
]
}


Folders · Folders are resources that are used for grouping files. They represent the file system concept of folders or directories and can be used to mirror a client's computer file system on GSS. Familiar metadata from modern file systems are also maintained in GSS, like folder name, creation/modification times, creator, modifier, permissions, etc. The URI of a folder named documents located in the root folder of the user with username paul would be:
http://host.domain/gss/rest/paul/files/documents
The JSON representation of this folder would be something like this:

{
"name": "documents",
"owner": "paul",
"deleted": false,
"createdBy": "paul",
"creationDate": 1223372795825,
"modifiedBy": "paul",
"modificationDate": 1223372795825,
"parent": {
"uri": "http://hostname.domain/gss/rest/paul/files/",
"name": "Paul Smith"
},
"files": [
{
"name": "notes.txt",
"owner": "paul",
"creationDate": 1233758218866,
"deleted":false,
"size":4567,
"content": "text/plain",
"version": 1,
"uri": "http://hostname.domain/gss/rest/paul/files/documents/notes.txt",
"folder": {
"uri": "http://hostname.domain/gss/rest/paul/files/documents/",
"name": "documents"
},
"path": "/documents/"
}
],
"folders": [],
"permissions": [
{
"modifyACL": true,
"write": true,
"read": true,
"user": "paul"
},
{
"modifyACL": false,
"write": true,
"read": true,
"group": "work"
}
]
}

Working with these resources is accomplished by sending HTTP protocol requests to the resource URI with GET, HEAD, DELETE, POST, PUT methods. GET requests retrieve the resource representation, either the file contents, or the JSON representations for the resources specified above. HEAD requests for files return just the metadata of the file and DELETE requests remove the resource from the system. PUT requests upload files to the system from the client, while POST requests perform various modifications to the resources, like renaming, moving, copying, moving files to the trash, restoring them from the trash, creating folders and more. The operations are numerous and I hope to cover them in more detail in a future post.

One important aspect of every RESTful API is the use of URIs to allow the client to maintain a stateful conversation. For example, fetching the user URI would provide the files URI for fetching the available files and folders. Fetching the files URI would in turn return the URIs for the particular files and folders contained in the root folder (along with other folder properties). Returning to the parent of the current folder would entail following the URI contained in the parent property. This mechanism removes the state handling from the server and puts the burden on the client, providing excellent scalability for the service. Furthermore, since the URIs are treated opaquely by the client, the API allows client reuse across server deployments. A client can target multiple GSS services, as long as they speak the same RESTful API. Moreover, links from service A can refer to resources in service B without a problem (in the same authentication domain, e.g. the same Shibboleth federation). This is the same as using a single web browser to communicate with multiple web servers, by following links among them.

Monday, April 20, 2009

Reconciling Apache Commons Configuration with JBoss 5

There are many ways to configure a JavaEE application. Among the available solutions are DBMS tables, JNDI, JMX MBeans and even plain old files in a variety of formats. While we have used most of the above in various occasions, I find that plain files resonate with all types of sysadmins, when no other administrative interface is available. For such scenarios, Apache Commons Configuration is undoubtedly the best tool for the job. Recently, I came across an undocumented incompatibility when using Commons Configuration with JBoss 5 and I thought I should describe our solution for the benefit of others.

Usually we are storing our configuration files in the standard place for JBoss, which is JBOSS_HOME/server/default/conf, for the default server configuration. This has the disadvantage that is not as easy to remember as /etc in UNIX/Linux or \Program Files and \Windows in Windows systems, but it has the important advantage of being specified as a relative path in our code, making it more cross-platform without cluttering it with platform-specific if/else path resolution checks.

Commons Configuration can reload the configuration files automatically when changed in the file system, which helps prolong the server uptime. However JBoss 5 has introduced the concept of a virtual file system that caches all file system accesses performed through the context class loaders using relative paths. Unfortunately this generates resource URLs in the form vfsfile:foo.properties that Commons Configuration does not know how to deal with. Fixing this requires extending FileChangedReloadingStrategy, like we do in gss. Alternatively, one could patch Commons Configuration with the following change and use the standard FileChangedReloadingStrategy unchanged:


Index: FileChangedReloadingStrategy.java
===================================================================
--- FileChangedReloadingStrategy.java (revision 764760)
+++ FileChangedReloadingStrategy.java (working copy)
@@ -46,6 +46,9 @@
/** Constant for the jar URL protocol.*/
private static final String JAR_PROTOCOL = "jar";

+ /** Constant for the JBoss MC VFSFile URL protocol.*/
+ private static final String VFSFILE_PROTOCOL = "vfsfile";
+
/** Constant for the default refresh delay.*/
private static final int DEFAULT_REFRESH_DELAY = 5000;

@@ -161,7 +164,8 @@

/**
* Helper method for transforming a URL into a file object. This method
- * handles file: and jar: URLs.
+ * handles file: and jar: URLs, as well as JBoss VFS-specific vfsfile:
+ * URLs.
*
* @param url the URL to be converted
* @return the resulting file or null
@@ -181,6 +185,18 @@
return null;
}
}
+ else if (VFSFILE_PROTOCOL.equals(url.getProtocol()))
+ {
+ String path = url.getPath();
+ try
+ {
+ return ConfigurationUtils.fileFromURL(new URL("file:" + path));
+ }
+ catch (MalformedURLException mex)
+ {
+ return null;
+ }
+ }
else
{
return ConfigurationUtils.fileFromURL(url);


Neither of these solutions covers the case of storing configuration files in zip or jar containers, but since it is something I haven't found a use for yet, I can't test a fix for it. If anyone is interested in such a use case, I'd advise extending FileChangedReloadingStrategy, combining the logic in jar: and vfsfile: URL handling.

Monday, April 13, 2009

GSS architecture

Handling a large number of concurrent connections requires many servers. Not only because scaling vertically (throwing bigger hardware at the problem) is very costly, but also because even if an application can be designed to scale vertically, the underlying stack probably can not. Java applications for instance, like GSS, run on the JVM and although the latter is an excellent piece of engineering, using huge amounts of heap is not something it's tuned for. Big Iron servers with many cores and 20+ GB of RAM are usually running more than one JVM, since garbage collection is not all that efficient with huge heaps. And since running application instances with a 4-8 GB heap size can be done with cheap off-the-shelf hardware, why spend big bucks on Big Iron?

So having a large number of servers is a sane choice, but brings it's own set of problems. Unless one partitions users to servers (having all requests a particular user makes be delivered to the same server), all servers must have a consistent view of the system data, in order to deliver meaningful results. Assigning user requests to particular servers, usually requires expensive application layer load-balancers or customized application code on each server, so it would rarely be your first option. Having all servers work on the same data is a more tractable problem, since it can be solved by having the application state being replicated among server nodes. Usually, only a small part of the application state needs to be replicated, for each user, that is the part which concerns his current session. But even though session clustering solutions have been a well studied field and implementations abound, having no session to replicate is an even better option.

For GSS we have implemented a stateless architecture for the core server, that should provide us with good scalability in a very cost-effective manner. The most important part in this architecture is the REST-like API that moves part of the responsibility for session state maintenance to the client applications, effectively distributing the system load to more systems than the available server pool. Furthermore, client requests can be authenticated without requiring an SSL/TLS transport layer (even though it can be used if extra privacy is required), which would entail higher load on the application servers or require expensive load balancers. In the server side, API requests are being handled by servlets that enlist the services of stateless session beans, for easier transaction management. Our persistence story so far is JPA with a DBMS backing, plus high-speed SAN storage for the file contents. If or when this becomes a bottleneck, we have various contingency plans, depending on the actual characteristics of the load that will be observed.


The above image depicts the path user requests will travel along, while various nodes interact in order to serve them. A key element in this diagram is the number of different servers that can be found, effectively specializing in their own particular domain. Although the system can be deployed on a single physical server (and regularly is, for development and testing), consisting of a number of standalone sub-services instead of a big monolithic service is a boon to scalability.

This high-level overview of the GSS architecture should help those interested to find their way around the open-source codebase and explain some of the design decisions. But the most interesting part from a user's point of view would be the REST-like API, that allows one to take advantage of the service for scratching his own itch.

So that will be the subject of my next post.

Wednesday, April 8, 2009

Introducing GSS

During my recent work-induced blog hiatus, I've been working on a new software system, called GSS. I've been more than enjoying the ride so far and since we have released the code as open-source, I thought discussing some of the experience I've gained might be interesting to others as well.

GSS is a network, er grid, er I mean cloud service, for providing access to a file system on a remote storage space. It is the name of both a service (currently in beta) for the Greek research and academic community and the open source software used for it, that can also be used by others for deploying such services. It is similar in some ways to services like iDrive, DropBox and drop.io, but it can also be regarded as a more high-level Amazon S3. Its purpose is to let the desktop computer's file system meet the cloud. The familiar file system metaphors of files and folders are used to store information in a remote storage space, that can be accessed from a variety of user and system interfaces, from any place in the world that has an Internet connection. All usual file manager operations are supported and users can share their files with selected other users or groups, or even make them public. Currently there are four user interfaces available, a web-based application, a desktop client, a WebDAV interface and an iPhone web application, in various stages of development. Underlying these user interfaces is a common REST-like API that can be used to extend the service in new, unanticipated ways.


The main focus of this service was to provide the users of the Greek research and academic community with a free, large storage space that can be used to store, access, backup and share their work, from as many computer systems as they want. Since the available user base is close to half a million (although the expected users of the service are projected to the low ten thousands), we needed a scalable system, that would be able to accommodate high network traffic and a high storage capacity at the same time. A Java Enterprise Edition server coupled with a GWT-based web client and a stateless architecture were our solution. In future posts I will describe the system architecture with all the gory details. The exposed virtual file system features file versioning, trash bin support, access control lists, tagging, full text search and more.

All of these features are presented through an API for third party developers to create scripts, applications or even full blown services that will fulfill their own particular needs or serve other niches. This API has a REST-like design and though it will probably fail a formal RESTful definition, it sports many of the advantages of such architectures:

  • system resources such as users, groups, files and folders are represented by URIs
  • GET, HEAD, POST, PUT and DELETE methods on resources have the expected semantics
  • HTTP caching is explicitly supported via Last-Modified, ETag & If-* headers
  • resource formats for everything besides files are simple JSON representations
  • only authenticated requests are allowed, except for public resources

Users are authenticated through the GRNET Shibboleth infrastructure. User passwords are never transmitted to the GSS service. Instead GSS-issued authentication tokens are used by both client and server to sign the API requests after the initial user login. SSL transport can provide even stronger privacy guarantees, but it is not required, nor enabled by default.

The GSS code base is GPL-licensed and therefore anyone can use it as a starting point to implement his own file storage service. We have yet to provide binary downloads, due to the various dependencies, but the build instructions should be enough to get someone started. We are always interested in source or documentation patches, of course (did I mention it's open source?). Most importantly, the REST API will ensure that clients developed for one such service can be reused for every other one.

I will have much more to say about the API in a future post. In the meantime you can peruse the code and documentation, or even try it out yourself. I'd be very interested in any comments you might have.

Saturday, March 14, 2009

Applications meme

It's been a while since my last post, but I've been wanting to write about the interesting stuff that I've been working on. Unfortunately it took longer than anticipated, but now we're almost done and I'll be posting soon with the gory details. However, since I got tagged, I suppose I can throw in a not-so-interesting post, about my Linux application preferences.


  1. Which desktop manager do you use more often ?

    Gnome. It's the only one that reminds me of OS X somewhat (appearance- and functionality-wise).

  2. Which desktop application you would not like to see implemented again on linux? And why?

    A desktop manager. If you are going to provide yet another incarnation of a 30-year old idea, please don't bother. The concept is pretty well understood: icons/workspace/file manager/drag'n'drop/mouse/menus/launcher/whatever, it's been done before. Like a million times. If you want to be useful, try to fix some of the shortcomings of the existing ones (notification mechanisms, translucent effects, faster access patterns, application integration, etc.).

  3. Which desktop application you definitely would like to see implemented on linux? Describe it briefly or point out to a similar application.

    Adobe Premiere, or iMovie, or any other semi-decent video editing software. This was the main reason I bought a Mac.

  4. Write the name of the last project (not the very best, the last!) that made you wish to thank their developers so you can thank them now!

    Git. You guys rock! (And if you improve on the UI, you will jazz!)

  5. (Optional) Link the blogs of 1-3 people you’d like to take part to this meme. (no more than three). you can skip this question if you like.

    Let's hear from chstath, ckotso and keramida (who may s/Linux/FreeBSD/ at his discretion).



Sunday, December 9, 2007

How programming languages grow


Q: How do programming languages grow?
A: With pain.


Unless you were lost on a deserted island far away from civilization, you must have heard something about the ECMAScript v4 shenanigans. ECMAScript 4 is the future standard specification for what most people will undoubtedly refer to as JavaScript 2. This forthcoming specification brings a whole slew of features into the JavaScript language, about a decade after the current ECMAScript 3 standard came out. Many of the new features are about facilitating the creation of large programs in the language and improving their safety and robustness. As an intentional side-effect, they maintain and improve the syntactic similarity between JavaScript and Java, so that most young programmers will find it easy to learn and use (in case you didn't know, Java is one of the languages students learn in almost every CS curriculum nowadays).

The breadth of the changes as well as the increased similarity to Java has led some people to protest against them, while they portray the future of their beloved language with gloom and doom. Some members of the ECMAScript standardization committee decided to get off the standardization effort and pursue an ECMAScript v3.1, that is much less ambitious in scope, though still quite vague. These members are Microsoft and Douglas Crockford and while Redmond's move has set off the (usually correct) conspiracy reflexes of the community, Crockford's objections carry more weight to those who pay attention.

Doug Crockford has been known for many things in the JavaScript community, but what I respect most is his simplified JavaScript parser, which is itself written in the same simplified JavaScript. This is the second JavaScript parser in JavaScript that I'm aware of, the first being Brendan Eich's Narcissus. This subset of JavaScript that Crockford advocates for (and is still available in the ECMAScript 4 specification) prefers a more functional style of programming with heavy use of prototypal inheritance, compared to the traditional object-oriented style used in Java and proposed for ECMAScript 4. To cut a long story short, the creator of JavaScript convincingly makes the point that JavaScript must evolve if it is to keep up with the needs of its users, otherwise they will pick something else, like Silverlight or Flex.

In that presentation, Brendan Eich makes a reference to a talk given by Guy Steele in 1998, titled "Growing a Language". It was about the time that the Java community was having a debate about adding generics, operator overloading, complex numbers and other features. In the end some of the proposed changes made it to the standard, like generics, while others like operator overloading, did not. Today another debate is raging in the Java community, about adding closures to the language. Though perhaps less emotional than the JavaScript debate, it is still highly divisive and the reactions are occasionally overboard. It seems changing a language always involves fear, anxiety and pain. Guy Steele's talk provides some insights.

Its been about a decade since that talk, and it shows. No Powerpoint/Keynote slides, just hand-written ones manually placed on the projector. Even the haircut is out of fashion. However the actual presentation is sheer genius. Steele uses the form of his talk to illustrate the point of his argument. In order to demonstrate the difference between small languages and big languages in terms of the programs they can create and the difficulty of their use, he picks a subset of English as a given, all words with one syllable, and every time he needs to use another word he provides a definition. In the same way you provide a class definition of a Person in Java and then go on talking about that person in your business code as if it was a language primitive, Steele makes a talk sound like a computer program and as he confesses in the end, creating that talk was a lot like writing a program.

It may seem weird at first, but as you get the hang of it, it's an eye-opener. Not suitable for computer-language illiterate people of course. Your girlfriend definitely ain't gonna like it. Even the jokes are kinda geeky. Just watch it when you have an hour to spare and nobody is watching you. Then perhaps you might be able to understand Brendan Eich's passion. And do the right thing: use Firefox.

Monday, November 19, 2007

About Macs



If I hear one more time how Macs are expensive and just for fashion victims, I'll throw up. This urban myth keeps coming up for so long, that it's not really funny any more. These two statements that Macs are a) expensive and b) merely a fashion statement, are so easily debunked if one cares to look objectively for the truth that it's mind-boggling to see them come around so often. From personal experience, the (a) above is a farce. It is most ironic, that I mainly hear this from people who spend quite a lot on computers and tech gadgets in general. Like they are quite happy to shell out hundreds of euros for doubtful upgrades on PC hardware and assorted gizmos, but when contemplating a different platform altogether they become Ebenezer Scrooge.

When I picked a locally-assembled PC with Ubuntu for my desktop at work, I did it for two reasons. First, to save a little extra cash, since the budget was low and second, to keep up with developments on FLOSS desktops in general, since I already had a Mac at home. Both systems would work equally well for what I do at work. Now, the purchase savings from getting the PC, amounted to what I cost the company per day. Having spent about a day fiddling with driver's and software that was not readily available through synaptic (that was in Edgy if memory serves), that advantage was gone. I pretty much knew this was going to happen from the start. However, the second reason still holds. I believe that the inevitable progress in FLOSS desktop systems is eventually going to make proprietary products pointlessly expensive. Ubuntu's polish in each new version attests to this. However we are not there yet.

The "fashion" argument (b) is even worse. It might have had some merit in the nineties, when Apple was floundering and targeted mainly the publishing and multimedia markets, but as anyone can see today things have changed. Are all the Mac-carrying uber-hackers in large conferences fashion victims? Really? Those guys with the pony-tails, beards, glasses, t-shirts, shorts and slippers? Funny how they don't seem to spend much on clothes.

Actually, what people like Yakov Fain are really afraid of, is change. And that's perfectly OK. I'm afraid of change, too. Otherwise I might have moved already. Or changed jobs. Or get divorced. Um, nope, scratch that one. It's just that, occasionally, I do manage to build up the courage to face something foreign and exotic and learn to live with it. And sometimes even learn to like it. For someone like Fain who has spent most of his time in the Windows world, every other world will appear difficult to learn. I have a friend (hi George!) whose first computer was a SPARCstation. When he started using Windows, years later, the experience seemed weird and clunky. It's the same thing, only on the flip side of the coin.

Also, Mark Pilgrim's latest mocking of MySQL installation on Mac OS X while hilarious (which is why I like his blog), is unfair. Sam Ruby's too. Installing or upgrading MySQL on OS X is just a matter of getting the package from the vendor's site and launching it, not compiling from sources. The fact that there might be no package yet for Leopard or that the current package does not function well on it is utterly irrelevant. It will be fixed. Ubuntu is no different. I updated Firefox on my Mac at home the day 2.0.0.9 was shipped, yet one week later my Ubuntu box at work is still at 2.0.0.8. Of course, it will be fixed.

This is what you lose with centralized package repositories, in order to gain consistency and ease of upgrading. I'm no stranger to this kind of thing, having used FreeBSD and Linux as my main desktop for many years now. If you think installing things in Ubuntu is always as easy as launching Synaptic, try to use Skype on amd64. Or Flash and Adobe Reader pre-Gutsy. I'm quite used to watching compiler output scroll for hours so all of it was a walk in the park for me, but I can imagine how it might have been frustrating for someone less experienced. Ubuntu's (and FreeBSD's, Fedora's, etc.) advantage over the Mac is when installing something not packaged specifically for OS X by the vendor, like mutt or nmap. That is where the value of a community-maintained repository shines. Of course you can use MacPorts / Fink / pkgsrc / whatever, but they are not integrated into the system, so you merely moved the goal post a little further.

As a parting thought, I have a confession to make: I'd love to work with this guy. Interacting with human beings requires a set of skills that not many people in the technology world can brag about. Understanding how humans work and what makes them tickle is fundamentally different than being an expert with machines and software. Michael Lopp is an engineering manager at Apple. It figures, I guess.

Friday, November 2, 2007

GWT and animation effects


I've already praised GWT and its highly productive environment for generating AJAX applications. I've been using it in my Very Cool Project with great pleasure, I must confess. Creating a highly interactive web application, brings back some of the entertaining aspects of programming again. Although, to be honest, it would have been nice to get rid of all those anonymous inner functions I find myself dealing with. Life (and code) would be a lot simpler with closures and higher order functions. Sometimes I find it ironic that GWT translates my anonymous-inner-classes-using code to JavaScript code with closures, higher order functions and all the other goodies. Apparently, a change of perspective is always an eye-opener.

My nagging aside, GWT is an enormous leap over other solutions for interactive web applications in Java. However, one area that has received little attention so far, is support for animation effects. The stuff that puts the candy in eye-candy. Certainly, there is always the option to use other JavaScript libraries that provide such effects through JSNI, like Scriptaculous, YUI, Ext JS and others. But that is not an efficient nor elegant way to do it. Memory leaks may creep up (particularly on Internet Explorer), separate download requests for the other scripts must be made and JSNI references are, er, how should I put it, um, chatty?

A better way involves using a GWT wrapper around the external effects JavaScript library. This way you get to reap the usual benefits of GWT, namely the minimum number of roundtrips to the server, compilation of just the code you need (the effects you actually use) and no detour to JavaScript-land (though lately I'm having second-thoughts about the goodness of this). The main solutions that have emerged so far are various Scriptaculous wrappers, an ext wrapper and gwt-fx.

I've tried both one Scriptaculous wrapper and the gwt-fx codebase and I would wholeheartedly recommend the latter. For starters, it feels like things are done "the GWT way": a single EffectPanel to decorate the widget that will be animated, separate effect classes for the most popular effects, sequential and parallel combinations of effects, deferred binding for browser-specific functionality, Listeners and Adapters and much more. Implementing a fade effect took me about 10 lines of Java code. And we all know Java is not the most succinct girl in town, right? Furthermore, while the Scriptaculous solution worked on IE, Firefox and Opera, it would barf on Safari (version 2 if you must know). gwt-fx worked on all of them without any special-casing in my code.

Also, when things don't work as expected, the author, Adam Tacy, is very cooperative and helpful. He has endured a flood of patches from me to solve some problems that I encountered, and when not satisfied with them, he implemented even better solutions after careful consideration and thoughtful reasoning. Just make sure to get the latest version (1.0.0) that has every bug I encountered so far, fixed.

Adding a supported effects library in the main GWT distribution has been discussed a few times on the contributors list, but apparently it is not a high priority task at the moment. For a good reason I might add, since the release of GWT 1.5 is just around the corner, with support for Java 5 and a whole slew of compiler optimizations. However, with the recent introduction of the GWT incubator project it might be appropriate to start trying out some design ideas on such a library and see how it goes. If you care for such an outcome, don't hesitate to let the GWT developers know about it, by joining the discussion in the recent thread on the subject.

Tuesday, September 4, 2007

An exceptional interview

My friend Alfred was in a job interview the other day, with a guy named Quincy. It was for a Java programming gig and they were apparently getting too many resumes, so they sat him down with a paper and a pen and asked various questions in order to determine his skills. I hear it is very trendy nowadays, all the cool kids are doing it. After a lot of rather boring, Java-for-dummies kind of stuff, he was given a paper with something more-or-like the following code printed on it:


public String getSomething(String one, Object two, Integer three) {
if (one != null) {
if (two != null) {
if (three != null) {
String result = reallyGetSomething(one, two, three);
doSomethingMore(one, two);
return result;
} else throw new ObjectNotDefinedException("three is undefined");
} else throw new IllegalArgumentException("two is not legal");
} else throw new NullPointerException("one is null");
}

After taking a few moments to read the code, Quincy started firing away:

Q: What is wrong with this method?
A: Lot's of things.

Q: You mean more than one?
A: Of course. The most obvious mistake is that the method does not declare that it can throw ObjectNotDefinedException.

Q: Yep, that's right. Is there anything else?
A: Sure. That's the easy part that the compiler can tell you right away. Furthermore, the method is needlessly complex and has a questionable API.

Q: Really?
A: Sure, the order the null checks are in, force the indentation to increase, making the code difficult to follow. Moreover, if doSomethingMore() and reallyGetSomething() do not modify their parameters and have no side-effects that require this particular ordering, they could be swapped, saving one line:



public String getSomething(String one, Object two, Integer three)
throws ObjectNotDefinedException {
// Validate.
if (one == null)
throw new NullPointerException("one is null");
if (two == null)
throw new IllegalArgumentException("two is not legal");
if (three == null)
throw new ObjectNotDefinedException("three is undefined");

// Do the actual work.
doSomethingMore(one, two);
return reallyGetSomething(one, two, three);
}



Q: OK, now what's wrong with the API?
A: Check out the exceptions the method throws back to the caller.

Q: What about them?
A: Only one of them, ObjectNotDefinedException, is a checked exception that would give the caller a chance to react to such an anomaly. The others are unchecked exceptions that will bubble up the call stack and probably blow up in the users face.

Q: Well, perhaps the API designer wanted to differentiate the handling of the three error cases.
A: Perhaps, that's why I said "questionable". But looking at the similarities in the way the method handles its parameters, that would be hard to believe, don't you think?

Q: I'll ask the questions.


Then, after a bit of fiddling with the internals of his briefcase, Quincy presented another sheet of paper with the following printed code listing:


public class ThrowNull {

public static void main(String[] args) {
System.out.println(getFluff(null));
System.out.println(getStuff(null));
}

public static String getFluff(String name) {
if (name == null)
throw new NullPointerException("BOOM!");
return "Fluff: "+name;
}

public static String getStuff(String name) {
if (name == null)
throw null;
return "Stuff: "+name;
}
}


Alfred was given a few moments to digest it and then Quincy went on:

Q: What does the program print?
A: That's easy. It prints nothing. At least, nothing useful. It throws a NullPointerException since the caller of getFluff() is null.

Q: Why does getFluff() throw an NPE if the name parameter is null?
A: I suppose the getFluff() API designer considered that it's the caller's job to make sure it is not called with a null argument. He should have put that in the javadoc, though. You do write javadoc comments don't you?

Q: I'll ask the questions. What will the program output if we change the first println() in main to
System.out.println(getFluff("bad"));

A: It's not much of a change. The line "Fluff: bad" will be printed, followed by a new NullPointerException.

Q: So the "throw null" syntax is legal?
A: Hell yeah! Even Neal Gafter is using it.

Q: Which way of throwing an NPE is better?
A: Better in what way?

Q: I'll ask the questions.
A: Well, each one has its merits. The first form is more explicit and traditional, but longer. The second is more succinct and closer to the natural language, but cryptic to newcomers.

Q: So what would you recommend that we use?
A: Does that mean I got the job?

Q: I'll ask the questions.
A: Well, I kinda like the short, concise form, but I don't feel particularly strong about it.

Q: Good answer, because we picked the other one after a three-hour long debate last week.
A: You mean you were debating about ways to throw a NullPointerException for three hours?

Q: Yeah, why?
A: Don't you have real work to do?

Q: I'll ask the questions.



I don't believe Alfred has heard back from them ever since.


I'm actually glad about it.

Thursday, August 30, 2007

The case of the disappeared Exception message in GWT RPC

Regular readers of this blog (both of you) will remember my recent love confession for GWT. While I am glad to say that my feelings have not changed one bit, like all maturing relationships, we are getting more intimately familiar with one another. To the point where you know things about your significant other that you'd rather never found out. And since I know there are many others with feelings for GWT, I thought I'd give you a tip or two, in case you want to make a pass.

In my previous post I didn't elaborate on the marvelous feature of GWT RPC. The RPC feature gives your GWT client the ability to communicate with your Java-based backend in a very powerful, yet painless, way. I still plan to discuss it more thoroughly in a future post, but for now I'd like to mention a particular bug (or feature) of the current implementation.

The RPC mechanism allows a client to make a Remote Procedure Call to the server supplying the necessary call parameters and getting back the results. Quite often (as it turns out) the server will encounter an exceptional condition during the execution of this call and will throw an exception to the caller. Luckily an Exception in Java contains a detailed message about the problem encountered (or more accurately its ancestor, Throwable) that the client can rely upon to present the situation to the user. To give an example, you could have an Exception class EarthShatteringException like the following:

public EarthShatteringException extends Exception implements Serializable {

private static final long serialVersionUID = 1L;

public
EarthShatteringException() {
}

public
EarthShatteringException(String message) {
super(message);
}

public
EarthShatteringException(Throwable cause) {
super(cause);
}

public
EarthShatteringException(String message, Throwable cause) {
super(message, cause);
}

}



This is pretty much elementary stuff, you extend the base Exception class and also implement the Serializable interface, in order to give GWT a chance to convert your exception object to tiny little bits, transmit them over the wire and recreate the object on the client. So the way you actually throw such an exception on your server might be something like the following:

public void doGreatStuff() throws EarthShatteringException {
if (something.isWrong())
throw new EarthShatteringException("God help us!");
else
doTheGreatStuff();
}


On the client you deal with the exception in a callback function you provide, called onFailure:

public void onFailure(Throwable caught) {
displayError(caught.getMessage());
}


In this example we just display the message contained in the exception to the user.

At least that's what you would expect. In fact, what this code will do in GWT 1.4.60 (the latest release as of this writing) is display the string null.

How could that be you say? I'm glad you asked.

Serialization in GWT is a little different than in the rest of Javaland. This is because the client in runtime is actually JavaScript code, compiled from our original Java code by the miraculous GWT compiler. The compiler uses its own private implementation of the standard Java class libraries, that implements a quite large, but still limited subset of it. In our particular case the implementation of the Throwable class does not implement the Serializable interface and the side effects that entails.

So when our exception gets transmitted over to the client, what gets instantiated is an EarthShatteringException type, but its supertypes are not serialized (hence transmitted) themselves. Therefore our stored error message gets lost somewhere in Cyberspace, never to be seen again. If your server-side code attempted to throw a standard exception subclass from the standard class library, like IllegalArgumentException, things could be even worse, like getting a ClassCastException.

The good news is that this is a known issue among the GWT developers. The bad news is that it is not fixed yet. However, a simple workaround exists. If you store a detailed error message in your own exception object and override the getMessage method (or its cousins) to return that copy, instead of the supertype's, it will produce the excpected outcome. For the previous example we could do it like this (changes in bold):


public EarthShatteringException extends Exception implements Serializable {

private static final long serialVersionUID = 1L;

private String message;

public
EarthShatteringException() {
}

public
EarthShatteringException(String message) {
super(message);
this.message = message;
}

public
EarthShatteringException(Throwable cause) {
super(cause);
}

public
EarthShatteringException(String message, Throwable cause) {
super(message, cause);
this.message = message;
}

public String getMessage() {
return message;
}
}


If you are a grumpy kind of person and hasten to whine about the apparent intricacies of GWT, rest assured that most of the time GWT RPC is painless as advertised. In fact it seems so easy that people are already hooking it to other server-side frameworks, like Seam and Spring. It provides an elegant way to hook a modern server architecture with the most innovative web client technology on the planet.

I promise you, you'll love it.

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