Let’s say we have the following problem: we have to check whether a date is more than a month ago or less than a month ago. Many developers go in the wrong direction by calculating the current month and then subtracting the number of months from it. Of course, this approach is slow and full of risks of allowing bugs. Since, two months before January, which is the first month of the year, is actually November, which is the eleventh month. Because of these pitfalls, this approach is entirely wrong. strtotime() is a lot more powerful than you think! The question is whether PHP cannot help us with built-in functions to perform these calculations for us. It is obvious, that from version 5.3.0 and later, there is an OOP section, which is great, but unfortunately this version is still not updated everywhere. So, how to accomplish the task? The Wrong Approach As I said, there are many ways to go in the wrong direction. One of them is to subtract 30 days from current date. This is completely wrong, because not every month has 30 days. Here, some developers will begin to predefine arrays to indicate the number of days in each month, which then will be used in their complicated calculations. Here is an example of this wrong approach. echo date('Y-m-d', strtotime(date('Y-m-d')) - 60*60*24*30); This line is full of mistakes. First of all strtotime(date(‘Y-m-d’)) can be replaced by the more elegant strtotime(‘now’), but for this later. Another big mistake is that 60*60*24*30, which is number of seconds in 30 days can be predefined as a constant. Eventually the result is wrong, because not every month has 30 days. The Correct Approach A small research of the problem and the functions in versions prior of 5.3.0 of PHP is needed. Typical case study of date formatting happen when working with dates from a database. The following code is a classical example. // 2008 05 23, 2008-05-23 is stored into the DB echo date('Y m d', strtotime('2008-05-23')); // 2008 May 23 echo date('Y F d', strtotime('2008-05-23')); The problem, perhaps, is that too often strtotime() is used like this, with exactly this type of strings. However much more interesting is that strtotime() can do much more. strtotime() Can Do Much More Let us first look at the documentation of this function. What parameters it accepts? int strtotime ( string $time [, int $now = time() ] ) The function expects to be given a string containing an English date format and will try to parse that format into a Unix timestamp (the number of seconds since January 1 1970 00:00:00 UTC), relative to the timestamp given in now, or the current time if now is not supplied. In particular we are interested in the first parameter, time. time - A date/time string. Valid formats are explained in Date and Time Formats. It is especially important to note what are the valid Date and Time Formats. Here are the supported formats, but most interesting are those that are Relative. Exactly these formats are very convenient in our case, because they give us the ability to work with human readable strings, and here are some examples from the documentation of strtotime(). echo strtotime("now"), "\n"; echo strtotime("10 September 2000"), "\n"; echo strtotime("+1 day"), "\n"; echo strtotime("+1 week"), "\n"; echo strtotime("+1 week 2 days 4 hours 2 seconds"), "\n"; echo strtotime("next Thursday"), "\n"; echo strtotime("last Monday"), "\n"; Thus, a valid string would be “1 month ago”. // if current date is 2011-11-04, this will return 2011-10-04 echo date('Y-m-d', strtotime('1 month ago')) Or “-1 month”: // the same as the example above echo date('Y-m-d', strtotime('-1 month')); It’s interesting that “+1 -1 month” is also a valid string. // 2011-10-04, if today's 2011-11-04 echo date('Y-m-d', strtotime('+1 -1 month')); In fact strtotime() can do a lot more than most of the developers have ever imagined. Maybe its frequent use with string formatted dates (2010-01-13) makes it a bit unknown. Here are some interesting use cases. // 1970-01-01, Calculations in braces are bad! echo date('Y-m-d', strtotime('(60*60) minute')); // 2 months into the future echo date('Y-m-d', strtotime('-2 months ago')); For instance, do you know how to get the date of the day before yesterday? Yes 2 days before today, but here’s yet another solution. // 1 day before yesterday echo date('Y-m-d', strtotime('yesterday -1 day')); Another example is the fully human readable: // get the first monday of the current month echo date('Y-m-d', strtotime('first monday this month')); The Solution of the Task Finally, what is the solution of the original task? Well, just have to check whether a date is more or less than a month ago. // a random date $my_date = '2011-09-23'; // true if my_date is more than a month ago (strtotime($my_date) < strtotime('1 month ago')) Related posts: Thing to Know About PHP Arrays javascript get locale month with full name PHP Strings: How to Get the Extension of a File Source: http://www.stoimen.com/blog/2011/11/04/how-to-check-if-a-date-is-more-or-less-than-a-month-ago-with-php/

Most Java developers who come from a C/C++ background have probably at one time wished for a Java equivalent of sizeof(). Although Java lacks a true sizeof() equivalent, the Instrumentation interface introduced with J2SE5 can be used to get an estimate of the size of a particular object via its getObjectSize(Object) method. Although this approach only supports the object being considered itself and does not take into account the sizes of the objects it references, code can be built to traverse those references and calculate an estimated total size. The Instrumentation interface provides several methods, but the focus of this post is the getObjectSize(Object) method. This method's Javadoc documentation describes the method: Returns an implementation-specific approximation of the amount of storage consumed by the specified object. The result may include some or all of the object's overhead, and thus is useful for comparison within an implementation but not between implementations. The estimate may change during a single invocation of the JVM. This description tells us what the method does (provides an "implementation-specific approximation" of the specified object's size), its potential inclusion of overhead in the approximated size, and its potentially different values during a single JVM invocation. It's fairly obvious that one can call Instrumentation.getObjectSize(Object) on an object to get its approximate size, but how does one access an instance of Instrumentation in the first place? The package documentation for the java.lang.instrument package provides the answer (and is an example of an effective Javadoc package description). The package-level documentation for the java.lang.instrument package describes two ways an implementation might allow use JVM instrumentation. The first approach (and the one highlighted in this post) is to specify an instrumentation agent via the command-line. The second approach is to use an instrumentation agent with an already running JVM. The package documentation goes on to explain a high-level overview of using each approach. In each approach, a specific entry is required in the agent JAR's manifest file to specify the agent class: Premain-Class for the command-line approach and Agent-Class for the post-JVM startup approach. The agent class requires a specific method be implemented for either case: premain for command-line startup or agentmain forpost JVM startup. The next code listing features the Java code for the instrumentation agent. The class includes both a premain (command-line agent) method and a agentmain (post JVM startup agent) method, though only the premain will be demonstrated in this post. package dustin.examples; import static java.lang.System.out; import java.lang.instrument.Instrumentation; /** * Simple example of an Instrumentation Agent adapted from blog post * "Instrumentation: querying the memory usage of a Java object" * (http://www.javamex.com/tutorials/memory/instrumentation.shtml). */ public class InstrumentationAgent { /** Handle to instance of Instrumentation interface. */ private static volatile Instrumentation globalInstrumentation; /** * Implementation of the overloaded premain method that is first invoked by * the JVM during use of instrumentation. * * @param agentArgs Agent options provided as a single String. * @param inst Handle to instance of Instrumentation provided on command-line. */ public static void premain(final String agentArgs, final Instrumentation inst) { out.println("premain..."); globalInstrumentation = inst; } /** * Implementation of the overloaded agentmain method that is invoked for * accessing instrumentation of an already running JVM. * * @param agentArgs Agent options provided as a single String. * @param inst Handle to instance of Instrumentation provided on command-line. */ public static void agentmain(String agentArgs, Instrumentation inst) { out.println("agentmain..."); globalInstrumentation = inst; } /** * Provide the memory size of the provided object (but not it's components). * * @param object Object whose memory size is desired. * @return The size of the provided object, not counting its components * (described in Instrumentation.getObjectSize(Object)'s Javadoc as "an * implementation-specific approximation of the amount of storage consumed * by the specified object"). * @throws IllegalStateException Thrown if my Instrumentation is null. */ public static long getObjectSize(final Object object) { if (globalInstrumentation == null) { throw new IllegalStateException("Agent not initialized."); } return globalInstrumentation.getObjectSize(object); } } The agent class above exposes a statically available method for accessing Instrumentation.getObjectSize(Object). The next code listing demonstrates a simple 'application' that makes use of it. package dustin.examples; import static java.lang.System.out; import java.math.BigDecimal; import java.util.ArrayList; import java.util.Calendar; import java.util.List; /** * Build up some sample objects and throw them at the Instrumentation example. * * Might run this class as shown next: * java -javaagent:dist\agent.jar -cp dist\agent.jar dustin.examples.InstrumentSampleObjects * * @author Dustin */ public class InstrumentSampleObjects { public enum Color { RED, WHITE, YELLOW } /** * Print basic details including size of provided object to standard output. * * @param object Object whose value and size are to be printed to standard * output. */ public static void printInstrumentationSize(final Object object) { out.println( "Object of type '" + object.getClass() + "' has size of " + InstrumentationAgent.getObjectSize(object) + " bytes."); } /** * Main executable function. * * @param arguments Command-line arguments; none expected. */ public static void main(final String[] arguments) { final StringBuilder sb = new StringBuilder(1000); final boolean falseBoolean = false; final int zeroInt = 0; final double zeroDouble = 0.0; final Long zeroLong = 0L; final long zeroLongP = 0L; final Long maxLong = Long.MAX_VALUE; final Long minLong = Long.MIN_VALUE; final long maxLongP = Long.MAX_VALUE; final long minLongP = Long.MIN_VALUE; final String emptyString = ""; final String string = "ToBeOrNotToBeThatIsTheQuestion"; final String[] strings = {emptyString, string, "Dustin"}; final String[] moreStrings = new String[1000]; final List someStrings = new ArrayList(); final EmptyClass empty = new EmptyClass(); final BigDecimal bd = new BigDecimal("999999999999999999.99999999"); final Calendar calendar = Calendar.getInstance(); printInstrumentationSize(sb); printInstrumentationSize(falseBoolean); printInstrumentationSize(zeroInt); printInstrumentationSize(zeroDouble); printInstrumentationSize(zeroLong); printInstrumentationSize(zeroLongP); printInstrumentationSize(maxLong); printInstrumentationSize(maxLongP); printInstrumentationSize(minLong); printInstrumentationSize(minLongP); printInstrumentationSize(maxLong); printInstrumentationSize(maxLongP); printInstrumentationSize(emptyString); printInstrumentationSize(string); printInstrumentationSize(strings); printInstrumentationSize(moreStrings); printInstrumentationSize(someStrings); printInstrumentationSize(empty); printInstrumentationSize(bd); printInstrumentationSize(calendar); printInstrumentationSize(Color.WHITE); } } To use the instrumentation agent via the command-line start-up, I need to ensure that a simple metafile is included in the agent JAR. It might look like what follows in the next code listing for the agent class in this case (dustin.examples.InstrumentationAgent). Although I only need the Premain-class entry for the command-line startup of the agent, I have included Agent-class as an example of how to use the post JVM startup agent. It doesn't hurt anything to have both present just as it did not hurt anything to have both premain and agentmain methods defined in the object class. There are prescribed rules for which of these is first attempted based on the type of agent being used. Premain-class: dustin.examples.InstrumentationAgent Agent-class: dustin.examples.InstrumentationAgent To place this manifest file into the JAR, I could use the jar cmf with the name of the manifest file and the Java classes to be archived into the JAR. However, it's arguably easier to do with Ant and certainly is preferred for repeatedly doing this. A simple use of the Ant jar task with the manifest sub-element is shown next. With the JAR built, I can easily run it with the Java launcher and specifying the Java agent (-javaagent): java -javaagent:dist\Instrumentation.jar -cp Instrumentation.jar dustin.examples.InstrumentSampleObjects The next screen snapshot shows the output. The above output shows some of the estimated sizes of various objects such as BigDecimal, Calendar, and others. There are several useful resources related to the topic of this post. The java.sizeOf Project is "a little java agent what use the package java.lang.Instrument introduced in Java 5 and is released under GPL license." Dr. Heinz M. Kabutz's Instrumentation Memory Counter provides a significantly more sophisticated example than my post of using the Instrumentation interface to estimate object sizes. Instrumentation: querying the memory usage of a Java object provides a nice overview of this interface and provides a link to the Classmexer agent, "a simple Java instrumentation agent that provides some convenience calls for measuring the memory usage of Java objects from within an application." The posts How much memory the java objects consume? and Estimating the memory usage of a java object are also related. From http://marxsoftware.blogspot.com/2011/12/estimating-java-object-sizes-with.html

This Post is a continuation of my series on Google Guava, this time covering Guava Cache. Guava Cache offers more flexibility and power than either a HashMap or ConcurrentHashMap, but is not as heavy as using EHCache or Memcached (or robust for that matter, as Guava Cache operates solely in memory). The Cache interface has methods you would expect to see like ‘get’, and ‘invalidate’. A method you won’t find is ‘put’, because Guava Cache is ‘self-populating’, values that aren’t present when requested are fetched or calculated, then stored. This means a ‘get’ call will never return null. In all fairness, the previous statement is not %100 accurate. There is another method ‘asMap’ that exposes the entries in the cache as a thread safe map. Using ‘asMap’ will result in not having any of the self loading operations performed, so calls to ‘get’ will return null if the value is not present (What fun is that?). Although this is a post about Guava Cache, I am going to spend the bulk of the time talking about CacheLoader and CacheBuilder. CacheLoader specifies how to load values, and CacheBuilder is used to set the desired features and actually build the cache. CacheLoader CacheLoader is an abstract class that specifies how to calculate or load values, if not present. There are two ways to create an instance of a CacheLoader: Extend the CacheLoader class Use the static factory method CacheLoader.from If you extend CacheLoader you need to override the V load(K key) method, instructing how to generate the value for a given key. Using the static CacheLoader.from method you build a CacheLoader either by supplying a Function or Supplier interface. When supplying a Function object, the Function is applied to the key to calculate or retrieve the results. Using a Supplier interface the value is obtained independent of the key. CacheBuilder The CacheBuilder is used to construct cache instances. It uses the fluent style of building and gives you the option of setting the following properties on the cache: Cache Size limit (removals use a LRU algorithm) Wrapping keys in WeakReferences (Strong references used by default for keys) Wrapping values in either WeakReferences or SoftReferences (Strong references used by default) Time to expire entires after last access Time based expiration of entries after being written or updated Setting a RemovalListener that can recieve events once an entry is removed from the cache Concurrency Level of the cache (defaults to 4) The concurrency level option is used to partition the table internally such that updates can occur without contention. The ideal setting would be the maximum number of threads that could potentially access the cache at one time. Here is an example of a possible usage scenario for Guava Cache. public class PersonSearchServiceImpl implements SearchService> { public PersonSearchServiceImpl(SampleLuceneSearcher luceneSearcher, SampleDBService dbService) { this.luceneSearcher = luceneSearcher; this.dbService = dbService; buildCache(); } @Override public List search(String query) throws Exception { return cache.get(query); } private void buildCache() { cache = CacheBuilder.newBuilder().expireAfterWrite(10, TimeUnit.MINUTES) .maximumSize(1000) .build(new CacheLoader>() { @Override public List load(String queryKey) throws Exception { List ids = luceneSearcher.search(queryKey); return dbService.getPersonsById(ids); } }); } } In this example, I am setting the cache entries to expire after 10 minutes of being written or updated in the cache, with a maximum amount of 1,000 entires. Note the usage of CacheLoader on line 15. RemovalListener The RemovalListener will receive notification of an item being removed from the cache. These notifications could be from manual invalidations or from a automatic one due to time expiration or garbage collection. The RemovalListener parameters can be set to listen for specific type. To receive notifications for any key or value set them to use Object. It should be noted here that a RemovalListener will receive a RemovalNotification object that implements the Map.Entry interface. The key or value could be null if either has already been garbage collected. Also the key and value object will be strong references, regardless of the type of references used by the cache. CacheStats There is also a very useful class CacheStats that can be retrieved via a call to Cache.stats(). The CacheStats object can give insight into the effectiveness and performance of your cache by providing statistics such as: hit count miss count total load timme total requests CacheStats provides many other counts in addition to the ones listed above. Conclusion The Guava Cache presents some very compelling functionality. The decision to use a Guava Cache really comes down to the tradeoff between memory availability/usage versus increases in performance. I have added a unit test CacheTest demonstrating the usages discussed here. As alway comments and suggestions are welcomed. Thanks for your time. Resources Guava Project Home Cache API Source Code for blog series From http://codingjunkie.net/google-guava-cache/

This is the sixth of a series of articles about setting up a secure RESTful Web Service using Spring 3.1 and Spring Security 3.1. A previous article introduced security in the context of a RESTful service, using form-based authentication. This article will focus on configuration of Basic and Digest authentication and on configuring both protocols for the same URI mapping of the API, using Spring Security 3.1. The REST with Spring series: Part 1 – Bootstrapping a web application with Spring 3.1 and Java based Configuration Part 2 – Building a RESTful Web Service with Spring 3.1 and Java based Configuration Part 3 – Securing a RESTful Web Service with Spring Security 3.1 Part 4 – RESTful Web Service Discoverability Part 5 – REST Service Discoverability with Spring Configuration of Basic Authentication In part 3 of the series, the Spring Security configuration was done using form based authentication, which is not really ideal for a RESTful service. To start setting up basic authentication, first we remove the old custom entry point and filter from the main security element: Note how support for basic authentication has been added with a single configuration line – – which handles the creation and wiring of both the BasicAuthenticationFilter and the BasicAuthenticationEntryPoint. Satisfying the stateless constraint – getting rid of sessions One of the main constraints of the RESTful architectural style is that the client-server communication is fully stateless, as the original dissertation reads: 5.1.3 Stateless We next add a constraint to the client-server interaction: communication must be stateless in nature, as in the client-stateless-server (CSS) style of Section 3.4.3 (Figure 5-3), such that each request from client to server must contain all of the information necessary to understand the request, and cannot take advantage of any stored context on the server. Session state is therefore kept entirely on the client. The concept of Session on the server is one with a long history in Spring Security, and removing it entirely has been difficult until now, especially when configuration was done by using the namespace. However, Spring Security 3.1 augments the namespace configuration with a new stateless option for session creation, which effectively guarantees that no session will be created or used by Spring. What this new option does is completely removes all session related filters from the security filter chain, ensuring that authentication is performed for each request. Configuration of Digest Authentication Starting with the previous configuration, the filter and entry point necessary to set up digest authentication will be defined as beans. Then, the digest entry point will override the one created by behind the scenes. Finally, the custom digest filter will be introduced in the security filter chain using the after semantics of the security namespace to position it directly after the basic authentication filter. Unfortunately there is no support in the security namespace to automatically configure the digest authentication the way basic authentication can be configured with . Because of that, the necessary beans had to be defined and wired manually into the security configuration. Supporting both authentication protocols in the same RESTful service Basic or Digest authentication alone can be easily implemented in Spring Security 3.x; it is supporting both of them for the same RESTful web service, on the same URI mappings that introduces a new level of complexity into the configuration and testing of the service. Anonymous request With both basic and digest filters in the security chain, the way a anonymous request – a request containing no authentication credentials (Authorization HTTP header) – is processed by Spring Security is – the two authentication filters will find no credentials and will continue execution of the filter chain. Then, seeing how the request wasn’t authenticated, an AccessDeniedException is thrown and caught in the ExceptionTranslationFilter, which commences the digest entry point, prompting the client for credentials. The responsibilities of both the basic and digest filters are very narrow – they will continue to execute the security filter chain if they are unable to identify the type of authentication credentials in the request. It is because of this that Spring Security can have the flexibility to be configured with support for multiple authentication protocols on the same URI. When a request is made containing the correct authentication credentials – either basic or digest – that protocol will be rightly used. However, for an anonymous request, the client will get prompted only for digest authentication credentials. This is because the digest entry point is configured as the main and single entry point of the Spring Security chain; as such digest authentication can be considered the default. Request with authentication credentials A request with credentials for Basic authentication will be identified by the Authorization header starting with the prefix “Basic”. When processing such a request, the credentials will be decoded in the basic authentication filter and the request will be authorized. Similarly, a request with credentials for Digest authentication will use the prefix “Digest” for it’s Authorization header. Testing both scenarios The tests will consume the REST service by creating a new resource after authenticating with either basic or digest: @Test public void givenAuthenticatedByBasicAuth_whenAResourceIsCreated_then201IsReceived(){ // Given // When Response response = given() .auth().preemptive().basic( ADMIN_USERNAME, ADMIN_PASSWORD ) .contentType( HttpConstants.MIME_JSON ).body( new Foo( randomAlphabetic( 6 ) ) ) .post( this.paths.getFooURL() ); // Then assertThat( response.getStatusCode(), is( 201 ) ); } @Test public void givenAuthenticatedByDigestAuth_whenAResourceIsCreated_then201IsReceived(){ // Given // When Response response = given() .auth().digest( ADMIN_USERNAME, ADMIN_PASSWORD ) .contentType( HttpConstants.MIME_JSON ).body( new Foo( randomAlphabetic( 6 ) ) ) .post( this.paths.getFooURL() ); // Then assertThat( response.getStatusCode(), is( 201 ) ); } Note that the test using basic authentication adds credentials to the request preemptively, regardless if the server has challenged for authentication or not. This is to ensure that the server doesn’t need to challenge the client for credentials, because if it did, the challenge would be for Digest credentials, since that is the default. Conclusion This article covered the configuration and implementation of both Basic and Digest authentication for a RESTful service, using mostly Spring Security 3.0 namespace support as well as some new features added by Spring Security 3.1. In the next articles I will focus on OAuth authentication. In the meantime, check out the github project. From the REST with Spring series.

In statically typed languages, each variable must have a minimal type known at compile time. PHP instead, a is dynamic language where variable can contain any object, and the only enforcement of an interface can be performed on method parameters via type hinting. Statically typed languages sometimes encounter the problem of downcasting: the compiler is only able to guarantee a basic type, and the object contained instead is an instance of a richer subtype. A Java example can be a collection of Object instances where some of them are actually a String: to obtain a String instance to be able to call string.startsWith("prefix_"), the code using the collection needs a down cast: String myString = (String) myObject; This problem was really diffused in old Java code (before Generics introduction) and still today in some cases. What about PHP? You'll never need to downcast objects: variables can contain handlers to objects or even scalars without compile-time checks. Casting with (ClassName) is not even supported by the language (while casting a non-object with (object) will give you a stdClass.) Downcasting however means to promote a variable from a stricter interface to a richer one: we will apply this refactoring to scalars and their OO equivalents, Value Objects. Note that in Fowler's book downcasting is applied only to objects: the same instance just aquires a new (larger) interface. Since this casting is absent in PHP and the type coincide with the current content of the variable, we will talk about conversions of variables to different types. Scalars First of all, you may need to cast scalar variables to other types (e.g. integer to boolean). PHP rules tell us how they are evaluated in its specification for type juggling. Encapsulate Downcast is equally valid when we want to convert a type and only want to expose the right one. For example, we want to avoid this smelly code: public function isASeatAvailable() { return $this->numberOfSeats - 42; // 42 is a total of sold tickets } $result = (bool) $theater->isASeatAvailable(); The (bool) cast will be spread throughout all the client code calling $object. The logic of the refactoring is the same as for the casts on objects: encapsulating them into the method results in a cleaner API and the lack of duplication of the cast in all the client code. Value Objects Another form of casting/conversion that we need in hybrid languages like PHP is the conversion of a primitive (scalar or array) value into an object (Value Object usually). Sometimes this conversion gets duplicated like for the case of casting primitives: $topic = new Topic($object->getAllPosts()); $firstPage = new Topic($topic->getPart($offset = 0, $limit = 10)); A simple reason for why this happens in this little example is that the the Topic object, representing a collection of Posts, gets introduced into the codebase to host some new methods that make sense only on a set of Posts. However, it is not introduced in all the code, since it will take long for such a refactoring to be completed. The result is that conversions to and from the primitive structure flourish; what we want to target with this refactoring is to encapsulate the initial conversions as much as possible, an only work with a closed algebra of objects in all the rest of the code: /** @var Topic */ $topic = $object->getAllPosts(); /** @var Topic */ $firstPage = $topic->getPart(0, 10); /** @var Topic */ $filteredTopic = $topic->getSelectedPostsForQuery("refactoring"); Docblocks Docblocks applied to methods have also to be modified to reflect into the API documentation what you're returning (an object, a Traversable, an IteratorAggregate or a MyIterator). Thus this refactoring affects them. While the @return information is embodied into the code in statically typed languages, PHP gives you freedom to return whichever type you need but does not provide a formal way to document the choices. The standard however, is the @return annotation: /** * @return Traversable containing strings */ public function threadTitles() { ... } Steps The most important step in applying this refactoring is to identify the cases where it would work. There are many possible smells: new MyClass(...) statements often executed on the result of a method. Value Objects having many getters for their fields, or calculated fields, can often return another Value Object; look for duplicated logic on the client code. Ultimately (the other way around), any method returning an array or scalar value is a suspect. The second step is moving the down cast into the method. This mean modifying both the call and for objects, while you can do one step at the time in the case of scalar casting due to the (type) operation being idempotent. Finally, remember to update the docblock of the modified methods accordingly. Example In the example, we target the most useful case: a Value Object whose creation from its primitive value should be encapsulated in a method. This object models a license plate used in a Car. I just implemented the most basic case of advancement of a plate (it will overflow after 26 next() calls), to keep this code simple and to the point. We see next() is the target of our refactoring. next()); $this->assertEquals(new Plate('AB123XZ'), $newPlate); } } class Plate { private $value; public function __construct($value) { $this->value = $value; } /** * @return string */ public function next() { // we're dealing just with the basic case $lastLetter = substr($this->value, -1); $lastLetter++; $nextValue = substr_replace($this->value, $lastLetter, -1); return $nextValue; } } In a single step we can keep the test passing. We modify what is expected by the client code, now a Plate instance: next(); $this->assertEquals(new Plate('AB123XZ'), $newPlate); } } We modify the docblock, in particular @return, and we perform the instantiation inside the method. class Plate { private $value; public function __construct($value) { $this->value = $value; } /** * @return Plate */ public function next() { // we're dealing just with the basic case $lastLetter = substr($this->value, -1); $lastLetter++; $nextValue = substr_replace($this->value, $lastLetter, -1); return new self($nextValue); } }

A string[] array and use a LINQ query expression to order its contents alphabetically. Note that we are ordering the strings, not the letters in the strings. using System; using System.Linq; class Program { static void Main() { string[] a = new string[] {"Indonesian","Korean","Japanese","English","German"}; var sort = from s in a orderby s select s; foreach (string c in sort) { Console.WriteLine(c); } } } /*OUTPUT English German Indonesian Japanese Korean */ Eclipse IDE and Eclipse

Frequently developers rely on 3d party libraries to avoid reinventing the wheel, particularly in the Java world, with projects like Apache and Spring so prevalent. When dealing with these frameworks, we often have little or no control of the behaviour of their classes. This can sometimes lead to problems. For instance, if you want to deep clone an object that doesn’t provide a suitable clone method, what are your options, short of writing a bunch of code? Clone through Serialization The simplest approach is to clone by taking advantage of an object being Serializable. Apache Commons provides a method to do this, but for completeness, code to do it yourself is below also. @SuppressWarnings("unchecked") public static T cloneThroughSerialize(T t) throws Exception { ByteArrayOutputStream bos = new ByteArrayOutputStream(); serializeToOutputStream(t, bos); byte[] bytes = bos.toByteArray(); ObjectInputStream ois = new ObjectInputStream(new ByteArrayInputStream(bytes)); return (T)ois.readObject(); } private static void serializeToOutputStream(Serializable ser, OutputStream os) throws IOException { ObjectOutputStream oos = null; try { oos = new ObjectOutputStream(os); oos.writeObject(ser); oos.flush(); } finally { oos.close(); } } // using our custom method Object cloned = cloneThroughSerialize (someObject); // or with Apache Commons cloned = org.apache.commons.lang. SerializationUtils.clone(someObject); But what if the class we want to clone isn’t Serializable and we have no control over the source code or can’t make it Serializable? Option 1 – Java Deep Cloning Library There’s a nice little library which can deep clone virtually any Java Object – cloning. It takes advantage of Java’s excellent reflection capabilities to provide optimized deep-cloned versions of objects. Cloner cloner=new Cloner(); Object cloned = cloner.deepClone(someObject); As you can see, it’s very simple and effective, and requires minimal code. It has some more advanced abilities beyond this simple example, which you can check out here. Option 2 – JSON Cloning What about if we are not able to introduce a new library to our codebase? Some of us deal with approval processes to introduce new libraries, and it may not be worth it for a simple use case. Well, as long as we have some way to serialize and restore an object, we can make a deep copy. JSON is commonly used, so it’s a good candidate,since most of us use one JSON library or another. Most JSON libraries in Java have the ability to effectively serialize any POJO without any configuration or mapping required. This means that if you have a JSON library and cannot or will not introduce more libraries to provide deep cloning, you can leverage an existing JSON library to get the same effect. Note this method will be slower than others, but for the vast majority of applications, this won’t cause any performance problems. Below is an example using the GSON library. @SuppressWarnings("unchecked") public static T cloneThroughJson(T t) { Gson gson = new Gson(); String json = gson.toJson(t); return (T) gson.fromJson(json, t.getClass()); } // ... Object cloned = cloneThroughJson(someObject); Note that this is likely only to work if the copied object has a default no-argument constructor. In the case of GSON, you can use an instance creator to get around this. Other frameworks have similar concepts, so you can use that if you hit an issue with an unmodifiable class having not having the default constructor. Conclusion One thing I do recommend is that for any classes you need to clone, you should add some unit tests to ensure everything behaves as expected. This can prevent changes to the classes (e.g. upgrading library versions) from breaking your application without your knowledge, especially if you have a continuous integration environment set up. I’ve outlined a couple methods to clone an object outside of normal cases without any custom code. If you’ve used any other methods to get the same result, please share. From http://www.carfey.com/blog/easy-deep-cloning-of-serializable-and-non-serializable-objects-in-java/

In this post I am going to explain URL rewriting in greater details. This post will contain basic of URL rewriting and will explain how we can do URL rewriting in fewer lines of code. Why we need URL rewriting? Let’s consider a simpler scenario we want to display a customer details on a ASP.NET Page so how our page will know that for which customer we need to display details? The simplest way of doing is to use query string we will pass a customer id which uniquely identifies customer in query string. So our url will look like this. Customer.aspx?Id=1 This will work but the problem with above URL is that its not user friendly and search engine friendly. who is going to remember that what query string parameter I am going to pass and why we need that parameter. Also when search engine will crawl this site it will going to read this URL blindly as this url is not informative because it query string is not readable for search engine crawlers. So your search engine will be ranked lower as this URL is not readable to search engine crawlers.Now when do a URL rewriting our URL will be cleaner shorter and simpler like this. Customers/Id/1/ Here anybody in world can understand it talking about customer and this page will used to show customer details.Even search engine crawler will also know that you are talking about customers. That is why we need URL rewriting. URL rewriting and ASP.NET In earlier versions of ASP.NET we have to write lots of code for URL rewriting but Now with ASP.NET 4.0 you can easily rewrite in fewer lines of code. So let’s start a Demo where I will demonstrate you how we can easily rewrite URLs. So let’s first create a ASP. NET web form application via File->New->Project and a dialog box will open just like below and then created a empty project called URL rewriting. After creating a project I have added global.asax – where we are going to write url mapping logic and then I have added an asp.net page called which will display customer information just like below. So everything is now ready let’s start writing code. First thing we need to do is to define routes. Route will map a URL to physical page.First I will create static function called Register route which map route to particular file and then I am going to call this from application_start event of global.asax. Following is code for that. using System; using System.Web.Routing; namespace UrlRewriting { public class Global : System.Web.HttpApplication { protected void Application_Start(object sender, EventArgs e) { RegisterRoutes(RouteTable.Routes); } public static void RegisterRoutes(RouteCollection routeCollection) { routeCollection.MapPageRoute("RouteForCustomer", "Customer/{Id}", "~/Customer.aspx"); } } } Now as mapping code has been done let’s right code for customer.aspx page. I have have following code in page_load event of customer.aspx using System; namespace UrlRewriting { public partial class Customer : System.Web.UI.Page { protected void Page_Load(object sender, EventArgs e) { string id = Page.RouteData.Values["Id"].ToString(); Response.Write("Customer Details page"); Response.Write(string.Format("Displaying information for customer : {0}",id)); } } } Here in above code you can see that I am getting value from page route data and then just printing it. In real world it will fetch customer data from database and show customer details on page. Now let’s run that application. It will print a details of customer as I have passed Id in URL suppose you pass 1 as id in URL then it will look like following. Now if you put 2 in url it will print information about customer 2. That’s it. So we have enabled URL rewriting in asp.net in fewer lines of code. In next post I am going to explain redirection with URL rewriting. Hope you like this post. Stay tuned for more.. Till then Happy programming

JSR 303 (Bean Validation) is the specification of the Java API for JavaBean validation in Java EE and Java SE. Simply put it provides an easy way of ensuring that the properties of your JavaBean(s) have the right values in them. This post aims to show you how to use the Bean Validation API in your project. To begin, imagine that you were building the next Facebook and you would need member(s) to register to use your application. In order to successfully register, prospective member(s) have to provide the following: a last name, a first name, a gender, an email address and a date of birth. In addition, the individual who is registering must be between 18 and 150 years inclusive. Prior to JSR 303, you probably would have needed a bunch of if-else statements to achieve the above requirements. Thankfully, not any more. We will begin by creating a JavaBean named 'Member' that would hold all the properties we are interested in. package validationapiblog.model; import java.util.Date; import validationapiblog.enums.Gender; /** * * @author Adedayo Ominiyi */ public class Member { private String lastName = null; private String firstName = null; private Gender gender = null; private String emailAddress = null; private Date dateOfBirth = null; public Member() { } public String getFirstName() { return firstName; } public void setFirstName(String firstName) { this.firstName = firstName; } public Gender getGender() { return gender; } public void setGender(Gender gender) { this.gender = gender; } public String getLastName() { return lastName; } public void setLastName(String lastName) { this.lastName = lastName; } public Date getDateOfBirth() { return dateOfBirth; } public void setDateOfBirth(Date dateOfBirth) { this.dateOfBirth = dateOfBirth; } public Integer getAge() { if (this.dateOfBirth != null) { // calculate age of member here } return null; } public String getEmailAddress() { return emailAddress; } public void setEmailAddress(String emailAddress) { this.emailAddress = emailAddress; } } The gender property is a simple enum and is shown below package validationapiblog.enums; /** * * @author Adedayo Ominiyi */ public enum Gender { MALE, FEMALE; } Now that we have the pieces to the puzzle. The next step is to download an implementation of JSR 303. For this post we would be using the reference implementation namely Hibernate Validator. The version as at the time this post was written is 4.2.0 Final. After downloading it you should add the following 4 jars to the classpath of your project: hibernate-validator-4.2.0.Final.jar hibernate-validator-annotation-processor-4.2.0.Final.jar slf4j-api-1.6.1.jar validation-api-1.0.0.GA.jar Once this is done, you simply annotate the 'Member' JavaBean we created earlier to indicate which properties need be validated. You can annotate either the fields or the accessor (or getter) methods of the JavaBean. In this post I will be annotating the accessor methods. package validationapiblog.model; import java.util.Date; import javax.validation.constraints.Max; import javax.validation.constraints.Min; import javax.validation.constraints.NotNull; import javax.validation.constraints.Past; import javax.validation.constraints.Pattern; import org.hibernate.validator.constraints.Email; import org.hibernate.validator.constraints.NotBlank; import validationapiblog.enums.Gender; /** * * @author Adedayo Ominiyi */ public class Member { private String lastName = null; private String firstName = null; private Gender gender = null; private String emailAddress = null; private Date dateOfBirth = null; public Member() { } @NotNull(message = "First name is compulsory") @NotBlank(message = "First name is compulsory") @Pattern(regexp = "[a-z-A-Z]*", message = "First name has invalid characters") public String getFirstName() { return firstName; } public void setFirstName(String firstName) { this.firstName = firstName; } @NotNull(message = "Gender is compulsory") public Gender getGender() { return gender; } public void setGender(Gender gender) { this.gender = gender; } @NotNull(message = "Last name is compulsory") @NotBlank(message = "Last name is compulsory") @Pattern(regexp = "[a-z-A-Z]*", message = "Last name has invalid characters") public String getLastName() { return lastName; } public void setLastName(String lastName) { this.lastName = lastName; } @Past(message = "Date of Birth must be the past") @NotNull public Date getDateOfBirth() { return dateOfBirth; } public void setDateOfBirth(Date dateOfBirth) { this.dateOfBirth = dateOfBirth; } @Min(value = 18, message = "Age must be greater than or equal to 18") @Max(value = 150, message = "Age must be less than or equal to 150") public Integer getAge() { if (this.dateOfBirth != null) { // calculate age of member here } return null; } @NotNull(message="Email Address is compulsory") @NotBlank(message="Email Address is compulsory") @Email(message = "Email Address is not a valid format") public String getEmailAddress() { return emailAddress; } public void setEmailAddress(String emailAddress) { this.emailAddress = emailAddress; } } Please note that these are just some of the annotations available in JSR 303. In addition Hibernate Validator introduces a few of its own that are not in the specification. Feel free to study the annotations not in this post in your free time you might find something interesting. There is also the ability to create your own custom validator if the need arises. Now lets review the annotations used: @NotNull - Checks that the annotated value is not null. Unfortunately it doesn't check for empty string values @Pattern - Checks if the annotated string matches the regular expression given. We used it to ensure that the last name and first name properties have valid string values @Past - The annotated element must be a date in the past. @Min - The annotated element must be a number whose value must be greater or equal to the specified minimum @Max - The annotated element must be a number whose value must be lower or equal to the specified maximum @NotBlank - Checks that the annotated string is not null and the trimmed length is greater than 0. This annotation is not in JSR 303 @Email - Checks whether the specified string is a valid email address. This annotation is also not in JSR 303 To test the validation we could use a unit test as shown below. package validationapiblog.test; import java.util.Set; import javax.validation.ConstraintViolation; import javax.validation.Validation; import javax.validation.Validator; import javax.validation.ValidatorFactory; import validationapiblog.model.Member; import org.junit.Test; import static org.junit.Assert.*; /** * * @author Adedayo Ominiyi */ public class ValidationAPIUnitTest { public ValidationAPIUnitTest() { } @Test public void testMemberWithNoValues() { Member member = new Member(); // validate the input ValidatorFactory factory = Validation.buildDefaultValidatorFactory(); Validator validator = factory.getValidator(); Set> violations = validator.validate(member); assertEquals(violations.size(), 5); } } In conclusion, you should experiment with JSR 303 and see for yourself which annotations you like. Thank you and have fun. Original URL: Bean Validation Made Simple With JSR 303

// A fairly generic method to store arrays and also to add them to a pool to reverse lookup their ids based on values that they contain. This method extends my own redis client but will work for the better clients out there such as predis. class storage extends redis { public function save($key, array $object, $timestamp=true){ $timestamp && $object['timestamp'] = date('Ymdhis'); $id = $this->incr('id:'.$key); foreach ($object as $k => $v) { $this->sadd(sprintf("%s:%s:%s", $key, $k, $v), $id); } $key = sprintf("%s:%s", $key, $id); $this->hmset($key, $object); } }

In this post I will demonstrate how to leverage the -episode XJC extension to reuse classes previously generated from.an XML schema. This is useful when an XML schema is imported by other XML schemas and you do not want the same classes generated each time. Imported Schema (Product.xsd) The following XML schema represents basic information about a product. Product is a common concept in this example domain so I have decided to define one representation that can be leveraged by other schemas, rather than having each schema define its own representation of product information. Since multiple XML schemas import Product.xsd we can leverage episode files so that the classes corresponding to Product.xsd are only generated once. The following XJC call demonstrates how to generate an episode file called product.episode along with the generated classes: xjc -d out -episode product.episode Product.xsd Importing Schema (ProductPurchaseRequest.xsd) Below is an example of an XML schema that imports Product.xsd: When we generate classes from this XML schema we will reference the episode file we created when we generated Java classes from Product.xsd. If we do not specify the episode file then classes will be generated for both ProductPurchaseRequest.xsd and Product.xsd: xjc -d out ProductPurchaseRequest.xsd -extension -b product.episode Another Importing Schema (ProductQuoteRequest.xsd) Below is another example of an XML schema that imports Product.xsd: Again when we generate classes from this XML schema we will reference the episode file we created when we generated Java classes from Product.xsd. xjc -d out ProductQuoteRequest.xsd -extension -b product.episode How Does it Work? (product.episode) For those of you curious how this works. The episode file generated by XJC is really just a standard JAXB bindings file that is used to customize the class generation. This generated bindings/episode file contains entries that tells XJC that a class already exists for this type. You could write this file by hand, but -episode flag to XJC does it for you. From http://blog.bdoughan.com/2011/12/reusing-generated-jaxb-classes.html

This post examines what options one has for handling footnotes and references in HTML. It then presents a library that helps you with handling them. Requirements Handling footnotes and references comes with several requirements: On screen, one wants to show the footnote text as close as possible to the number pointing to the footnote. Whatever solution one chooses, it should also work on touch devices. Hence, a hover-only approach is not feasible. In print, footnotes should be shown, as well. Hence, a tooltip-only solution is not acceptable. Lastly, things should degrade gracefully if JavaScript is switched off. The HTML5 spec recommendations for footnotes The HTML5 specification gives several tips on how to format footnotes. Short inline annotations: title attribute. Customer: Hello! I wish to register a complaint. Hello. Miss? Shopkeeper: Watcha mean, miss? Customer: Uh, I'm sorry, I have a cold. I wish to make a complaint. Shopkeeper: Sorry, we're closing for lunch. Longer annotations: bidirectional linking via : Announcer: Number 16: The hand. Interviewer: Good evening. I have with me in the studio tonight Mr Norman St John Polevaulter, who for the past few years has been contradicting people. Mr Polevaulter, why do you contradict people? Norman: I don't. [1] Interviewer: You told me you did! ... [1] This is, naturally, a lie, but paradoxically if it were true he could not say so without contradicting the interviewer and thus making it false. Wikipedia-style highlighting of the currently active footnote The CSS pseudo-selector :target allows you to style the HTML element whose ID is the same as the page fragment identifier: li:target { background-color: #BFEFFF; } Thus, if the page URL ends with #explanation then the following list item would be highlighted: It works like this: ... Using the html_footnotes library You can download html_footnotes on GitHub and try it out online. Terminology: An annotation is either a footnote or a reference (citation). The markers in the main text referring to those annotations are called annotation pointers. A footnote pointer is a number written in parentheses. Example: (1) A reference pointer is a number written in square brackets. Example: [1] Activating the library: The library consists of CSS to style annotations and pointers and of JavaScript that post-processes the HTML so that less code has to be written. Footnotes: The library processes the HTML so that footnote pointers are formatted as superscript and become links that, when clicked on, display the text of the footnote inline. You can use an IIFE(1) to avoid the global namespace(2) being polluted. ... Footnotes IIFE is an acronym for Immediately-Invoked Function Expression.The global scope is reified as an object in JavaScript. References: Reference pointers are processed and become links. The library also adds IDs to the reference list items. Due to the appropriate CSS, a list item will be highlighted and scrolled to if one clicks on a pointer. JavaScript has many functional language constructs [1]. For example: consult [2] for an introduction to closures. ... References Functional programming. In Wikipedia. Retrieved 2011-12-03.Douglas Crockford, JavaScript: The Good Parts. O’Reilly. 2008-05-16. Source: http://www.2ality.com/2011/12/footnotes.html

this post presents an analysis of mysql (a relational database) and neo4j (a graph database) in a side-by-side comparison on a simple graph traversal. the data set that was used was an artificially generated graph with natural statistics. the graph has 1 million vertices and 4 million edges. the degree distribution of this graph on a log-log plot is provided below. a visualization of a 1,000 vertex subset of the graph is diagrammed above. loading the graph the graph data set was loaded both into mysql and neo4j. in mysql a single table was used with the following schema. create table graph ( outv int not null, inv int not null ); create index outv_index using btree on graph (outv); create index inv_index using btree on graph (inv); after loading the data, the table appears as below. the first line reads: “vertex 0 is connected to vertex 1.” mysql> select * from graph limit 10; +------+-----+ | outv | inv | +------+-----+ | 0 | 1 | | 0 | 2 | | 0 | 6 | | 0 | 7 | | 0 | 8 | | 0 | 9 | | 0 | 10 | | 0 | 12 | | 0 | 19 | | 0 | 25 | +------+-----+ 10 rows in set (0.04 sec) the 1 million vertex graph data set was also loaded into neo4j. in gremlin , the graph edges appear as below. the first line reads: “vertex 0 is connected to vertex 992915.” gremlin> g.e[1..10] ==>e[183][0-related->992915] ==>e[182][0-related->952836] ==>e[181][0-related->910150] ==>e[180][0-related->897901] ==>e[179][0-related->871349] ==>e[178][0-related->857804] ==>e[177][0-related->798969] ==>e[176][0-related->773168] ==>e[175][0-related->725516] ==>e[174][0-related->700292] warming up the caches before traversing the graph data structure in both mysql and neo4j, each database had a “ warm up ” procedure run on it. in mysql, a “select * from graph” was evaluated and all of the results were iterated through. in neo4j, every vertex in the graph was iterated through and the outgoing edges of each vertex were retrieved. finally, for both mysql and neo4j, the experiment discussed next was run twice in a row and the results of the second run were evaluated. traversing the graph the traversal that was evaluated on each database started from some root vertex and emanated n-steps out. there was no sorting, no distinct-ing, etc. the only two variables for the experiments are the length of the traversal and the root vertex to start the traversal from. in mysql, the following 5 queries denote traversals of length 1 through 5. note that the “?” is a variable parameter of the query that denotes the root vertex. select a.inv from graph as a where a.outv=? select b.inv from graph as a, graph as b where a.inv=b.outv and a.outv=? select c.inv from graph as a, graph as b, graph as c where a.inv=b.outv and b.inv=c.outv and a.outv=? select d.inv from graph as a, graph as b, graph as c, graph as d where a.inv=b.outv and b.inv=c.outv and c.inv=d.outv and a.outv=? select e.inv from graph as a, graph as b, graph as c, graph as d, graph as e where a.inv=b.outv and b.inv=c.outv and c.inv=d.outv and d.inv=e.outv and a.outv=? for neo4j, the blueprints pipes framework was used. a pipe of length n was constructed using the following static method. public static pipeline createpipeline(final integer steps) { final arraylist pipes = new arraylist(); for (int i = 0; i < steps; i++) { pipe pipe1 = new vertexedgepipe(vertexedgepipe.step.out_edges); pipe pipe2 = new edgevertexpipe(edgevertexpipe.step.in_vertex); pipes.add(pipe1); pipes.add(pipe2); } return new pipeline(pipes); } for both mysql and neo4j, the results of the query (sql and pipes) were iterated through. thus, all results were retrieved for each query. in mysql, this was done as follows. while (resultset.next()) { resultset.getint(finalcolumn); } in neo4j, this is done as follows. while (pipeline.hasnext()) { pipeline.next(); } experimental results the artificial graph dataset was constructed with a “ rich get richer “, preferential attachment model . thus, the vertices created earlier are the most dense (i.e. highest number of adjacent vertices). this property was used to limit the amount of time it would take to evaluate the tests for each traversal. only the first 250 vertices were used as roots of the traversals. before presenting timing results, note that all of these experiments were run on a macbook pro with a 2.66ghz intel core 2 duo and 4gigs of ram at 1067 mhz ddr3. the packages used were java 1.6, mysql jdbc 5.0.8, and blueprints pipes 0.1.2. java version "1.6.0_17" java(tm) se runtime environment (build 1.6.0_17-b04-248-10m3025) java hotspot(tm) 64-bit server vm (build 14.3-b01-101, mixed mode) the following java virtual machine parameters were used: -xmx1000m -xms500m below are the total running times for both mysql (red) and neo4j (blue) for traversals of length 1, 2, 3, and 4. the raw data is presented below along with the total number of vertices returned by each traversal—which, of course, is the same for both mysql and neo4j given that its the same graph data set being processed. also realize that traversals can loop and thus, many of the same vertices are returned multiple times. finally, note that only neo4j has the running time for a traversal of length 5. mysql did not finish after waiting 2 hours to complete. in comparison, neo4j took 14.37 minutes to complete a 5 step traversal. [mysql steps-1] time(ms):124 -- vertices_returned:11360 [mysql steps-2] time(ms):922 -- vertices_returned:162640 [mysql steps-3] time(ms):8851 -- vertices_returned:2206437 [mysql steps-4] time(ms):112930 -- vertices_returned:28125623 [mysql steps-5] n/a [neo4j steps-1] time(ms):27 -- vertices_returned:11360 [neo4j steps-2] time(ms):474 -- vertices_returned:162640 [neo4j steps-3] time(ms):3366 -- vertices_returned:2206437 [neo4j steps-4] time(ms):49312 -- vertices_returned:28125623 [neo4j steps-5] time(ms):862399 -- vertices_returned:358765631 next, the individual data points for both mysql and neo4j are presented in the plot below. each point denotes how long it took to return n number of vertices for the varying traversal lengths. finally, the data below provides the number of vertices returned per millisecond (on average) for each of the traversals. again, mysql did not finish in its 2 hour limit for a traversal of length 5. [mysql steps-1] vertices/ms:91.6128847554668 [mysql steps-2] vertices/ms:176.399127537985 [mysql steps-3] vertices/ms:249.286746556076 [mysql steps-4] vertices/ms:249.053599519823 [mysql steps-5] n/a [neo4j steps-1] vertices/ms:420.740351166341 [neo4j steps-2] vertices/ms:343.122344772028 [neo4j steps-3] vertices/ms:655.507125256186 [neo4j steps-4] vertices/ms:570.360621871775 [neo4j steps-5] vertices/ms:416.00886711325 conclusion in conclusion, given a traversal of an artificial graph with natural statistics, the graph database neo4j is more optimal than the relational database mysql. however, no attempts have been made to optimize the java vm, the sql queries, etc. these experiments were run with both neo4j and mysql “out of the box” and with a “natural syntax” for both types of queries. source: http://markorodriguez.com/2011/02/18/mysql-vs-neo4j-on-a-large-scale-graph-traversal/

In a previous post I covered how to use namespace qualification with JAXB. In this post I will cover how to control the prefixes that are used. This is not covered in the JAXB (JSR-222) specification but I will demonstrate the extensions available in both the reference and EclipseLink MOXy implementations for handling this use case Java Model The following domain model will be used for this post. The @XmlRootElement and @XmlElement annotation are used to specify the appropriate namespace qualification. package blog.prefix; import javax.xml.bind.annotation.XmlElement; import javax.xml.bind.annotation.XmlRootElement; @XmlRootElement(namespace="http://www.example.com/FOO") public class Root { private String a; private String b; private String c; @XmlElement(namespace="http://www.example.com/BAR") public String getA() { return a; } public void setA(String a) { this.a = a; } @XmlElement(namespace="http://www.example.com/FOO") public String getB() { return b; } public void setB(String b) { this.b = b; } @XmlElement(namespace="http://www.example.com/OTHER") public String getC() { return c; } public void setC(String c) { this.c = c; } } Demo Code We will use the following code to populate the domain model and produce the XML. package blog.prefix; import javax.xml.bind.JAXBContext; import javax.xml.bind.Marshaller; public class Demo { public static void main(String[] args) throws Exception { JAXBContext ctx = JAXBContext.newInstance(Root.class); Root root = new Root(); root.setA("A"); root.setB("B"); root.setC("OTHER"); Marshaller m = ctx.createMarshaller(); m.setProperty(Marshaller.JAXB_FORMATTED_OUTPUT, true); m.marshal(root, System.out); } } Output XML like the following is produced by default. The JAXB implementation has arbitrarily assigned prefixes to the namespace URIs specified in the domain model: A B OTHER Specify Prefix Mappings with JAXB RI & Metro JAXB The reference and Metro implementations of JAXB provide a mechanism called NamespacePrefixMapper to control the prefixes that will be assigned to namespaces. NamespacePrefixMapper package blog.prefix; import com.sun.xml.internal.bind.marshaller.NamespacePrefixMapper; //import com.sun.xml.bind.marshaller.NamespacePrefixMapper; public class MyNamespaceMapper extends NamespacePrefixMapper { private static final String FOO_PREFIX = ""; // DEFAULT NAMESPACE private static final String FOO_URI = "http://www.example.com/FOO"; private static final String BAR_PREFIX = "bar"; private static final String BAR_URI = "http://www.example.com/BAR"; @Override public String getPreferredPrefix(String namespaceUri, String suggestion, boolean requirePrefix) { if(FOO_URI.equals(namespaceUri)) { return FOO_PREFIX; } else if(BAR_URI.equals(namespaceUri)) { return BAR_PREFIX; } return suggestion; } @Override public String[] getPreDeclaredNamespaceUris() { return new String[] { FOO_URI, BAR_URI }; } } Demo Code The NamespacePrefixMapper is set on an instance of Marshaller. I would recommend wrapping the setPropery call in a try/catch block so that your application does not fail if you change JAXB implementations. package blog.prefix; import javax.xml.bind.JAXBContext; import javax.xml.bind.Marshaller; public class Demo { public static void main(String[] args) throws Exception { JAXBContext ctx = JAXBContext.newInstance(Root.class); Root root = new Root(); root.setA("A"); root.setB("B"); root.setC("OTHER"); Marshaller m = ctx.createMarshaller(); m.setProperty(Marshaller.JAXB_FORMATTED_OUTPUT, true); try { m.setProperty("com.sun.xml.internal.bind.namespacePrefixMapper", new MyNamespaceMapper()); //m.setProperty("com.sun.xml.bind.namespacePrefixMapper", new MyNamespaceMapper()); } catch(PropertyException e) { // In case another JAXB implementation is used } m.marshal(root, System.out); } } Output The resulting document now uses the NamespacePrefixMapper to determine the prefixes that should be used in the resulting document. A B OTHER Specify Prefix Mappings with EclipseLink JAXB (MOXy) MOXy will use the namespace prefixes as they are defined on the @XmlSchema annotation. In order for MOXy to be able to use the default namespace the elementFormDefault property on the @XmlSchema annotation must be set to XmlNsForm.QUALIFIED. package-info XmlSchema( elementFormDefault=XmlNsForm.QUALIFIED, namespace="http://www.example.com/FOO", xmlns={@XmlNs(prefix="bar", namespaceURI="http://www.example.com/BAR")} ) package blog.prefix; import javax.xml.bind.annotation.XmlNs; import javax.xml.bind.annotation.XmlNsForm; import javax.xml.bind.annotation.XmlSchema; Output The resulting document now uses the xmlns setting from the @XmlSchema annotation to determine the prefixes that should be used in the resulting document. A B OTHER Further Reading If you enjoyed this post then you may also be interested in: JAXB & Namespaces Specifying EclipseLink MOXy as Your JAXB Provider From http://blog.bdoughan.com/2011/11/jaxb-and-namespace-prefixes.html

Develop your own API service for your PHP projects.

In the scenario of today, two or more parameters are often passed together to a set of similar methods. This happens for example with timing information containing day and month, or hours and minutes; or, in other domains, with parameters that are coupled to each other - such as an host and a port (google.com, 80), or an image and its alt text. A long list of coupled parameters is not necessarily the sign that a method does too much. Today's refactoring is a solution to simplify the signature and express the coupling between the current parameters: wrapping them into a Parameter Object. Why writing code for a new class? We shouldn't be afraid of adding classes, at the similar pace as we add methods. When parameters are almost always passed together, they will be written down together in each signature and each call: it's a form of duplication and as such can and should be eliminated. Moreover, the duplication is not limited to a single method: the set of coupled arguments can be passed to multiple methods, each called in many more places which must be synchronized. For example, adding a parameter in the initial situation means modifying lots of different source files. The parameters are often the sign of an hidden concept: an object modelling their union. You know you are on the right track if a name for this concepts comes up quickly; otherwise you will have to invent it. This refactoring enables you to put more logic on an object representing this set of values, instead of passing them around in an array (Primitive Obsession) or, like in this case, always together as multiple parameters. The end result is also a shorter and more clear parameter list, again reaching the goal of simplifying method calls as we are doing with lots of refactorings in this part of the series. Steps Create a new class: an instance of this class should wrap the various values which are passed to it in the constructor. The Parameter Object will usually be a Value Object, with an immutable state and with getters for each of its fields (for now). Execute Add Parameter to pass in also the new object (created on the spot) together with the various parameters. For each of the old parameters, apply Remove Parameter on it and access it inside the method by calling a getter on the Parameter Object. The tests should always pass between the steps. The final step enabled by this refactoring consists in moving logic onto the Parameter Object. If you're lucky, this even leads to some of the getters vanishing. Example We have an Invoice object, which accepts some rows in order to calculate a total. A copious amount of money covering the Value Added Tax is added to the net total. addRow(1000); $quotation->specifyTaxes(20, 'VATCODE'); $this->assertEquals(1200, $quotation->getTotal()); $this->assertEquals('Type: VATCODE', $quotation->getTypeOfService()); } } class Quotation { private $netTotal = 0; private $vatPercentage; private $vatCode; public function addRow($row) { // including just the logic to implement the test we have $this->netTotal += $row; } public function specifyTaxes($percentage, $code) { $this->vatPercentage = $percentage; $this->vatCode = $code; } public function getTotal() { return $this->netTotal * (1 + $this->vatPercentage / 100); } public function getTypeOfService() { return 'Type: ' . $this->vatCode; } } We notice two things: one in the rest of the code (not shown here): the 20% percentage and its related code are passed together to many methods. It makes sense, as different codes (bread vs. cars) may imply different tax percentages. in the class itself, the fields storing tax informations have very similar names: $vatRate and $vatCode. This is a mild form of duplication. So we want to transform the couple of parameters into a Parameter Object. We create the class we need: class VatRate { private $rate; private $code; public function __construct($rate, $code) { $this->rate = $rate; $this->code = $code; } public function getRate() { return $this->rate; } public function getCode() { return $this->code; } } Now we can add a parameter to the method, which is an instance of our Parameter Object: addRow(1000); $quotation->specifyTaxes(new VatRate(20, 'VATCODE'), 20, 'VATCODE'); $this->assertEquals(1200, $quotation->getTotal()); $this->assertEquals('Type: VATCODE', $quotation->getTypeOfService()); } } class Quotation { private $netTotal = 0; private $vatRate; private $vatPercentage; private $vatCode; public function addRow($row) { // including just the logic to implement the test we have $this->netTotal += $row; } public function specifyTaxes(VatRate $vatRate, $percentage, $code) { $this->vatRate = $vatRate; $this->vatPercentage = $percentage; $this->vatCode = $code; } public function getTotal() { return $this->netTotal * (1 + $this->vatPercentage / 100); } public function getTypeOfService() { return 'Type: ' . $this->vatCode; } } Invoice objects have all the information they need, available from the VatRate instance. So let's remove $percentage, the first parameter wrapped into the Parameter Object: class Quotation { private $netTotal = 0; private $vatRate; private $vatPercentage; private $vatCode; public function addRow($row) { // including just the logic to implement the test we have $this->netTotal += $row; } public function specifyTaxes(VatRate $vatRate, $code) { $this->vatRate = $vatRate; $this->vatCode = $code; } public function getTotal() { return $this->netTotal * (1 + $this->vatRate->getRate() / 100); } public function getTypeOfService() { return 'Type: ' . $this->vatCode; } } And now we can also remove $code, the other parameter: class Quotation { private $netTotal = 0; private $vatRate; public function addRow($row) { // including just the logic to implement the test we have $this->netTotal += $row; } public function specifyTaxes(VatRate $vatRate) { $this->vatRate = $vatRate; } public function getTotal() { return $this->netTotal * (1 + $this->vatRate->getRate() / 100); } public function getTypeOfService() { return 'Type: ' . $this->vatRate->getCode(); } } We notice this refactoring has enabled a further step: moving the calculation of the tax into VatRate. This also means we can delete the getRate() method. class Quotation { private $netTotal = 0; private $vatRate; public function addRow($row) { // including just the logic to implement the test we have $this->netTotal += $row; } public function specifyTaxes(VatRate $vatRate) { $this->vatRate = $vatRate; } public function getTotal() { return $this->vatRate->tax($this->netTotal); } public function getTypeOfService() { return 'Type: ' . $this->vatRate->getCode(); } } class VatRate { private $rate; private $code; public function __construct($rate, $code) { $this->rate = $rate; $this->code = $code; } public function getCode() { return $this->code; } public function tax($netAmount) { return $netAmount * (1 + $this->rate / 100); } }

Guava currently (Release 10) includes four annotations in its com.google.common.annotations package: Beta, VisibleForTesting, GwtCompatible, and GwtIncompatible. The last two are specific to use with Google Web Toolkit (GWT), but the former two can be useful in a more general context. The @Beta annotation is used within Guava's own code base to indicate "that a public API (public class, method or field) is subject to incompatible changes, or even removal, in a future release." Although this annotation is used to indicate at-risk public API constructs in Guava, it can also be used in code that has access to Guava on its classpath. Developers can use this annotation to advertise their own at-risk public API constructs. The @Beta annotation is defined as a @Documented, which means that it marks something that is part of the public API and should be considered by Javadoc and other source code documentation tools. The @VisibleForTesting annotation "indicates that the visibility of a type or member has been relaxed to make the code testable." I have never liked having to relax type or member visibility to make something testable. It feels wrong to have to compromise one's design to allow testing to occur. This annotation is better than nothing in such a case because it at least makes it clear to others using the construct that there is a reason for its otherwise surprisingly relaxed visibility. Conclusion Guava provides two annotations that are not part of the standard Java distribution, but cover situations that we often run into during Java development. The @Beta annotation indicates a construct in a public API that may be changed or removed. The @VisibleForTesting annotation advertises to other developers (or reminds the code's author) when a decision was made for relaxed visibility to make testing possible or easier. From http://marxsoftware.blogspot.com/2011/11/two-generally-useful-guava-annotations.html

One of NoSQL's goals: handle previously-unthinkable amounts of data. One of unthinkable-amounts-of-data's problems: previously-improbable events become extremely probable, precisely because the set of interactions is so large. Flip a coin a hundred times, and you're not likely to get 50 heads in a row. But flip it a few trillion times, and you probably will find some 50-heads streaks. So NoSQL's performance strength is also its mathematical weakness. This order of scale can result in lots of problems, but one of the most common is consistency -- the C in ACID -- clearly a fundamental desideratum for any database system, but in principle much harder to acheive for NoSQL databases than for others. Emerging database technologies have forced developers and computer scientists to define more exactly what kind of consistency is really needed, for any given application. Two years ago, ACM (the Association for Computing Machinery) published an extremely helpful examination of the attenuated notion of consistency called 'eventual consistency'. Their summary: Data inconsistency in large-scale reliable distributed systems must be tolerated for two reasons: improving read and write performance under highly concurrent conditions; and handling partition cases where a majority model would render part of the system unavailable even though the nodes are up and running. The article surveys technical solutions as well as user considerations that might soften the undesirability of anything less than perfect, instantaneous consistency. It's not long (4 pages plus pictures), and explains some deep database issues quite clearly. On the more practical side of the problem: Russell Brown recently gave a talk at the NoSQL Exchange 2011 on exactly this topic. More specifically, he showed how some distributed systems (Riak in particular) try to minimize conflicts, and suggested some ways to reconcile conflicts automatically using smart semantic techniques. Check out the NoSQL Exchange page for Russell's talk here, which includes an embedded video. But read the ACM article first for a broader overview, since Russell launches into technical details pretty quickly.

Lynden is a family of transportation and logistics companies specialized in shipping to Alaska and other locations worldwide. Over land, on the water, in the air - or in any combination - Lynden has been helping customers solve transportation problems for over a century. The Lynden Freight Management System is a NetBeans Platform application which serves a dual purpose as both a planning and freight tracking tool. The Planning module allows terminal managers to see all freight that is currently inbound to their location as well as freight that is scheduled to depart from their location so they can make the most efficient use of their dock space and resources as possible. The Trace module allows customer service personnel to search for customer account information, view the tracking history of any given freight item in the system as well as display any documents related to the shipment, such as bills of lading or delivery receipts. NetBeans Platform Lynden has benefited from the NetBeans Platform as it allows developers to focus on the business logic of our applications rather than the underlying "plumbing". We are able to leverage built-in support for event handling, enable/disable functionality on UI controls, dockable windows, and automatic updates for our application with minimal work compared to rolling our own framework. We chose to go the desktop application route as we have a number of existing desktop applications here that this application will likely need to interface with at some point, as well as a commercial set of rich UI components that we have been using for some time now. For the initial deployment, we will be pushing the installer out to employee PCs via the Landesk remote desktop administration tool. Future updates to various modules within the application will be done via the update center functionality built into the NetBeans Platform. Screenshots

mock is a library for testing in python. it allows you to replace parts of your system under test with mock objects. the main feature of mock is that it's simple to use, but mock also makes possible more complex mocking scenarios. this is my philosophy of api design as it happens: simple things should be simple but complex things should be possible . several of these more complex scenarios are shown in the further examples section of the documentation. i've just updated one of these, the example of mocking properties. properties in python are descriptors . when they are fetched from the class of an object they trigger code that is then executed. the code that is executed is the method that you have wrapped as the property getter. note that there is a special rule for attribute lookup on certain types of descriptors, which include properties. even if an instance attribute exists, the class attribute will still be used instead. this is an exception to the normal attribute lookup rule that instance attributes are fetched in preference to class attributes. this is important because it means that when you want to mock a property you have to do it on the class and can't simply stick an attribute onto an object. if you're using mock 0.7, with its support for magic methods , we can patch the property name and add a __get__ method to our mock. the presence of the __get__ method makes it a descriptor, so we can use it as a property: >>> from mock import mock, patch >>> class foo(object): ... @property ... def fish(self): ... return 'fish' ... >>> with patch.object(foo, 'fish') as mock_fish: ... mock_fish.__get__ = mock(return_value='mocked fish') ... foo = foo() ... print foo.fish ... mocked fish >>> mock_fish.__get__.assert_called_with(mock_fish, foo, foo) in this example mock_fish replaces the property and the mock we put in place of __get__ becomes the mocked getter method. as we're patching on the class this affects all instances of foo . there's no point in using magicmock for this. magicmock normallly makes using the python protocol methods simpler by preconfiguring them. as you can see from the example above, mocking __get__ is supported but it isn't hooked up by default. it wouldn't be helpful if mocking any method on a class replaced it with a mock that acted as a descriptor, so if you want a mock to behave as a descriptor then you have to configure __get__ , __set__ and __delete__ yourself. here's an alternative approach that works with all recent-ish versions of mock: >>> from mock import mock, patch >>> class propertymock(mock): ... def __get__(self, instance, owner): ... return self() ... >>> prop_mock = propertymock() >>> with patch.object(foo, 'fish', prop_mock): ... foo = foo() ... prop_mock.return_value = 'mocked fish' ... print foo.fish ... mocked fish >>> prop_mock.assert_called_with() as an added bonus, both of these examples work even if the foo instance is created outside of the patch block. so long as the code using the property is executed whilst the patch is in place the attribute lookup will find our mocked version. source: http://www.voidspace.org.uk/python/weblog/arch_d7_2011_06_04.shtml