What is Functional Programming? Functional programming is a specific way to look at problems and model their solutions. Pragmatically, functional programming is a coding style that exhibits the following characteristics: Power and flexibility. We can solve many general real-world problems using functional constructs Simplicity. Most functional programs exhibit a small set of keywords and concise syntax for expressing concepts Suitable for parallel processing. Via immutable values and operators, functional programs lend themselves to asynchronous and parallel processing. In functional programming, programs are executed by evaluating expressions, in contrast with imperative programming where programs are composed of statements which change global state when executed. Functional programming typically avoids using mutable state. Everything is a mathematical function. Functional programming languages can have objects, but generally those objects are immutable -- either arguments or return values to functions. There are no for/next loops, as those imply state changes. Instead, that type of looping is performed with recursion and by passing functions as arguments. Functional Programming vs. Imperative Programming: We can think of imperative programming as writing code that describes in exacting detail the steps the software must take to execute a given computation. These steps are generally expressed as a combination of statement executions, state changes, loops and conditional branches. Many programming languages support programming in both functional and imperative style but the syntax and facilities of a language are typically optimised for only one of these styles, and social factors like coding conventions and libraries often force the programmer towards one of the styles. Therefore, programming languages may be categorized into functional and imperative ones. Why Functional Programming? While you can develop concurrent, scalable and asynchronous software without embracing functional programming, it's simpler, safer, and easier to use the right tool for the job. Functional programming enables you to take advantage of multi-core systems, develop robust concurrent algorithms, parallelize compute-intensive algorithms, and to readily leverage the growing number of cloud computing platforms. Imagine you've implemented a large program in a purely functional way. All the data is properly threaded in and out of functions, and there are no truly destructive updates to speak of. Now pick the two lowest-level and most isolated functions in the entire codebase. They're used all over the place, but are never called from the same modules. Now make these dependent on each other: function A behaves differently depending on the number of times function B has been called and vice-versa. In addition, if you've not already explored non-imperative programming, it's a great way to expand your problem solving skills and your horizons. The new concepts that you'll learn will help you to look at many problems from a different perspective and will help you to become a better and more insightful OO programmer. I encourage everyone who wants to be a better programmer: consider learning a functional language. Haskell and OCaml are both great choices, and F# and Erlang are pretty good as well. It won’t be easy, but that is probably a good sign. Try and identify the difficult concepts you encounter and see if other people are leveraging them; frequently you can break through a mental roadblock by finding out what the intent of an unfamiliar abstraction really is. While you’re learning, do be careful not to take it too seriously. Like anything that requires time and effort, there is a danger of becoming over-invested in FP. Falling into this cognitive trap will ruin your investment. It’s easy to forget how many models of computation there are out there, and even easier to forget how much beautiful software has been written with any of them. It’s a narrow path to walk down, but on the other side, you emerge with more core concepts and models to leverage in your everyday programming. You will almost certainly become more comfortable with denser code, and will certainly gain new insights into how to be a better software engineer.

Over the years I have been a panelist in many of the interviews for Java Developers. I have previously written a post titled Top 7 tips for succeeding in a technical interview for software engineers which covers few of the general guidelines. In this post I will share a mind map containing general topics covered in a Java developer interview. I have prepared this as a general reference for myself to remember the pointers and to keep a common standard across the multiple interviews. XMind gives a nice listing of the map. You can find the map here. Here is Image which you can download and use. Finally here is a old fashioned tabbed content list which is easier to copy paste. Java-Topics OOPs Encapsulation Abstraction Inheritance Interface - Abstract Class Casting IS-A vs HAS-A Relationships Aggregation vs Composition Plymorphism Method overloading vs Method Overloading Compile time vs Runtime Threads Creating threads Multitasking Synchronization Thread Transitions Marker Interface Serialization Clonnable Shallow copy vs Deep Copy Collections Map, List and Set Equals - Hashcode Legacy - Synchronized Classes JVM Stack vs Heap Memory Garbage Collection JRE, JVM, JDK Class loaders Exception Checked Vs Unchecked Exceptions Exception handling best practices try, catch, finally, throw, throws APIs Files String - StringBuffer - String Builder Java IO XML SAX Based & DOM Based JAXB - Java API for XML Binding Access specifier Access modifier public protected deafult private final static synchronized abstract transient volatile Inner/Nested Classes JavaEE Basics Packaging the Applications WAR EAR Basics MVC Servlets Listeners Lifecycle JSPs APIs JPA JAX-WS SOAP, WSDL Webservices basics Contract first vs JAX-RS RESTful and its advantages JSF This is a work in progress and I hope to refine it further. Let me know if you have any comments. - See more at: http://jyops.blogspot.ie/2013/10/a-mindmap-for-java-developer-interviews.html#sthash.K0A5wDAz.dpuf

In this seventh post of my series on addressing the issue of too many parameters in a Java method or constructor, I look at using state to reduce the need to pass parameters. One of the reasons I have waited until the 7th post of this series to address this is that it is one of my least favorite approaches for reducing parameters passed to methods and constructors. That stated, there are multiple flavors of this approach and I definitely prefer some flavors over others. Perhaps the best known and most widely scorned approach in all of software development for using state to reduce parameter methods is the use global variables. Although it may be semantically accurate to say thatJava does not have global variables, the reality is that for good or for bad the equivalent of global variables is achieved in Java via public static constructs. A particularly popular way to achieve this in Java is via the Stateful Singleton. In Patterns of Enterprise Application Architecture, Martin Fowler wrote that "any global data is always guilty until proven innocent." Global variables and "global-like" constructs in Java are considered bad form for several reasons. They can make it difficult for developers maintaining and reading code to know where the values are defined or last changed or even come from. By their very nature and intent, global data violates the principles of encapsulation and data hiding. Miško Hevery has written the following regarding the problems of static globals in an object-oriented language: Accessing global state statically doesn’t clarify those shared dependencies to readers of the constructors and methods that use the Global State. Global State and Singletons make APIs lie about their true dependencies. ... The root problem with global state is that it is globally accessible. In an ideal world, an object should be able to interact only with other objects which were directly passed into it (through a constructor, or method call). Having state available globally reduces the need for parameters because there is no need for one object to pass data to another object if both objects already have direct access to that data. However, as Hevery put it, that's completely orthogonal to the intent of object-oriented design. Mutable state is also an increasing problem as concurrent applications become more common. In his JavaOne 2012 presentation on Scala, Scala creator Martin Odersky stated that "every piece of mutable state you have is a liability" in a highly concurrent world and added that the problem is "non-determinism caused by concurrent threads accessing shared mutable state." Although there are reasons to avoid mutable state, it still remains a generally popular approach in software development. I think there are several reasons for this including that it's superfically easy to write mutable state sharing code and mutable shared code does provide ease of access. Some types of mutable data are popular because those types of mutable data have been taught and learned as effective for years. Finally, three are times when mutable state may be the most appropriate solution. For that last reason and to be complete, I now look at how the use of mutable state can reduce the number of parameters a method must expect. Stateful Singleton and Static Variables A Java implementation of Singleton and other public Java static fields are generally available to any Java code within the same Java Virtual Machine (JVM) and loaded with the same classloader [for more details, see When is a Singleton not a Singleton?]. Any data stored universally (at least from JVM/classloader perspective) is already available to client code in the same JVM and loaded with the same class loader. Because of this, there is no need to pass that data between clients and methods or constructors in that same JVM/classloader combination. Instance State While "statics" are considered "globally available," narrower instance-level state can also be used in a similar fashion to reduce the need to pass parameters between methods of the same class. An advantage of this over global variables is that the accessibility is limited to instances of the class (private fields) or instances of the class's children (private fields). Of course, if the fields are public, accessibility is pretty wide open, but the same data is not automatically available to other code in the same JVM/classloader. The next code listing demonstrates how state data can and sometimes is used to reduce the need for parameters between two methods internal to a given class. Example of Instance State Used to Avoid Passing Parameters /** * Simple example of using instance variable so that there is no need to * pass parameters to other methods defined in the same class. */ public void doSomethingGoodWithInstanceVariables() { this.person = Person.createInstanceWithNameAndAddressOnly( new FullName.FullNameBuilder(new Name("Flintstone"), new Name("Fred")).createFullName(), new Address.AddressBuilder(new City("Bedrock"), State.UN).createAddress()); printPerson(); } /** * Prints instance of Person without requiring it to be passed in because it * is an instance variable. */ public void printPerson() { out.println(this.person); } The above example is somewhat contrived and simplified, but does illustrate the point: the instance variableperson can be accessed by other instance methods defined in the same class, so that instance does not need to be passed between those instance methods. This does reduce the signature of potentially (public accessibility means it may be used by external methods) internal methods, but also introduces state and now means that the invoked method impacts the state of that same object. In other words, the benefit of not having to pass the parameter comes at the cost of another piece of mutable state. The other side of the trade-off, needing to pass the instance of Person because it is not an instance variable, is shown in the next code listing for comparison. Example of Passing Parameter Rather than Using Instance Variable /** * Simple example of passing a parameter rather than using an instance variable. */ public void doSomethingGoodWithoutInstanceVariables() { final Person person = Person.createInstanceWithNameAndAddressOnly( new FullName.FullNameBuilder(new Name("Flintstone"), new Name("Fred")).createFullName(), new Address.AddressBuilder(new City("Bedrock"), State.UN).createAddress()); printPerson(person); } /** * Prints instance of Person that is passed in as a parameter. * * @param person Instance of Person to be printed. */ public void printPerson(final Person person) { out.println(person); } The previous two code listings illustrate that parameter passing can be reduced by using instance state. I generally prefer to not use instance state solely to avoid parameter passing. If instance state is needed for other reasons, than the reduction of parameters to be passed is a nice side benefit, but I don't like introducing unnecessary instance state simply to remove or reduce the number of parameters. Although there was a time when the readability of reduced parameters might have justified instance state in a large single-threaded environment, I feel that the slight readability gain from reduced parameters is not worth the cost of classes that are not thread-safe in an increasingly multi-threaded world. I still don't like to pass a whole lot of parameters between methods of the same class, but I can use the parameters object (perhaps with a package-private scope class) to reduce the number of these parameters and pass that parameters object around instead of the large number of parameters. JavaBean Style Construction The JavaBeans convention/style has become extremely popular in the Java development community. Many frameworks such as Spring Framework and Hibernate rely on classes adhering to the JavaBeans conventions and some of the standards like Java Persistence API also are built around the JavaBeans conventions. There are multiple reasons for the popularity of the JavaBeans style including its ease-of-use and the ability to usereflection against this code adhering to this convention to avoid additional configuration. The general idea behind the JavaBean style is to instantiate an object with a no-argument constructor and then set its fields via single-argument "set" methods and access it fields via no-argument "get" methods. This is demonstrated in the next code listings. The first listing shows a simple example of a PersonBean class with no-arguments constructor and getter and setter methods. That code listing also includes some of the JavaBeans-style classes it uses. That code listing is followed by code using that JavaBean style class. Examples of JavaBeans Style Class public class PersonBean { private FullNameBean name; private AddressBean address; private Gender gender; private EmploymentStatus employment; private HomeownerStatus homeOwnerStatus; /** No-arguments constructor. */ public PersonBean() {} public FullNameBean getName() { return this.name; } public void setName(final FullNameBean newName) { this.name = newName; } public AddressBean getAddress() { return this.address; } public void setAddress(final AddressBean newAddress) { this.address = newAddress; } public Gender getGender() { return this.gender; } public void setGender(final Gender newGender) { this.gender = newGender; } public EmploymentStatus getEmployment() { return this.employment; } public void setEmployment(final EmploymentStatus newEmployment) { this.employment = newEmployment; } public HomeownerStatus getHomeOwnerStatus() { return this.homeOwnerStatus; } public void setHomeOwnerStatus(final HomeownerStatus newHomeOwnerStatus) { this.homeOwnerStatus = newHomeOwnerStatus; } } /** * Full name of a person in JavaBean style. * * @author Dustin */ public final class FullNameBean { private Name lastName; private Name firstName; private Name middleName; private Salutation salutation; private Suffix suffix; /** No-args constructor for JavaBean style instantiation. */ private FullNameBean() {} public Name getFirstName() { return this.firstName; } public void setFirstName(final Name newFirstName) { this.firstName = newFirstName; } public Name getLastName() { return this.lastName; } public void setLastName(final Name newLastName) { this.lastName = newLastName; } public Name getMiddleName() { return this.middleName; } public void setMiddleName(final Name newMiddleName) { this.middleName = newMiddleName; } public Salutation getSalutation() { return this.salutation; } public void setSalutation(final Salutation newSalutation) { this.salutation = newSalutation; } public Suffix getSuffix() { return this.suffix; } public void setSuffix(final Suffix newSuffix) { this.suffix = newSuffix; } @Override public String toString() { return this.salutation + " " + this.firstName + " " + this.middleName + this.lastName + ", " + this.suffix; } } package dustin.examples; /** * Representation of a United States address (JavaBeans style). * * @author Dustin */ public final class AddressBean { private StreetAddress streetAddress; private City city; private State state; /** No-arguments constructor for JavaBeans-style instantiation. */ private AddressBean() {} public StreetAddress getStreetAddress() { return this.streetAddress; } public void setStreetAddress(final StreetAddress newStreetAddress) { this.streetAddress = newStreetAddress; } public City getCity() { return this.city; } public void setCity(final City newCity) { this.city = newCity; } public State getState() { return this.state; } public void setState(final State newState) { this.state = newState; } @Override public String toString() { return this.streetAddress + ", " + this.city + ", " + this.state; } } Example of JavaBeans Style Instantiation and Population public PersonBean createPerson() { final PersonBean person = new PersonBean(); final FullNameBean personName = new FullNameBean(); personName.setFirstName(new Name("Fred")); personName.setLastName(new Name("Flintstone")); person.setName(personName); final AddressBean address = new AddressBean(); address.setStreetAddress(new StreetAddress("345 Cave Stone Road")); address.setCity(new City("Bedrock")); person.setAddress(address); return person; } The examples just shown demonstrate how the JavaBeans style approach can be used. This approach makes some concessions to reduce the need to pass a large number of parameters to a class's constructor. Instead, no parameters are passed to the constructor and each individual attribute that is needed must be set. One of the advantages of the JavaBeans style approach is that readability is enhanced as compared to a constructor with a large number of parameters because each of the "set" methods is hopefully named in a readable way. The JavaBeans approach is simple to understand and definitely achieves the goal of reducing lengthy parameters in the case of constructors. However, there are some disadvantages to this approach as well. One advantage is a lot of tedious client code for instantiating the object and setting its attributes one-at-a-time. It is easy with this approach to neglect to set a required attribute because there is no way for the compiler to enforce all required parameters be set without leaving the JavaBeans convention. Perhaps most damaging, there are several objects instantiated in this last code listing and these objects exist in different incomplete states from the time they are instantiated until the time the final "set" method is called. During that time, the objects are in what is really an "undefined" or "incomplete" state. The existence of "set" methods necessarily means that the class's attributes cannot be final, rendering the entire object highly mutable. Regarding the prevalent use of the JavaBeans pattern in Java, several credible authors have called into questionits value. Allen Holub's controversial article Why getter and setter methods are evil starts off with no holds barred: Though getter/setter methods are commonplace in Java, they are not particularly object oriented (OO). In fact, they can damage your code's maintainability. Moreover, the presence of numerous getter and setter methods is a red flag that the program isn't necessarily well designed from an OO perspective. Josh Bloch, in his less forceful and more gently persuasive tone, says of the JavaBeans getter/setter style: "The JavaBeans pattern has serious disadvantages of its own" (Effective Java, Second Edition, Item #2). It is in this context that Bloch recommends the builder pattern instead for object construction. I'm not against using the JavaBeans get/set style when the framework I've selected for other reasons requires it and the reasons for using that framework justify it. There are also areas where the JavaBeans style class is particularly well suited such as interacting with a data store and holding data from the data store for use by the application. However, I am not a fan of using the JavaBeans style for instantiating a question simply to avoid the need to pass parameters. I prefer one of the other approaches such as builder for that purpose. Benefits and Advantages I've covered different approaches to reducing the number of arguments to a method or constructor in this post, but they also share the same trade-off: exposing mutable state to reduce or eliminate the number of parameters that must be passed to a method or to a constructor. The advantages of these approaches are simplicity, generally readable (though "globals" can be difficult to read), and ease of first writing and use. Of course, their biggest advantage from this post's perspective is that they generally eliminate the need for any parameter passing. Costs and Disadvantages The trait that all approaches covered in this post share is the exposure of mutable state. This can lead to an extremely high cost if the code is used in a highly concurrent environment. There is a certain degree of unpredictability when object state is exposed for anyone to tinker with it as they like. It can be difficult to know which code made the wrong change or failed to make a necessary change (such as failing to call a "set" method when populating a newly instantiated object). Conclusion Some of the approaches covered in this post are highly popular despite their drawbacks. This may be for a variety of reasons including prevalence of use in popular frameworks (forcing users of the framework to use that style and also providing examples to others for their own code development). Other reasons for these approaches' popularity is the relative ease of initial development and the seemingly (deceptively) relatively little thought that needs to go into design with these approaches. In general, I prefer to spend a little more design and implementation effort to use builders and less mutable approaches when practical. However, there are cases where these mutable approaches work well in reducing the number of parameters passed around and introduce no more risk than was already present. My feeling is that Java developers should carefully consider use of any mutable Java classes and ensure that the mutability is either desired or is a cost that is justified by the reasons for using a mutable state approach.

I wanted to know: how would Java EE compare to Node.js in this particular case?

Previous posts such as this one have shown using embedded Jetty to REST-enable a standalone Java program. Those posts were lacking an important feature for real applications: packaging into a JAR so the application will run outside of Eclipse and won’t be dependent on Maven and jetty:run. To make this happen, we will use Maven to build an executable JAR that also includes all of the Jetty and Spring dependencies we need. The goal of this work is to get to the point where we can run the example application by: Cloning the Git repository. Running mvn package. Running java -jar target/webmvc-standalone.jar When I started adding the necessary bits to the pom.xml file of my sample application, I expected a relatively straightforward solution. I ended up with a relatively straightforward solution that was completely different from what I expected. So I think it’s worth a detailed discussion of how this solution works and what Maven is doing for us. Our desire to make an executable JAR is complicated by the fact that we want our Maven project to build a WAR as a default package, so that we can use this code in a Java web container if desired. Additionally, we introduce some complexity by making a single JAR with all dependencies, because that causes files in the Spring JARs to collide. I’ll show what I did to address each of these. Build both JAR and WAR The basic idea here is that we want Maven to make both a JAR file and a WAR file during the “package” phase. Our pom.xml file specifies war as the packaging for this project, so the WAR file will be created as expected. We need to add the JAR file without disturbing this. I found a great post here that got me started. The basic idea is to add the following to pom.xml under build/plugins: org.apache.maven.plugins maven-jar-plugin 2.4 package-jar package jar This is the behavior we would get for “free” if we used jar packaging inpom.xml. The execution section ties it to the package phase so that it runs during the default build process. The jar goal tells the plugin what to make. This gets us a basic JAR with the classes in the normal place for a JAR (rather than in WEB-INF/classes as they must be in the WAR file). At the same time, we need to deal with the fact that the Maven resources plugin considers only src/main/resources to be a resources directory, while in our case we have files in src/main/webapp that also need to be included. We want to copy these resources to the target directory so the JAR plugin will pick them up. (This is an important distinction; the typical Maven question, “how do I include extra resources in my JAR?” should really be “how do I get extra resources into target so the JAR plugin will pick them up?”) We add this to the build section of pom.xml: src/main/resources src/main/webapp This causes our new webmvc.jar file to include the HTML, JavaScript, etc. required for our embedded Jetty webapp. JAR with dependencies Next, we make an additional JAR that has the correct Main-Class entry in theMANIFEST.MF file and includes the necessary dependencies so we only have to ship one file. This is done using the Maven assembly plugin. The assembly plugin does repackaging only; that’s why we had to add a JAR artifact above. Without that JAR artifact to work from, the assembly plugin repackages the WAR, and we end up with classes in WEB-INF/classes. This causes Java to complain that it can’t find our main class when we try to run the JAR. The assembly plugin comes with a jar-with-dependencies configuration that can be used simply by adding it as a descriptorRef to the relevant section of pom.xml, as shown in this StackOverflow question. However, this configuration doesn’t work in our particular case, as the Spring dependencies we need have files with overlapping names. As a result, we need to make our own assembly configuration. Fortunately, this is pretty simple. We first add this to the build/plugins section of pom.xml: org.apache.maven.plugins maven-assembly-plugin 2.4 src/assemble/distribution.xml org.anvard.webmvc.server.EmbeddedServer package single As before, we use the executions section to make sure this is run automaticaly during package. We also specify the main class for our application. Finally, we point the plugin to our assembly configuration file, which lives in src/assemble. I present the assembly configuration below, but first we need to talk about the issue with the Spring JARs that made this custom assembly necessary. Spring schemas and handlers With this sample application, we use Spring WebMVC to provide a REST API for ordinary Java classes, as discussed in this post. The Spring code we use is spread across a few different JARs. Recent versions of Spring added a “custom XML namespace” feature that allows the contents of a Spring XML configuration file to be very extensible. Spring WebMVC, and other Spring libraries, use this feature to provide custom XML tags. In order to parse the XML file with these custom tags, Spring needs to be able to match these custom namespaces to handlers. To do this, Spring expects to find files called spring.handlers andspring.schemas in the META-INF directory of any JAR providing a Spring custom namespace. Several of the Spring JARs used by this application include thosespring.handlers and spring.schemas files. Of course, each JAR only includes its own handlers and schemas. When the Maven assembly plugin uses the jar-with-dependencies configuration, only one copy of those files “wins” and makes it into the executable JAR. We really just need a single spring.handlers and spring.schemas that are the concatentation of the respective files. There is probably some Maven magic to accomplish this, but I elected to do it manually as my Bash-fu is much greater than my Maven-fu. I added two files to the src/assemble directory that have the combined contents of the various files in the Spring JARs. Maven assembly configuration The assembly file looks like this: standalone jar true META-INF/spring.handlers META-INF/spring.schemas src/assemble/spring.handlers /META-INF false src/assemble/spring.schemas /META-INF false The id will be used to name this assembly. The baseDirectory tells the assembly plugin that the pieces it assembles should go at the root of the new JAR. (Otherwise they would go into a directory using the project name, in this case “webapp”.) The next two sections are important. We want to exclude thespring.handlers and spring.schemas from the Spring JARs (a.k.a. the dependency set). Instead, we want to explicitly include them from oursrc/assemble directory, and put them into the right place. We also want the assembly plugin to unpack the dependency set JARs so we wind up with Java class files in our new JAR, rather than just JAR-files-inside-JAR-file, which would not run correctly. Notice that there is no directive telling Spring to include all dependencies from the dependency set, including transitive dependencies. This is the default so we don’t need to specify it. It’s also the default to include the unpacked files from our own artifact (webmvc.jar) into the new JAR. Conclusion A real-world application would probably pick either WAR packaging or executable JAR packaging, and be simpler. Additionally, it would be possible to use multiple Maven modules to build a JAR and embed it in the WAR. But it’s interesting to see how to implement a more complex solution that builds everything we need from a single project.

In my two immediately previous posts, I looked at reducing the number of parameters required for a constructor or method invocation via custom types and parameter objects. In this post, I look at use of thebuilder pattern to reduce the number of parameters required for a constructor with some discussion on how this pattern can even help with non-constructor methods that take too many parameters. In the Second Edition of Effective Java, Josh Bloch introduces use of the builder pattern in Item #2 for dealing with constructors that require too many parameters. Bloch not only demonstrates how to use the Builder, but explains it advantages over constructors accepting a large number of parameters. I will get to those advantages at the end of this post, but think it's important to point out that Bloch has devoted an entire item in his book to this practice. To illustrate the advantages of this approach, I'll use the following example Person class. It doesn't have all the methods I would typically add to such a class because I want to focus on its construction. Person.java (without Builder Pattern) package dustin.examples; /** * Person class used as part of too many parameters demonstration. * * @author Dustin */ public class Person { private final String lastName; private final String firstName; private final String middleName; private final String salutation; private final String suffix; private final String streetAddress; private final String city; private final String state; private final boolean isFemale; private final boolean isEmployed; private final boolean isHomewOwner; public Person( final String newLastName, final String newFirstName, final String newMiddleName, final String newSalutation, final String newSuffix, final String newStreetAddress, final String newCity, final String newState, final boolean newIsFemale, final boolean newIsEmployed, final boolean newIsHomeOwner) { this.lastName = newLastName; this.firstName = newFirstName; this.middleName = newMiddleName; this.salutation = newSalutation; this.suffix = newSuffix; this.streetAddress = newStreetAddress; this.city = newCity; this.state = newState; this.isFemale = newIsFemale; this.isEmployed = newIsEmployed; this.isHomewOwner = newIsHomeOwner; } } This class's constructor works, but it is difficult for client code to use properly. The Builder pattern can be used to make the constructor easier to use. NetBeans will refactor this for me as I have written about previously. An example of the refactored code is shown next (NetBeans does this by creating all new Builder class). PersonBuilder.java package dustin.examples; public class PersonBuilder { private String newLastName; private String newFirstName; private String newMiddleName; private String newSalutation; private String newSuffix; private String newStreetAddress; private String newCity; private String newState; private boolean newIsFemale; private boolean newIsEmployed; private boolean newIsHomeOwner; public PersonBuilder() { } public PersonBuilder setNewLastName(String newLastName) { this.newLastName = newLastName; return this; } public PersonBuilder setNewFirstName(String newFirstName) { this.newFirstName = newFirstName; return this; } public PersonBuilder setNewMiddleName(String newMiddleName) { this.newMiddleName = newMiddleName; return this; } public PersonBuilder setNewSalutation(String newSalutation) { this.newSalutation = newSalutation; return this; } public PersonBuilder setNewSuffix(String newSuffix) { this.newSuffix = newSuffix; return this; } public PersonBuilder setNewStreetAddress(String newStreetAddress) { this.newStreetAddress = newStreetAddress; return this; } public PersonBuilder setNewCity(String newCity) { this.newCity = newCity; return this; } public PersonBuilder setNewState(String newState) { this.newState = newState; return this; } public PersonBuilder setNewIsFemale(boolean newIsFemale) { this.newIsFemale = newIsFemale; return this; } public PersonBuilder setNewIsEmployed(boolean newIsEmployed) { this.newIsEmployed = newIsEmployed; return this; } public PersonBuilder setNewIsHomeOwner(boolean newIsHomeOwner) { this.newIsHomeOwner = newIsHomeOwner; return this; } public Person createPerson() { return new Person(newLastName, newFirstName, newMiddleName, newSalutation, newSuffix, newStreetAddress, newCity, newState, newIsFemale, newIsEmployed, newIsHomeOwner); } } I prefer to have my Builder as a nested class inside the class whose object it builds, but the NetBeans automatic generation of a standalone Builder is very easy to use. Another difference between the NetBeans-generated Builder and the Builders I like to write is that my preferred Builder implementations have required fields provided in the Builder's constructor rather than provide a no-arguments constructor. The next code listing shows my Person class from above with a Builder added into it as a nested class. Person.java with Nested Person.Builder package dustin.examples; /** * Person class used as part of too many parameters demonstration. * * @author Dustin */ public class Person { private final String lastName; private final String firstName; private final String middleName; private final String salutation; private final String suffix; private final String streetAddress; private final String city; private final String state; private final boolean isFemale; private final boolean isEmployed; private final boolean isHomewOwner; public Person( final String newLastName, final String newFirstName, final String newMiddleName, final String newSalutation, final String newSuffix, final String newStreetAddress, final String newCity, final String newState, final boolean newIsFemale, final boolean newIsEmployed, final boolean newIsHomeOwner) { this.lastName = newLastName; this.firstName = newFirstName; this.middleName = newMiddleName; this.salutation = newSalutation; this.suffix = newSuffix; this.streetAddress = newStreetAddress; this.city = newCity; this.state = newState; this.isFemale = newIsFemale; this.isEmployed = newIsEmployed; this.isHomewOwner = newIsHomeOwner; } public static class PersonBuilder { private String nestedLastName; private String nestedFirstName; private String nestedMiddleName; private String nestedSalutation; private String nestedSuffix; private String nestedStreetAddress; private String nestedCity; private String nestedState; private boolean nestedIsFemale; private boolean nestedIsEmployed; private boolean nestedIsHomeOwner; public PersonBuilder( final String newFirstName, final String newCity, final String newState) { this.nestedFirstName = newFirstName; this.nestedCity = newCity; this.nestedState = newState; } public PersonBuilder lastName(String newLastName) { this.nestedLastName = newLastName; return this; } public PersonBuilder firstName(String newFirstName) { this.nestedFirstName = newFirstName; return this; } public PersonBuilder middleName(String newMiddleName) { this.nestedMiddleName = newMiddleName; return this; } public PersonBuilder salutation(String newSalutation) { this.nestedSalutation = newSalutation; return this; } public PersonBuilder suffix(String newSuffix) { this.nestedSuffix = newSuffix; return this; } public PersonBuilder streetAddress(String newStreetAddress) { this.nestedStreetAddress = newStreetAddress; return this; } public PersonBuilder city(String newCity) { this.nestedCity = newCity; return this; } public PersonBuilder state(String newState) { this.nestedState = newState; return this; } public PersonBuilder isFemale(boolean newIsFemale) { this.nestedIsFemale = newIsFemale; return this; } public PersonBuilder isEmployed(boolean newIsEmployed) { this.nestedIsEmployed = newIsEmployed; return this; } public PersonBuilder isHomeOwner(boolean newIsHomeOwner) { this.nestedIsHomeOwner = newIsHomeOwner; return this; } public Person createPerson() { return new Person( nestedLastName, nestedFirstName, nestedMiddleName, nestedSalutation, nestedSuffix, nestedStreetAddress, nestedCity, nestedState, nestedIsFemale, nestedIsEmployed, nestedIsHomeOwner); } } } The Builder can be even nicer when enhanced through use of custom types and parameters objects as outlined in my first two posts on the "too many parameters" problem. This is shown in the next code listing. Person.java with Nested Builder, Custom Types, and Parameters Object package dustin.examples; /** * Person class used as part of too many parameters demonstration. * * @author Dustin */ public class Person { private final FullName name; private final Address address; private final Gender gender; private final EmploymentStatus employment; private final HomeownerStatus homeOwnerStatus; /** * Parameterized constructor can be private because only my internal builder * needs to call me to provide an instance to clients. * * @param newName Name of this person. * @param newAddress Address of this person. * @param newGender Gender of this person. * @param newEmployment Employment status of this person. * @param newHomeOwner Home ownership status of this person. */ private Person( final FullName newName, final Address newAddress, final Gender newGender, final EmploymentStatus newEmployment, final HomeownerStatus newHomeOwner) { this.name = newName; this.address = newAddress; this.gender = newGender; this.employment = newEmployment; this.homeOwnerStatus = newHomeOwner; } public FullName getName() { return this.name; } public Address getAddress() { return this.address; } public Gender getGender() { return this.gender; } public EmploymentStatus getEmployment() { return this.employment; } public HomeownerStatus getHomeOwnerStatus() { return this.homeOwnerStatus; } /** * Builder class as outlined in the Second Edition of Joshua Bloch's * Effective Java that is used to build a {@link Person} instance. */ public static class PersonBuilder { private FullName nestedName; private Address nestedAddress; private Gender nestedGender; private EmploymentStatus nestedEmploymentStatus; private HomeownerStatus nestedHomeOwnerStatus; public PersonBuilder( final FullName newFullName, final Address newAddress) { this.nestedName = newFullName; this.nestedAddress = newAddress; } public PersonBuilder name(final FullName newName) { this.nestedName = newName; return this; } public PersonBuilder address(final Address newAddress) { this.nestedAddress = newAddress; return this; } public PersonBuilder gender(final Gender newGender) { this.nestedGender = newGender; return this; } public PersonBuilder employment(final EmploymentStatus newEmploymentStatus) { this.nestedEmploymentStatus = newEmploymentStatus; return this; } public PersonBuilder homeOwner(final HomeownerStatus newHomeOwnerStatus) { this.nestedHomeOwnerStatus = newHomeOwnerStatus; return this; } public Person createPerson() { return new Person( nestedName, nestedAddress, nestedGender, nestedEmploymentStatus, nestedHomeOwnerStatus); } } } The last couple of code listings show how a Builder is typically used - to construct an object. Indeed, the item on the builder (Item #2) in Joshua Bloch's Second Edition of Effective Java is in the chapter on creating (and destroying) object. However, the builder can help indirectly with non-constructor methods by allowing an easier way to build parameters objects that are passed to methods. For example, in the last code listing, the methods have some parameters objects (FullName and Address) passed to them. It can be tedious for clients to have to construct these parameters objects and the builder can be used to make that process less tedious. So, although the builder is used for construction in each case, it indirectly benefits non-constructor methods by allowing for easier use of the parameters objects that reduce a method's argument count. The new definitions of the FullName and Address classes to be used as parameters objects and using the Builder themselves are shown next. FullName.java with Builder package dustin.examples; /** * Full name of a person. * * @author Dustin */ public final class FullName { private final Name lastName; private final Name firstName; private final Name middleName; private final Salutation salutation; private final Suffix suffix; private FullName( final Name newLastName, final Name newFirstName, final Name newMiddleName, final Salutation newSalutation, final Suffix newSuffix) { this.lastName = newLastName; this.firstName = newFirstName; this.middleName = newMiddleName; this.salutation = newSalutation; this.suffix = newSuffix; } public Name getLastName() { return this.lastName; } public Name getFirstName() { return this.firstName; } public Name getMiddleName() { return this.middleName; } public Salutation getSalutation() { return this.salutation; } public Suffix getSuffix() { return this.suffix; } @Override public String toString() { return this.salutation + " " + this.firstName + " " + this.middleName + this.lastName + ", " + this.suffix; } public static class FullNameBuilder { private final Name nestedLastName; private final Name nestedFirstName; private Name nestedMiddleName; private Salutation nestedSalutation; private Suffix nestedSuffix; public FullNameBuilder( final Name newLastName, final Name newFirstName) { this.nestedLastName = newLastName; this.nestedFirstName = newFirstName; } public FullNameBuilder middleName(final Name newMiddleName) { this.nestedMiddleName = newMiddleName; return this; } public FullNameBuilder salutation(final Salutation newSalutation) { this.nestedSalutation = newSalutation; return this; } public FullNameBuilder suffix(final Suffix newSuffix) { this.nestedSuffix = newSuffix; return this; } public FullName createFullName() { return new FullName( nestedLastName, nestedFirstName, nestedMiddleName, nestedSalutation, nestedSuffix); } } } Address.java with Builder package dustin.examples; /** * Representation of a United States address. * * @author Dustin */ public final class Address { private final StreetAddress streetAddress; private final City city; private final State state; private Address(final StreetAddress newStreetAddress, final City newCity, final State newState) { this.streetAddress = newStreetAddress; this.city = newCity; this.state = newState; } public StreetAddress getStreetAddress() { return this.streetAddress; } public City getCity() { return this.city; } public State getState() { return this.state; } @Override public String toString() { return this.streetAddress + ", " + this.city + ", " + this.state; } public static class AddressBuilder { private StreetAddress nestedStreetAddress; private final City nestedCity; private final State nestedState; public AddressBuilder(final City newCity, final State newState) { this.nestedCity = newCity; this.nestedState = newState; } public AddressBuilder streetAddress(final StreetAddress newStreetAddress) { this.nestedStreetAddress = newStreetAddress; return this; } public Address createAddress() { return new Address(nestedStreetAddress, nestedCity, nestedState); } } } With the above builders included in the classes, a Person instance can be created as shown in the next code listing. A more traditional instantiation of a Person instance is shown after that for comparison. Two Examples of Client Code Instantiating a Person with Builders final Person person1 = new Person.PersonBuilder( new FullName.FullNameBuilder( new Name("Dynamite"), new Name("Napoleon")).createFullName(), new Address.AddressBuilder( new City("Preston"), State.ID).createAddress()).createPerson(); final Person person2 = new Person.PersonBuilder( new FullName.FullNameBuilder( new Name("Coltrane"), new Name("Rosco")).middleName(new Name("Purvis")).createFullName(), new Address.AddressBuilder( new City("Hazzard"), State.GA).createAddress()) .gender(Gender.MALE).employment(EmploymentStatus.EMPLOYED).createPerson(); Instantiating a Person Without a Builder final person = new Person("Coltrane", "Rosco", "Purvis", null, "Hazzard", "Georgia", false, true, true); As the previous code snippets show, the client code for calling a traditional Java constructor is far less readable and far easier to mess up than use of the builder classes. The variety of the same types (strings and booleans) and the necessity to place nulls in the constructor call for optional attributes make provide many ways for this approach to end badly. Benefits and Advantages There is a considerable cost to the Builder pattern in that one must essentially double the number of lines of code each attribute and for setting those attributes. This price pays off, however, when the client code benefits greatly in terms of usability and readability. The parameters to the constructor are reduced and are provided in highly readable method calls. Another advantage of the Builder approach is the ability to acquire an object in a single statement and state without the object in multiple states problem presented by using "set" methods. I am increasingly appreciating the value of immutability in a multi-core world and the Builder pattern is perfectly suited for an immutable class when that class features a large number of attributes. I also like that there is no need to pass in null for optional parameters to the constructor. The Builder pattern not only makes the code more readable, but makes it even easier to apply an IDE's code completion feature. Further benefits of the Builder pattern when used with constructors are outlined in Item #2 of the Second Edition of Effective Java. Costs and Disadvantages As shown and mentioned above, the number of lines of code of a given class must be essentially doubled for "set" methods with the builder approach. Furthermore, although client code is more readable, the client code is also more verbose. I consider the benefit of greater readability worth the cost as the number of arguments increase or as more arguments share the same type or as the number of optional arguments increase. More lines of code in the class with the builder sometimes mean that developers may forget to add support for a new attribute to the builder when they add that attribute to the main class. To try to help with this, I like to nest my builders inside the class that they build so that it's more obvious to the developer that there is a relevant builder that needs to be similarly updated. Although there is still risk of the developer forgetting to add support for a new attribute to the builder, this is really no different than the risk of forgetting to add a new attribute to a class's toString(), equals(Object), hashCode() or other methods often based on all attributes of a class. In my implementation of the Builder, I made the client pass required attributes into the builder's constructor rather than via "set" methods. The advantage of this is that the object is always instantiated in a "complete" state rather than sitting in an incomplete state until the developer calls (if ever calls) the appropriate "set" method to set additional fields. This is necessary to enjoy the benefits of immutability. However, a minor disadvantage of that approach is that I don't get the readability advantages of methods named for the field I am setting. The Builder, as its name suggests, is really only an alternative to constructors and not directly used to reduce the number of non-constructor method parameters. However, the builder can be used in conjunction with parameters objects to reduce the number of non-constructor method arguments. Further arguments against use of the Builder for object construction can be found in a comment on the A dive into the Builder pattern post. Conclusion I really like the Builder pattern for constructing objects when I have a lot of parameters, especially if many of these parameters are null and when many of them share the same data type. A developer might feel that the extra code to implement a Builder might not justify its benefits for a small number of parameters, especially if the few parameters are required and of different types. In such cases, it might be considered desirable to use traditional constructors or, if immutability is not desired, use a no-argument constructor and require the client to know to call the necessary "set" methods.

I’ve been doing some work that involves reading in CSV files, for which I’ve been using OpenCSV, and my initial approach was to read through the file line by line, parse the contents, and save it into a list of maps. This works when the contents of the file fit into memory, but is problematic for larger files where I needed to stream the file and process each line individually, rather than all of them after the file was loaded. I initially wrote a variation on totallylazy’s Strings#lines to do this, and while I was able to stream the file, I made a mistake somewhere which meant the number of maps on the heap was always increasing. After spending a few hours trying to fix this, Michael suggested that it’d be easier to use an iterator instead, and I ended up with the following code: public class ParseCSVFile { public static void main(String[] args) throws IOException { final CSVReader csvReader = new CSVReader( new BufferedReader( new FileReader( "/path/to/file.csv" ) ), '\t' ); final String[] fields = csvReader.readNext(); Iterator>() lazilyLoadedFile = return new Iterator>() { String[] data = csvReader.readNext(); @Override public boolean hasNext() { return data != null; } @Override public Map next() { final Map properties = new HashMap(); for ( int i = 0; i < data.length; i++ ) { properties.put(fields[i], data[i]); } try { data = csvReader.readNext(); } catch ( IOException e ) { data = null; } return properties; } @Override public void remove() { throw new UnsupportedOperationException(); } }; } } Although this code works, it’s not the most readable function I’ve ever written, so any suggestions on how to do this in a cleaner way are welcome.

With these changes, we can access the REST API equally well fromhttp://:9999 and https://:9998.

I have recently started the Coursera Functional Programming with Scala course (taught by Martin Odersky - the creator of Scala) - which is actually serving as an introduction to both FP and Scala at the same time having done neither before. The course itself is great, however, trying to watch the videos and take in both the new Scala syntax and the FP concepts at the same time can take a bit of effort. I wanted to work through some of the core FP concepts in a more familiar context, so am going to apply some of the lessons/principles/exercises in Groovy. Functions: If you have done any Groovy programming then you will have come across Groovy functions/closures. As Groovy is dynamically typed (compared to Scala's static typing), you can play it fairly fast and loose. For example, if we take the square root function that is demonstrated in the Scala course, it is defined as follows: def sqrt(x: Double): Double = ... As you can see, Scala expects the values to be typed (aside, you don't actually always need to provide a return type in Scala). But in the Groovy function it is: def sqrt = {x-> ... } A groovy function can be defined and assigned to any variable, thereby allowing it to be passed around as a first class object. If we look at the complete solution for calculating the square root of a number (using Newton's method - To compute the square root of "x" we start with an estimate of the square root, "y" and continue to improve the the guess by taking the mean of x and x/y ) def sqrtIter(guess: Double, x: Double): Double = if (isGoodEnough(guess, x)) guess else sqrtIter(improve(guess, x), x) def improve(guess: Double, x: Double) = (guess + x / guess) / 2 def isGoodEnough(guess: Double, x: Double) = abs(guess * guess - x) < 0.001 def sqrt(x: Double) = srqtIter(1.0, x) So that's in Scala, if we try Groovy we will see we can achieve pretty much the same thing easily: //Improve the guess using Newton's method def improve = { guess, x -> (guess + x / guess) / 2 } //Check if our guess is good enough, within a chosen threshold def isGoodEnough = {guess, x -> abs(guess * guess - x) < 0.001 } //iterate over guesses until our guess is good enough def sqrtIter = { guess, x -> if (isGoodEnough(guess, x)) guess else sqrtIter(improve(guess, x), x) } //wrap everythin in the square root function call def sqrt = {x -> srqtIter(1.0, x)} Recursion (and tail-recursion): As FP avoids having mutable state, the most common approach to solve problems is to break the problem down in to simple functions and call them recursively - This avoids having to maintain state whilst iterating through loops, and each function call is given its input and produces an output. If we again consider an example from the Scala course, with the example of a simple function that calculates the factorial for a given number. def factorial ={ n -> if (n == 0) 1 else n * factorial(n - 1) } factorial(4) This simple function recursively calculates the factorial, continuing to call itself until all numbers to zero have been considered. As you can see, there is no mutable state - every call to the factorial function simply takes the input and returns an output (the value of n is never changed or re-assigned, n is simply used to calculate output values) There is a problem here, and that is as soon as you attempt to calculate the factorial of a significantly large enough number you will encounter a StackOverflow exception - this is because in the JVM every time a function is called, a frame is added to the stack, so working recursively its pretty easy to hit upon the limit of the stack and encounter this problem. The common way to solve this is by using Tail-Call recursion. This trick is simply to have the last code that is evaluated in the function to be the recursive call - normally in FP languages the compiler/interpreter will recognise this pattern and under the hood, it will really just run the code as a loop (e.g. if we know the very last piece of code in the block of code is calling itself, its really not that different to just having the block of code/function inside a loop construct) In the previous factorial example, it might look like the last code to be executed is the recursive callfactorial(n-1) - however, the value of that call is actually returned to the function and THENmultiplied by n - so actually the last piece of code to be evaluated in the function call is actually n * return value of factorial(n-1). Let's have a look at re-writing the function so it is tail-recursive. def factorial ={ n, accumulator=1 -> if (n == 1) accumulator else factorial(n-1, n*accumulator) } factorial(4) Now, using an accumulator, the last code to be evaluated in the function is our recursive function call. In most FP languages, including Scala, this is enough - however, the JVM doesn't automatically support tail-call recursion, so you actually need to use a rather clunkier approach in Groovy: def factorial ={ n, accumulator=1 -> if (n == 1) accumulator else factorial.trampoline(n-1, n*accumulator) }.trampoline() factorial(4) The use of the trampoline() method means that the function will now be called using tail-call recursion, so there should never be a StackOverflow exception. It's not as nice as in Scala or other languages, but the support is there so we can continue. Currying: This is like function composition - the idea being you take a generic function, and then you curry it with some value to make a more specific application of the function. For example, if we look at a function that given values x and y, it returns z which is the value x percent of y (e.g. given x=10, y=100, it returns the 10 percent of 100, z=10) def percentage = { percentage, x -> x/100 * percentage } The above simple function is a generic mechanism to get a percentage value of another, but if we consider that we wanted a common application of this function was to always calculate 10% of a given value - rather than write a slightly modified version of the function we can simply curry the function as follows: def tenPercent = percentage.curry(10) Now, if the function tenPercent(x) is called, it uses the original percentage() function, but curries the value 10 as the first argument. (If you need to curry other argument positions you can also use the rcurry() function to curry the right most argument, or ncurry() which also takes an argument position - check the Groovy docs on currying for more info) Immutability: Immutability is partially supported in Java normally with use of the final keyword (meaning variables can't be changed after being initially set on object instantiation). Groovy also provides a quick and easy @Immutable annotation that can be added to a class to easily make it immutable. But really, there is more to avoiding immutable state than just having classes as immutable - As we have functions as first class objects, we can easily assign variables and mutate them within a function - so this is more of a mindset or philosophy that you have to get used to. For example: def list = ['groovy', 'functional'] //This mutates the original list list.add('programming') //This creates a new list leaving the original unchanged def newList = list.plus(2, 'programming') The first example is probably more like the Groovy/Java code we are used to writing, but that is mutating the state of the list - where as the second approach leaves the original list unchanged. Map Reduce: As a final note, there are some functions in FP that are pretty common techniques - the most famous of which these days (in part thanks to Google) is Map-Reduce, but the trio of functions are actually Map, Reduce(also known as Fold) & Filter - you can read more about the functions here (or just google them!), but these functions actually correlate pretty nicely to core Groovy functions that you probably use a lot of (assuming you are groovy programmers). Map map is the easiest to understand of the three. It takes in two inputs - a function, and a list. It then applies this function to every element in the list. You can basically do the same thing with a list comprehension however. Sound familiar? This is basically the .collect{} function in Groovy Reduce/Fold fold takes in a function and folds it in between the elements of a list. It's a bit hard to understand at first This one is a bit more complicated to descibe, but is the same as the .inject{} function in groovy Filter filter is easy. It takes in a 'test' and a list, and it chucks out any elements of the list which don't satisfy that test. And another simple one - filtering out a list for desired elements, this is Groovy's .findAll{} function As I said at the start, I am new to FP and coming from an OO background, but hopefully the above isn't too far from the truth! As I get further through the Coursera course I will try to post again, maybe with some of the assignments attempted in Groovy to see how it really stands up. Some useful references: Groovy docs on FP: http://groovy.codehaus.org/Functional+Programming+with+Groovy Coursera Scala course: https://www.coursera.org/course/progfun

The following question will again test your knowledge of the Oracle Weblogic threading model. I’m looking forward for your comments and experience on the same. If you are a Weblogic administrator, I’m certain that you heard of this common problem: stuck threads. This is one of the most common problems you will face when supporting a Weblogic production environment. A Weblogic stuck thread simply means a thread performing the same request for a very long time and more than the configurable Stuck Thread Max Time. Question: How can you detect the presence of STUCK threads during and following a production incident? Answer: As we saw from our last article “Weblogic Thread Monitoring Tips”, Weblogic provides functionalities allowing us to closely monitor its internal self-tuning thread pool. It will also highlight you the presence of any stuck thread. This monitoring view is very useful when you do a live analysis but what about after a production incident? The good news is that Oracle Weblogic will also log any detected stuck thread to the server log. Such information includes details on the request and more importantly, the thread stack trace. This data is crucial and will allow you to potentially better understand the root cause of any slowdown condition that occurred at a certain time. < ExecuteThread: '11' for queue: 'weblogic.kernel.Default (self-tuning)'> <[STUCK] ExecuteThread: '35' for queue: 'weblogic.kernel.Default (self-tuning)' has been busy for "608" seconds working on the request "Workmanager: default, Version: 0, Scheduled=true, Started=true, Started time: 608213 ms POST /App1/jsp/test.jsp HTTP/1.1 Accept: application/x-ms-application... Referer: http://.. Accept-Language: en-US User-Agent: Mozilla/4.0 .. Content-Type: application/x-www-form-urlencoded Accept-Encoding: gzip, deflate Content-Length: 539 Connection: Keep-Alive Cache-Control: no-cache Cookie: JSESSIONID= ]", which is more than the configured time (StuckThreadMaxTime) of "600" seconds. Stack trace: ................................... javax.servlet.http.HttpServlet.service(HttpServlet.java:727) javax.servlet.http.HttpServlet.service(HttpServlet.java:820) weblogic.servlet.internal.StubSecurityHelper$ServletServiceAction.run(StubSecurityHelper.java:227) weblogic.servlet.internal.StubSecurityHelper.invokeServlet(StubSecurityHelper.java:125) weblogic.servlet.internal.ServletStubImpl.execute(ServletStubImpl.java:301) weblogic.servlet.internal.ServletStubImpl.execute(ServletStubImpl.java:184) weblogic.servlet.internal.WebAppServletContext$ServletInvocationAction.... weblogic.servlet.internal.WebAppServletContext$ServletInvocationAction.run() weblogic.security.acl.internal.AuthenticatedSubject.doAs(AuthenticatedSubject.java:321) weblogic.security.service.SecurityManager.runAs(SecurityManager.java:120) weblogic.servlet.internal.WebAppServletContext.securedExecute(WebAppServletContext.java:2281) weblogic.servlet.internal.WebAppServletContext.execute(WebAppServletContext.java:2180) weblogic.servlet.internal.ServletRequestImpl.run(ServletRequestImpl.java:1491) weblogic.work.ExecuteThread.execute(ExecuteThread.java:256) weblogic.work.ExecuteThread.run(ExecuteThread.java:221) Here is one more tip: the generation and analysis of a JVM thread dump will also highlight you stuck threads. As we can see from the snapshot below, the Weblogic thread state is now updated to STUCK, which means that this particular request is being executed since at least 600 seconds or 10 minutes. This is very useful information since the native thread state will typically remain to RUNNABLE. The native thread state will only get updated when dealing with BLOCKED threads etc. You have to keep in mind that RUNNABLE simply means that this thread is healthy from a JVM perspective. However, it does not mean that it truly is from a middleware or Java EE container perspective. This is why Oracle Weblogic has its own internal ExecuteThread state. Finally, if your organization or client is using any commercial monitoring tool, I recommend that you enable some alerting around both hogging thread and stuck thread. This will allow your support team to take some pro-active actions before the affected Weblogic managed server(s) become fully unresponsive.

I’m going to start by discussing the Spring WebMVC configuration and move on from there in future posts.

In this article, I will show how to implement auto-completion using Hibernate Search. The same can be achieved using Solr or ElasticSearch. But I decided to use Hibernate Search as its the simplest to get started with, easily integrates with an existing application and leverages the same core - Lucene. And we get all of this without the overhead of managing Solr/ElasticSearch cluster. In all, I found Hibernate Search to be the go-to search engine for simple use cases. For our use case, we build a product title based auto-completion where often, the user queries are searches for product title. While typing, users should immediately see titles matching their requests, and Hibernate Search should do the hard work to filter the relevant documents in near real-time. Lets have the following JPA annotated Product entity class. public class Product { @Id @Column(name = "sku") private String sku; @Column(name = "upc") private String upc; @Column(name = "title") private String title; .... } We are interested in returning suggestions based on the 'title' field. Title will be indexed based on 2 strategies - N-Gram and Edge N-Gram. Edge N-Gram - This will match only from the left edge of the suggestion text. For this we use KeywordTokenizerFactory (emits the entire input as a single token) and EdgeNGramFilterFactory along with some regex cleansing. N-Gram matches from the start of every word, so that you can get right-truncated suggestions for any word in the text, not only from the first word. The main difference from N-gram is the tokenizer which is StandardTokenizerFactory along with NGramFilterFactory. Using these strategies, if the document field is "A brown fox" and the query is a) "A bro"- Will match b) "bro" - Will match Implementation: In the entity defined above, we can map 'title' property twice with the above strategies. Below are the annotations to instruct Hibernate to index 'title' twice. @Entity @Table(name = "item_master") @Indexed(index = "Products") @AnalyzerDefs({ @AnalyzerDef(name = "autocompleteEdgeAnalyzer", // Split input into tokens according to tokenizer tokenizer = @TokenizerDef(factory = KeywordTokenizerFactory.class), filters = { // Normalize token text to lowercase, as the user is unlikely to // care about casing when searching for matches @TokenFilterDef(factory = PatternReplaceFilterFactory.class, params = { @Parameter(name = "pattern",value = "([^a-zA-Z0-9\\.])"), @Parameter(name = "replacement", value = " "), @Parameter(name = "replace", value = "all") }), @TokenFilterDef(factory = LowerCaseFilterFactory.class), @TokenFilterDef(factory = StopFilterFactory.class), // Index partial words starting at the front, so we can provide // Autocomplete functionality @TokenFilterDef(factory = EdgeNGramFilterFactory.class, params = { @Parameter(name = "minGramSize", value = "3"), @Parameter(name = "maxGramSize", value = "50") }) }), @AnalyzerDef(name = "autocompleteNGramAnalyzer", // Split input into tokens according to tokenizer tokenizer = @TokenizerDef(factory = StandardTokenizerFactory.class), filters = { // Normalize token text to lowercase, as the user is unlikely to // care about casing when searching for matches @TokenFilterDef(factory = WordDelimiterFilterFactory.class), @TokenFilterDef(factory = LowerCaseFilterFactory.class), @TokenFilterDef(factory = NGramFilterFactory.class, params = { @Parameter(name = "minGramSize", value = "3"), @Parameter(name = "maxGramSize", value = "5") }), @TokenFilterDef(factory = PatternReplaceFilterFactory.class, params = { @Parameter(name = "pattern",value = "([^a-zA-Z0-9\\.])"), @Parameter(name = "replacement", value = " "), @Parameter(name = "replace", value = "all") }) }), @AnalyzerDef(name = "standardAnalyzer", // Split input into tokens according to tokenizer tokenizer = @TokenizerDef(factory = StandardTokenizerFactory.class), filters = { // Normalize token text to lowercase, as the user is unlikely to // care about casing when searching for matches @TokenFilterDef(factory = WordDelimiterFilterFactory.class), @TokenFilterDef(factory = LowerCaseFilterFactory.class), @TokenFilterDef(factory = PatternReplaceFilterFactory.class, params = { @Parameter(name = "pattern", value = "([^a-zA-Z0-9\\.])"), @Parameter(name = "replacement", value = " "), @Parameter(name = "replace", value = "all") }) }) // Def }) public class Product { .... } Explanation: 2 custom analyzers - autocompleteEdgeAnalyzer andautocompleteNGramAnalyzer have been defined as per theory in the previous section. Next, we apply these analyzers on the 'title' field to create 2 different indexes. Here is how we do it: @Column(name = "title") @Fields({ @Field(name = "title", index = Index.YES, store = Store.YES, analyze = Analyze.YES, analyzer = @Analyzer(definition = "standardAnalyzer")), @Field(name = "edgeNGramTitle", index = Index.YES, store = Store.NO, analyze = Analyze.YES, analyzer = @Analyzer(definition = "autocompleteEdgeAnalyzer")), @Field(name = "nGramTitle", index = Index.YES, store = Store.NO, analyze = Analyze.YES, analyzer = @Analyzer(definition = "autocompleteNGramAnalyzer")) }) private String title; Start indexing: public void index() throws InterruptedException { getFullTextSession().createIndexer().startAndWait(); } Once indexed, inspect the index using Luke and you should be able to see title analyzed and stored as N-Grams and Edge N-Grams. Search Query: private static final String TITLE_EDGE_NGRAM_INDEX = "edgeNGramTitle"; private static final String TITLE_NGRAM_INDEX = "nGramTitle"; @Transactional(readOnly = true) public synchronized List getSuggestions(final String searchTerm) { QueryBuilder titleQB = getFullTextSession().getSearchFactory() .buildQueryBuilder().forEntity(Product.class).get(); Query query = titleQB.phrase().withSlop(2).onField(TITLE_NGRAM_INDEX) .andField(TITLE_EDGE_NGRAM_INDEX).boostedTo(5) .sentence(searchTerm.toLowerCase()).createQuery(); FullTextQuery fullTextQuery = getFullTextSession().createFullTextQuery( query, Product.class); fullTextQuery.setMaxResults(20); @SuppressWarnings("unchecked") List results = fullTextQuery.list(); return results; } And we have a working suggester. What next? Expose the functionality via a REST API and integrate it with jQuery, examples of which can be easily found. You can also use the same strategy with Solr and ElasticSearch.

When putting together data sets to play around with, one of the more boring tasks is stripping out characters that you’re not interested in and more often than not those characters are white spaces. Since I’ve been building data sets using Clojure I wanted to write a function that would do this for me. I started out with the following string: (def word " with a little bit of space we can make it through the night ") which I wanted to format in such a way that there would be a maximum of one space between each word. I start out by using the trim function but that only removes white space from the beginning and end of a string: > (clojure.string/trim word) "with a little bit of space we can make it through the night" I wanted to get rid of the space in between ‘a’ and ‘little’ as well so I wrote the following code to split on a space and filter out any excess spaces that still remained before joining the words back together: > (clojure.string/join " " (filter #(not (clojure.string/blank? %)) (clojure.string/split word #" "))) "with a little bit of space we can make it through the night" I wanted to try and make it a bit easier to read by using the thread last (->>) macro but that didn’t work as well as I’d hoped because clojure.string/split doesn’t take the string in as its last parameter: > (->> (clojure.string/split word #" ") (filter #(not (clojure.string/blank? %))) (clojure.string/join " ")) "with a little bit of space we can make it through the night" I worked around it by creating a specific function for splitting on a space: (defn split-on-space [word] (clojure.string/split word #"\s")) which means we can now chain everything together nicely: > (->> word split-on-space (filter #(not (clojure.string/blank? %))) (clojure.string/join " ")) "with a little bit of space we can make it through the night" I couldn’t find a cleaner way to do this but I’m sure there is one and my googling just isn’t up to scratch so do let me know in the comments!

I wanted to do some date manipulation in Clojure recently and figured that since clj-time is a wrapper around Joda Time it’d probably do the trick. The first thing we need to do is add the dependency to our project file and then run lein reps to pull down the appropriate JARs. The project file should look something like this: project.clj (defproject ranking-algorithms "0.1.0-SNAPSHOT" :license {:name "Eclipse Public License" :url "http://www.eclipse.org/legal/epl-v10.html"} :dependencies [[org.clojure/clojure "1.4.0"] [clj-time "0.6.0"]]) Now let’s load the clj-time.format namespace into the REPL since we know we’ll be parsing dates: > (require '(clj-time [format :as f])) The string that I want to convert into a date looks like this: (def string-date "18 September 2012") The first thing we should do is check whether there is an existing formatter that we can use by evaluating the following function: > (f/show-formatters) ... :hour-minute 06:45 :hour-minute-second 06:45:22 :hour-minute-second-fraction 06:45:22.473 :hour-minute-second-ms 06:45:22.473 :mysql 2013-09-20 06:45:22 :ordinal-date 2013-263 :ordinal-date-time 2013-263T06:45:22.473Z :ordinal-date-time-no-ms 2013-263T06:45:22Z :rfc822 Fri, 20 Sep 2013 06:45:22 +0000 ... There are a lot of different built in formatters but unfortunately I couldn’t find one that exactly matched our date format so we’ll have to write our own one. For that we’ll need to refresh our knowledge of Java date formatting: We end up with the following formatter: > (f/parse (f/formatter "dd MMM YYYY") string-date) # It took me much longer than it should have to remember that ‘MMM’ is the pattern to match a short form of a month but it’s just the same as what we’d have to do in Java but with some neat wrapper functions.

This post comes from Alberto Pose at the MuleSoft blog. Introduction Suppose that you have a Maven project and you want to download Node.js modules previously uploaded to NPM. One way of doing that without running node is by using the npm-maven-plugin. It allows the user to download the required Node modules without running node.js: It is completely implemented on the JVM. Getting Started First of all, you will need to add the Mule Maven repo to your pom.xml file: mulesoft-releases MuleSoft Repository https://repository.mulesoft.org/releases/ After doing that, you will need to add the following to the build->plugin section of your pom.xml file: org.mule.tools.javascript npm-maven-plugin 1.0 generate-sources fetch-modules colors:0.5.1 jshint:0.8.1 Then just execute: mvn generate-sources and that’s it! One more thing… By default, the modules can be found in src/main/resources/META-INF but that path can be changed setting the ‘outputDirectory’ parameter. Also, module transitivity is taken into account. That means that it will download all the required dependencies before downloading the specified module. Show me the code! The source code can be found here. Feel free to fork the project and propose changes to it. Happy (Node.js and Maven) hacking!

ElasticSearch provides Java API, thus it executes all operations asynchronously by using client object.

When I was implementing the Elo Rating algorithm a few weeks ago one thing I needed to do was come up with a base ranking for each team. I started out with a set of teams that looked like this: (def teams #{ "Man Utd" "Man City" "Arsenal" "Chelsea"}) and I wanted to transform that into a map from the team to their ranking e.g. Man Utd -> {:points 1200} Man City -> {:points 1200} Arsenal -> {:points 1200} Chelsea -> {:points 1200} I had read the documentation of array-map, a function which can be used to transform a collection of pairs into a map, and it seemed like it might do the trick. I started out by building an array of pairs using mapcat: > (mapcat (fn [x] [x {:points 1200}]) teams) ("Chelsea" {:points 1200} "Man City" {:points 1200} "Arsenal" {:points 1200} "Man Utd" {:points 1200}) array-map constructs a map from pairs of values e.g. > (array-map "Chelsea" {:points 1200} "Man City" {:points 1200} "Arsenal" {:points 1200} "Man Utd" {:points 1200}) ("Chelsea" {:points 1200} "Man City" {:points 1200} "Arsenal" {:points 1200} "Man Utd" {:points 1200}) Since we have a collection of pairs rather than individual pairs we need to use the apply function as well: > (apply array-map ["Chelsea" {:points 1200} "Man City" {:points 1200} "Arsenal" {:points 1200} "Man Utd" {:points 1200}]) {"Chelsea" {:points 1200}, "Man City" {:points 1200}, "Arsenal" {:points 1200}, "Man Utd" {:points 1200} And if we put it all together we end up with the following: > (apply array-map (mapcat (fn [x] [x {:points 1200}]) teams)) {"Man Utd" {:points 1200}, "Man City" {:points 1200}, "Arsenal" {:points 1200}, "Chelsea" {:points 1200} It works but the function we pass to mapcat feels a bit clunky. Since we just need to create a collection of team/ranking pairs we can use the vector and repeat functions to build that up instead: > (mapcat vector teams (repeat {:points 1200})) ("Chelsea" {:points 1200} "Man City" {:points 1200} "Arsenal" {:points 1200} "Man Utd" {:points 1200}) And if we put the apply array-map code back in we still get the desired result: > (apply array-map (mapcat vector teams (repeat {:points 1200}))) {"Chelsea" {:points 1200}, "Man City" {:points 1200}, "Arsenal" {:points 1200}, "Man Utd" {:points 1200} Alternatively we could use assoc like this: > (apply assoc {} (mapcat vector teams (repeat {:points 1200}))) {"Man Utd" {:points 1200}, "Arsenal" {:points 1200}, "Man City" {:points 1200}, "Chelsea" {:points 1200} I also came across the into function which seemed useful but took in a collection of vectors: > (into {} [["Chelsea" {:points 1200}] ["Man City" {:points 1200}] ["Arsenal" {:points 1200}] ["Man Utd" {:points 1200}] ]) We therefore need to change the code to use map instead of mapcat: > (into {} (map vector teams (repeat {:points 1200}))) {"Chelsea" {:points 1200}, "Man City" {:points 1200}, "Arsenal" {:points 1200}, "Man Utd" {:points 1200} However, my favourite version so far uses the zipmap function like so: > (zipmap teams (repeat {:points 1200})) {"Man Utd" {:points 1200}, "Arsenal" {:points 1200}, "Man City" {:points 1200}, "Chelsea" {:points 1200} I’m sure there are other ways to do this as well so if you know any let me know in the comments.

one of the goals of our development with our javafx application is to try to keep as much of the ui design as possible within the scene builder ui design tool , and the business logic for the application in java. one of the things that is not entirely clear is how to create a new component in scene builder and then reuse that component within other components created in scene builder. in the example below, i illustrate how to create a custom table and ‘add plan’ components, and then add them to a new scene using fxml. the first step is to create a simple component which acts as an “add plan” widget on the ui. the widget contains an anchorpane, imageview and label. for the next step, open up the fxml file and change the first “anchorpane” declaration to “ create a class which will act as both the root of the component as well as its controller. the class must extend the type that was previously defined in the fxml file. use the fxml loader to set the root and controller of the component to “this” class, and then load the component’s fxml file. /* * to change this template, choose tools | templates * and open the template in the editor. */ package com.lynden.fx.test; import com.lynden.ui.util.uiutilities; import java.io.ioexception; import javafx.event.eventhandler; import javafx.fxml.fxml; import javafx.fxml.fxmlloader; import javafx.scene.input.dragevent; import javafx.scene.input.dragboard; import javafx.scene.input.transfermode; import javafx.scene.layout.anchorpane;/** * * @author robt */ public class testbutton extends anchorpane { @fxml private anchorpane mytestbutton; public testbutton() { fxmlloader fxmlloader = new fxmlloader( getclass().getresource("/com/lynden/planning/ui/testbutton.fxml")); fxmlloader.setroot(this); fxmlloader.setcontroller(this); try { fxmlloader.load(); } catch (ioexception exception) { throw new runtimeexception(exception); } } } next, the 2nd component is a tableview which contains a collection of beans, and displays their corresponding data. as with the last component, the first declaration is changed to next, the corresponding root and controller class is created for the table component. /* * to change this template, choose tools | templates * and open the template in the editor. */ package com.lynden.fx.test; import com.lynden.fx.inboundbean; import java.io.ioexception; import javafx.event.eventhandler; import javafx.event.eventtype; import javafx.fxml.fxml; import javafx.fxml.fxmlloader; import javafx.scene.control.tableview; import javafx.scene.input.clipboardcontent; import javafx.scene.input.dragboard; import javafx.scene.input.mouseevent; import javafx.scene.input.transfermode; import javafx.scene.layout.anchorpane; /** * * @author robt */ public class testtable extends anchorpane { @fxml private tableview mytableview; public testtable() { fxmlloader fxmlloader = new fxmlloader( getclass().getresource("/com/lynden/planning/ui/testtable.fxml")); fxmlloader.setroot(this); fxmlloader.setcontroller(this); try { fxmlloader.load(); } catch (ioexception exception) { throw new runtimeexception(exception); } } } finally, a new scene can be created which includes both the testtable and testbutton components that were constructed above. unfortunately, custom components can’t be added to the scene builder palette, so they must be inserted manually into the fxml file. you just need to ensure that you have the proper import statements defined, and the testtable and testbutton components can be inserted into the fxml code just as any native javafx component. when scene builder opens the fxml file you will see that both components are displayed on the new scene that’s it, hopefully this will help others who have been looking at adding custom components to their uis that are designed with scene builder. twitter: @robterp

I’ve been playing with Clojure over the last few weeks and as a result I’ve been using a lot of maps to represent the data. For example if we have the following map of teams to Glicko ratings and ratings deviations: (def teams { "Man. United" {:points 1500 :rd 350} "Man. City" {:points 1450 :rd 300} }) We might want to increase Man. United’s points score by one for which we could use the update-in function: > (update-in teams ["Man. United" :points] inc) {"Man. United" {:points 1501, :rd 350}, "Man. City" {:points 1450, :rd 300} The 2nd argument to update-in is a nested associative structure i.e. a sequence of keys into the map in this instance. If we wanted to reset Man. United’s points score we could use assoc-in: > (assoc-in teams ["Man. United" :points] 1) {"Man. United" {:points 1, :rd 350}, "Man. City" {:points 1450, :rd 300} If we want to update multiple keys at once then we can chain them using the -> (thread first) macro: (-> teams (assoc-in ["Man. United" :points] 1600) (assoc-in ["Man. United" :rd] 200)) {"Man. United" {:points 1600, :rd 200}, "Man. City" {:points 1450, :rd 300} If instead of replacing just one part of the value we want to replace the whole entry we could use associnstead: > (assoc teams "Man. United" {:points 1600 :rd 300}) {"Man. United" {:points 1600, :rd 300}, "Man. City" {:points 1450, :rd 300} assoc can also be used to add a new key/value to the map. e.g. > (assoc teams "Arsenal" {:points 1500 :rd 330}) {"Man. United" {:points 1500, :rd 350}, "Arsenal" {:points 1500, :rd 330}, "Man. City" {:points 1450, :rd 300} dissoc plays the opposite role and returns a new map without the specified keys: > (dissoc teams "Man. United" "Man. City") {} And those are all the map based functions I’ve played around with so far…

Program Statement How to generate Hailstone Sequence in Java? Solution The Hailstone sequence of numbers can be generated from a starting positive integer, n by: If n is 1 then the sequence ends. If n is even then the next n of the sequence = n/2 If n is odd then the next n of the sequence = (3 * n) + 1 Code ? package com.skilledmonster.examples.operations; import java.util.Scanner; /** * Program to generate Hailstone Sequence. * This program reads a number from the user then displays the Hailstone sequence * for that number followed by a line that shows the number of steps taken to reach 1. * * @author Jagadeesh Motamarri * @version 1.0 */ public class HailstoneSequenceGenerator { public static void main(String[] args) { Scanner inputScanner = new Scanner(System.in); System.out.printf("Enter a Number: "); try { int number = inputScanner.nextInt(); int steps = 0; while (number != 1) { if (number % 2 == 0) { System.out.println(number + " is even, so I take half: " + number / 2); number /= 2; } else { System.out.println(number + " is odd, so I make 3n + 1: " + (number * 3 + 1)); number = number * 3 + 1; } steps++; } System.out.println("The process took " + steps + (steps < 2 ? " step" : " steps") + " to reach 1"); } catch (Exception e) { System.out.println("Not a Number!! Run your Program again "); } } } Output As shown in the console output, for interger 17, it took 12 steps to reach 1 using Hailstone Sequence. References http://en.wikipedia.org/wiki/Collatz_conjecture