import win32gui from re import match def draw_line(): print 'x1,y1,x2,y2?' s=raw_input() if match('\d+,\d+,\d+,\d+',s): x1,y1,x2,y2=s.split(',') x1=int(x1) y1=int(y1) x2=int(x2) y2=int(y2) hwnd=win32gui.WindowFromPoint((x1,y1)) hdc=win32gui.GetDC(hwnd) x1c,y1c=win32gui.ScreenToClient(hwnd,(x1,y1)) x2c,y2c=win32gui.ScreenToClient(hwnd,(x2,y2)) win32gui.MoveToEx(hdc,x1c,y1c) win32gui.LineTo(hdc,x2c,y2c) win32gui.ReleaseDC(hwnd,hdc) main() def draw_point(): print 'x,y,color?' s=raw_input() if match('\d+,\d+,\d+',s): x,y,color=s.split(',') x=int(x) y=int(y) color=int(color) hwnd=win32gui.WindowFromPoint((x,y)) hdc=win32gui.GetDC(hwnd) x1,y1=win32gui.ScreenToClient(hwnd,(x,y)) win32gui.SetPixel(hdc,x1,y1,color) win32gui.ReleaseDC(hwnd,hdc) main() def get_pixel_col(): print 'x,y?' s=raw_input() if match('\d+,\d+',s): x,y=s.split(',') x=int(x) y=int(y) hwnd=win32gui.WindowFromPoint((x,y)) hdc=win32gui.GetDC(hwnd) x1,y1=win32gui.ScreenToClient(hwnd,(x,y)) color=win32gui.GetPixel(hdc,x1,y1) win32gui.ReleaseDC(hwnd,hdc) print color main() def get_current_pos_info(): x,y=win32gui.GetCursorPos() hwnd=win32gui.WindowFromPoint((x,y)) hdc=win32gui.GetDC(hwnd) x1,y1=win32gui.ScreenToClient(hwnd,(x,y)) print x,y,win32gui.GetPixel(hdc,x1,y1) win32gui.ReleaseDC(hwnd,hdc) main() def main(): print ('''l. draw line p. draw point g. get pixel color c. get current mouse position's info''') s=raw_input() if s.lower()=='l': draw_line() if s.lower()=='p': draw_point() if s.lower()=='g': get_pixel_col() if s.lower()=='c': get_current_pos_info() main()

This article is taken from NHibernate in Action from Manning Publications. This article delves into the NHibernate type system. For the table of contents, the Author Forum, and other resources, go to http://www.manning.com/kuate/. It is being reproduced here by permission from Manning Publications. Manning ebooks are sold exclusively through Manning. Visit the book's page for more information. Softbound print: February 2009 | 400 pages ISBN: 1932394923 Use code "dzone30" to get 30% off any version of this book. Entities are the coarse-grained classes in a system. You usually define the features of a system in terms of the entities involved: “the user places a bid for an item” is a typical feature definition that mentions three entities - user, bid and item. In contrast, value types are the much more fine grained classes in a system, such as strings, numbers, dates and monetary amounts. These fine grained classes can be used in many places and serve many purposes; the value type string can store email address, usernames and many other things. Strings are simple value types, but it is possible (but less common) to create value types that are more complex. For example, a value type could contain several fields, like an Address. So how do we differentiate between value types and entities? From a more formal standpoint, we an say an entity is any class whose instances have their own persistent identity, and a value type is a class who’s instances do not. The entity instances may therefore be in any of the three persistent lifecycle states: transient, detached, or persistent. However, we don’t consider these lifecycle states to apply to the simpler value type instances. Furthermore, because entities have their own lifecycle, the Save() and Delete() methods of the NHibernate ISession interface will apply to them, but never to value type instances. To illustrate, lets consider Figure A. Figure A – An order entity with TotalAmount value type TotalAmount is an instance of value type Money. Because value types are completely bound to that their owning entities, TotalAmount is only saved when the Order is saved. Associations and Value Types As we said, not all value types are simple. It’s possible for value types to also define associations. For example, our Money value type could have a property called Currency that is an association to a Currency entity as shown in figure 6.1.2 Figure B – The Money value type with association to a Currency entity. If your value types have associations, they must always point to entities. The reason is that, if those associations could point from entities to value types, a value type could potentially belong to several entities, which isn’t desirable. This is one of the great things about value types; if you update a value type instance, you know that it only affects the entity that owns it. For example, changing the TotalAmount of one Order simply cannot accidentally affect others. So far we’ve talked about value types and entities from an object oriented perspective. To build a more complete picture, we shall now take a look at how the relational model sees value types and entities, and how NHibernate bridges the gap. Bridging from objects to database You may be aware that a database architect would see the world of value types and entities slightly differently to this object oriented view of things. In the database, tables represent the entities, and columns represent the values. Even join tables and lookup tables are entities. So, if all tables represent entities in the database, does that mean we have to map all tables to entities in our .NET domain model? What about those value types we wanted in our model? NHibernate provides constructs for dealing with this. For example, a many-to-many association mapping hides the intermediate association table from the application, so we don’t end up with an unwanted entity in our domain model. Similarly, a collection of value typed strings behaves like a value type from the point of view of the .NET domain model even though it’s mapped to its own table in the database. These features have their uses and can often simplify your C# code. However, over time we have become suspicious of them; these “hidden” entities often end up needing exposure in our applications as business requirements evolve. The many-to-many association table, for example, often has additional columns added as the application matures, so the relationship itself becomes an entity. You might not go far wrong if you make every database-level entity be exposed to the application as an entity class. For example, we’d be inclined to model the many-to-many association as two one-to-many associations to an intervening entity class. We’ll leave the final decision to you, and return to the topic of many-to-many entity associations later in this chapter. Mapping types So far we’ve discussed the differences between value types and entities, as seen from the object oriented and relational database perspectives. We know that mapping entities is quite straight forward – entity classes are simply always mapped to database tables using , , and mapping elements. Value types need something more, which is where mapping types enter the picture. Consider this mapping of the CaveatEmptor User and email address: In ORM, you have to worry about both .NET types and SQL data types. In the example above imagine that the Email field is a .NET string, and EMAIL column is an SQL varchar. We want to tell NHibernate know how to carry out this conversion, which is where NHibernate mapping types come in. In this case, we’ve specified the mapping type "String", which we know is appropriate for this particular conversion. The String mapping type isn’t the only one built into NHibernate; NHibernate comes with various mapping types that define default persistence strategies for primitive .NET types and certain classes, such as like DateTime. Built-in mapping types NHibernate’s built-in mapping types usually reflect the name of the .NET type they map. Sometimes you’ll have a choice of mapping types available to map a particular .NET type to the database. However, the built-in mapping types aren’t designed to perform arbitrary conversions, such as mapping a VARCHAR field value to a .NET Int32 property value. If you want this kind of functionality, you will have to define your own custom value types. We will get to that topic a little later in this chapter. We’ll now discuss the basic types; date and time, objects, large objects, and various other built-in mapping types and show you what .NET and System.Data.DbType data types they handle. DbTypes are used to infer the data provider types (hence SQL data types). .NET primitive mapping types The basic mapping types in table A map .NET primitive types to appropriate DbTypes. Table A Primitive types Mapping Type .NET Type System.Data.DbType Int16 System.Int16 DbType.Int16 Int32 System.Int32 DbType.Int32 Int64 System.Int64 DbType.Int64 Single System.Single DbType.Single Double System.Double DbType.Double Decimal System.Decimal DbType.Decimal Byte System.Byte DbType.Byte Char System.Char DbType.StringFixedLength - 1 character AnsiChar System.Char DbType.AnsiStringFixedLength - 1 character Boolean System.Boolean DbType.Boolean Guid System.Guid DbType.Guid PersistentEnum System.Enum (an enumeration) The DbType for the underlying value TrueFalse System.Boolean DbType.AnsiStringFixedLength - either 'T' or 'F' YesNo System.Boolean DbType.AnsiStringFixedLength - either 'Y' or 'N' You’ve probably noticed that your database doesn’t support some of the DbTypes listed in table A. However, ADO.NET provides a partial abstraction of vendor-specific SQL data types, allowing NHibernate to work with ANSI-standard types when executing data manipulation language (DML). For database-specific DDL generation, NHibernate translates from the ANSI-standard type to an appropriate vendor-specific type, using the built-in support for specific SQL dialects. (You usually don’t have to worry about SQL data types if you’re using NHibernate for data access and data schema definition.) NHibernate supports a number of mapping types coming from Hibernate for compatibility (useful for those coming over from Hibernate or using Hibernate tools to generate hbm.xml files). Table B lists the additional names of NHibernate mapping types. Table B Additional names of NHibernate mapping types Mapping type Additional name Binary binary Boolean boolean Byte byte Character character CultureInfo locale DateTime datetime Decimal big_decimal Double double Guid guid Int16 short Int32 int Int32 integer Int64 long Single float String string TrueFalse true_false Type class YesNo yes_no From this table, you can see that writing type="integer" or type="int" is identical to type="Int32". Note that this table contains many mapping types that will be discussed in the following sections. Date/time mapping types Table C lists NHibernate types associated with dates, times, and timestamps. In your domain model, you may choose to represent date and time data using either System.DateTime or System.TimeSpan. As they have different purposes, the choice should be easy. Table C Date and time typesExcerptOpenSourceSOAch5-6.doc Mapping Type .NET Type System.Data.DbType DateTime System.DateTime DbType.DateTime - ignores the milliseconds Ticks System.DateTime DbType.Int64 TimeSpan System.TimeSpan DbType.Int64 Timestamp System.DateTime DbType.DateTime - as specific as database supports Object mapping types All .NET types in tables A and C are value types (i.e. derived from System.ValueType). This means that they can’t be null; unless you use the .NET 2.0 Nullable structure or the Nullables add-in, as discussed in the next section. Table D lists NHibernate types for handling .NET types derived from System.Object (which can store null values). Table D Nullable object typesExcerptOpenSourceSOAch5-6.doc Mapping Type .NET Type System.Data.DbType String System.String DbType.String AnsiString System.String DbType.AnsiString This table is completed by tables E and F which also contain nullable mapping types. Large object mapping types Table E lists NHibernate types for handling binary data and large objects. Note that none of these types may be used as the type of an identifier property. Table E Binary and large object typesExcerptOpenSourceSOAch5-6.doc Mapping Type .NET Type System.Data.DbType Binary System.Byte[] DbType.Binary BinaryBlob System.Byte[] DbType.Binary StringBlob System.String DbType.String Serializable Any System.Object marked with SerializableAttribute DbType.Binary BinaryBlob and StringClob are mainly supported by SQL Server. They can have a very large size and are fully loaded in memory. This can be a performance killer if used to store very large objects. So use this feature carefully. Note that you must set the NHibernate property "prepare_sql" to "true" to enable this feature. You can find up-to-date design patterns and tips for large object usage on the NHibernate website. Various CLR mapping types Table F lists NHibernate types for various other types of the CLR that may be represented as DbType.Strings in the database. Table F Other CLR-related typesExcerptOpenSourceSOAch5-6.doc Mapping Type .NET Type System.Data.DbType CultureInfo System.Globalization.CultureInfo DbType.String - 5 chars for culture Type System.Type DbType.String holding Assembly Qualified Name Certainly, isn’t the only NHibernate mapping element that has a type attribute. Using mapping types All of the basic mapping types may appear almost anywhere in the NHibernate mapping document, on normal property, identifier property, and other mapping elements. The , , , , , and elements all define an attribute named type. (There are certain limitations on which mapping basic types may function as an identifier or discriminator type, however.) You can see how useful the built-in mapping types are in this mapping for the BillingDetails class: ... The BillingDetails class is mapped as an entity. Its discriminator, id, and Number properties are value typed, and we use the built-in NHibernate mapping types to specify the conversion strategy. It’s often not necessary to explicitly specify a built-in mapping type in the XML mapping document. For instance, if you have a property of .NET type System.String, NHibernate will discover this using reflection and select String by default. We can easily simplify the previous mapping example: .... For each of the built-in mapping types, a constant is defined by the class NHibernate. NHibernateUtil. For example, NHibernate.String represents the String mapping type. These constants are useful for query parameter binding, as discussed in more detail in chapter 8: session.CreateQuery("from Item i where i.Description like :desc") .SetParameter("desc", desc, NHibernate.String) .List(); These constants are also useful for programmatic manipulation of the NHibernate mapping metamodel, as discussed in chapter 3. Of course, NHibernate isn’t limited to the built-in mapping types; you can create your own custom mapping types for handling certain scenarios. We’ll take a look this next, and explain how the mapping type system is a central to NHibernates flexibility. Creating custom mapping types Object-oriented languages like C# make it easy to define new types by writing new classes. Indeed, this is a fundamental part of the definition of object orientation. If you were limited to the predefined built-in NHibernate mapping types when declaring properties of persistent classes, you’d lose much of C#’s expressiveness. Furthermore, your domain model implementation would be tightly coupled to the physical data model, since new type conversions would be impossible. In order to avoid that, NHibernate provides a very powerful feature called custom mapping types. NHibernate provides two user-friendly interfaces that applications may use when defining new mapping types, the first being NHibernate.UserTypes.IUserType. IUserType is suitable for most simple cases and even for some more complex problems. Let’s use it in a simple scenario. Our Bid class defines an Amount property and our Item class defines an InitialPrice property, both monetary values. So far, we’ve only used a simple System.Double to represent the value, mapped with Double to a single DbType.Double column. Suppose we wanted to support multiple currencies in our auction application and that we had to refactor the existing domain model for this change. One way to implement this change would be to add new properties to Bid and Item: AmountCurrency and InitialPriceCurrency. We would then map these new properties to additional VARCHAR columns with the built-in String mapping type. Imagine if we had currency stored in 100 places, this would be lots of changes. We hope you never use this approach! Creating an implementation of IUserType Instead, we should create a MonetaryAmount class that encapsulates both currency and amount. This is a class of the domain model and doesn’t have any dependency on NHibernate interfaces: [Serializable] public class MonetaryAmount { private readonly double value; private readonly string currency; public MonetaryAmount(double value, string currency) { this.value = value; this.currency = currency; } public double Value { get { return value; } } public string Currency { get { return currency; } } public override bool Equals(object obj) { ... } public override int GetHashCode() { ... } } We’ve also made life simpler by making MonetaryAmount an immutable class, meaning it can’t be changed after it’s instantiated. We would have to implement Equals() and GetHashCode() to complete the class - but there is nothing special to consider here aside that they must be consistent, and GetHashCode() should return mostly unique numbers. We will use this new MonetaryAmount to replace the Double, as defined on the InitialPrice property for Item. We would benefit by using this new class in other places, such as the Bid.Amount. The next challenge is in mapping our new MonetaryAmount properties to the database. Suppose we’re working with a legacy database that contains all monetary amounts in USD. Our new class means our application code is no longer restricted to a single currency, but it will take time to get the changes done by the database team. Until this happens, we’d like to store just the Amount property of MonetaryAmount to the database. Because we can’t store the currency yet, we’ll convert all Amounts to USD before we save them, and from USD when we load them. The first step to handling this is to tell NHibernate how to handle our Monetarymount type. To do this, we create a MonetaryAmountUserType class that implements the NHibernate interface IUserType. Our custom mapping type is shown in listing A. Listing A Custom mapping type for monetary amounts in USD using System; using System.Data; using NHibernate.UserTypes; public class MonetaryAmountUserType : IUserType { private static readonly NHibernate.SqlTypes.SqlType[] SQL_TYPES = { NHibernateUtil.Double.SqlType }; public NHibernate.SqlTypes.SqlType[] SqlTypes { |1 get { return SQL_TYPES; } } public Type ReturnedType { get { return typeof(MonetaryAmount); } } |2 public new bool Equals( object x, object y ) { |3 if ( object.ReferenceEquals(x,y) ) return true; if (x == null || y == null) return false; return x.Equals(y); } public object DeepCopy(object value) { return value; } |4 public bool IsMutable { get { return false; } } |5 public object NullSafeGet(IDataReader dr, string[] names, object owner){ |6 object obj = NHibernateUtil.Double.NullSafeGet(dr, names[0]); if ( obj==null ) return null; double valueInUSD = (double) obj; return new MonetaryAmount(valueInUSD, "USD"); } public void NullSafeSet(IDbCommand cmd, object obj, int index) { |7 if (obj == null) { ((IDataParameter)cmd.Parameters[index]).Value = DBNull.Value; } else { MonetaryAmount anyCurrency = (MonetaryAmount)obj; MonetaryAmount amountInUSD = MonetaryAmount.Convert( anyCurrency, "USD" ); ((IDataParameter)cmd.Parameters[index]).Value = amountInUSD.Value; } } public static MonetaryAmount Convert( MonetaryAmount m, string targetCurrency) { ... |8 } } The SqlTypes property tells NHibernate what SQL column types to use for DDL schema generation, as seen in #1. The types are subclasses of NHibernate.SqlTypes.SqlType. Notice that this property returns an array of types. An implementation of IUserType may map a single property to multiple columns, but our legacy data model only has a single Double. In #2, we can see that ReturnedType tells NHibernate what .NET type is mapped by this IUserType. The IUserType is responsible for dirty-checking property values (#3). The Equals() method compares the current property value to a previous snapshot and determines whether the property is dirty and must by saved to the database. The IUserType is also partially responsible for creating the snapshot in the first place, as shown in #4. Since MonetaryAmount is an immutable class, the DeepCopy() method returns its argument. In the case of a mutable type, it would need to return a copy of the argument to be used as the snapshot value. This method is also called when an instance of the type is written to or read from the second level cache. NHibernate can make some minor performance optimizations for immutable types. The IsMutable (#5) property tells NHibernate that this type is immutable. The NullSafeGet() method shown near #6 retrieves the property value from the ADO.NET IDataReader. You can also access the owner of the component if you need it for the conversion. All database values are in USD, so you have to convert the MonetaryAmount returned by this method before you show it to the user. In #7, the NullSafeSet() method writes the property value to the ADO.NET IDbCommand. This method takes whatever currency is set and converts it to a simple Double USD value before saving. Note that, for briefness, we haven’t provided a Convert function as shown in #8. If we were to implement it, it would have code that converts between various currencies. Mapping the InitialPrice property of Item can be done as follows: This is the simplest kind of transformation that an implementation of IUserType could perform. It takes a Value Type class and maps it to a single database column. Much more sophisticated things are possible; a custom mapping type could perform validation, it could read and write data to and from an Active Directory, or it could even retrieve persistent objects from a different NHibernate ISession for a different database. You’re limited mainly by your imagination and performance concerns! In a perfect world, we’d prefer to represent both the amount and currency of our monetary amounts in the database, so we’re not limited to storing just USD. We could still use an IUserType for this, but it’s limited; If an IUserType is mapped with more than one property, we can’t use them our HQL or Criteria queries. The NHibernate query engine wouldn’t know anything about the individual properties of MonetaryAmount. You still access the properties in your C# code (MonetaryAmount is just a regular class of the domain model, after all), but not in NHibernate queries. To allow for a custom value type with multiple properties that can be accessed in queries, we should use the ICompositeUserType interface. This interface exposes the properties of our MonetaryAmount to NHibernate. Creating an implementation of ICompositeUserType To demonstrate the flexibility of custom mapping types, we won’t have to change our MonetaryAmount domain model class at all—we change only the custom mapping type, as shown in listing B. Listing B Custom mapping type for monetary amounts in new database schemas using System; using System.Data; using NHibernate.UserTypes; public class MonetaryAmountCompositeUserType : ICompositeUserType { public Type ReturnedClass { get { return typeof(MonetaryAmount); } } public new bool Equals( object x, object y ) { if ( object.ReferenceEquals(x,y) ) return true; if (x == null || y == null) return false; return x.Equals(y); } public object DeepCopy(object value) { return value; } public bool IsMutable { get { return false; } } public object NullSafeGet(IDataReader dr, string[] names, NHibernate.Engine.ISessionImplementor session, object owner) { object obj0 = NHibernateUtil.Double.NullSafeGet(dr, names[0]); object obj1 = NHibernateUtil.String.NullSafeGet(dr, names[1]); if ( obj0==null || obj1==null ) return null; double value = (double) obj0; string currency = (string) obj1; return new MonetaryAmount(value, currency); } public void NullSafeSet(IDbCommand cmd, object obj, int index, NHibernate.Engine.ISessionImplementor session) { if (obj == null) { ((IDataParameter)cmd.Parameters[index]).Value = DBNull.Value; ((IDataParameter)cmd.Parameters[index+1]).Value = DBNull.Value; } else { MonetaryAmount amount = (MonetaryAmount)obj; ((IDataParameter)cmd.Parameters[index]).Value = amount.Value; ((IDataParameter)cmd.Parameters[index+1]).Value = amount.Currency; } } public string[] PropertyNames { |1 get { return new string[] { "Value", "Currency" }; } } public NHibernate.Type.IType[] PropertyTypes { |2 get { return new NHibernate.Type.IType[] { NHibernateUtil.Double, NHibernateUtil.String }; } } public object GetPropertyValue(object component, int property) { |3 MonetaryAmount amount = (MonetaryAmount) component; if (property == 0) return amount.Value; else return amount.Currency; } public void SetPropertyValue(object comp, int property, object value) { |4 throw new Exception("Immutable!"); } public object Assemble(object cached, |5 NHibernate.Engine.ISessionImplementor session, object owner) { return cached; } public object Disassemble(object value, |6 NHibernate.Engine.ISessionImplementor session) { return value; } } #1 shows how an implementation of ICompositeUserType has its own properties, defined by PropertyNames. Similarly, the properties each have their own type, as defined by PropertyTypes (#2). The GetPropertyValue() method, shown in #3, returns the value of an individual property of the MonetaryAmount. Since MonetaryAmount is immutable, we can’t set property values individually (see #4) This isn’t a problem because this method is optional anyway. In #5, the Assemble() method is called when an instance of the type is read from the second-level cache. The Disassemble() method is called when an instance of the type is written to the second-level cache, as shown in #6. The order of properties must be the same in the PropertyNames, PropertyTypes, and GetPropertyValues() methods. The InitialPrice property now maps to two columns, so we declare both in the mapping file. The first column stores the value; the second stores the currency of the MonetaryAmount. Note that the order of columns must match the order of properties in your type implementation: In a query, we can now refer to the Amount and Currency properties of the custom type, even though they don’t appear anywhere in the mapping document as individual properties: from Item i where i.InitialPrice.Value > 100.0 and i.InitialPrice.Currency = 'XAF' In this example we’ve expanded the buffer between the .NET object model and the SQL database schema with our custom composite type. Both representations can now handle changes more robustly. If implementing custom types seems complex, relax; you rarely need to use a custom mapping type. An alternative way to represent the MonetaryAmount class is to use a component mapping, as in section 4.4.2, “Using components.” The decision to use a custom mapping type is often a matter of taste. There are few more interfaces that can be used to implement custom types; they are introduced in the next section. Other interfaces to create custom mapping types You may find that the interfaces IUserType and ICompositeUserType do not allow you to easily add more features to your custom types. In this case, you will need to use some of the other interfaces which are in the NHibernate.UserTypes namespace: The IParameterizedType interface allows you to supply parameters to your custom type in the mapping file. This interface has a unique method: SetParameterValues(IDictionary parameters) that will be called at the initialization of your type. Here is an example of mapping providing a parameter: Euro This mapping tells the custom type to use Euro as currency if it isn’t specified. The IEnhancedUserType interface makes it possible to implement a custom type that can be marshalled to and from its string representation. This functionality allows this type to be used as identifier or discriminator type. To create a type that can be used as version, you must implement the IUserVersionType interface. The INullableUserType interface allows you to interpret non-null values in a property as null in the database. When using dynamic-insert or dynamic-update, fields identified as null will not be inserted or updated. This information may also be used when generating the where clause of the SQL command when optimistic locking is enabled. The last interface is different from the previous because it is meant to implement user defined collection types: IUserCollectionType. For more details, take a look at the implementation NHibernate.Test.UserCollection.MyListType in the source code of NHibernate. Now, let’s look at an extremely important application of custom mapping types. Nullable types are found in almost all enterprise applications. Using Nullable types With .NET 1.1, primitive types can not be null; but this is no longer the case in .NET 2.0. Let’s say that we want to add a DismissDate to the class User. As long as a user is active, its DismissDate should be null. But the System.DateTime struct can not be null. And we don’t want to use some "magic" value to represent the null state. With .NET 2.0 (and 3.5 of course), you can simply write: public class User { ... private DateTime? dismissDate; public DateTime? DismissDate { get { return dismissDate; } set { dismissDate = value; } } ... } We omit other properties and methods because we focus on the nullable property. And no change is required in the mapping. If you work with .NET 1.1, the Nullables add-in (in the NHibernateContrib package for versions prior to NHibernate 1.2.0) contains a number of custom mapping types which allow primitive types to be null. For our previous case, we can use the Nullables.NullableDateTime class: using Nullables; [Class] public class User { ... private NullableDateTime dismissDate; [Property] public NullableDateTime DismissDate { get { return dismissDate; } set { dismissDate = value; } } ... } The mapping is quite straightforward: ... It is important to note that, in the mapping, the type of DismissDate must be Nullables.NHibernate.NullableDateTimeType (from the file Nullables.NHibernate.dll). This type is a wrapper used to translate Nullables types from/to database types. But if when using the NHibernate.Mapping.Attributes library, this operation is automatic, that’s why we just had to put the attribute [Property]. The NullableDateTime type behaves exactly like System.DateTime; there are even implicit operators to easily interact with it. The Nullables library contains nullable types for most .NET primitive types supported by NHibernate. You can find more details in NHibernate documentation. Using enumerated types An enumeration (enum) is a special form of value type, which inherits from System.Enum and supplies alternate names for the values of an underlying primitive type. For example, the Comment class defines a Rating. If you recall, in our CaveatEmptor application, users are able to give other comments about other users. Instead of using a simple int property for the rating, we create an enumeration: public enum Rating { Excellent, Ok, Low } We then use this type for the Rating property of our Comment class. In the database, ratings would be represented as the type of the underlying value. In this case (and by default), it is Int32. And that’s all we have to do. We may specify type="Rating" in our mapping, but it is optional; NHibernate can use reflection to find this. One problem you might run into is using enumerations in NHibernate queries. Consider the following query in HQL that retrieves all comments rated “Low”: IQuery q = session.CreateQuery("from Comment c where c.Rating = Rating.Low"); This query doesn’t work, because NHibernate doesn’t know what to do with Rating.Low and will try to use it as a literal. We have to use a bind parameter and set the rating value for the comparison dynamically (which is what we need for other reasons most of the time): IQuery q = session.CreateQuery("from Comment c where c.Rating = :rating"); q.SetParameter("rating", Rating.Low, NHibernateUtil.Enum(typeof(Rating)); The last line in this example uses the static helper method NHibernateUtil.Enum() to define the NHibernate Type, a simple way to tell NHibernate about our enumeration mapping and how to deal with the Rating.Low value. We’ve now discussed all kinds of NHibernate mapping types: built-in mapping types, user-defined custom types, and even components. They’re all considered value types, because they map objects of value type (not entities) to the database. With a good understanding of what value types are, and how they are mapped, you can now move on to the more complex issue of collections of value typed instances.

I occasionally create custom JavaServer Faces components. Just enough to sort of remember what the steps are, but not nearly frequently enough to quickly put a new component together. This article demonstrates the quick step approach to creating a new custom component in the old fashioned way (that means: it is not a Facelets template based or an ADF Faces 11g Declarative Component). Its primary purpose is to help me quickly retrace my steps. But perhaps it will benefit some of you as well. The Shuffler component I will develop supports facets. It will render its facet children - one after the other. Which one is rendered first can be indicated through an attribute facetOrder (values normal, reverse and random), which is EL enabled. A shuffler-method-expression can optionally be set to provide the Shuffler with a shuffle-order-processor: the method is invoked with the list of facets to shuffle and will return it in the order in which to render the children. The component can render with a shuffle icon that when pressed causes the children to be shuffled. The Shuffler component allows registration of Shuffle Event Listeners, custom listeners that are informed whenever the shuffle event occurs. An example of how the Shuffler can be used inside a JSF page: Some elements of custom JSF components that are explicitly discussed in this article: dynamic attributes of type ValueExpression (EL enabled) attributes of type MethodExpression (also EL enabled) facets (custom) events and listeners Bare essentials for custom JSF components A custom JSF component is represented by a Java Class - one that extends from UIComponentBase. An instance of this class is created whenever a new page is rendered that contains the component (and for each occurrence of the component in the page, a new instance of the class is created). The component class holds the attributes that are set by the page developer and that determine the behavior and appearance of the component. The component class has the internal logic of the component and it deals for example with events and listeners. This class may also render the markup (HTML) for the component - though it is a better practice to leave the actual rendering to a Renderer class. public class Shuffler extends UIComponentBase { ... } Most custom JSF component will also have an associated Renderer class, that extends from Renderer. Note that some components will not actually be rendered (such as Listeners, Iterators or Parameters) and therefore will not have a Renderer class. The Renderer is not only responsible for rendering the HTML, it will also inspect (decode) the incoming request from the browser to see whether the request parameter map contains values that are of interest to the component - that indicate for example that a value has been entered or set on the component(’s representation in the browser) or an action has been executed against it. Note that one JSF component may have multiple Renderers, for example for different channels and protocols (to render a representation of the component in plain XML, in WML, in JavaFX or XUL) or for different user agents (Firefox, Internet Explorer) or themes (professional user, internet surfer). public class ShufflerRenderer extends SuperRenderer { ... } JavaServer Faces pages can be created in various ways - including programmatically, using Facelets and using JSP pages. The latter option, through JSP, is still the most common one, though that is about to change with JSF 2.0 favoring Facelets. Page developers using JSPs will describe the JSF component tree that will need to be instantiated in memory for rendering a certain View using a plain JSP page. The tags in the JSP page are normal JSP tags - described by TLD (tag library descriptors) - corresponding to JSF components and therefore JSF component classes. Every JSF component that needs to be used in JSPs has to have a corresponding JSP tag-class, one that will typically extend from UIComponentELTag (or just from TagSupport when no JSF component is added to the component tree for a certain tag, for example when that tag represents a listener or parameter). The Tag Class specifies which JSF Component it represents. It also indicates which Renderer should be used to render the component. This means that one component can have multiple JSP tags associated with it, each providing a different way of rendering the component. Note: the renderer can also be specified dynamically - taking user preferences or characteristics into account public class ShufflerTag extends UIComponentELTag { public static final String COMPONENT_TYPE = "nl.amis.jsf.UIShuffler"; public static final String RENDERER_TYPE = "nl.amis.jsf.ShufflerRenderer"; public String getComponentType() { return COMPONENT_TYPE; } public String getRendererType() { return RENDERER_TYPE; } ... } Tags representing JSF components need to be described in TLD files (Tag Library Descriptors) just like any other JSP tag.The entry in the TLD defines the tag label to use in the page, whether the tag can contain child-tags, some descriptive meta data and every attribute that can be configured in the tag. For each attribute the TLD-entry specifies the type, whether it is required and if the attribute can contain an EL expression passing in a value or an EL expression passing in a method; in the latter case, the entry also prescribes the signature of the method: ShufflerLib 1.0 ShufflerLib /nl.amis,jsf/ShufflerLib Writes a DIV element that contains the facets in a specific order. shuffler nl.amis.jsf.shuffler.ShufflerTag JSP id false true rendered false boolean binding false javax.faces.component.UIComponent styleClass false java.lang.String .... JSF components need to be registered in a special faces-config.xml file (special in the sense that it is not the faces-config.xml that drives a web application but rather one that acts like a repository of components and their renderers. Note however that all entries in this special faces-config.xml is merged together with the ‘normal’ faces-config.xml. That means in turn that while the special file is primarily seen as the registry of components, it can also configure PhaseListeners, Navigation Rules (hard to see the value in that) and Managed Beans (which can be very useful). The component registration in faces-config.xml consists of a component type that is associated with a the component class. nl.amis.jsf.UIShuffler nl.amis.jsf.shuffler.Shuffler Renderers can also be registered in this file. A renderer entry registers a renderer-type (corresponding to the value returned by the getRendererType() method in the tag class) associated with the RendererClass. Based on the value (rendererType) returned by the tag class, the correct class to instantiate can be determined from this entry: nl.amis.Shuffler nl.amis.jsf.ShufflerRenderer nl.amis.jsf.shuffler.ShufflerRenderer Implementing the Classes: Component, Renderer and TagHandler The TagHandler ShufflerTag is the intermediary between the world of JSP pages (and the Servlet/JSP engine that translates the JSP file into a servlet class) and the JSF realm. Every tag in the JSP page needs to be turned into its corresponding JSF representation. The tag handler needs to override the setProperties() method inherited from the UIComponentELTag class; this method takes all the values set on the tag attributes in the page and passes them onwards to the Component. In our initial case, the tag is used in JSPs like this: ... other content The styleClass attribute is the only one we defined - id and rendered are defined on every JSP-tag based on JSF’s UIComponentELTag. Thye styleClass attribute is also the only attribute we need to take responsibility for in the tag class, by providing a setter method that sets a private member and by passing the value of that private member to the component in the setProperties() method. The code for the ShufflerTag class now becomes: package nl.amis.jsf.shuffler; import javax.el.ValueExpression; import javax.faces.component.UIComponent; import javax.faces.webapp.UIComponentELTag; public class ShufflerTag extends UIComponentELTag { public static final String COMPONENT_TYPE = "nl.amis.jsf.UIShuffler"; public static final String RENDERER_TYPE = "nl.amis.jsf.ShufflerRenderer"; private ValueExpression styleClass; public String getComponentType() { return COMPONENT_TYPE; } public String getRendererType() { return RENDERER_TYPE; } protected void setProperties(UIComponent component) { super.setProperties(component); processProperty(component, styleClass, Shuffler.STYLECLASS_ATTRIBUTE_KEY); } public void release() { super.release(); styleClass= null; } protected final void processProperty(final UIComponent component, final ValueExpression property, final String propertyName) { if (property != null) { if(property.isLiteralText()) { component.getAttributes().put(propertyName, property.getExpressionString()); } else { component.setValueExpression(propertyName, property); } } } public void setStyleClass(ValueExpression styleClass) { this.styleClass = styleClass; } } We cater for the fact that styleClass can contain a ValueExpression - as all attributes can, starting from JSF 1.2. In the method processProperty we check whether the string passed for styleClass is a literal string or should be considered an EL expression. In the latter case, we pass a ValueExpression to the component, otherwise a ‘normal’ attribute. Also note that the super class takes care of the attributes id, rendered and binding. However, we do have to specify them in the tag-library. The component class in our case leads a pretty comfortable life: the tag handler informs him of all the attribute values and the actual rendering is left to a special Renderer class. The component is a pretty passive element in this simple example: package nl.amis.jsf.shuffler; import javax.faces.component.UIComponentBase; import javax.faces.context.FacesContext; public class Shuffler extends UIComponentBase { public static final String FAMILY = "nl.amis.Shuffler"; public static final String STYLECLASS_ATTRIBUTE_KEY = "styleClass"; public String getFamily() { return FAMILY; } @Override public Object saveState(FacesContext facesContext) { Object values[] = new Object[2]; values[0] = super.saveState(facesContext); values[1] = this.getAttributes().get(STYLECLASS_ATTRIBUTE_KEY); return values; } @Override public void restoreState(FacesContext facesContext, Object state) { Object values[] = (Object[])state; super.restoreState(facesContext, values[0]); this.getAttributes().put(STYLECLASS_ATTRIBUTE_KEY, values[1]); } } The only really useful thing the component does is implementing the saveState and restoreState methods. These methods play an important part in turning the state of the component into a serializable object array and restoring that state of the component in the RestoreView phase, based on the serialized array. The Tag Handler specifies in its getRendererType() method that the renderer to use for this component when using the shuffler tag, is one called nl.amis.jsf.ShufflerRenderer. In the faces-config.xml file, we have indicated that this renderer type is associated with the class nl.amis.jsf.shuffler.ShufflerRenderer that extends Renderer. The renderers in JSF can override methods like encodeBegin(), encodeEnd(), encodeChildren() and decode() - the latter only when we have to process the incoming request, looking for new values set on or events that occurred on the component. In our case, we initially will simply have the ShufflerRenderer render a DIV element with a class attribute (based on the styleClass attribute). The DIV will allow the children of the Shuffler component to render - by not overriding the encodeChildren() method. package nl.amis.jsf.shuffler; import javax.faces.context.FacesContext; import javax.faces.context.ResponseWriter; import javax.faces.render.Renderer; public class ShufflerRenderer extends Renderer { @Override public void encodeBegin(final FacesContext facesContext, final UIComponent component) throws IOException { super.encodeBegin(facesContext, component); final ResponseWriter writer = facesContext.getResponseWriter(); writer.startElement("DIV", component); String styleClass = (String)attributes.get(Shuffler.STYLECLASS_ATTRIBUTE_KEY); writer.writeAttribute("class", styleClass, null); } @Override public void encodeEnd(final FacesContext facesContext, final UIComponent component) throws IOException { final ResponseWriter writer = facesContext.getResponseWriter(); writer.endElement("DIV"); } } Next steps - working with facets The Shuffler component is created to dynamically (re)order its child contents. It will do so using facets. The content you want this component to shuffle is passed in two or more facets. The facets are named using string representations of integers, so for example: ... content ... content ... content Facets are automatically supported on JSF components. The getFacets() method is available inside the Shuffler component class and will return a collection of facet UIComponents. Facets are special children for a JSF component: the framework will never render the contents of facets on its own. It is up to the component to determine when and how to render the contents of its facets. So, there is some work to do for the ShuffleRenderer class. But first we need to add support for the new facetOrder attribute. Adding an attribute means: adding an attribute entry in the TLD adding support for processing the attribute in the Tag Handler (a setter and a line of code in setProperties()) adding the attribute in saveState() and restoreState() in the Component class Here we go: In the tld entry, add: facetOrder false java.lang.String In the tag-handler class ShufflerTag add: private ValueExpression facetOrder; public void setFacetOrder(ValueExpression facetOrder) { this.facetOrder = facetOrder; } and in setProperties(): processProperty(component, facetOrder, Shuffler.FACETORDER_ATTRIBUTE_KEY); Finally in the component class Shuffler , add: public static final String FACETORDER_ATTRIBUTE_KEY = "facetOrder"; @Override public Object saveState(FacesContext facesContext) { Object values[] = new Object[3]; values[0] = super.saveState(facesContext); values[1] = this.getAttributes().get(STYLECLASS_ATTRIBUTE_KEY); values[2] = this.getAttributes().get(FACETORDER_ATTRIBUTE_KEY); return values; } @Override public void restoreState(FacesContext facesContext, Object state) { Object values[] = (Object[])state; super.restoreState(facesContext, values[0]); this.getAttributes().put(STYLECLASS_ATTRIBUTE_KEY, values[1]); this.getAttributes().put(FACETORDER_ATTRIBUTE_KEY, values[2]); } The Shuffler also needs to make the facets available to the renderer, in the order that is prescribed by the facetOrder attribute. This attribute supports three values: normal, reverse and random. public List getOrderedFacets(FacesContext facesContext) { // allowable values: normal (default) and reverse // the normal order of the facets is determined by ordering the facets by name (assuming the facetnames are string representations of integers) // create a sorted list with the integers representing the facets List facetIndexValues = new ArrayList(); List facetNames = new ArrayList(getFacets().keySet()); for (String facetName : facetNames) { facetIndexValues.add(new Integer(facetName)); } Collections.sort(facetIndexValues); // create the list of facets corrresponding to the sorted list of facet index values List orderedFacets = new ArrayList(); for (Integer index : facetIndexValues) { orderedFacets.add(getFacets().get(index.toString())); } // depending on the value for the facetOrder attribute, we may need to reorganize the orderedFacets list String facetOrder = (String)this.getAttributes().get(Shuffler.FACETORDER_ATTRIBUTE_KEY); if ("reverse".equalsIgnoreCase(facetOrder)) { Collections.reverse(orderedFacets); } else if ("random".equalsIgnoreCase(facetOrder)) { Collections.shuffle(orderedFacets); } else if ("normal".equalsIgnoreCase(facetOrder)) { // need to do nothing as with normal the order returned by getFacets() is the correct one } return orderedFacets; } The ShufflerRenderer will have to do the real work. It will retrieve the facets - in the proper order - from the Shuffler Component class and ask JSF to render them. package nl.amis.jsf.shuffler; import javax.faces.context.FacesContext; import javax.faces.context.ResponseWriter; import javax.faces.render.Renderer; import javax.faces.component.UIComponent; public class ShufflerRenderer extends Renderer { @Override public void encodeBegin(final FacesContext facesContext, final UIComponent component) throws IOException { super.encodeBegin(facesContext, component); final ResponseWriter writer = facesContext.getResponseWriter(); writer.startElement("DIV", component); String styleClass = (String)attributes.get(Shuffler.STYLECLASS_ATTRIBUTE_KEY); writer.writeAttribute("class", styleClass, null); List orderedFacets = ((Shuffler)component).getOrderedFacets(facesContext); for (UIComponent facet:orderedFacets) { facet.encodeAll(facesContext); } } @Override public void encodeEnd(final FacesContext facesContext, final UIComponent component) throws IOException { final ResponseWriter writer = facesContext.getResponseWriter(); writer.endElement("DIV"); } } With these changes, we can now add real content to the Shuffler and have it rendered, in the order we specified - which can be random. Also note that we can use an EL expression to have the facetOrder dynamically derived: facetOrder="#{bean.liveFacetOrder}" id="s1" > ... content ... content ... content Downloading Resources The next step in our exploration of the development of custom JSF components is the addition of resources like images and JavaScript libraries. Note that in JavaServer Faces 2.0 a new facility is available, especially for this purpose. However, in our 1.2 setting we have to come up with something ourselves. That is not to say no solutions exist for JSF 1.2; almost every library comes with a form of resource handling. Then there is the Weblet framework that was introduced especially for this purpose. Another option leverages JSF itself: its capability through PhaseListeners to intercept a request, interpret the requested ViewId and optionally serve up an image or JS file in response to the request. This approach is proposed in JavaServer Faces, The Complete Reference by Ed Burns and Chris Schalk. I have slightly modified there code for my own purposes. However, the central idea clearly is theirs. My objective is to add an image to the Shuffler component. The next step will be to allow the user to click on the image and by doing so tgrigger a re-shuffle. But that part is for later, first add the image itself. The HTML rendered by the ShufflerRenderer needs to be extended with the IMG tag, that is easy enough. Less trivial is the value for the SRC attribute on the IMG tag. The change in the encodeBegin method in the ShufflerRenderer: writer.startElement("IMG", component); writer.writeAttribute("src", imageUrl( facesContext,SHUFFLE_IMAGE), null); writer.writeAttribute("alt", "Click to reshuffle", null); writer.writeAttribute("width", "20px", null); writer.endElement("IMG"); With SHUFFLE_IMAGE specified as: private static String SHUFFLE_IMAGE = "shuffleIcon.png"; The imageUrl() method is defined as follows private final static String IMAGE_PATH ="/faces/images/"; protected String imageUrl(FacesContext facesContext, String image) { ViewHandler handler = facesContext.getApplication().getViewHandler(); String imageUrl = handler.getResourceURL(facesContext, IMAGE_PATH + image); return imageUrl; } The URLs for images are now constructed to look like this: http://somehost:7101/CustomJSFConsumer/faces/images/shuffleIcon.png The request for the shuffleIcon.png that is sent by the browser should be intercepted by a component that knows how to handle it. Because of the /faces/ part, this request is sent to the FacesServlet and processed through the JSF lifecycle. The componoent to intercept it will be a phaseListener that fires after restore view. It inspects the ViewId. When the ViewId contains the predefined indicator ("/images/") it steps in and takes over processing of the request. It will find the name of the image that is requested by taking the part of the ViewId that comes after /images/. It will then locate the image file on the classpath (that works well for a component packaged in a jar file, it can have the images packaged in the jar file too), looking for a directory called /images/ - as specified by the IMAGE_PATH constant. It copies the image from the file to the outputstream after setting the content type. package nl.amis.jsf; import java.io.BufferedReader; import java.io.IOException; import java.io.InputStream; import java.io.InputStreamReader; import java.io.OutputStreamWriter; import java.net.URL; import java.net.URLConnection; import javax.faces.context.FacesContext; import javax.faces.event.PhaseEvent; import javax.faces.event.PhaseId; import javax.faces.event.PhaseListener; import javax.servlet.ServletContext; import javax.servlet.http.HttpServletResponse; public class ResourceServerPhaseListener implements PhaseListener { public ResourceServerPhaseListener() { super(); } public PhaseId getPhaseId() { return PhaseId.RESTORE_VIEW; } public void afterPhase(PhaseEvent event) { // If this is restoreView phase if (PhaseId.RESTORE_VIEW == event.getPhaseId()) { if (-1 != event.getFacesContext().getViewRoot().getViewId().indexOf(RENDER_IMAGE_TAG)) { // extract the name of the image resource from the ViewId String image = event.getFacesContext().getViewRoot().getViewId().substring(event.getFacesContext() .getViewRoot().getViewId().indexOf(RENDER_IMAGE_TAG) + RENDER_IMAGE_TAG.length()); // render the script writeImage(event, image); event.getFacesContext().responseComplete(); } } } public void beforePhase(PhaseEvent event) { } public static final String RENDER_IMAGE_TAG = "/images/"; public static final String IMAGE_PATH = "/images/"; private void writeImage(PhaseEvent event, String resourceName) { URL url = getClass().getResource(IMAGE_PATH + resourceName); URLConnection conn = null; InputStream stream = null; HttpServletResponse response = (HttpServletResponse)event.getFacesContext().getExternalContext().getResponse(); try { conn = url.openConnection(); conn.setUseCaches(false); stream = conn.getInputStream(); ServletContext servletContext = (ServletContext)FacesContext.getCurrentInstance().getExternalContext().getContext(); String mimeType = servletContext.getMimeType(resourceName); response.setContentType(mimeType); response.setStatus(200); // Copy the contents of the file to the output stream byte[] buf = new byte[1024]; int count = 0; while ((count = stream.read(buf)) >= 0) { response.getOutputStream().write(buf, 0, count); } response.getOutputStream().close(); } catch (Exception e) { String message = null; message = "Can't load image file:" + url.toExternalForm(); try { response.sendError(HttpServletResponse.SC_BAD_REQUEST, message); } catch (IOException f) { f.printStackTrace(); } } } } PhaseListeners need to be configured in order to be active. This configuration usually is done in the faces-config.xml of the application. Fortunately, we can also configure the PhaseListener in the faces-config.xml file that we create for the custom component. This faces-config.xml is part of the jar file in which the custom component is shipped and deployed. Its contents are merged with the application’s own faces-config.xml. The registration of our PhaseListener looks like this: nl.amis.jsf.ResourceServerPhaseListener ... Triggering events on the custom component Time to take another big step. We will support clicking the image by the end user and turn that event into a reshuffle of the facets of the Shuffler component. In the next section we will not only act on that click ourselves, but also publish an event that others can listen to. We will have to add a JavaScript event listener in the HTML rendered for the Shuffler. This client side code is triggered when the image is clicked. It will submit the form - after it has added an input element to the DOM and set a value on it. Note: this approach to have a custom component trigger an event that can be received by the server side renderer class has been described in Pro JSF and Ajax: Building Rich Internet Components - by John R. Fallows and Jonas Jacobi, the guys who first introduced me to JavaServer Faces. The JavaScript for the Shuffler component looks like this: /** * The onclick handler for ShufflerRenderer. * * @param formClientId the clientId of the enclosing UIForm component * @param clientId the clientId of the Shuffler component */ function _shuffle_click( formClientId, clientId) { var form = document.forms[formClientId]; var input = form[clientId]; if (!input) // if the input element does not already exist, create it and add it to the form { input = document.createElement("input"); input.type = 'hidden'; input.name = clientId; form.appendChild(input); } input.value = 'clicked'; form.submit(); } The JavaScript is not be directly included in the page - as it is part of the jar file in which the Shuffler component is shipped. We need a way to attach this JavaScript (it is in a file called shuffle.js) to the page from within the custom component, or in this case rather its Renderer class. We extend the ResourceServerPhaseListener to also handle JavaScript resources, just like it can handle images. public class ResourceServerPhaseListener implements PhaseListener { public static final String RENDER_SCRIPT_TAG = "/js/"; public static final String RENDER_IMAGE_TAG = "/images/"; public static final String SCRIPT_PATH = "/js/"; public static final String IMAGE_PATH = "/images/"; public PhaseId getPhaseId() { return PhaseId.RESTORE_VIEW; } public void afterPhase(PhaseEvent event) { // If this is restoreView phase if (PhaseId.RESTORE_VIEW == event.getPhaseId()) { // if the request is for a JavaScript library if (-1 != event.getFacesContext().getViewRoot().getViewId().indexOf(RENDER_SCRIPT_TAG)) { // extract the name of the script from the ViewId String script = event.getFacesContext().getViewRoot().getViewId().substring(event.getFacesContext() .getViewRoot().getViewId().indexOf(RENDER_SCRIPT_TAG) + RENDER_SCRIPT_TAG.length()); // render the script writeScript(event, script); event.getFacesContext().responseComplete(); } ... image handling, same as before } } public void beforePhase(PhaseEvent event) { } private void writeScript(PhaseEvent event, String resourceName) { URL url = getClass().getResource(SCRIPT_PATH + resourceName); URLConnection conn = null; InputStream stream = null; BufferedReader bufReader = null; HttpServletResponse response = (HttpServletResponse)event.getFacesContext().getExternalContext().getResponse(); OutputStreamWriter outWriter = null; String curLine = null; try { outWriter = new OutputStreamWriter(response.getOutputStream(), response.getCharacterEncoding()); conn = url.openConnection(); conn.setUseCaches(false); stream = conn.getInputStream(); bufReader = new BufferedReader(new InputStreamReader(stream)); response.setContentType("text/javascript"); response.setStatus(200); while (null != (curLine = bufReader.readLine())) { outWriter.write(curLine + "\n"); } outWriter.close(); } catch (Exception e) { String message = null; message = "Can't load script file:" + url.toExternalForm(); try { response.sendError(HttpServletResponse.SC_BAD_REQUEST, message); } catch (IOException f) { f.printStackTrace(); } } } private void writeImage(PhaseEvent event, String resourceName) { ... same as before } } The Renderer class is responsible for rendering the markup that will include the JavaScript resources to the page (the script element). We could have multiple occurrences of our custom component in a page. However, the JavaScript file shuffle.js should be loaded only once, to prevent excessive and completely pointless browser requests. In order to make that happen, the Renderer indicates to a method writeScriptResource that it has a JavaScript resource that should be included. This method verifies whether a script tag for downloading that same resource has already been added in the current request. If so, it will not add another script tag. If not [already included] then the tag is added with its src attribute referring to the proper PhaseListener controlled url: protected void writeScriptResource( FacesContext context, String resourcePath) throws IOException { Set scriptResources = _getScriptResourcesAlreadyWritten(context); // Set.add() returns true only if item was added to the set // and returns false if item was already present in the set if (scriptResources.add(resourcePath)) { ViewHandler handler = context.getApplication().getViewHandler(); String resourceURL = handler.getResourceURL(context, SCRIPT_PATH +resourcePath); ResponseWriter out = context.getResponseWriter(); out.startElement("script", null); out.writeAttribute("type", "text/javascript", null); out.writeAttribute("src", resourceURL, null); out.endElement("script"); } } private Set _getScriptResourcesAlreadyWritten( FacesContext context) { ExternalContext external = context.getExternalContext(); Map requestScope = external.getRequestMap(); Set written = (Set)requestScope.get(_SCRIPT_RESOURCES_KEY); if (written == null) { written = new HashSet(); requestScope.put(_SCRIPT_RESOURCES_KEY, written); } return written; } static private final String _SCRIPT_RESOURCES_KEY = ShufflerRenderer.class.getName() + ".SCRIPTS_WRITTEN"; With these helper methods in place, the ShufflerRenderer can be extended to include the client side click handling code: @Override public void encodeBegin(final FacesContext facesContext, final UIComponent component) throws IOException { super.encodeBegin(facesContext, component); final Map attributes = component.getAttributes(); final ResponseWriter writer = facesContext.getResponseWriter(); String formClientId = _findFormClientId(facesContext, component); String shuffleClientId = component.getClientId(facesContext); writeScriptResource(context, "shuffle.js"); writer.startElement("DIV", component); String styleClass = (String)attributes.get(Shuffler.STYLECLASS_ATTRIBUTE_KEY); writer.writeAttribute("class", styleClass, null); writer.startElement("SPAN", component); writer.writeAttribute("onClick", "_shuffle_click('" + formClientId + "'," + "'" + shuffleClientId + "')", null); writer.startElement("IMG", component); writer.writeAttribute("src", imageUrl( facesContext,SHUFFLE_IMAGE), null); writer.writeAttribute("alt", "Click to reshuffle", null); writer.writeAttribute("width", "20px", null); writer.endElement("IMG"); writer.endElement("SPAN"); List orderedFacets = ((Shuffler)component).getOrderedFacets(facesContext); for (UIComponent facet:orderedFacets) { facet.encodeAll(facesContext); } } protected void encodeResources(FacesContext context, UIComponent component) throws IOException { writeScriptResource(context, "shuffle.js"); } /** * Finds the parent UIForm component client identifier. * * @param context the Faces context * @param component the Faces component * * @return the parent UIForm or RichForm (for usage in ADF) client identifier, if present, otherwise null */ private String _findFormClientId(FacesContext context, UIComponent component) { if (component==null) { return null; } if (component instanceof UIForm || component.getClass().getName().endsWith("RichForm")) { return component.getClientId(context); } else { return _findFormClientId(context, component.getParent()); } } The image is wrapped in a SPAN and the onclick event handler is defined on that SPAN element (this allows us to later on add more clickable stuff to the SPAN). When the image is clicked, the _shuffle_click function is invoked - that was loaded from shuffle.js. The element is added to the form and the form is submitted. The HTML rendered from this renderer now looks like this:

At the New England Software Symposium, I attended Brian Goetz's session called "The Java Memory Model". When I saw the phrase "memory model" in the title I thought it would be about garbage collection, memory allocation and memory types. Instead, it is really about multithreading. The difference is that this presentation focuses on visibility, not locking or atomicity. This is my attempt to summarize his talk. The importance of visibility Visibility here refers to the memory that an executing thread can see once it is written. The big gotcha is that when thread A writes something before thread B reads it, it does not mean thread B will read the correct value. You could ensure that threads A and B are ordered with locking but you can still be in deep doo doo because the memory is not written and read in order, or is read in a partially written state. A big part of this peril comes from the layered memory architecture of modern hardware: multi-CPU, multi-core CPUs, multi-level caches on and off chip etc. Instructions could be executed in parallel or out of order. The memory being written may not even be in RAM at all: it could be on a remote core's register. But the danger could also come from old-fashioned compiler optimizations. One of Brian's examples is the following loop which depends on another thread to set the boolean field asleep: while (!asleep) ++sheep; The compiler may notice that asleep is loop-invariant and optimize its evaluation out of the loop if (!asleep) while (true) ++sleep; The result is an infinite loop. The fix in this case is to use a volatile variable. The Java Memory Model A memory model describes when one thread's actions are guaranteed to be visible to another. The Java memory model (JMM) is quite an achievement: previously, memory models were specific to each processor architecture. A cross-platform memory model takes portability well beyond being able to compile the same source code: you really can run it anywhere. It took until Java 5 (JSR 133) to get the JMM right. The JMM defines a partial ordering on program actions (read/write, lock/unlock, start/join threads) called happens-before. Basically, if action X happens-before Y, then X's results are visible to Y. Within a thread, the order is basically the program order. It's straightforward. But between threads, if you don't use synchronized or volatile, there are no visibility guarantees. As far as visible results go, there is no guarantee that thread A will see them in the order that thread B executes them. Brian even invoked special relativity to describe the disorienting effects of relative views of reality. You need synchronization to get inter-thread visibility guarantees. The basic tools of thread synchronization are: The synchronized keyword: an unlock happens-before every subsequent lock on the same monitor. The volatile keyword: a write to a volatile variable happens-before subsequent reads of that variable. Static initialization: done by the class loader, so the JVM guarantees thread safety In addition to the above, the JMM offers a guarantee of initialization safety for immutable objects. The Rules Here are points that Brian emphasized: If you read or write a field that is read/written by another thread, you must synchronize. This must be done by both the reading and writing threads, and on the same lock. Don't try to reason about ordering in undersynchronized programs. Avoiding synchronization can cause subtle bugs that only blow up in production. Do it right first, then make it fast. Case study: double-checked locking One example of synchronization avoidance gone bad is the popular double-checked locking idiom for lazy initialization, which we now know is broken: private Thing instance = null; public Thing getInstance() { if (instance == null) { synchronized (this) { if (instance == null) instance = new Thing(); } } return instance; } This idiom can result in a partially constructed Thing object, because it only worries about atomicity at the expense of visibility. There are ways to fix this, of course, such as using a volatile field or switching to using static initializers. But it's easy to get it wrong, so Brian questions why we would want to do something like this in the first place. The main motivation was to avoid synchronization in the common case. While it used to be expensive in the past, uncontended synchronization is much cheaper now. There is still a lot of advice to avoid supposedly expensive Java operations out there, but the JVM has improved tremendously and a lot of old performance tips (like object pooling) just don't make sense anymore. Beware of reading years-old advice when you Google for Java tips. Remember Brian's advice above against premature optimization. That said, he also showed a couple of better alternatives for lazy initialization. Some thoughts This talk was a reminder to me that low-level multithreading is hard. It's hard enough that it took years to get the JMM right. It's hard enough that a university professor would say "don't do it". And if you faithfully follow Brian's rules and use synchronization primitives everywhere, you might find yourself vulnerable to thread deadlocks (hmmm ... why does JConsole have a deadlock detection function?). The primary danger in multithreading is in shared, mutable state. Without shared mutable data, threads might as well be separate processes, and the danger evaporates. So while it's wonderful what JMM has done for cross-platform visibility guarantees, I think we would do ourselves a favor if we tried to minimize shared mutable data. There are often higher level alternatives. For example, Scala's Actor construct relies on passing immutable messages instead of sharing memory. From http://chriswongdevblog.blogspot.com/

When you have collections of associated objects in domain objects, you generally want to specify some kind of default sort order. For example, suppose I have domain objects Timeline and Event: @Entity class Timeline { @Required String description @OneToMany(mappedBy = "timeline") @javax.persistence.OrderBy("startYear, endYear") Set events } @Entity class Event { @Required Integer startYear Integer endYear @Required String description @ManyToOne Timeline timeline } In the above example I've used the standard JPA (Java Persistence API) @OrderBy annotation which allows you to specify the order of a collection of objects via object properties, in this example a @OneToMany association . I'm ordering first by startYear in ascending order and then by endYear, also in ascending order. This is all well and good, but note that I've specified that only the start year is required. (The @Required annotation is a custom Hibernate Validator annotation which does exactly what you would expect.) How are the events ordered when you have several events that start in the same year but some of them have no end year? The answer is that it depends on how your database sorts null values by default. Under Oracle 10g nulls will come last. For example if two events both start in 2001 and one of them has no end year, here is how they are ordered: 2001 2002 Some event 2001 2003 Other event 2001 Event with no end year What if you want to control how null values are ordered so they come first rather than last? In Hibernate there are several ways you could do this. First, you could use the Hibernate-specific @Sort annotation to perform in-memory (i.e. not in the database) sorting, using natural sorting or sorting using a Comparator you supply. For example, assume I have an EventComparator helper class that implements Comparator. I could change Timeline's collection of events to look like this: @OneToMany(mappedBy = "timeline") @org.hibernate.annotations.Sort(type = SortType.COMPARATOR, comparator = EventCompator) Set events Using @Sort will perform sorting in-memory once the collection has been retrieved from the database. While you can certainly do this and implement arbitrarily complex sorting logic, it's probably better to sort in the database when you can. So we now need to turn to Hibernate's @OrderBy annotation, which lets you specify a SQL fragment describing how to perform the sort. For example, you can change the events mapping to : @OneToMany(mappedBy = "timeline") @org.hibernate.annotations.OrderBy("start_year, end_year") Set events This sort order is the same as using the JPA @OrderBy with "startYear, endYear" sort order. But since you write actual SQL in Hibernate's @OrderBy you can take advantage of whatever features your database has, at the possible expense of portability across databases. As an example, Oracle 10g supports using a syntax like "order by start_year, end_year nulls first" to order null end years before non-null end years. You could also say "order by start_year, end year nulls last" which sorts null end years last as you would expect. This syntax is probably not portable, so another trick you can use is the NVL function, which is supported in a bunch of databases. You can rewrite Timeline's collection of events like so: @OneToMany(mappedBy = "timeline") @org.hibernate.annotations.OrderBy("start_year, nvl(end_year , start_year)") Set events The expression "nvl(end_year , start_year)" simply says to use end_year as the sort value if it is not null, and start_year if it is null. So for sorting purposes you end up treating end_year as the same as the start_year if end_year is null. In the contrived example earlier, applying the nvl-based sort using Hibernate's @OrderBy to specify SQL sorting criteria, you now end with the events sorted like this: 2001 Event with no end year 2001 2002 Some event 2001 2003 Other event Which is what you wanted in the first place. So if you need more complex sorting logic than what you can get out of the standard JPA @javax.persistence.OrderBy, try one of the Hibernate sorting options, either @org.hibernate.annotations.Sort or @org.hibernate.annotations.OrderBy. Adding a SQL fragment into your domain class isn't necessarily the most elegant thing in the world, but it might be the most pragmatic thing.

Faz o cálculo da idade de uma pessoa utilizando sql oracle Select Trunc ( (SYSDATE - to_date('14/07/1980','dd/mm/yyyy')) /365, 0 ) as "age" from Dual

Get a perspective on the aspects of JVM internals, controls, and switches that can be used to optimize your Java application.

Good Database schema design is important for performance. One of the most basic optimizations is to design your tables to take as little space on the disk as possible , this makes disk reads faster and uses less memory for query processing. Data Types You should use the smallest data types possible, especially for indexed fields. The smaller your data types, the more indexes (and data) can fit into a block of memory, the faster your queries will be. Normalization Database Normalization eliminates redundant data, which usually makes updates faster since there is less data to change. However a Normalized schema causes joins for queries, which makes queries slower, denormalization speeds retrieval. More normalized schemas are better for applications involving many transactions, less normalized are better for reporting types of applications. You should normalize your schema first, then de-normalize later. Applications often need to mix the approaches, for example use a partially normalized schema, and duplicate, or cache, selected columns from one table in another table. With JPA O/R mapping you can use the @Embedded annotation for denormalized columns to specify a persistent field whose @Embeddable type can be stored as an intrinsic part of the owning entity and share the identity of the entity. Database Normalization and Mapping Inheritance Hiearchies The Class Inheritance hierarchy shown below will be used as an example of JPA O/R mapping. In the Single table per class mapping shown below, all classes in the hierarchy are mapped to a single table in the database. This table has a discriminator column (mapped by @DiscriminatorColumn), which identifies the subclass. Advantages: This is fast for querying, no joins are required. Disadvantages: wastage of space since all inherited fields are in every row, a deep inheritance hierarchy will result in wide tables with many, some empty columns. In the Joined Subclass mapping shown below, the root of the class hierarchy is represented by a single table, and each subclass has a separate table that only contains those fields specific to that subclass. This is normalized (eliminates redundant data) which is better for storage and updates. However queries cause joins which makes queries slower especially for deep hierachies, polymorphic queries and relationships. In the Table per Class mapping (in JPA 2.0, optional in JPA 1.0), every concrete class is mapped to a table in the database and all the inherited state is repeated in that table. This is not normlalized, inherited data is repeated which wastes space. Queries for Entities of the same type are fast, however polymorphic queries cause unions which are slower. Know what SQL is executed You need to understand the SQL queries your application makes and evaluate their performance. Its a good idea to enable SQL logging, then go through a use case scenario to check the executed SQL. Logging is not part of the JPA specification, With EclipseLink you can enable logging of SQL by setting the following property in the persistence.xml file: With Hibernate you set the following property in the persistence.xml file: Basically you want to make your queries access less data, is your application retrieving more data than it needs, are queries accessing too many rows or columns? Is the database query analyzing more rows than it needs? Watch out for the following: queries which execute too often to retrieve needed data retrieving more data than needed queries which are too slow you can use EXPLAIN to see where you should add indexes With MySQL you can use the slow query log to see which queries are executing slowly, or you can use the MySQL query analyzer to see slow queries, query execution counts, and results of EXPLAIN statements. Understanding EXPLAIN For slow queries, you can precede a SELECT statement with the keyword EXPLAIN to get information about the query execution plan, which explains how it would process the SELECT, including information about how tables are joined and in which order. This helps find missing indexes early in the development process. You should index columns that are frequently used in Query WHERE, GROUP BY clauses, and columns frequently used in joins, but be aware that indexes can slow down inserts and updates. Lazy Loading and JPA With JPA many-to-one and many-to-many relationships lazy load by default, meaning they will be loaded when the entity in the relationship is accessed. Lazy loading is usually good, but if you need to access all of the "many" objects in a relationship, it will cause n+1 selects where n is the number of "many" objects. You can change the relationship to be loaded eagerly as follows : However you should be careful with eager loading which could cause SELECT statements that fetch too much data. It can cause a Cartesian product if you eagerly load entities with several related collections. If you want to override the LAZY fetch type for specific use cases, you can use Fetch Join. For example this query would eagerly load the employee addresses: In General you should lazily load relationships, test your use case scenarios, check the SQL log, and use @NameQueries with JOIN FETCH to eagerly load when needed. Partitioning The main goal of partitioning is to reduce the amount of data read for particular SQL operations so that the overall response time is reduced Vertical Partitioning splits tables with many columns into multiple tables with fewer columns, so that only certain columns are included in a particular dataset, with each partition including all rows. Horizontal Partitioning segments table rows so that distinct groups of physical row-based datasets are formed. All columns defined to a table are found in each set of partitions. An example of horizontal partitioning might be a table that contains historical data being partitioned by date. Vertical Partitioning In the example of vertical partitioning below a table that contains a number of very wide text or BLOB columns that aren't referenced often is split into two tables with the most referenced columns in one table and the seldom-referenced text or BLOB columns in another. By removing the large data columns from the table, you get a faster query response time for the more frequently accessed Customer data. Wide tables can slow down queries, so you should always ensure that all columns defined to a table are actually needed. The example below shows the JPA mapping for the tables above. The Customer data table with the more frequently accessed and smaller data types is mapped to the Customer Entity, the CustomerInfo table with the less frequently accessed and larger data types is mapped to the CustomerInfo Entity with a lazily loaded one to one relationship to the Customer. Horizontal Partitioning The major forms of horizontal partitioning are by Range, Hash, Hash Key, List, and Composite. Horizontal partitioning can make queries faster because the query optimizer knows what partitions contain the data that will satisfy a particular query and will access only those necessary partitions during query execution. Horizontal Partitioning works best for large database Applications that contain a lot of query activity that targets specific ranges of database tables. Hibernate Shards Partitioning data horizontally into "Shards" is used by google, linkedin, and others to give extreme scalability for very large amounts of data. eBay "shards" data horizontally along its primary access path. Hibernate Shards is a framework that is designed to encapsulate support for horizontal partitioning into the Hibernate Core. Caching JPA Level 2 caching avoids database access for already loaded entities, this makes reading frequently accessed unmodified entities faster, however it can give bad scalability for frequent or concurrently updated entities. You should configure L2 caching for entities that are: read often modified infrequently Not critical if stale You should also configure L2 (vendor specific) caching for maxElements, time to expire, refresh... References and More Information: JPA Best Practices presentation MySQL for Developers Article MySQL for developers presentation MySQL for developers screencast Keeping a Relational Perspective for Optimizing Java Persistence Java Persistence with Hibernate Pro EJB 3: Java Persistence API Java Persistence API 2.0: What's New ? High Performance MySQL book Pro MySQL, Chapter 6: Benchmarking and Profiling EJB 3 in Action sharding the hibernate way JPA Caching Best Practices for Large-Scale Web Sites: Lessons from eBay

Model your complete database with all its relations with this JPA pattern for lazy loading.

DELIMITER ; DROP FUNCTION IF EXISTS multiurldecode; DELIMITER | CREATE FUNCTION multiurldecode (s VARCHAR(4096)) RETURNS VARCHAR(4096) DETERMINISTIC CONTAINS SQL BEGIN DECLARE pr VARCHAR(4096) DEFAULT ''; IF ISNULL(s) THEN RETURN NULL; END IF; REPEAT SET pr = s; SELECT urldecode(s) INTO s; UNTIL pr = s END REPEAT; RETURN s; END; | DELIMITER ;

Easily interrupt long portions of code if they take too long to run. #!/usr/bin/python # file: watchdog.py # license: MIT License import signal class Watchdog(Exception): def __init__(self, time=5): self.time = time def __enter__(self): signal.signal(signal.SIGALRM, self.handler) signal.alarm(self.time) def __exit__(self, type, value, traceback): signal.alarm(0) def handler(self, signum, frame): raise self def __str__(self): return "The code you executed took more than %ds to complete" % self.time Example: #!/usr/bin/python # import the class from watchdog import Watchdog # don't allow long_function to take more than 5 seconds to complete try: with Watchdog(5): long_function() except Watchdog: print "long_function() took too long to complete"

SELECT attributes_ean FROM products_attributes WHERE LENGTH(attributes_ean) = 13 AND SUBSTRING((10 - (((( SUBSTRING(attributes_ean FROM 2 FOR 1) + SUBSTRING(attributes_ean FROM 4 FOR 1) + SUBSTRING(attributes_ean FROM 6 FOR 1) + SUBSTRING(attributes_ean FROM 8 FOR 1) + SUBSTRING(attributes_ean FROM 10 FOR 1) + SUBSTRING(attributes_ean FROM 12 FOR 1) )*3) + ( SUBSTRING(attributes_ean FROM 1 FOR 1) + SUBSTRING(attributes_ean FROM 3 FOR 1) + SUBSTRING(attributes_ean FROM 5 FOR 1) + SUBSTRING(attributes_ean FROM 7 FOR 1) + SUBSTRING(attributes_ean FROM 9 FOR 1) + SUBSTRING(attributes_ean FROM 11 FOR 1) )) MOD 10)) FROM -1 FOR 1) != SUBSTRING(attributes_ean FROM 13 FOR 1)

Optimistic locking lets concurrent transactions process simultaneously, but detects and prevent collisions, this works best for applications where most concurrent transactions do not conflict. JPA Optimistic locking allows anyone to read and update an entity, however a version check is made upon commit and an exception is thrown if the version was updated in the database since the entity was read. In JPA for Optimistic locking you annotate an attribute with @Version as shown below: public class Employee { @ID int id; @Version int version; The Version attribute will be incremented with a successful commit. The Version attribute can be an int, short, long, or timestamp. This results in SQL like the following: “UPDATE Employee SET ..., version = version + 1 WHERE id = ? AND version = readVersion” The advantages of optimistic locking are that no database locks are held which can give better scalability. The disadvantages are that the user or application must refresh and retry failed updates. Optimistic Locking Example In the optimistic locking example below, 2 concurrent transactions are updating employee e1. The transaction on the left commits first causing the e1 version attribute to be incremented with the update. The transaction on the right throws an OptimisticLockException because the e1 version attribute is higher than when e1 was read, causing the transaction to roll back. Additional Locking with JPA Entity Locking APIs With JPA it is possible to lock an entity, this allows you to control when, where and which kind of locking to use. JPA 1.0 only supported Optimistic read or Optimistic write locking. JPA 2.0 supports Optimistic and Pessimistic locking, this is layered on top of @Version checking described above. JPA 2.0 LockMode values : OPTIMISTIC (JPA 1.0 READ): perform a version check on locked Entity before commit, throw an OptimisticLockException if Entity version mismatch. OPTIMISTIC_FORCE_INCREMENT (JPA 1.0 WRITE) perform a version check on locked Entity before commit, throw an OptimisticLockException if Entity version mismatch, force an increment to the version at the end of the transaction, even if the entity is not modified. PESSIMISTIC: lock the database row when reading PESSIMISTIC_FORCE_INCREMENT lock the database row when reading, force an increment to the version at the end of the transaction, even if the entity is not modified. There are multiple APIs to specify locking an Entity: EntityManager methods: lock, find, refresh Query methods: setLockMode NamedQuery annotation: lockMode element OPTIMISTIC (READ) LockMode Example In the optimistic locking example below, transaction1 on the left updates the department name for dep , which causes dep's version attribute to be incremented. Transaction2 on the right gives an employee a raise if he's in the "Eng" department. Version checking on the employee attribute would not throw an exception in this example since it was the dep Version attribute that was updated in transaction1. In this example the employee change should not commit if the department was changed after reading, so an OPTIMISTIC lock is used : em.lock(dep, OPTIMISTIC). This will cause a version check on the dep Entity before committing transaction2 which will throw an OptimisticLockException because the dep version attribute is higher than when dep was read, causing the transaction to roll back. OPTIMISTIC_FORCE_INCREMENT (write) LockMode Example In the OPTIMISTIC_FORCE_INCREMENT locking example below, transaction2 on the right wants to be sure that the dep name does not change during the transaction, so transaction2 locks the dep Entity em.lock(dep, OPTIMISTIC_FORCE_INCREMENT) and then calls em.flush() which causes dep's version attribute to be incremented in the database. This will cause any parallel updates to dep to throw an OptimisticLockException and roll back. In transaction1 on the left at commit time when the dep version attribute is checked and found to be stale, an OptimisticLockException is thrown Pessimistic Concurrency Pessimistic concurrency locks the database row when data is read, this is the equivalent of a (SELECT . . . FOR UPDATE [NOWAIT]) . Pessimistic locking ensures that transactions do not update the same entity at the same time, which can simplify application code, but it limits concurrent access to the data which can cause bad scalability and may cause deadlocks. Pessimistic locking is better for applications with a higher risk of contention among concurrent transactions. The examples below show: reading an entity and then locking it later reading an entity with a lock reading an entity, then later refreshing it with a lock The Trade-offs are the longer you hold the lock the greater the risks of bad scalability and deadlocks. The later you lock the greater the risk of stale data, which can then cause an optimistic lock exception, if the entity was updated after reading but before locking. The right locking approach depends on your application: what is the risk of risk of contention among concurrent transactions? What are the requirements for scalability? What are the requirements for user re-trying on failure? For More Information: Preventing Non-Repeatable Reads in JPA Using EclipseLink Java Persistence API 2.0: What's New ? What's New and Exciting in JPA 2.0 Beginning Java™ EE 6 Platform with GlassFish™ 3 Pro EJB 3: Java Persistence API (JPA 1.0)

import java.awt.EventQueue; import java.awt.GridLayout; import java.awt.event.ActionEvent; import java.awt.event.ActionListener; import java.awt.event.KeyAdapter; import java.awt.event.KeyEvent; import java.util.ArrayList; import java.util.List; import javax.swing.AbstractListModel; import javax.swing.ComboBoxModel; import javax.swing.JComboBox; import javax.swing.JFrame; import javax.swing.JLabel; import javax.swing.Timer; import javax.swing.text.AttributeSet; import javax.swing.text.BadLocationException; import javax.swing.text.JTextComponent; import javax.swing.text.PlainDocument; import org.apache.log4j.ConsoleAppender; import org.apache.log4j.Logger; import org.apache.log4j.PatternLayout; /** * Autocomplete combobox with filtering and * text inserting of new text * @author Exterminator13 */ public class AutoCompleteCombo extends JComboBox{ private static final Logger logger = Logger.getLogger(AutoCompleteCombo.class); private Model model = new Model(); private final JTextComponent textComponent = (JTextComponent) getEditor().getEditorComponent(); private boolean modelFilling = false; private boolean updatePopup; public AutoCompleteCombo() { setEditable(true); logger.debug("setPattern() called from constructor"); setPattern(null); updatePopup = false; textComponent.setDocument(new AutoCompleteDocument()); setModel(model); setSelectedItem(null); new Timer(20, new ActionListener() { @Override public void actionPerformed(ActionEvent e) { if (updatePopup && isDisplayable()) { setPopupVisible(false); if (model.getSize() > 0) { setPopupVisible(true); } updatePopup = false; } } }).start(); } private class AutoCompleteDocument extends PlainDocument { boolean arrowKeyPressed = false; public AutoCompleteDocument() { textComponent.addKeyListener(new KeyAdapter() { @Override public void keyPressed(KeyEvent e) { int key = e.getKeyCode(); if (key == KeyEvent.VK_ENTER) { logger.debug("[key listener] enter key pressed"); //there is no such element in the model for now String text = textComponent.getText(); if (!model.data.contains(text)) { logger.debug("addToTop() called from keyPressed()"); addToTop(text); } } else if (key == KeyEvent.VK_UP || key == KeyEvent.VK_DOWN) { arrowKeyPressed = true; logger.debug("arrow key pressed"); } } }); } void updateModel() throws BadLocationException { String textToMatch = getText(0, getLength()); logger.debug("setPattern() called from updateModel()"); setPattern(textToMatch); } @Override public void remove(int offs, int len) throws BadLocationException { if (modelFilling) { logger.debug("[remove] model is being filled now"); return; } super.remove(offs, len); if (arrowKeyPressed) { arrowKeyPressed = false; logger.debug("[remove] arrow key was pressed, updateModel() was NOT called"); } else { logger.debug("[remove] calling updateModel()"); updateModel(); } clearSelection(); } @Override public void insertString(int offs, String str, AttributeSet a) throws BadLocationException { if (modelFilling) { logger.debug("[insert] model is being filled now"); return; } // insert the string into the document super.insertString(offs, str, a); // if (enterKeyPressed) { // logger.debug("[insertString] enter key was pressed"); // enterKeyPressed = false; // return; // } String text = getText(0, getLength()); if (arrowKeyPressed) { logger.debug("[insert] arrow key was pressed, updateModel() was NOT called"); model.setSelectedItem(text); logger.debug( String.format("[insert] model.setSelectedItem(%s)", text) ); arrowKeyPressed = false; } else if(!text.equals(getSelectedItem())){ logger.debug("[insert] calling updateModel()"); updateModel(); } clearSelection(); } } public void setText(String text) { if (model.data.contains(text)) { setSelectedItem(text); } else { addToTop(text); setSelectedIndex(0); } } public String getText() { return getEditor().getItem().toString(); } private String previousPattern = null; private void setPattern(String pattern) { if(pattern!=null && pattern.trim().isEmpty()) pattern = null; if(previousPattern==null && pattern ==null || pattern!=null && pattern.equals(previousPattern)) { logger.debug("[setPatter] pattern is the same as previous: "+previousPattern); return; } previousPattern = pattern; modelFilling = true; // logger.debug("setPattern(): start"); model.setPattern(pattern); if(logger.isDebugEnabled()) { StringBuilder b = new StringBuilder(100); b.append("pattern filter '").append(pattern==null ? "null" : pattern).append("' set:\n"); for(int i=0; i list = new ArrayList(limit); private List lowercase = new ArrayList(limit); private List filtered; void add(String s) { list.add(s); lowercase.add(s.toLowerCase()); } void addToTop(String s) { list.add(0, s); lowercase.add(0, s.toLowerCase()); } void remove(int index) { list.remove(index); lowercase.remove(index); } List getList() { return list; } List getFiltered() { if(filtered==null) filtered = list; return filtered; } int size() { return list.size(); } void setPattern(String pattern) { if (pattern == null || pattern.isEmpty()) { filtered = list; AutoCompleteCombo.this.setSelectedItem(model.getElementAt(0)); logger.debug( String.format("[setPattern] combo.setSelectedItem(null)") ); } else { filtered = new ArrayList(limit); pattern = pattern.toLowerCase(); for(int i=0; isize2) { fireIntervalRemoved(this, size2, size1-1); fireContentsChanged(this, 0, size2-1); } } public void addToTop(String aString) { if(aString==null || data.contains(aString)) return; if(data.size()==0) data.add(aString); else data.addToTop(aString); while(data.size()>limit) { int index = data.size()-1; data.remove(index); } setPattern(null); model.setSelectedItem(aString); logger.debug( String.format("[addToTop] model.setSelectedItem(%s)", aString) ); //saving into options if (data.size() > 0) { writeData(); } } @Override public Object getSelectedItem() { return selected; } @Override public void setSelectedItem(Object anObject) { if ((selected != null && !selected.equals(anObject)) || selected == null && anObject != null) { selected = (String) anObject; fireContentsChanged(this, -1, -1); } } @Override public int getSize() { return data.getFiltered().size(); } @Override public Object getElementAt(int index) { return data.getFiltered().get(index); } } public static void main(String[] args) { EventQueue.invokeLater(new Runnable() { @Override public void run() { // Logger root = Logger.getRootLogger(); // root.addAppender(new ConsoleAppender(new PatternLayout("%d{ISO8601} [%5p] %m at %l%n"))); Logger root = Logger.getRootLogger(); root.addAppender(new ConsoleAppender(new PatternLayout("%d{ISO8601} %m at %L%n"))); // BasicConfigurator.configure(); JFrame frame = new JFrame(); frame.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE); frame.setLayout(new GridLayout(3, 1)); final JLabel label = new JLabel("label "); frame.add(label); final AutoCompleteCombo combo = new AutoCompleteCombo(); // combo.getEditor().getEditorComponent().addKeyListener(new KeyAdapter() { // // @Override // public void keyReleased(KeyEvent e) { // if (e.getKeyCode() == KeyEvent.VK_ENTER) { // String text = combo.getEditor().getItem().toString(); // if(text.isEmpty()) // return; // combo.addToTop(text); // } // } // }); frame.add(combo); JComboBox combo2 = new JComboBox(new String[] {"Item 1", "Item 2", "Item 3", "Item 4"}); combo2.setEditable(true); frame.add(combo2); frame.pack(); frame.setSize( 500, frame.getHeight() ); frame.setLocationRelativeTo(null); frame.setVisible(true); } }); } }

A few months ago I ventured into the world of Mobile development and created an application (Hudson Helper) for both iPhone and Android. This article is about my experiences, comparing Android and iPhone development with a focus on tools, platform and the developer experience. Before going much further I should note that my comparison is with considerable bias. I’ve spent the past 12+ years in Java development, having spent much of my career building developer tools. Since January of 2004 I’ve been building plug-ins for Eclipse, and before that plug-ins for NetBeans. This bias is somewhat tempered with several years of C and C++ development. With this background I find that I’m very critical of developer tools. Developer productivity is key — anything that takes away from the flow of a developer in the zone is a real problem. Language, Programming Model and Platform Language The language of choice for iPhone development is Objective-C. Objective-C is a language based on C with extensions for object-oriented concepts, such as classes, inheritance, interfaces, messages, dynamic typing, etc. The Java language is used when developing for Android (though it doesn’t actually get compiled to bytecode). Java is a no-brainer. I have to say that it’s nice not to have to learn a new language to target mobile. Existing skillsets don’t come easy — so reuse of expertise is worth a lot. It took a little while to wrap my head around some of the language features available with Objective-C. I soon discovered that I really loved certain language features, such as message passing (instead of calling methods), categories and named arguments. I did find however that the syntax of Objective-C is cumbersome. I’m still not used to ‘+’ and ‘-’ for static and member methods, too many parentheses are required, and in general I just felt like I had to type way to much to express a simple concept. The IDE didn’t help much with this either (more on that later). One thing that really became clear to me is that Objective-C, though it may have been visionary for its time, is really a language of the '80s. Certain issues such as split header and implementation files and violation of DRY are really time-wasters, and not small ones at that. I found myself constantly switching back and forth between files, which not only has a cost in navigation (which file to open?) but with every file opened your sense of context must be recreated (where’s the caret, what’s selected, where am I in the file, how is this file organized). As far as DRY, must I really do 5 things to declare a property?? (declare in the class definition, again to declare getter/settter, initialize in the init method, @synthesize in the implementation, release in dealloc). Here’s what I mean: Server.h @interface Server : Updatable {NSString *name; <-- declare the property }@property (nonatomic,retain) NSString *name; <--- declare the property again Server.m @synthesize name; <-- implement getter/setter-(void) dealloc {[name release]; <-- release memory} If you ask me, everything in Server.m should go away. Another gotcha here is the positional relevance of @synthesize. Java has a similar problem with properties, though not quite so bad — and the IDE helps you write your getter/setter. Pointers in Objective-C, though powerful, are also another time-waster. This is where Java really shines with its garbage collection. I found that I was constantly considering whether allocated objects were freed appropriately. Code flow is poor since application logic is littered with memory management. I only have so many brain cycles available — why do I have to think about this other cruft that’s not really a core concern of the application domain? Of course this gets even worse when trying to figure out where things went wrong if you make a mistake. Zombies help, but still don’t make it obvious if you’ve accessed something that was deallocated. Other issues include deallocating something twice, autoreleasing something twice. I also found it non-intuitive when to retain return values from methods. Another annoyance of Objective-C is the patterns that must be followed: implementing correct init and dealloc methods is non-trivial. @synthesized getters and setters for properties with retain should not be called in these methods. So many conventions and rules to remember! Though I understand why there’s a separation of alloc and init, it’s still overly wordy to specify [[aloc Foo] initWithArg: arg]. Why not just [new Foo arg]? Or how about new Foo(arg) -- oh, wait, that’s just like Java! Objective-C’s imports and forward-declarations (@class) are a pain. Though these issues exist with Java development, Eclipse’s JDT is so good that I’ve almost forgotten what it’s like to write an import. All you have to do is Ctrl+Space to auto-complete a class name or Ctrl+Shift+O to organize imports and voila! Of course Java is not perfect either, however this fact is hidden from me due to the fact that I’ve been living in Java for a very long time. Sometimes I wish that Java were more Groovy-like, however I’m used to it and the tooling is so good. Platform On Android I found that I could readily use the Java runtime classes. Some, but not all, of the standard Java RT classes are available on Android. I didn’t find this a problem, since most of the standard Java IO, network and regex libraries are available. Android RT classes appear to be based on Harmony, which has been around long enough to be stable. With iPhone on the other hand, finding the functionality that I needed was painful. Classes and methods are poorly organized. When to look for a static method versus a class with members was not clear to me. Also depending on the framework used, naming conventions and code organization would differ. I suppose this is the legacy of an older platform. Areas where functionality was lacking that I found painful were regular expressions, string handling and XML parsing. I ended up using the excellent Regex Kit Lite for regular expressions. For XML parsing I implemented a parser abstraction over libxml, only to discover later that I may have had an easier time with NSXMLParser which is a lot more like SAX. On the iPhone when things didn’t work as expected I had to resort to Google and hope that others had encountered the same problem. This technique was hampered by Apple’s earlier NDA policy, which meant that iPhone content is pretty thin on the net. In some cases I would resort to guesswork and experimentation to find a solution. Android has the benefit of being open source. Within minutes I had the full Android platform source code on my system, and had re-built the SDK from sources to ensure that the source I had matched the runtime classes in the emulator. So not only could I see how things were implemented in the Android platform and learn by example, I could step through the platform code in the emulator and discover why my code wasn’t producing the desired results. In general I found the layout, organization, and naming conventions of Android platform classes was consistent and predictable. This made it much easier to learn. Programming Model The iPhone platform does a great job of encouraging an MVC design pattern. With this design pattern built in to the platform, building the UI was simple and I didn’t have to figure out how to organize the UI component design myself. It also means that when looking at sample code, it’s all organized in the same way. Android also does a good job with design patterns, though their concepts varied significantly from the iPhone. With Android’s support for multiple processes and component reuse, the platform itself provides support for Intents and Activities (an Intent is just a variant of a command). The design results in a better user experience, however it does introduce some complexity for the developer: when starting one Activity from another, an Intent is used to communicate any parameters. These parameters cannot be passed by reference — only by value. Where on the iPhone it’s simple to have screens sharing the same data structures, on Android this requires some forethought. Apparently Android applications can manage the back button and have everything occur inside a single Activity, however this is not the norm. Both Android and iPhone provide a way of declaring user preferences in XML. Both platforms provide a default UI for editing those preferences, which is great. Android’s XML format is extensible allowing custom UI components to be integrated, which makes user preferences a breeze. iPhone developers that wish to customize preferences will have to implement a UI from scratch, which is a lot more work. Testing and Continuous Integration I’m of the opinion that every development effort should include unit tests. Teams of size greater than one should also include Continuous Integration. Android developers will be happy to know that they can write JUnit tests. I could even launch these from the Eclipse UI after some classpath fiddling. Though I didn’t try it, I assume that it’s trivial to run these from Ant and your favorite CI server such as Hudson. I did see some iPhone unit test documentation with the iPhone SDK but didn’t take the time to explore it — so I can’t comment there. Resources Apple does an excellent job of providing lots of resources for developers. Important concepts are explained in videos, which makes grasping concepts easy — however I did find that videos progressed slowly and I was watching for what seemed like hours to find information that should have taken minutes. Luckily Apple also provides lots of sample applications and code to demonstrate API usage. Android developers also have access to loads of resources. The guide and API reference are installed with the SDK, so everything is available when offline (which for me is important since I do a lot of my work in transit). I found the Android development resources better organized and spent less time looking and more time finding. In particular the ApiDemos sample app provides a great starting point. I also downloaded many open source Android projects for ideas on architecture and API usage. This is an area where Android has the advantage, with Apple’s previous NDA policy there isn’t much out there in terms of open source for iPhone. Tooling For me tooling was a real shocker. These are the categories of tooling that I’ll cover: IDE, UI builder, debugger, profiler. Almost everything else is related to provisioning, and in that area I didn’t notice much in the way of differences between Android and iPhone. IDE Android development leverages the excellent JDT tools, which are pretty much stock and standard with every Eclipse installation. I’ve used these tools now for many years and they’re excellent. Everything Java is indexed, the IDE has a rich model of the source code, and refactoring is so seamless that it has changed the way that I work. Perhaps the best feature of JDT is its incremental compiler, which provides immediate feedback with errors and warnings as you type. This eliminates the code-compile-wait-for-feedback cycle that was so common in the '80s and '90s. Errors and warnings are updated in the Java editor as I type, giving me instant feedback. I didn’t realize just how valuable this feature is until I was coding Objective-C in XCode — when I became acutely aware at how waiting for compiler feedback can break the flow of programming. Other key features that make Eclipse so amazing to work with are: content assist quick-fixes organize imports open type (CTRL+Shift+T) refactorings Integrated javadoc and content assist is quite possibly the best way to learn an unfamiliar API. In Ecipse not only are all classes and methods immediately available in the context in which you’re writing code, their documentation is presented alongside. Content Assist with Integrated Javadoc XCode is so shockingly bad that I almost don’t know where to start. Here’s a minimum list of things that I think need fixing in order for XCode to become a viable IDE: Content assist that actually works. Content assist provided by XCode is often wrong, and almost always suggests a small subset of what’s actually available. A decent window/editor management system. XCode and it’s associated tools (debugger) like to open lots of windows. Want to open a file? How about a new window for you! Very quickly I found myself in open-window-hell. The operating system’s window management is designed for managing multiple applications, not multiple editors within an IDE. It’s simply not capable of providing management of editors in an environment as sophisticated as an IDE. A project tree view that sorts files alphabetically. Really! Integrated API documentation. I found that I was constantly switching out of the IDE and searching for API documentation using Appkido. This may seem trivial, but it really breaks the flow. One area of Eclipse that simply can’t be matched is Mylyn. Integrated task management and a focused interface introduce huge efficiencies into any project, small or large. If you haven’t yet tried out Mylyn, it’s definitely worth your time to take a look. A good place to start is Mylyn’s Getting Started page. UI Builder iPhone app developers are given a pretty good UI builder. It does a great job of showing the UI as it will actually appear. It’s flexible and can model some pretty sophisticated UIs, so I was impressed. I found that using it was a little tricky — I had to read the documentation two or three times before I could really figure out how to use it properly. The Android UI builder I found pretty useless: it can’t display UIs how they’ll actually appear, and it’s UI is way too inefficient. I found that I coded all of the UIs directly in the XML source view of the UI builder. There the content assist and validation were pretty good, making it the easiest way for me to build a UI. Debugger Having used to the Java debugger in Eclipse I was shocked at the state of the debugger in XCode. With Eclipse I can see and modify variable values. Not so in XCode. Maybe this is simply the state of affairs when debugging native code, but it sure affects the usefulness of the debugger. XCode often seemed confused as to the type of an object and presented me with a pointer value and no detail. This is a sharp contrast to Eclipse, where I can drill down through an object graph with ease. I found the XCode debugger UI extremely difficult to use. Clicking on the stack to show code in an editor caused new windows to open, eventually resulting in dozens of windows open. In addition I found that watch expressions rarely worked for me. Profiler and Heap Analysis An area where Apple development tools excel is in profiling and heap analysis. These tools seemed mature and easy to use. With no prior experience with these specific tools I was able to gain a better understanding of my app within minutes, find and fix several memory leaks and improve performance. XCode Memory Leak Detection Android developers must use Android’s traceview application, which I found worked well but required significantly more effort to configure and operate. I was surprised to find that the source code must be changed in order to get the trace files required for analysis. I’m not sure if Android can provide heap dumps in hprof format. If it can then the awesome MAT tool could be used to analyze heap usage. According to this article Android can produce hprof heap data, though I haven’t tried it. App Store It goes without saying that the iPhone app store is excellent in that you can sell into many countries worldwide with a single setup. I was able to provide my Canadian bank account number, sign a few legal agreements and I was up and running. Getting an app into the store however is frustrating to say the least. Apple must approve every app before it is accepted into the store. Mine got rejected multiple times. Each time it was rejected I was given almost no information about why. When I emailed them to clarify the problem, I received what looked like a canned response indicating that I should refer to previous correspondence. If it weren’t so frustrating I would have found it funny. I highly recommend reading Brian Stormont’s Avoiding iPhone App Rejection from Apple and Dan Grigsby’s Part 2 follow-up. Of course once I started selling Hudson Helper I realized that Apple won’t send me any money unless the payout is greater than $250. This is true not only of the first payout, but every payout. Google market on the other hand requires a minimum of $1 for each payout. Both the iPhone app store and Google market take about %30 of your app selling price. $0.99 applications have to have high volume, or they’re simply not worth your time. The Google market by comparison to the Apple app store is terrible in that you can only sell into a handful of countries. You also can’t see or install apps that cost money on a developer phone. Actually you can, but not if the app has copy protection — which is almost every non-free app. On the other hand when you upload your app to the app store it’s available within minutes, so you don’t have to worry about an approval process. To set up a merchant account with Google market, I had to provide a US address and bank account number, since Google doesn’t support Canada. For me this was a pain, but not too bad since I live within a few kilometers of the US border. I rode my bike down to the US and opened an account with Horizon bank. The bank required a passport and driver’s license, so no problem there. Why Google doesn’t support more countries I don’t know. At the very least Google market should accept alternate payment methods for countries that are not supported by Google checkout. Summary Android’s platform and developer tools are excellent. Leveraging Java and the Eclipse IDE are major winning factors for Android. Apple’s developer tools are shockingly bad by comparison. The Objective-C language and platform APIs are cumbersome and poorly organized. Overall when developing for the iPhone I felt like I was back in 1993. These factors combined in my estimation make application development about three times more expensive when developing for iPhone. The only area where Apple’s developer tools excelled was in profiling and heap analysis. Apple’s app store from a user’s standpoint and from a worldwide coverage standpoint are excellent. In this area Google market for Android is weak. Development for iPhone may improve as tools such as iphonical (MDD for iPhone) and objectiveclipse (Eclipse plug-in for Objective-C) emerge. We may see a shake-up in the mobile market, with at least 18 new Android handsets being released this year. Until that happens, iPhone will remain a market leader and developers will have to put up with XCode and Objective-C. For me, my love is with Android. Sure, the iPhone is great — but can you install a new Linux kernel? From http://greensopinion.blogspot.com/

You may have already faced a situation where you need to have messaging capabilities in your application while your client application runs in an environment, which you have no control over its network configuration and restrictions. Such situation lead to the fact that you can not use JMS communication over designated ports like 7676 and so. You may simply put JMS away and follow another protocol or even plain HTTP communication to address your architecture and design requirement, but we can not easily put pure JMS API capabilities away as we may need durable subscription over a proven and already well tested and established design and architecture. Different JMS implementation providers provide different type capabilities to address such a requirement. ActiveMQ provide HTTP and HTTPS transport for JMS API and described it here. OpenMQ provide different transport protocol and access channels to access OpenMQ functionalities from different prgramming . One of the access channles which involve HTTP is named Universal Message Service (UMS) which provide a simple REST interaction template to place messages and comsume them from any programming language and device which can interact with a network server. UMS has some limitations which is simply understandable based on the RESTful nature of UMS. For current version of OpenMQ, it only supports Message Queues as destinations so there is no publish-subscribe functionality available. Another capability which involve HTTP is JMS over HTTP or simply JMS HTTP tunneling. OpenMQ JMS implementation supports HTTP/s as transport protocol if we configure the message broker properly. Well I said the JMS implementation support HTTP/S as a transport protocol which means we as user of the JMS API see almost no difference in the way that we use the JMS API. We can use publish-subscribe, point to point, durable subscription, transaction and whatever provided in the JMS API. First, lets overview the OpenMQ installation and configuration then we will take a look at an example to see what changes between using JMS API and JMS API over HTTP transport. Installation process is as follow: OpenMQ project provides a Java EE web application which interact with OpenMQ broker from one side and Sun JMS implementation on the other side. Interaction of this application with the client and MQ broker is highly customizable in different aspects like Broker port number, client poll inrval, Broker address and so on. Download OpenMQ from https://mq.dev.java.net/ it should be a zip which is different for each platform. Install the MQ by unzipping the above file and running ./installer or installer.bat or so. After the installation completed, go to install_folder/var/mq/instances/imqbroker/props and open the config.properties in a text editor like notepad or emeditor or gedit. Add the following line to the end of the above file: imq.service.activelist=jms,admin,httpjms Now goto install_folder/mq/lib/ and pick the imqhttp.war file. deploy the file into your Servlet container or application server (I went with GlassFish). After you deployed the file start the application server or Servlet container Now it is time to start the MQ broker: launch a terminal or cmd console and goto install_folder/mq/bin now execute ./imqbrokerd -port 7979 (it maybe like imqbrokerd.bat -port 7979 for Windows ) This command will start the MQ broker and keep it listening on port 7979 for incoming connection To test the overall operations: Open a browser and tray to surf http://127.0.0.1:8080/imqhttp/tunnel or whatever URL which points to the newly deployed application . If you saw "HTTP tunneling Servlet ready." as the first line in the response page then we are ready for last step. Now let's see how we can publish some messages, this sample code assume that we have configured the message broker and assumes that we have the following two JAR files in the classpath. These JAR files are available in install_folder/mq/lib/ imq.jar jms.jar Now the Publisher code: public class Publisher { public void publish(String messageContent) { try { String addressList = "http://127.0.0.1:8080/imqhttp/tunnel"; com.sun.messaging.TopicConnectionFactory topicConnectionFactory = new com.sun.messaging.TopicConnectionFactory(); topicConnectionFactory.setProperty(com.sun.messaging.ConnectionConfiguration.imqAddressList, addressList); javax.jms.Topic top; javax.jms.Connection con = topicConnectionFactory.createTopicConnection("admin", "admin"); javax.jms.Session session = con.createSession(false, javax.jms.Session.AUTO_ACKNOWLEDGE); top = session.createTopic("DIRECT_TOPIC"); MessageProducer prod = session.createProducer(top); Message textMessage = session.createTextMessage(messageContent); prod.send(textMessage); prod.close(); session.close(); con.close(); } catch (JMSException ex) { ex.printStackTrace(); } } public static void main(String args[]) { Publisher p = new Publisher(); for (int i = 1; i < 10; i++) { p.publish("Sample Text Message Content: " + i); } } } As you can see the only difference is the connection URL which uses http instead of mq and point to a Servlet container address instead of pointing to the Broker listening address. The subscriber sample code follow a similar pattern. Here I write a sample durable subscriber so you can see that we can use durable subscribtion over HTTP. But you should note that HTTP transport uses polling and continuesly open communication channel which can introduce some overload on the server. class SimpleListener implements MessageListener { public void onMessage(Message msg) { System.out.println("On Message Called"); if (msg instanceof TextMessage) { try { System.out.print(((TextMessage) msg).getText()); } catch (JMSException ex) { ex.printStackTrace(); } } } } public class Subscriber { /** * @param args the command line arguments */ public void subscribe(String clientID, String susbscritpionID) { try { // TODO code application logic here String addressList = "http://127.0.0.1:8080/imqhttp/tunnel"; com.sun.messaging.TopicConnectionFactory topicConnectionFactory = new com.sun.messaging.TopicConnectionFactory(); topicConnectionFactory.setProperty(com.sun.messaging.ConnectionConfiguration.imqAddressList, addressList); javax.jms.Topic top; javax.jms.Connection con = topicConnectionFactory.createTopicConnection("admin", "admin"); con.setClientID(clientID); javax.jms.Session session = con.createSession(false, javax.jms.Session.AUTO_ACKNOWLEDGE); top = session.createTopic("DIRECT_TOPIC"); TopicSubscriber topicSubscriber = session.createDurableSubscriber(top, susbscritpionID); topicSubscriber.setMessageListener(new SimpleListener()); con.start(); } catch (JMSException ex) { ex.printStackTrace(); } } public static void main(String args[]) { Subscriber sub = new Subscriber(); sub.subscribe("C19", "C1_011"); } } Now how you can test the entire example and monitor the MQ? it is very simple by utilizing the provided tools. Do the following steps to test the overall durable subscription system: Run a subscriber Run another subscriber with a different client ID Run a publisher once or twice Kill the second subscriber Run a publisher once Run the subscriber and you can see that the subscriber will fetch all messages which arrived after it shut down-ed. Note that we can not have two separate client with same client ID running because the broker will not be able to distinguish which client it should send the messages. You can monitor the queue and the broker using: ./imqadmin which can be found in install_folder/mq/bin this software shows how many durable subscribers are around and how many messages are pending for each subscriber and so on. You can monitor the Queue in real-time mode using the following command which can be executed in install_folder/mq/bin ./imqcmd -b 127.0.0.1:7979 metrics dst -t t -n DIRECT_TOPIC The command will ask for username and password, give admin/admin for it The sample code for this entry can be found Here. The sample code is a NetBeans project with the publisher and the subscriber source code. A complete documentation of OpenMQ is available at its documentation centre. You can see how you can change different port numbers or configure different properties of the Broker and HTTP tunneling web application communication.

Hibernate is a powerful, high performance object/relational persistence and query service. Hibernate lets you develop persistent classes following object-oriented idiom - including association, inheritance, polymorphism, composition, and collections. Hibernate allows you to express queries in its own portable SQL extension (HQL), as well as in native SQL, or with an object-oriented Criteria and Example API. Quintessential to using any ORM framework like hibernate is to know how to leverage the various performance tuning methods supported by the framework. In this volume Wings Jiang discusses three performance tuning strategies for hibernate: SQL Optimization Session Management Data Caching SQL Optimization When using Hibernate in your application, you already have been coding HQL (Hibernate Query Language) somewhere. For example, “from User user where user.name = ‘John’”. If issuing your SQL statement like this, Hibernate cannot use the SQL cache implemented by database because name of the user, in most scenarios, is extremely distinct. On the contrary, while using placeholder to achieve this, like “from User user where user.name =?” will be cached by the Database to fulfill the performance improvement. You can also set some Hibernate properties to improve performance, such as setting the number of records retrieved while fetching records via configuring property hibernate.jdbc.fetch_size, setting the batch size when committing the batch processing via configuring property hibernate.jdbc.batch_size and switching off the SQL output via setting property hibernate.show_sql to false in product environments. In addition, the performance tuning of your target Database is also significant, like SQL clauses tuning, reasonable indexes, delicate table structures, data partitions etc. Session Management Undoubtedly, Session is the pith of Hibernate. It manages the Database related attributes, such as JDBC connections, data entities’ states. Managing the Session efficiently is the key to getting high performance in enterprise applications. One of the many commonly used and equally elegant approaches to session management in hibernate is to use ThreadLocal. Threadlocal will create a local copy of session for every thread. Thus synchronization problems are averted, when objects are put in the Threadlocal, . To understand how ThreadLocal variables are used in Java, refer to Sun Java Documentation at http://java.sun.com/j2se/1.5.0/docs/api/java/lang/ThreadLocal.html Data Caching Before accomplishing any data caching, it is essential to set the property hibernate.cache.user_query_cache = true. There are three kinds of commonly used Caching Strategies in Hibernate: Using cache based on Session level (aka Transaction layer level cache). This is also called first-level cache. Using cache based on SessionFactory level (Application layer level cache). This is also called second-level cache. Using cluster cache which is employed in distributed application (in different JVMs). In fact, some techniques, like loading data by id, lazy initialization which betokens loading appropriate data in proper time rather than obtaining a titanic number of useless records, which are fairly useless in the subsequent operations are consummated via data caching. First Level Cache (aka Transaction layer level cache) Fetching an object from database always has a cost associated with it. This can be offset by storing the entities in hibernate session. Next time the entities are required, they are fetched from the session, rather than fetching from the database. To clear an object from the session use: session.evict(object). To clear all the objects from the session use session.clear(). Second Level Cache (aka Application layer level cache) In this approach, if an object is not found in session, it is searched for in the session factory before querying the database for the object. If an object is indeed fetched from database, the selected data should be put in session cache. This would improve the performance when the object is required next time. To remove an entity from session factory use the various overloaded implementations of evict() method of SessionFactory. In fact, Hibernate lets you tailor your own caching implementation by specifying the name of a class that implements org.hibernate.cache.CacheProvider using the property hibernate.cache.provider_class. But it is recommended to employ a few built-in integrations with open source cache providers (listed below). Cache Type Cluster Safe Query Cache Supported Hashtable Memory NO YES EHCache Memory, Disk NO YES OSCache Memory, Disk NO YES SwarmCache Clustered YES (clustered invalidation) NO JBoss TreeCache Clustered YES (replication) YES Terracota Clustered YES YES In order to use second level caching, developers have to append some configurations in hibernate.cfg.xml (for example, using EHCache here). net.sf.ehcache.hibernate.Provider In addition, developers also need to create a cache specific configuration file (Example: ehcache.xml for EHCache). (1) diskStore : Sets the path to the directory where cache .data files are created. The following properties are translated: a.user.home - User's home directory b.user.dir - User's current working directory c.java.io.tmpdir (Default temp file path) maxElementsInMemory : Sets the maximum number of objects that will be created in memory. eternal : Sets whether elements are eternal. If eternal, timeouts are ignored and the element is never expired. timeToIdleSeconds : Sets the time to idle for an element before it expires. Is only used if the element is not eternal. Idle time is now - last accessed time. timeToLiveSeconds : Sets the time to live for an element before it expires. Is only used if the element is not eternal. TTL is now - creation time overflowToDisk : Sets whether elements can overflow to disk when the in-memory cache has reached the maxInMemory limit. Finally the cache concurrency strategy has to be specified in mapping files. For example, the following code fragment shows how to configure your cache strategy. … … Cache Concurrency Strategies There are four kinds of built-in cache concurrency strategies provided by Hibernate. Chosing a right concurrency strategy for your hibernate implementation is the key to cache performance optimization. Besides to ensure data consistency and transaction integrity it is indispensable to master these strategies. read-only If your application needs to read but never modify instances of a persistent class, a read-only cache may be used. This is the simplest and best performing strategy. It's even perfectly safe for use in a cluster. nonstrict-read-write If the application only occasionally needs to update data (For example, if it is extremely unlikely that two transactions would try to update the same item simultaneously) and strict transaction isolation is not required, a nonstrict-read-write cache might be appropriate. read-write If the application needs to update data, a read-write cache might be appropriate. This cache strategy should never be used if serializable transaction isolation level is required. transactional If the application seldom needs to update data and at the same time, application also needs to avoid “dirty read” and “repeatable read”, this kind of concurrency strategy can be employed. The transactional cache strategy provides support for fully transactional cache providers such as JBoss TreeCache. The following table lists cache concurrency strategy supported by various cache providers. Cache Read-only Nonstrict-read-write Read-write Transactional Hashtable YES YES YES N/A EHCache YES YES YES N/A OSCache YES YES YES N/A SwarmCache YES YES N/A N/A JBoss TreeCache YES N/A N/A YES Cluster Cache (in different JVMs) Hibernate also supports cluster caching in disparate JVMs. At present, both SwarmCache and JBoss TreeCache support cluster caching across multiple JVMs. In some situations, especially at the level of enterprise, certain application has to support the concurrency accessing of thousands of users, at that time, cluster cache can help you because the cluster can provide failover and load balancing which improve the performance of application. Points to Note When employing one of the four cache strategies above, pay close attention to the following situation: Data cached almost immutable If data you want to cache is almost constant, you can use data caching which can improve the performance of the application. On the contrary, if the caching data are quiet volatile, Hibernate have to maintain and update the caching over time which extremely leads to performance hit. Data sizes in reasonable range If the size of data you is caching is massive, Hibernate will occupy the most memories of system, which causes the long waiting time of the whole application. Low frequency of data updating If data you are caching needs to be modified frequently, Hibernate have to take an array of time to update and modify the data in caching, which impacts the performance of the application as well. High frequency of data querying If data you are caching is steady, which means that most of the operations are querying, searching, no updating and modifying, making the most use of caching will be affording huge performance improvement. None crucial data Because of existing some incongruities when keeping the data in caching, so if the data you are caching is fairly crucial, do not use caching. By contrast, if the data in caching is insignificant, just use it without any vacillation. Summary Actually, after employing SQL Optimization, Session Management, Data Caching, we will obtain great battalions of performance gains, which make applications achieve acceptable waiting time for the final customers. External Links for Further Study http://www.hibernate.org/hib_docs/reference/en/html/performance.html http://blogs.jboss.com/blog/acoliver/2006/01/23/Hibernate_EJB3_Tuning.txt About Author I am Wings Jiang from BCM China. I have mainly focused on J2EE technologies in recent years and worked in several projects involving Struts/Tapestry, Spring, Hibernate, WebLogic, Websphere, Oracle, DB2 etc. I have experience in design and code of several Java applications. Hibernate performance is one of the areas I pay close heed to in my current working.

During the last Devoxx conference, Mark Reinhold, Sun's chief engineer for Java SE, gave a presentation on the latest directions for Java 7. (Hamlet D'Arcy's summary of Mark's presentation is available here.) One of the features that was discussed for possible inclusion in Java 7, but won't find its way into the final release, is first class properties for Java. First-class support for properties would have gone beyond the simple setter and getter methods of the JavaBeans specification, and provided a succinct and elegant way for defining properties for Java objects. Properties are already first-class elements of many modern languages, so this lack in Java 7 will be felt by many developers accustomed to other languages' property support. At the same time, Java developers can resort to a handful of other techniques in working with property-like Java attributes, and some of the possible techniques work even in Java 1.4. In the rest of this article, I will demonstrate one such technique use a simple aspect, with AspectJ, and some following some conventions. Motivation The idea for this solution arose while working with the OpenXava 3 framework. OpenXava defines a mechanism to develop Java Enterprise applications using Business Components. It's an alternative way to MVC: instead of organizing the code into Model, a View and a Controller, the code with OpenXava is organized around Invoice, Customer, Order, and similar business-centric objects. OpenXava initially used XML for defining components, but since version 3 the use of POJOs with Java 5 annotations also became available as the preferred way to define business components. When using the XML-based object definition, you may specify a component in the following manner: Using the annotation-based OpenXava 3, the same component would be defined as follows: @Entity public class Teacher { @Id @Column(length=5) @Required private String id; @Column(length=40) @Required private String name; @OneToMany(mappedBy="teacher") private Collection pupils; public String getId() { return id; } public void setId(String id) { this.id = id; } public String getName() { return name; } public void setName(String name) { this.name = name; } public Collection getPupils() { return pupils; } public void setPupils(Collection pupils) { this.pupils = pupils; } } This illustrates some of the verbosity with the Java definition: 37 lines against the 13 of XML version. The problem occurs because of the getters and setters. The boilerplate code adds noise and increases the size of the file without increasing the information to the programmer. Use Java and annotations as a definition language in OpenXava would welcome a more succinct and elegant syntax. A More Succinct Solution A better solution can be obtained by defining the business component in this way: @Entity public class Teacher { @Id @Column(length=5) @Required public String id; @Column(length=40) @Required public String name; @OneToMany(mappedBy="teacher") public Collection pupils; } This makes Java more beautiful, succinct and elegant... just as XML. With this, you have to use the following properties without getters and setters. That is, instead of: teacher.setName("M. Carmen"); String result = teacher.getName(); you write: teacher.name = "M. Carmen"; String result = teacher.name; In this case name is not a field, but a property. You can refine the access to this property, and even create pure calculated properties. For example, if you wanted a calculated property, you could define it in this way: @Entity public class Person { ... public String name; public String surname; transient public String fullName; // (1) protected String getFullName() { // (2) return name + " " + surname; } } In order to define a calculated property, you define a public field (1) and then a protected (or private, but not public) getter (2). This getter, getFullName() in this case, is for implementing the logic for the property fullName. Using this property is simple: Person p = new Person(); p.name = "M. Carmen"; p.surname = "Gimeno Alabau"; assertEquals("M. Carmen Gimeno Alabau", p.fullName); When p.fullName is used, the method getFullName() is executed for returning the value. You can see that fullName is a property, not a simple field. You can also refine access to writing and reading the properties. For example, you can define a property as following: public String address; protected String getAddress() { return address.toUpperCase(); } When address is used from outside the class the method getAddress() is used to obtain the result, but this method only returns the address with some refinement. As we use address field from inside getAddress() field address from inside of its class is used, and the getter is not called. Now you can use this property as follows: Person p = new Person(); p.address = "Av. Baron de Carcer"; assertEquals("AV. BARON DE CARCER", p.address); As well, you can define setters, even for vetoing the data to be set, as in the next example: public int age; protected void setAge(int age) { if (age > 200) { throw new IllegalArgumentException("Too old"); } this.age = age; } As in the case of the getter, if a setter method is present it will be executed to set the data, you can use this logic to set the data to the field or for any other logic you want. Now you can use this property in this way: Person p = new Person(); p.age = 33; assertEquals(p.age, 33); p.age = 250; // Here an IllegalArgumentException is thrown In summary: Properties behave from outside of the class as public fields. If no getter or setter for the field exists, a direct access for the field is performed. If a getter exists for the field, it will be executed when trying to read the field from outside. If a setter exists for the field, it will be executed when trying to write the field from outside. From inside the class, all references to the field are direct access, without calling getter or setter. This provides a simple and natural way to have properties in Java without unnecessary getters and setters. Implementation This simple mechanism is easy to implement using AspectJ and a simple aspect, and it will work even in Java 1.4. For this to work, you only need to have an aspect in your project: aspect PropertyAspect { pointcut getter() : get(public !final !static * *..model*.*.*) && !get(public !final !static * *..model*.*Key.*) && !within(PropertyAspect); pointcut setter() : set(public !final !static * *..model*.*.*) && !set(public !final !static * *..model*.*Key.*) && !within(PropertyAspect); Object around(Object target, Object source) : target(target) && this(source) && getter() { if (target == source) { return proceed(target, source); } try { String methodName = "get" + Strings.firstUpper( thisJoinPointStaticPart.getSignature().getName()); Method method = target.getClass(). getDeclaredMethod(methodName, null); method.setAccessible(true); return method.invoke(target, null); } catch (NoSuchMethodException ex) { return proceed(target, source); } catch (InvocationTargetException ex) { Throwable tex = ex.getTargetException(); if (tex instanceof RuntimeException) { throw (RuntimeException) tex; } else throw new RuntimeException( XavaResources.getString("getter_failed", thisJoinPointStaticPart. getSignature().getName(), target.getClass()), ex); } catch (Exception ex) { throw new RuntimeException( XavaResources.getString("getter_failed", thisJoinPointStaticPart.getSignature().getName(), target.getClass()), ex); } } void around(Object target, Object source, Object newValue) : target(target) && this(source) && args(newValue) && setter() { if (target == source) { proceed(target, source, newValue); return; } try { String methodName = "set" + Strings.firstUpper(thisJoinPointStaticPart.getSignature().getName()); Class fieldType = ((FieldSignature) thisJoinPointStaticPart.getSignature()).getFieldType( Method method = target.getClass(). getDeclaredMethod(methodName, new Class[] {fieldType}); method.setAccessible(true); method.invoke(target, new Object[] { newValue } ); } catch (NoSuchMethodException ex) { proceed(target, source, newValue); } catch (InvocationTargetException ex) { Throwable tex = ex.getTargetException(); if (tex instanceof RuntimeException) { throw (RuntimeException) tex; } else throw new RuntimeException( XavaResources.getString("setter_failed", thisJoinPointStaticPart.getSignature().getName(), target.getClass()), ex); } catch (Exception ex) { throw new RuntimeException( XavaResources.getString("setter_failed", thisJoinPointStaticPart.getSignature().getName(), target.getClass()), ex); } } } Having defined this aspect, you will need to compile your project using AspectJ. The aspect intercepts all access to public fields in the model package, then use introspection to call to the getter or setter method if they exists. Drawbacks Unfortunately, this approach has at least two important drawbacks: It does not work when you access to the properties using introspection. With JPA, at least using the Hibernate implementation, lazy initialization does not work. You may think that the introspection problem can be overcome with your own custom introspection code. But the man third party libraries, frameworks, and toolkits will not obey those rules. For example, if you are using a report generator that can generate a report from a collection of Java objects, the report generator may expect real public getters and setters in the objects. The JPA the specification for Java Persistence API states that: 2.0: "Instance variables must not be accessed by clients of the entity. The state of the entity is available to clients only through the entity methods i.e., accessor methods (getter/setter methods) or other business methods." JSR 317 : JavaTM Persistence API, Version 2.0 - Public Review Draft - Section 2.1 That is, portable JPA code should not rely on direct access to properties. Conclusion This article presents a very simple way to work with properties in Java, even though the language doesn't support properties. If the AspectJ implementation is not practical, you can find other implementations of this idea using asm or cglib. References OpenXava - http://www.openxava.org/ AspectJ - http://www.eclipse.org/aspectj/

It's amazing the things that are right in front of you that you don't realise. VisualVM is probably the best example of this in the Java community.

If you knew that the language that you are reading supports it, you are just going to extend this mental path to operations that involve overridable operators.