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

JPA has 2 levels of caching. The first level of caching is the persistence context. The JPA Entity Manager maintains a set of Managed Entities in the Persistence Context. The Entity Manager guarantees that within a single Persistence Context, for any particular database row, there will be only one object instance. However the same entity could be managed in another User's transaction, so you should use either optimistic or pessimistic locking as explained in JPA 2.0 Concurrency and locking The code below shows that a find on a managed entity with the same id and class as another in the same persistence context , will return the same instance. @Stateless public ShoppingCartBean implements ShoppingCart { @PersistenceContext EntityManager entityManager; public OrderLine createOrderLine(Product product,Order order) { OrderLine orderLine = new OrderLine(order, product); entityManager.persist(orderLine); //Managed OrderLine orderLine2 =entityManager.find(OrderLine, orderLine.getId())); (orderLine == orderLine2) // TRUE return (orderLine); } } The diagram below shows the life cycle of an Entity in relation to the Persistent Context. The code below illustrates the life cycle of an Entity. A reference to a container managed EntityManager is injected using the persistence context annotation. A new order entity is created and the entity has the state of new. Persist is called, making this a managed entity. because it is a stateless session bean it is by default using container managed transactions , when this transaction commits , the order is made persistent in the database. When the orderline entity is returned at the end of the transaction it is a detached entity. The Persistence Context can be either Transaction Scoped-- the Persistence Context 'lives' for the length of the transaction, or Extended-- the Persistence Context spans multiple transactions. With a Transaction scoped Persistence Context, Entities are "Detached" at the end of a transaction. As shown below, to persist the changes on a detached entity, you call the EntityManager's merge() operation, which returns an updated managed entity, the entity updates will be persisted to the database at the end of the transaction. An Extended Persistence Context spans multiple transactions, and the set of Entities in the Persistence Context stay Managed. This can be useful in a work flow scenario where a "conversation" with a user spans multiple requests. The code below shows an example of a Stateful Session EJB with an Extended Persistence Context in a use case scenario to add line Items to an Order. After the Order is persisted in the createOrder method, it remains managed until the EJB remove method is called. In the addLineItem method , the Order Entity can be updated because it is managed, and the updates will be persisted at the end of the transaction. The example below contrasts updating the Order using a transaction scoped Persistence Context verses an extended Persistence context. With the transaction scoped persistence context, an Entity Manager find must be done to look up the Order, this returns a Managed Entity which can be updated. With the Extended Persistence Context the find is not necessary. The performance advantage of not doing a database read to look up the Entity, must be weighed against the disadvantages of memory consumption for caching, and the risk of cached entities being updated by another transaction. Depending on the application and the risk of contention among concurrent transactions this may or may not give better performance / scalability. JPA second level (L2) caching JPA second level (L2) caching shares entity state across various persistence contexts. JPA 1.0 did not specify support of a second level cache, however, most of the persistence providers provided support for second level cache(s). JPA 2.0 specifies support for basic cache operations with the new Cache API, which is accessible from the EntityManagerFactory, shown below: If L2 caching is enabled, entities not found in persistence context, will be loaded from L2 cache, if found. The advantages of L2 caching are: avoids database access for already loaded entities faster for reading frequently accessed unmodified entities The disadvantages of L2 caching are: memory consumption for large amount of objects Stale data for updated objects Concurrency for write (optimistic lock exception, or pessimistic lock) 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 protect any data that can be concurrently modified with a locking strategy: Must handle optimistic lock failures on flush/commit configure expiration, refresh policy to minimize lock failures The Query cache is useful for queries that are run frequently with the same parameters, for not modified tables. The EclipseLink JPA persistence provider caching Architecture The EclipseLink caching Architecture is shown below. Support for second level cache in EclipseLink is turned on by default, entities read are L2 cached. You can disable the L2 cache. EclipseLink caches entities in L2, Hibernate caches entity id and state in L2. You can configure caching by Entity type or Persistence Unit with the following configuration parameters: Cache isolation, type, size, expiration, coordination, invalidation,refreshing Coordination (cluster-messaging) Messaging: JMS, RMI, RMI-IIOP, … Mode: SYNC, SYNC+NEW, INVALIDATE, NONE The example below shows configuring the L2 cache for an entity using the @Cache annotation The Hibernate JPA persistence provider caching Architecture The Hibernate JPA persistence provider caching architecture is different than EclipseLink: it is not configured by default, it does not cache enities just id and state, and you can plug in different L2 caches. The diagram below shows the different L2 cache types that you can plug into Hibernate. The configuration of the cache depends on the type of caching plugged in. The example below shows configuring the hibernate L2 cache for an entity using the @Cache annotation For More Information: Introducing EclipseLink EclipseLink JPA User Guide Hibernate Second Level Cache Speed Up Your Hibernate Applications with Second-Level Caching Hibernate caching Java Persistence API 2.0: What's New ? Beginning Java™ EE 6 Platform with GlassFish™ 3 Pro EJB 3: Java Persistence API (JPA 1.0)

Often you will notice that Ehcache is used mostly like a tool that implements highly configurable maps. Sometimes developers configure time-to-live properties, or make use of disk-store functionality, but you can rarely meet someone who has cache population/eviction process that makes sense. In the perfect world I would expect cache to be a universal pool. I request a value for a key and would like to get it whenever it is possible and as fast as possible with just one line of code. But in reality I usually can see huge cache population code on the application startup, daemon threads that update caches in eternal loop and numerous “ifs” around cache.get() calls. In my strive to the perfect world I’ve discovered a SelfPopulatingCache class in Ehcache. In this article I will describe how using SelfPopulatingCache class one can implement a cache with self creating objects with optional auto-updating. In some way this example is an implementation of ideas mentioned in Ehcache documentation. Example What you will see down here: A Reader that fetches an object from cache 5 times every 0.5 seconds. Behind scenes cache will create a new object if there is no such object is there in cache for a key requested. A daemon thread will trigger cache refresh every 2 seconds. The most important class in this example is ExampleCacheProvider. package com.blogspot.mikler.java; import net.sf.ehcache.CacheManager; import net.sf.ehcache.Ehcache; import net.sf.ehcache.constructs.blocking.SelfPopulatingCache; import net.sf.ehcache.constructs.blocking.CacheEntryFactory; public class ExampleCacheProvider { private CacheManager cacheManager; private CacheEntryFactory updatingFactory; public SelfPopulatingCache selfPopulatingCache; public ExampleCacheProvider() throws Exception { cacheManager = CacheManager.create(); Ehcache originalCache = cacheManager.getCache("com.blogspot.mikler.java.cache"); final String cacheType = System.getProperty("com.blogspot.mikler.java.cache.factory"); if (cacheType == null || cacheType.equals("create")){ updatingFactory = new ExampleCacheEntryFactory(); } else { updatingFactory = new ExampleUpdatingCacheEntryFactory(); } selfPopulatingCache = new SelfPopulatingCache(originalCache, updatingFactory); //chache refresh thread Thread updatingThread = new Thread(){ public void run() { while (true){ System.out.println("!!!!! Doing refresh !!!!!"); selfPopulatingCache.refresh(); try { Thread.sleep(2000); } catch (InterruptedException e) { System.out.println("Interrupted"); } } } }; updatingThread.setDaemon(true); updatingThread.start(); } public Ehcache getCache(){ return selfPopulatingCache; } } What it does is creating simple Ehcache (original cache) and wrapping it with SelfPopulatingCache (selfPopulatingCache). We can use this class the same way as CacheManager, so one can consider extending CacheManager, but to keep it simple here we'll stick to this kind of cache source. While wrapping we specify updatingFactory, which can be set to one of two options: ExampleCacheEntryFactory (line 19) and ExampleUpdatingCacheEntryFactory(line 21). For the purposes of this example the choice between this two options is done based on the “com.blogspot.mikler.java.cache.factory” system property value. The difference between this two is that ExampleCacheEntryFactory implements CacheEntryFactory interface, while ExampleUpdatingCacheEntryFactory extends ExampleCacheEntryFactory and implements UpdatingCacheEntryFactory. The difference between using each of this options is explained later on. Meanwhile here is the code of both classes. package com.blogspot.mikler.java; import net.sf.ehcache.constructs.blocking.CacheEntryFactory; public class ExampleCacheEntryFactory implements CacheEntryFactory { public Object createEntry(Object key) throws Exception { System.out.println("++++++creating entry for key = " + key); return new StringBuffer(Long.toString(Math.round(100*Math.random())) + key+"0"); } } package com.blogspot.mikler.java; import net.sf.ehcache.constructs.blocking.UpdatingCacheEntryFactory; public class ExampleUpdatingCacheEntryFactory extends ExampleCacheEntryFactory implements UpdatingCacheEntryFactory { public void updateEntryValue(Object key, Object value) throws Exception { System.out.println("~~~~~~UPDATING entry for key = " + key); final StringBuffer stringBuffer = (StringBuffer) value; stringBuffer.append(stringBuffer.length()); } } As you can see in this example as cache element’s key string used, while StringBuffer is used as a value. In createEntry() method in ExampleCacheEntryFactory StringBuffer is created with leading random number. While in updateEntryValue() method of ExampleUpdatingCacheEntryFactory existing StringBuffer length is appended to the buffer itself. And finally, here goes our Reader main class. It fetches our wrapped cache, get’s value for “foo” key from it and stores it into final local variable fooOriginalBuffer, that is never changed late in Reader’s code. Then it starts doing 5 iterations of getting value for “foo” key from cache, displaying debug info and stats, and sleeping for one second. The code is simple as this. package com.blogspot.mikler.java; import net.sf.ehcache.Ehcache; public class Reader { private ExampleCacheProvider exampleCacheProvider; public Reader(ExampleCacheProvider exampleCacheProvider) { this.exampleCacheProvider = exampleCacheProvider; } public void run(){ Ehcache cache = exampleCacheProvider.getCache(); final StringBuffer fooOriginalBuffer = (StringBuffer) cache.get("foo").getValue(); for (int i = 0; i < 5; i++){ System.out.println("----------------------------------"); System.out.println("Starting iteration " + i); StringBuffer fooBuffer = (StringBuffer) cache.get("foo").getValue(); System.out.println("fooBuffer. = " + fooBuffer.toString()); System.out.println("fooOriginalBuffer = " + fooOriginalBuffer.toString()); System.out.println("cache.getSize() = " + cache.getSize()); System.out.println("----------------------------------"); try { Thread.sleep(1000); } catch (InterruptedException e) { System.out.println("Interrupted"); } } } public static void main(String[] args) throws Exception { ExampleCacheProvider cacheProvider = new ExampleCacheProvider(); Reader reader = new Reader(cacheProvider); reader.run(); } } Let’s run it with both updatingFactory options. Output of running the Reader with ExampleCacheEntryFactory (-Dcom.blogspot.mikler.java.cache.factory=create) !!!!! Doing refresh !!!!! ++++++creating entry for key = foo ---------------------------------- Starting iteration 0 fooBuffer. = 35foo0 fooOriginalBuffer = 35foo0 cache.getSize() = 1 ---------------------------------- ---------------------------------- Starting iteration 1 fooBuffer. = 35foo0 fooOriginalBuffer = 35foo0 cache.getSize() = 1 ---------------------------------- !!!!! Doing refresh !!!!! ++++++creating entry for key = foo ---------------------------------- Starting iteration 2 fooBuffer. = 36foo0 fooOriginalBuffer = 35foo0 cache.getSize() = 1 ---------------------------------- ---------------------------------- Starting iteration 3 fooBuffer. = 36foo0 fooOriginalBuffer = 35foo0 cache.getSize() = 1 ---------------------------------- !!!!! Doing refresh !!!!! ++++++creating entry for key = foo ---------------------------------- Starting iteration 4 fooBuffer. = 51foo0 fooOriginalBuffer = 35foo0 cache.getSize() = 1 ---------------------------------- And here how the output looks like while running Reader with ExampleUpdatingCacheEntryFactory as updatingFactory (-Dcom.blogspot.mikler.java.cache.factory=update) !!!!! Doing refresh !!!!! ++++++creating entry for key = foo ---------------------------------- Starting iteration 0 fooBuffer. = 19foo0 fooOriginalBuffer = 19foo0 cache.getSize() = 1 ---------------------------------- ---------------------------------- Starting iteration 1 fooBuffer. = 19foo0 fooOriginalBuffer = 19foo0 cache.getSize() = 1 ---------------------------------- !!!!! Doing refresh !!!!! ~~~~~~UPDATING entry for key = foo ---------------------------------- Starting iteration 2 fooBuffer. = 19foo06 fooOriginalBuffer = 19foo06 cache.getSize() = 1 ---------------------------------- ---------------------------------- Starting iteration 3 fooBuffer. = 19foo06 fooOriginalBuffer = 19foo06 cache.getSize() = 1 ---------------------------------- !!!!! Doing refresh !!!!! ~~~~~~UPDATING entry for key = foo ---------------------------------- Starting iteration 4 fooBuffer. = 19foo067 fooOriginalBuffer = 19foo067 cache.getSize() = 1 ---------------------------------- Conclusion As you can see the output is quite different and here are some conclusions we come to from analyzing it: No NullPointerException is occurs while trying to get object from cache that is not there. It is being created in both cases. If updatingFactory is instance of CacheEntryFactory (ExampleCacheEntryFactory in our case) when cache.refresh() is called each object in cache is being recreated. Also when updatingFactory is instance of CacheEntryFactory final fooOriginalBuffer variable is not updated. Meanwhile in case when updatingFactory is instance of CacheEntryFactory (UpdatingCacheEntryFactory in our case) when cache.refresh() is called each object in cache gets updated instead of being recreated. And final fooOriginalBuffer variable value is updated as well. (Actually this variable itself is passed to updateEntryValue() method of ExampleUpdatingCacheEntryFactory) Instructions about how to check out the source code for this article you can find in the original post. Originally posted on miklerjava.blogspot.com

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)

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.

We are seeing quite a number of exciting JavaFX demos around, demonstrating the pretty features of the language and the capability of easily integrating cool graphics. But, as a software designer, I can't prevent myself from seeing that in most examples we see bloated code - no good separation of concerns and poor applications of the MVC pattern. This is reasonable, as JavaFX was a new language and people needed first to be taught about the syntax and features; but now that - I presume - many of us have been introduced with the new language, it's high time we started worrying about good practices, as well as writing self-commenting code. Let's remember that good practices and good design are always more important than the language! So, let's introduce a very simple project - a Contact List whose specifications are: We have a list of "contacts", where each item is name, last name, email, phone, etc... The UI shows a list of contacts, that can be filtered by a text field; if you enter a value in it, only the contacts whose name starts with the entered text are shown. Selections are applied as you type. Selecting an item in the list of contacts, the details are shown in a form, where you can edit them. At any selection change, the form is animated (a rotation and a blur effect). You can get the code from: svn co -r 37 https://kenai.com/svn/javafxstuff~svn/trunk/ContactList/src/ContactList The model Let's first have a quick look at the model classes. First a simple value object representing a piece of data: package it.tidalwave.javafxstuff.contactlist.model; public class Contact { public var id: String; public var firstName: String; public var lastName: String; public var phone: String; public var email: String; public var photo: String; override function toString() { return "\{id: {id}, value: {firstName} {lastName}, phone: {phone}, email: {email}" } } Then a small service which provides a bunch of data: package it.tidalwave.javafxstuff.contactlist.model; public abstract class ContactRegistry { public abstract function items() : Contact[]; } In the demo code, you'll find a mock implementation with some wired values; in a real case this could be a Business Delegate encapsulating code for retrieving data remotely. So far, so good - it's pretty normal to keep these things separated from the UI. The Controllers We're not going to see a classic Controller here; actually, we're slightly departing from the "pure" MVC. The code I'm showing you is more a "Presentation Model", a pattern described by Martin Fowler as: The essence of a Presentation Model is of a fully self-contained class that represents all the data and behavior of the UI window, but without any of the controls used to render that UI on the screen. A view then simply projects the state of the presentation model onto the glass. This class is basically an hybrid between a classic model and a controller. It is also a façade between the view and the domain model. package it.tidalwave.javafxstuff.contactlist.model; import it.tidalwave.javafxstuff.contactlist.model.ContactRegistry; import it.tidalwave.javafxstuff.contactlist.model.ContactRegistryMock; public class PresentationModel { public var searchText : String; public var selectedIndex : Integer; // The Business Delegate def contactRegistry = ContactRegistryMock{} as ContactRegistry; def allContacts = bind contactRegistry.items(); // The contacts filtered according the contents of the search field public-read def contacts = bind allContacts[contact | "{contact.firstName} {contact.lastName}".startsWith(searchText)]; // The selected contact; the code also triggers a notification at each change public-read def selectedContact = bind contacts[selectedIndex] on replace previousContact { onSelectedContactChange(); }; // Notifies a change in the current Contact selection public-init var onSelectedContactChange = function() { } } Note the extreme compactness brought by functional programming. There's almost no imperative programming as everything is achieved by properly using the binding feature. The only imperative part is the 'onSelectedContactChange' function, which is just a listener to notify selection changes to some external code - it will be used only for triggering the animation. BTW, I'd like to remove it from here, but I wasn't able to. Maybe it's a JavaFX thing that I've not understood yet, but I'm keeping it for another post. Now, everything about the animation goes encapsulated in a specific class, which only exposes two properties controlling the animation: the effect and the rotation angle. A single play() function is provided to start the animation. package it.tidalwave.javafxstuff.contactlist.view; import javafx.animation.Interpolator; import javafx.animation.Timeline; import javafx.scene.effect.GaussianBlur; public class AnimationController { public-read var rotation = 0; public-read def effect = GaussianBlur{} def timeline = Timeline { repeatCount: 1 keyFrames: [ at(0s) { effect.radius => 20; rotation => 45 } at(300ms) { effect.radius => 0 tween Interpolator.EASEBOTH; rotation => 0 tween Interpolator.EASEBOTH } ] } public function play() { timeline.playFromStart(); } } The Views Now, a UI component. The way we design it largely depends on the process, as a graphic designer could be involved. In any case, I think that the whole UI should not be implemented in a single, bloated class; rather relevant pieces should be split apart. For instance, a CustomNode can model the "form" that renders the contact details (in the code below I've omitted all the attributes related to rendering): package it.tidalwave.javafxstuff.contactlist.view; import javafx.scene.CustomNode; import javafx.scene.Group; import javafx.scene.layout.HBox; import javafx.scene.layout.VBox; import javafx.scene.Node; import javafx.ext.swing.SwingLabel; import javafx.ext.swing.SwingTextField; import it.tidalwave.javafxstuff.contactlist.model.Contact; public class ContactView extends CustomNode { public var contact : Contact; public override function create() : Node { return Group { content: [ VBox { content: [ SwingLabel { text: bind "{contact.firstName} {contact.lastName}" } HBox { content: [ SwingLabel { text: "First name: " } SwingTextField { text: bind contact.firstName } ] } HBox { content: [ SwingLabel { text: "Last name: " } SwingTextField { text: bind contact.lastName } ] } HBox { content: [ SwingLabel { text: "Email: " } SwingTextField { text: bind contact.email } ] } HBox { content: [ SwingLabel { text: "Phone: " } SwingTextField { text: bind contact.phone } ] } ] } ] }; } } As you can see, we have only layout and data binding here, the only things a view should do. Putting all together Now the last piece of code, the Main, which builds up the application (again, I've omitted all attributes only related to rendering): package it.tidalwave.javafxstuff.contactlist.view; import javafx.scene.layout.HBox; import javafx.scene.layout.VBox; import javafx.scene.Scene; import javafx.stage.Stage; import javafx.ext.swing.SwingLabel; import javafx.ext.swing.SwingList; import javafx.ext.swing.SwingListItem; import javafx.ext.swing.SwingTextField; import it.tidalwave.javafxstuff.contactlist.controller.PresentationModel; Stage { def animationController = AnimationController{}; def presentationModel = PresentationModel { onSelectedContactChange : function() { animationController.play(); } }; scene: Scene { content: VBox { content: [ HBox { content: SwingLabel { text: "Contact List" } } HBox { content: [ SwingLabel { text: "Search: " } SwingTextField { text: bind presentationModel.searchText with inverse } ] } HBox { content: [ SwingList { items: bind for (contact in presentationModel.contacts) { SwingListItem { text:"{contact.firstName} {contact.lastName}" } } selectedIndex: bind presentationModel.selectedIndex with inverse } ContactView { contact: bind presentationModel.selectedContact effect: bind animationController.effect rotate: bind animationController.rotation } ] } ] } } } As in the previous code snippets, I think the listing can be easily read and understood. Basically, we are glueing all the pieces together and binding the relevant models. In the end, each class in this small project does a simple, cohese thing: representing data, encapsulating the presentation logic, controlling the animation, rendering the views. Dependencies are reduced to the minimum and they have the correct direction: views depend on the models (and not the opposite) and the AnimationController; the AnimationController is independent. You could replace the view components without affecting the rest of the classes, as well as removing or adding other animations by properly using different AnimationControllers. This good separation of roles and responsibilities is the good way to apply OO. There is a detail which is worth discussing. Note the two bind ... with inverse. They implement the so-called "bidirectional binding" where not only a change in the model (e.g. PresentationModel.selectedIndex) is reflected to attributes in the UI (e.g. SwingList.selectedIndex), but also the opposite happens. Indeed, the reverse binding is more important in our example, because it implements the controller responsibility (it captures user's gestures from the view and changes the model); the direct binding from the PresentationModel to SwingList, instead, is useless, as in our case the PresentationModel is never the originator of a change. So, why not using a simple, direct binding in PresentationModel towards SwingList? Such as: public class PresentationModel { var list : SwingList; public def selectedIndex = bind list.selectedIndex; ... } Because this would introduce a dependency from the model/controller to the view, which is plain wrong. Here, bind ... with inverse not only works as a shortcut for writing less code (that is, explicitly declaring a binding and its inverse), but it's also an essential feature for a better design. As far as I know - but I could be wrong - for example in ActionScript (Adobe Flex language) there's no bidirectional binding (you need to put binding keywords at both ends of the association), thus introducing unneeded or circular dependencies. I believe this is true at least at code level (as far as I understand, there are different ways to do binding in ActionScript).

Not that long ago, there was just ASP.NET. But ASP.NET has expanded to include different approaches to development. Recently, I was chatting with Microsoft’s Scott Hunter and Steve Walther over drinks at DevConnections Orlando and Steve mentioned “the four pillars of ASP.NET.” The four pillars are the four ways you can build web sites with ASP.NET, both today and in the future. The four pillars are: 1. ASP.NET Web Forms. Until recently, this was the only pillar of ASP.NET. Everything was done using the familiar rich server-side controls that many have grown to love (and some have learned to despise which is the seed for the other three pillars). So what’s wrong with Web Forms? Well, many developers believe that ASP.NET Web Forms are too much of a black box with a healthy-dose of black magic. There’s a price you pay for the Web Form event model and lifecycle and that price is control over the exchange of data between server and browser. Some say the Web Form model with its incessant ViewState is a pig. The Web Form model also makes it difficult to create testable applications and practice test-driven development (TDD). On the other hand, ASP.NET AJAX and ASP.NET MVC (pillars 2 and 3, respectively) come with a steep learning curve, and for many developers will take longer to develop the equivalent application. Pillar 4 (Dynamic Data), on the other hand, has limited applicability, IMO. My opinion is that with the possible exception of Dynamic Data for the creation of simpler intranet applications, nothing in my mind beats ASP.NET Web Forms (especially when paired with the ASP.NET AJAX UpdatePanel control) for creating good, solid, and responsive applications that, while not the leanest and meanest of applications nor very testable, are easy to grok and master for the novice through advanced developer. Web forms are also the best match for the developer looking to make the move to ASP.NET from Microsoft desktop (Win Forms or WPF) development. And with each new version, Microsoft is making it easier to tame the pig (ViewState) and reduce its size: ASP.NET 2.0 introduced ControlState and ASP.NET 4.0 changes the inheritance model of ViewState so it will be easier to turn off ViewState by default and only turn it on when needed. 2. ASP.NET AJAX. This pillar came to life with the ASP.NET AJAX Extensions for ASP.NET 2.0 / Visual Studio 2005. ASP.NET AJAX is now integrated into ASP.NET and Visual Studio 2008 and consists of both a set of server-side controls as well as the AJAX client-side libraries. In regards to its existence as a “pillar,” I would argue that Microsoft is really only talking about the client-side of ASP.NET AJAX. The reason I say this is that the Upgrade Panel and other server-side AJAX controls merely extend the Web Form pillar, giving Web Form controls the ability to do asynchronous postbacks. There are many in the hard-core ASP.NET AJAX community that believe that a true AJAX application needs to be built from the ground up without the use of Web Forms and the server-side controls. Using this approach, ASP.NET merely becomes a way to emit HTML with embedded JavaScript (and references to the Microsoft ASP.NET AJAX and JQuery libraries) that calls back to ASP.NET (or WCF) web services. When the HTML and JavaScript hit the browser, that’s when the action begins. The promise of this approach is a much snappier user interface and a much more scalable web site. On the downside, this requires programming in a loosely-typed language with a weird inheritance model, spotty support for IntelliSense, and, while improved, lousy debugger support. Another downside, the lack of smart client-side controls is likely to be remedied in the ASP.NET 4.0 timeframe. Microsoft is busy improving the client-side story, complete with client-side controls, for ASP.NET 4.0 (if you are curious, check out http://asp.net/ajax and click on the “ASP.NET AJAX Preview on CodePlex” link for a peek at what’s coming). Regardless, I believe this pillar will always be for a subset of ASP.NET developers who don’t shun the client-side. 3. ASP.NET MVC. This pillar is the newest to emerge from Microsoft. In fact, as of this writing, it’s only a couple of weeks old, having been released at Mix09. Some ASP.NET curmudgeons would call this a throwback to the days of ASP “classic” spaghetti code, but for many others--especially the alt.net crowd and transplants from Ruby and Java--this represents the cat’s pajamas on the Microsoft web stack. (Of course, it’s amazing how quickly developers find problems in the latest programmer’s paradise--usually before its release--and I’m sure the MVC aficionados are already looking to the next release.) The basic idea behind ASP.NET MVC is to separate out the three concerns of the MVC pattern: the model, view, and controller. The model represents the data model, the view is the user interface that presents the data and interacts with the user, and the controller is the command center that takes inputs from the view, pushes and pulls data into/from the model, and decides what to do next. By separating out these concerns (as purely as possible), you improve the ability to create unit tests for your applications and, at least on some level, improve application maintainability. If you are into test driven development, then this is the pillar to hook your horse to. 4. Dynamic Data. IMO, Dynamic Data is a misnomer. From its name, one would tend to think this is yet another data access technology from Microsoft. It is not. I would have preferred Microsoft to use the name Dynamic Application or Dynamic Application Builder. MSDN Help says, “ASP.NET Dynamic Data is a framework that lets you create data-driven ASP.NET Web applications easily.” You start with Dynamic Data by creating a database and then using either LINQ to SQL or the Entity Framework to create a model over your data. Next, create a new project or web site in Visual Studio 2008 (with SP1) using one of the Dynamic Data Web Application templates, make a fairly simple change to the web site’s Global.asax, and Visual Studio builds a dynamic ASP.NET application over your data model. The resulting site support the creation, retrieval, updating, and deletion (commonly referred to as the CRUD operations) of rows in the underlying database. Dynamic Data uses what is termed dynamic scaffolding to construct your application. This means if you change your data model, the application will be instantly updated: there’s no code that needs to be re-generated. Dynamic Data is customizable. Thus, if you don’t like how Dynamic Data presents a datatype or a particular field, or want to change how it performs validation of a field, you can change the templates behind these. You can also change the master page used as well as a number of other details. Kudos to Microsoft for Dynamic Data--even though I hate the name. Just realize that this pillar, unlike the other three, is only applicable to a subset of ASP.NET applications that fit in well with the Dynamic Data approach to applications: applications, which are primarily data-centric, intranet-based applications. That said I could see many places where I might use Dynamic Data, though I am still trying to work through the security implications of opening up the database for pretty much unrestricted reading and writing of database tables. (For those who would like to see an MVC version of Dynamic Data: I’d expect to see such a beast come down the pike at some point from Microsoft.) Conclusion So what does this mean to the developer? I have both good and bad news. The good news is that you now have a choice in how you develop your ASP.NET applications. If you love the responsiveness and coolness of AJAX or you need to scale your applications big-time, then you’ll love ASP.NET AJAX. If, OTOH, you are into unit tests or TDD, you will love ASP.NET MVC. Finally, if you were looking for an easier way to build you basic CRUD web application, you’ll want to take a look at Dynamic Data. Don’t need any of the above? There’s no need to despair--ASP.NET Web Forms are here for the long haul! The bad news is that you now have a choice in how you develop your ASP.NET applications. (Wait a second, wasn’t that also the good news?)This means you have more things to learn. It also means that in trying to support all four pillars, Microsoft may be taking some of its focus off Web Forms. After all, there’s only so many PMs and devs at Microsoft on the ASP.NET team. Furthermore, this means that if you are a manager like me worried about maintainability of applications and hiring developers, your job just got more difficult because one person’s idea of ASP.NET development is not necessarily someone else’s. Still, I think the good news here, outweighs the bad. Microsoft used to present ASP.NET Web Forms vs. MVC as a choice between a car and a motorcycle. Both will get you to your job , but some (the majority of the population, I might add) prefer driving a car, while a sizable minority love their motorcycles which give you better gas mileage and independence, but don’t protect you in the rain. To stretch this analogy to its breaking point, let me suggest that ASP.NET AJAX is like riding a bicycle to work (lean and mean, best gas mileage, but it requires you to exercise for your commute and exposes you to the elements like the motorcycle) while Dynamic Data is like taking the bus to work (let metro do the driving for you.) What about Silverlight? Silverlight is really just the next generation of a one-click desktop application, that is hosted in the browser and runs on a multi-platform .NET virtual machine. Not to take anything away from Silverlight, but it’s not ASP.NET. Does this mean that ASP.NET Web Forms is going away? Although some people “in the know” have stated in the past couple of years that either ASP.NET AJAX or ASP.NET MVC was the future of ASP.NET, this is not the official position of Microsoft. Think about it, since 98%--yes, this is a total educated guess--of ASP.NET development is still done using ASP.NET Web Forms, and this percentage is unlikely to change significantly over the next several years, Microsoft would be stupid to kill off Web Forms. It doesn’t make any economic sense, and since Microsoft is a for-profit entity, I think Web Forms will be a major thrust of ASP.NET for many years to come. In my opinion, Microsoft has added the three new pillars for the following reasons: · Microsoft is always trying to follow innovation and buzz in the industry. Three years ago, that buzz was in AJAX. Today, MVC, separation of concerns, and TDD is all the rage so Microsoft has countered with ASP.NET MVC. · Microsoft is always trying to broaden the appeal of ASP.NET. Microsoft has been trying to woo the open source community for years (after initially discounting it). And in order to do this, it needs to embrace many of the ideals of this community, which tends to live on the bleeding edge and is into AJAX, testability, and TDD, amongst other things. · Microsoft truly wants to improve the productivity of its customers. After all, if you improve the ability of your customers, in our case corporate and independent developers, to get their jobs done, you’ve gone a long way to attracting and retaining customers. In Microsoft’s eyes (and many of its customers), this is a win, win situation. I, for one, would like to thank Microsoft for the four pillars of ASP.NET. In producing the four pillars, Microsoft has given ASP.NET developers the choices they both want and need.

JSF has a simple Inversion-of-Control (IoC) container called the JSF Managed Bean Facility (MBF). Although it has a verbose XML syntax, and is not as robust as the Spring BeanFactory, PicoContainer, or the JBoss Microcontainer, the MBF does have the basics of an IoC container, and offers features like dependency injection. When a POJO is managed by the JSF MBF, it is typically referred to as a managed-bean. But if you're going to create a maintainable JSF webapp/portlet, it is necessary to distinguish between different kinds of managed-beans. This practice will also preserve the clean separation of concerns that JSF provides by implementing the Model-View-Controller (MVC) design pattern: Managed-Bean Type Nickname Typical Scope Model Managed-Bean model-bean session Description: This type of managed-bean participates in the "Model" concern of the MVC design pattern. When you see the word "model" -- think DATA. A JSF model-bean should be a POJO that follows the JavaBean design pattern with getters/setters encapsulating properties. The most common use case for a model bean is to be a database entity, or to simply represent a set of rows from the result set of a database query. Backing Managed-Bean backing-bean request Description: This type of managed-bean participates in the "View" concern of the MVC design pattern. The purpose of a backing-bean is to support UI logic, and has a 1::1 relationship with a JSF view, or a JSF form in a Facelet composition. Although it typically has JavaBean-style properties with associated getters/setters, these are properties of the View -- not of the underlying application data model. JSF backing-beans may also have JSF actionListener and valueChangeListener methods. Controller Managed-Bean controller-bean request Description: This type of managed-bean participates in the "Controller" concern of the MVC design pattern. The purpose of a controller bean is to execute some kind of business logic and return a navigation outcome to the JSF navigation-handler. JSF controller-beans typically have JSF action methods (and not actionListener methods). Support Managed-Bean support-bean session / application Description: This type of bean "supports" one or more views in the "View" concern of the MVC design pattern. The typical use case is supplying an ArrayList to JSF h:selectOneMenu drop-down lists that appear in more than one JSF view. If the data in the dropdown lists is particular to the user, then the bean would be kept in session scope. However, if the data applies to all users (such as a dropdown lists of provinces), then the bean would be kept in application scope, so that it can be cached for all users. Utility Managed-Bean utility-bean application Description: This type of bean provides some type of "utility" function to one or more JSF views. A good example of this might be a FileUpload bean that can be reused in multiple web applications. Now... One of the main benefits in making fine distinctions like this is loose coupling. What's that you ask? Well let's first take a look at an example of tight coupling, where MVC concerns can be smashed/confused into a single managed-bean: public class ModelAndBackingAndControllerBean { private String fullName; // model-bean property private boolean privacyRendered; // backing-bean property // model-bean getter public String getFullName() { return fullName; } // model-bean setter public void setFullName(String fullName) { this.fullName = fullName; } // backing-bean getter public boolean isPrivacyRendered() { return privacyRendered; } // backing-bean setter public void setPrivacyRendered(boolean privacyRendered) { this.privacyRendered = privacyRendered; } // backing-bean actionListener for UI support logic public void togglePrivacySection(ActionEvent actionEvent) { privacyRendered = !privacyRendered; } // controller-bean business logic public String submit() { System.out.println("fullName=" + fullName); return "success"; } } The problem here is that the bean would have to be kept in session scope because of the model-bean property. Additionally, what if we wanted to do some unit testing with mock model data? Can't do it. So in order to fix these problems, and to promote loose coupling, we would have three separate Java classes: public class ModelBean { private String fullName; public void setFullName(String fullName) { this.fullName = fullName; } public String getFullName() { return fullName; } } public class BackingBean { private boolean privacyRendered; public void setPrivacyRendered(boolean privacyRendered) { this.privacyRendered = privacyRendered; } public boolean isPrivacyRendered() { return privacyRendered; } public void togglePrivacySection(ActionEvent actionEvent) { privacyRendered = !privacyRendered; } } public class ControllerBean { private ModelBean modelBean; public ModelBean getModelBean() { return modelBean; } public void setModelBean(ModelBean modelBean) { // Dependency injected from the JSF managed-bean facility this.modelBean = modelBean; } public String submit() { System.out.println("fullName=" + getModelBean().getFullName()); return "success"; } } Now that the beans are found in different classes, they can all be kept in their appropriate scopes. The model-bean can be kept in session scope, and the backing-bean and controller-bean can be kept in request scope, thus saving memory resources on the server. Finally, we can use the dependency injection features of the JSF MBF in order to inject the model-bean into the controller-bean. This can be seen in the following WEB-INF/faces-config.xml example, where the #{modelBean} Expression Language (EL) binding is used: modelBean myproject.ModelBean session backingBean myproject.BackingBean request controllerBean myproject.ControllerBean request modelBean #{modelBean} From http://blog.icefaces.org/

A few months ago, this article by Andrew Trice inspired me to write a demo application to see how well Pivot would handle very large tabular data sets of up to one million rows (the results are here). Mr. Trice has again inspired me, this time to see how easy it might be to to write a Pivot application that consumes an RSS feed and presents the data in a list view using a custom item renderer. This article describes the results. The Demo Application The following image shows a screen shot of the demo application, which retrieves RSS feed data from Javalobby. A live example is available here (it requires Java 6 Update 10 or later; see notes at bottom of page). The application contains a single ListView component in a ScrollPane that is used to present the news data. A custom list item renderer is used to display the item's title, categories, and submitter. The WTKX source for the demo's UI is as follows: It's pretty straightforward: a root Border component contains a CardPane containing two sub-panes. The first is a status label that is used to provide feedback to the user while the feed is being loaded. The second is a ScrollPane containing the actual list view used to present the feed data. The Java source is a bit more involved. It is broken into two files: one contains the main application class, and the other contains an adapter class that is used to wrap an XML node list such that it can be used as the data model for the list view. The application class contains several inner classes that are used to facilitate loading and presenting the data, as well as opening the articles in an external browser window when the user double-clicks on the list. The Main Application Class The application's constructor is shown below: public RSSFeedDemo() { // Create an XPath instance xpath = XPathFactory.newInstance().newXPath(); // Set the namespace resolver xpath.setNamespaceContext(new NamespaceContext() { public String getNamespaceURI(String prefix) { String namespaceURI; if (prefix.equals("dz")) { namespaceURI = "http://www.developerzone.com/modules/dz/1.0"; } else { namespaceURI = XMLConstants.NULL_NS_URI; } return namespaceURI; } public String getPrefix(String uri) { throw new UnsupportedOperationException(); } public Iterator getPrefixes(String uri) { throw new UnsupportedOperationException(); } }); } Using the newInstance() factory method, it obtains an instance of javax.xml.xpath.XPath that is later used to retrieve element values from the returned data. A namespace resolver is then set on the XPath, allowing it to map the "dz" prefix to the "http://www.developerzone.com/modules/dz/1.0" namespace URI. The startup() method is defined as follows: public void startup(Display display, Dictionary properties) throws Exception { WTKXSerializer wtkxSerializer = new WTKXSerializer(); window = new Window((Component)wtkxSerializer.readObject(getClass().getResource("rss_feed_demo.wtkx"))); feedListView = (ListView)wtkxSerializer.getObjectByName("feedListView"); feedListView.setItemRenderer(new RSSItemRenderer()); feedListView.getComponentMouseButtonListeners().add(new FeedViewMouseButtonHandler()); final CardPane cardPane = (CardPane)wtkxSerializer.getObjectByName("cardPane"); final Label statusLabel = (Label)wtkxSerializer.getObjectByName("statusLabel"); LoadFeedTask loadFeedTask = new LoadFeedTask(); loadFeedTask.execute(new TaskListener() { public void taskExecuted(Task task) { feedListView.setListData(new NodeListAdapter(task.getResult())); cardPane.setSelectedIndex(1); } public void executeFailed(Task task) { statusLabel.setText(task.getFault().toString()); } }); window.setMaximized(true); window.open(display); } It loads the UI from the WTKX file, sets it as the content of a decorationless window, and obtains references to some of the components defined in the file. It assigns an instance of RSSItemRenderer as the item renderer for the list view and attaches an instance of FeedViewMouseButtonHandler as a mouse button listener on the list view (these classes are discussed in more detail below). It then creates an instance of LoadFeedTask, executes the task, and opens the window. LoadFeedTask LoadFeedTask is a private inner class that is used to load the feed data on a background thread so the UI doesn't block while it is being loaded. It is defined as follows: private class LoadFeedTask extends IOTask { public NodeList execute() throws TaskExecutionException { NodeList itemNodeList = null; DocumentBuilderFactory documentBuilderFactory = DocumentBuilderFactory.newInstance(); DocumentBuilder documentBuilder; try { documentBuilder = documentBuilderFactory.newDocumentBuilder(); } catch(ParserConfigurationException exception) { throw new TaskExecutionException(exception); } Document document; try { document = documentBuilder.parse(FEED_URI); } catch(IOException exception) { throw new TaskExecutionException(exception); } catch(SAXException exception) { throw new TaskExecutionException(exception); } try { itemNodeList = (NodeList)xpath.evaluate("/rss/channel/item", document, XPathConstants.NODESET); } catch(XPathExpressionException exception) { // No-op } return itemNodeList; } } The execute() method loads an XML document from the feed URI and then uses the XPath object to obtain a node list containing the item elements, which it returns. Upon successful execution, the taskExecuted() method of the task listener is called. This method wraps the returned node list in an instance of NodeListAdapter, which is used to adapt the contents of the NodeList for consumption by the ListView (the source code for this class is available here). If the load fails, the resulting execption is displayed in the status label. RSSItemRenderer The RSSItemRenderer class prepares the feed data for presentation in the list view. It implements the ListView.ItemRenderer interface and extends a vertical FlowPane, which it uses to arrange Label instances containing each article's title, categories, and submitter (note that, while this implementation creates the flow pane's layout programmatically, it could also have been defined in WTKX): private class RSSItemRenderer extends FlowPane implements ListView.ItemRenderer { private Label titleLabel = new Label(); private Label categoriesHeadingLabel = new Label("subject:"); private Label categoriesLabel = new Label(); private Label submitterHeadingLabel = new Label("submitter:"); private Label submitterLabel = new Label(); public RSSItemRenderer() { super(Orientation.VERTICAL); getStyles().put("padding", new Insets(2, 2, 8, 2)); add(titleLabel); FlowPane categoriesFlowPane = new FlowPane(); add(categoriesFlowPane); categoriesFlowPane.add(categoriesHeadingLabel); categoriesFlowPane.add(categoriesLabel); FlowPane submitterFlowPane = new FlowPane(); add(submitterFlowPane); submitterFlowPane.add(submitterHeadingLabel); submitterFlowPane.add(submitterLabel); } ... The render method obtains the font and color styles from the component and applies them to its internal labels. It then sets the contents of the labels by extracting the element content from the current node. ... public void render(Object item, ListView listView, boolean selected, boolean checked, boolean highlighted, boolean disabled) { // Render styles Font labelFont = (Font)listView.getStyles().get("font"); Font largeFont = labelFont.deriveFont(Font.BOLD, 14); titleLabel.getStyles().put("font", largeFont); categoriesLabel.getStyles().put("font", labelFont); submitterLabel.getStyles().put("font", labelFont); Color color = null; if (listView.isEnabled() && !disabled) { if (selected) { if (listView.isFocused()) { color = (Color)listView.getStyles().get("selectionColor"); } else { color = (Color)listView.getStyles().get("inactiveSelectionColor"); } } else { color = (Color)listView.getStyles().get("color"); } } else { color = (Color)listView.getStyles().get("disabledColor"); } if (color instanceof Color) { titleLabel.getStyles().put("color", color); categoriesHeadingLabel.getStyles().put("color", color); categoriesLabel.getStyles().put("color", color); submitterHeadingLabel.getStyles().put("color", color); submitterLabel.getStyles().put("color", color); } // Render data if (item != null) { Element itemElement = (Element)item; try { String title = (String)xpath.evaluate("title", itemElement, XPathConstants.STRING); titleLabel.setText(title); String categories = ""; NodeList categoryNodeList = (NodeList)xpath.evaluate("category", itemElement, XPathConstants.NODESET); for (int j = 0; j < categoryNodeList.getLength(); j++) { Element categoryElement = (Element)categoryNodeList.item(j); String category = categoryElement.getTextContent(); if (j > 0) { categories += ", "; } categories += category; } categoriesLabel.setText(categories); String submitter = (String)xpath.evaluate("dz:submitter/dz:username", itemElement, XPathConstants.STRING); submitterLabel.setText(submitter); } catch(XPathExpressionException exception) { System.err.println(exception); } } } } FeedViewMouseButtonHandler The FeedViewMouseButtonHandler class handles double-clicks on the list view. Clicking the list view once stores the index that was clicked (in case the user moves the mouse before a double-click occurs), and the selected item is opened on the double-click: private class FeedViewMouseButtonHandler extends ComponentMouseButtonListener.Adapter { private int index = -1; @Override public boolean mouseClick(Component component, Mouse.Button button, int x, int y, int count) { if (count == 1) { index = feedListView.getItemAt(y); } else if (count == 2 && feedListView.getItemAt(y) == index) { Element itemElement = (Element)feedListView.getListData().get(index); try { String link = (String)xpath.evaluate("link", itemElement, XPathConstants.STRING); BrowserApplicationContext.open(new URL(link)); } catch(XPathExpressionException exception) { System.err.print(exception); } catch(MalformedURLException exception) { System.err.print(exception); } } return false; } }; Summary So, building an RSS reader in Pivot was fairly straightforward. The XPath APIs included in the Java platform are very efficient for retrieving and parsing the feed data, and Pivot makes it easy to wrap the returned XML data in a list model and customize it's presentation in the list view. However, one important lesson learned is that that Java's XML factory methods don't play nicely with applets. They rely on the JAR service provider architecture and will repeatedly look for service descriptor files on the applet's classpath, resulting in many unnecessary requests to the web server. The only way to prevent this is to set the codebase_lookup applet parameter to false: This works, but it is an ugly workaround - there are certainly valid use cases for using both codebase lookup and XML parsing in an applet; for example, an applet that parses XML that is dynamically generated from a servlet on the applet's classpath. Hopefully Sun (or Oracle) will address this issue in a future JVM update. Also note that this demo takes advantage of Java 6 Update 10's new support for crossdomain.xml files. This handy feature allows an unsigned applet to make a network connection to a server outside of its origin, provided it was loaded from an approved URL. See this article for more information. The full source code for the demo is available here. For more information on Apache Pivot, visit http://incubator.apache.org/pivot.

GraphMLViewer is a freely available, Flash®-based, interactive viewer which displays diagrams, networks, and other graph-like structures in HTML web pages. It is optimized for diagrams created with the also freely available yEd graph editor and the yFiles Java diagramming library. Features of the GraphMLViewer include: Viewer application for diagrams in GraphML format: GraphMLViewer is created to display diagrams which are saved in GraphML format. GraphML is the XML-standard for saving graph-like diagrams. The viewer is optimized for diagrams which were created with the freely available yEd graph editor. Users can freely move and resize the displayed diagram A small, interactive overview of the diagram can be displayed. The current diagram can be printed. Descriptions which are added to graph elements in yEd can be displayed as tooltips. Users can navigate to URLs that can be added to graph elements in yEd via mouse click. Most of these features can be configured via parameters in the embedding HTML. This enables web authors to adapt the viewer to their requirements. The freely available yEd graph editor offers the option to export all needed files with a simple mouse click (export as "HTML Flash Viewer;" since version 3.2). GraphMLViewer makes use of the yFiles FLEX Actionscript library. This is a Flex® library that allows to integrate the viewing, editing, and animation of a wide range of diagrams, networks, and other graph-like structures into rich internet applications based on Adobe® Flex® or AIR™. For more information, please see the GraphMLViewer home page which provides more details on the features of the GraphMLViewer and explains howthe viewer can be embedded into web pages. About yWorks yWorks specializes in professional software solutions for the visualization of diagrams and graphs. Our yFiles product family offers high-quality diagramming for Java and .NET applications as well as for browser applications based on Adobe® Flex™ or AJAX technology. The extensive yFiles Java class library and the .NET class libraries yFiles.NET and yFiles WPF deliver state-of-the-art component technology which can easily be integrated into Java applications, servlets, and applets, and Windows Forms, ASP.NET, and Windows Presentation Foundation (WPF) applications, respectively. Our web products yFiles FLEX and yFiles AJAX are a perfect fit for web-based diagramming applications that use state-of-the art web technologies.

Each day this week will feature a new article with an in-depth look at the creation process behind setting up a Java project and implementing the frontend with Apache Wicket. Wicket is a Java web application framework which allows “Designers” (people good with Dreamweaver) and “Developers” (people good with Java and Databases) to collaborate on a project with minimal chances of stepping on each other’s toes or wearing each other’s hats. The beauty of Wicket is that it uses plain xhtml pages as it’s templating markup. This means that html pages can be loaded into Dreamweaver (or whatever tool the Designer is comfortable with) and they will look very close to the same as they would when rendered on the deployment web server. Workflow The basic workflow involved in creating and maintaining html rendered by Wicket is as follows: The Designer creates the html for the website and fleshes it out with “mock” sections. For instance in the application we intend to create during our Five Days of Wicket will be a pastebin application called “Mystic Paste”. In our application we’ll have an “Add Code to Mystic Paste” page, mock data might include some user created content in the textarea of the page. All css/images, etc… are setup such that if they were to be put on a webserver, everything would work. The Developer needs to flesh out the dynamic areas of the webpage, that is, he needs to instruct Wicket where it will need to show information from the server. The developer does this by decorating the designer’s html page with special Wicket tags and attributes. Because these tags and attributes are just considered part of another namespace separate from xhtml’s, editors like Dreamweaver and browsers will simply ignore them - It is important to note: The developer will still keep the “mocked” sections of the page intact, this is so the page renders and looks fleshed out on its own. The mocked sections will be replaced by real data when rendered by Wicket. The Developer hands the file back to the Designer. The Designer is free to make further edits, so long as he/she does not remove or manipulate the Wicket tags and attributes present in the file. If the Designer does need to remove any Wicket tags or attributes, they need to consult the Developer as such an action will “break” the webpage when Wicket renders it. Example Wicket Page Here is an example of a Wicket page. This example was taken from Manning Publishing’s book “Wicket in Action”: ... Gouda Gouda is a Dutch... $1.99 add to cart Emmental Emmental is a Swiss che... $2.99 add to cart ... This looks almost 100% like a normal webpage would look, the only difference is the addition of the “wicket:XXX” attributes and tags sprinkled through the document. The parts of the document using the special Wicket namespace modifiers will be replaced/removed in the final markup when Wicket renders the page to the user’s browser. Notice the “” element? This is where your designer can put a “mocked” version of what that area of the page should look like. You as a developer can take that mocked html and divide it out into a template that is dynamically driven from the backend. Here is how the final page looks if you were to simply load the page into a web browser (or Dreamweaver) from your hard drive: Preparing for Setup Deviating a bit from the Standard Wicket Convention One of the first things a developer notices when starting out with Wicket is the convention where Wicket likes having its html template files live at the same level and in the same packages as it’s Java source files. Sure you can jump through hoops to get Wicket to load the html template files from elsewhere but a nice compromise is to simply keep your html template files within the same package directory structure but in a source folder separate from the Java classes. Why? Well quite simply to keep your designers (Dreamweaver folks!) from having to grab Java source files along with the html files they are working on. It will just confuse them and clutter their directories. You can of course stick with the typical “Java source files along side html” convention if you wish, but I find it much cleaner to separate them during design time, and have Maven combine them only at build time into the target war (which it will gladly do automagically). Project Folder Structure . |-- pom.xml |-- src | `-- main | |-- filters | |-- java | | `-- com | | `-- mysticcoders | | `-- mysticpaste | | |-- model | | |-- persistence | | | |-- exception | | | |-- hibernate | | |-- services | | `-- web | | |-- ajax | | |-- pages | | |-- panels | | `-- servlet | |-- resources | | |-- com | | | `-- mysticcoders | | | `-- mysticpaste | | | |-- spring | | | `-- web | | | |-- ajax | | | |-- pages | | | `-- panels | | `-- log4j.properties | |-- sql | `-- webapp | |-- WEB-INF | |-- images | |-- js | `-- css src/main: maven builds source and resources from this directory to the main deployable target (i.e. our war file) filters: we keep a set of “filters” files that maven can use to interpolate variables at build time. What does this mean? It means that inside your configuration files, the files you use to setup database connections or file paths, you can insert variable place holders like ${db.host}. When maven does a build, it looks up the correct filter file to use and looks for the key=value part corresponding to “db.host” and inserts it into the configuration file for you. This ensures that you are able to configure your application per environment you deploy to (i.e. DEV, QA, PROD, etc…) by having different filter files with the same keys but different values. For more information see Maven’s documentation on filtering resource. java/*: this folder will contain all of the application’s source code. Everything from the database access code, wicket code and services code for the mysticpaste application (see below). model: all “domain” classes, that is, classes that represent the objects in the application. For mysticpaste you’ll see classes like “PasteItem” which represents an item pasted to the mysticpaste. persistence: at this level of the persistence package a list of interfaces will be kept. The interfaces comprise the basic access layer the services layer will use to save, retrieve and update items to/from the paste bin. exception: the peristence layer needs to tell the services layer when things have gone wrong. It does this via delcaring and throwing exceptions. hibernate: such is our case, our persistence interfaces will be implemented via the ORM known as Hibernate. This package will store all of the custom hibernate implementations and hibernate specific classes services: The services layer will be stored here. Both the generic interfaces and their implementation classes. The persistence layer will be injected via spring. web: this folder is where our Wicket classes will reside and it’s split into several category packages which are as follows: ajax: mysticpaste uses Ajax to render portions of its UI. The wicket classes which render the xml/html to be injected dynamically into the page are stored here. pages: standard Wicket page classes which are used throughout the application are stored here panels: reusable panel classes are stored here. Panels may be included within Wicket pages for sake of templating servlet: any run of the mill servlet code we need is stored here. A good example might be an ImageUploadServlet resources/*: the resources folder will hold our non-java based files. Noteably html files and spring confguration files spring: Holds any spring configuration files needed to wire the services and persistence layer web: this folder and all subfolders mirror the packages under src/main/java/…/web and hold the .html files that the Wicket page/panel classes use as their templates. As described above, a “standard” wicket application simply stores the .html files along side their Wicket classes under src/main/java/…/web, however we want to keep these files separate from the Java source so as to keep the directory our designers checkout from version control contianing only the files they need to work on. sql: any sql scripts we need to keep handy for building the mysticpaste database. webapp: this folder will keep the files which live at the base directory of our war file WEB-INF: where you keep your web.xml file images: any image resource, .gif/.png/.jpg files your webapp will reference js: javascript files your webapp will reference css: style sheets your webapp uses src/test/*: All files which reside under this folder are test classes and resources needed to support the tests. Maven will build everything under src/main/java and add it to the class path of the JUnit or TestNG classes you create. java: JUnit or TestNG test classes which will be run during a build resources: resource files which are needed to support the tests Getting Started Since we are using Maven as our build tool we can take advantage of the fact that the fine folks at the Wicket project have created a specialized “archetype“ which creates a skeleton web application complete with a folder structure which mimics roughly what we have outlined above and Maven pom.xml file used to build a war. The Wicket contributors have even gone one step further and have created a little web page which will, based off a few drop down options, generate the maven command you need to execute in order to create the boiler plate Wicket project. You can find this web page over on the Apache Wicket site under the “Quick Start” link. Copying the above Maven command creates a Skeleton Wicket Project To be precise, the command I used was: mvn archetype:create -DarchetypeGroupId=org.apache.wicket -DarchetypeArtifactId=wicket-archetype-quickstart -DarchetypeVersion=1.3.5 -DgroupId=com.mysticcoders -DartifactId=mysticpaste And I ended up with the following folder structure: . `-- mysticpaste |-- pom.xml `-- src |-- main | |-- java | | `-- com | | `-- mysticcoders | | |-- HomePage.html | | |-- HomePage.java | | `-- WicketApplication.java | |-- resources | | `-- log4j.properties | `-- webapp | `-- WEB-INF | `-- web.xml `-- test `-- java `-- com `-- mysticcoders |-- Start.java `-- TestHomePage.java Now obviously we’ll have to rearrange a few things, for instance I want my base package to be com.mysticcoders.mysticpaste, but that’s easy enough to do once we are in an IDE. For now, let’s test this example webapp out and see if it works. To do that switch into the mysticpaste directory (the directory that has pom.xml in it) and type the following: mvn jetty:run This will start up a Jetty webapp container running on port 8080 (if you have something running there already, use the -Djetty.port= option). Startup a webbrowser and navigate to http://localhost:8080/mysticpaste/ You should see: Your IDE Sooner or later you’re going to want to crack open your IDE and start hacking away. Maven makes this extremely easy by allowing you to create IDE specific project files based off of the Maven pom.xml file. Eclipse mvn eclipse:eclipse For eclipse you’ll also have to set the M2_REPO classpath variable for the workspace your project resides under. Do this by entering the following command: mvn -Declipse.workspace= eclipse:add-maven-repo IntelliJ IDEA mvn idea:idea -OR- in IDEA 7+ simply open the pom.xml file Netbeans Netbeans supports maven out of the box, just “Open Project” and choose the mysticpaste directory that contains the pom.xml file When generating the project files through Maven, the project is setup such that classpath entries point to your local Maven repository (i.e. ~/.m2/repository, or C:Documents and Settingsyourusername.M2repository on Windows). It also sets up src/main/java, src/main/resources as “source folders”. You may add other folders to the source folder list as per your IDE if needed, the only thing you have to remember is if you ever use mvn eclipse:clean followed by mvn eclipse:eclipse again, those other source folders will have to be readded through your IDE. Instead, you should add the source/resource folders directly to your pom.xml, this way they will be maintained. Spring The Mystic Paste application will use Spring, and really you should too. Unless you have been hiding under a rock or work in a corporate environment so lame as to which technologies newer than 2002 are forbidden you should learn to accept Spring as a defacto standard. Dependency injection for the win! We add the following to our pom.xml: org.apache.wicket wicket-spring-annot org.springframework spring org.springframework spring-test org.springframework spring-tx wicket-spring-annot: allows us to wire our Wicket application via handy dependency injection annotations (i.e. @SpringBean, see Wicket documentation for more detail) spring: is just the core spring libraries spring-test: is a set of Spring integration classes for Unit testing spring-tx: is the Spring Transaction Management api for declarative transactions web.xml additions for Spring In order for Spring to manage our Wicket application we need to setup the Wicket filter with a Spring-aware application factory. This allows us to wire our Wicket Application class in our applicationContext.xml file, which is really handy if you have a services and configuration settings you want to inject into the Wicket Application object so the rest of your application can access them. To do this, we change the original Wicket filter like so: wicket.mysticpaste org.apache.wicket.protocol.http.WicketFilter applicationFactoryClassName org.apache.wicket.spring.SpringWebApplicationFactory As well, we want our Spring context to be available to our webapp if ever there is a need for one of our pages to access the Spring managed beans directly: contextConfigLocation classpath:com/mysticcoders/mysticpaste/spring/applicationContext.xml org.springframework.web.context.ContextLoaderListener Hibernate Hibernate is our ORM of choice, it will allow us to persist and retrieve our model objects to and from the underlying database, whatever that database may be. We add the following to our pom.xml: org.hibernate hibernate-annotations c3p0 c3p0 commons-dbcp commons-dbcp javax.transaction jta 1.0.1B hibernate-annotations: used so we can annotate our model classes with mapping information, instead of having to create a separate mysticpaste.hbm.xml file. c3p0: provides a connection pooling library Hibernate can use commons-dbcp: another connection pooling library, we’ll add it as well and decide whether to use it or c3p0 later jta: this is the Java Transaction API which is needed by Hibernate (Hibernate provides an implementation of the API) web.xml additions for Hibernate To have a Hibernate Session open and ready for our webapplication during a Request Cycle we need to setup a Hibernate filter like so (otherwise, good luck getting lazy loading working!): open.hibernate.session.in.view org.springframework.orm.hibernate3.support.OpenSessionInViewFilter open.hibernate.session.in.view /* As the comment states above, make sure this filter-mapping exists *before* your wicket.mysticpaste filter or else it just plain won’t work. Database For the Mystic Paste we decided to use the freely available PostgreSQL. Adding support for PostgreSQL is very easy, unlike with some of the commercial DBMSes where you have to download and install their JDBC driver into your repository. To add support for Postgres, we simply add the following to our pom.xml: postgresql postgresql Servlets Regardless of which webapplication framework you choose there are just some times when a plain jane Servlet comes in really handy. If you have a need for Servlets and the Servlet must have access to the Wicket session add the following to your web.xml: wicket.session org.apache.wicket.protocol.http.servlet.WicketSessionFilter filterName wicket.mysticpaste And then, after your other filter-mappings add the following (assuming you mount your servlet-mappings under /servlet/): wicket.session /servlet/* Maven Filters and Profiles In order to build our Mystic Paste project for various environments (DEV/QA/PROD) we need to implement both Maven profiles and filters. Filters Filters allow you to place variables inside your configuration files and have those variables filled in durring build time. This is very handy for setting environment specific things such as database connection information. Enabling filters is quite easy, we open up the pom.xml file and find the section for and set the value for the element to true as follows: true src/main/resources . . . But for filtering to work, we need to specify a filters file. It’s not enough to specify only one filter file because we need to specify different filters per environment and we’ll do that by using Maven Profiles. Profiles To setup a profile, create a new set of elements following the section in your pom.xml file. Like so: DEV DEV DEV QA QA PROD PROD and just above your tag underneith your tag you would add the following elements: mysticpaste src/main/filters/filters-${env}.properties true src/main/resources src/main/filters will contain the following files. |-- pom.xml |-- src | `-- main | |-- filters | | `-- filters-DEV.properties | | `-- filters-QA.properties | | `-- filters-PROD.properties filters-DEV.properties jdbc.url=jdbc:postgresql://localhost:5432/mysticpaste jdbc.user=mysticpaste jdbc.password=password image.upload.path=/tmp/pasetbin/userimages image.upload.size.limit=4096K filters-PROD.properties jdbc.url=jdbc:postgresql://192.168.2.10:5432/mysticpaste jdbc.user=mysticpaste jdbc.password=CrYp71c image.upload.path=/mysticpaste/userimages image.upload.size.limit=4096K Now within any file under src/main/resources that has variables of the form ${variable.name} will have those variables replaced with the values specified in the proper filters file located under src/main/filters. For instance here is an example of a Spring applicationContext.xml file which will be interpolated with proper variables values at build time: applicationContext.xml To determine which filters file will be used depends on the profile chosen when building. For example, to build to production using the filters-PROD.properties we would execute the following: mvn clean deploy -P PROD The profile you use with the -P switch must match one of the values of the element for a profile. Conclusion Although it’s quite easy to get started with the Maven QuickStart project it is sometimes a bit frustrating putting some of the additonal pieces together. Building to several environments, setting up depenencies not included in the QuickStart project and strucuturing your project in an effort to make life easy for yourself as a developer and for your designer. I hope our Day 1 tutorial leaves you with a good sense of how a Wicket project is setup, now we can move onto coding the app! In the next four days we will be covering: Writing the Tests Designing the backend Designing the Wicket components Putting it all together Mystic Coders, LLC has been coding web magic since 2000. Mystic is a full-service Development Agency specializing in Enterprise development with Java. They are usually involved in developing enterprise-grade software for companies large and small, and have experience working in diverse industries, including b2b, b2c, and government-based projects. Mystic has done work with large companies such as LeapFrog, Nestlé, Harrah's Entertainment and the Los Angeles Conventions & Visitor's Bureau, among others. Andrew Lombardi, CTO of Mystic, is available for speaking engagements. For more about Mystic, check us out at http://www.mysticcoders.com

Numerous times in your projects you might have to face a situation where you need to pull chunks of data dynamically. The obvious issue that you then face is pagination\sorting and filtering. You then start to think if it would be better to handle it all at the server side or should hold back and handle it on the client side. Well there is no clear winner amongst the two; neither there is a right or wrong approach. The right answer depends on your priorities and the size of the data set to be paginated. If you have large number of pages doing it on client side will make your user download all the data at first which might not be needed, and will defeat the primary benefit of pagination. In such a scenario you are better of requesting pages in chunks from the server via AJAX. So let the server do the pagination. You can also pre-fetch the next few pages the user will likely view to make the interface seem more responsive. However, when implementing it, you need to make sure that you’re optimizing your SQL properly. For instance, I believe in MySQL, if you use the LIMIT option it doesn’t use the index so you need to rewrite your SQL to use the index properly. If there are only few pages, grabbing it all up-front and paginating on the client may be a better choice. That gives you the obvious benefit of faster subsequent page loads. Unless really required we should not choose the Server side pagination in such a case. Server side pagination is better for: Large data set Faster initial page load Accessibility for those not running JavaScript Complex view business logic Resilience to concurrent changes Client side pagination is better for: Small data set Faster subsequent page loads Sort & filter requirements supported fully (unless results greater than max size). To sum up, if you’re paginating for primarily cosmetic reasons, it makes more sense to handle it client side. And if you’re paginating to reduce initial load time, server side is the obvious choice. Of course, client side’s advantage on subsequent page load times diminishes if you utilize Ajax to load subsequent pages. for more information click here Comments\suggestions are welcome.

Recently, I wanted to be able to clear out all of the Hibernate caches via JBoss's JMX console. I could have taken the easy way out; we're using EHCache, so it could have been as simple as calling CacheManager.clearAll(). However, that would have tied me to a specific cache provider. We're still evaluating switching to other cache providers. Ideally, my solution would not be dependent on a specific cache implementation. Hibernate's API does provide a simple way to clear specific caches, but does not provide any method for clearing out all of them. Writing your own is fairly straightforward. First, you obtain all of the entity and collection metadata from the session factory. Next you iterate over the entities, and if the object is cached, you clear out all of the caches associated with the persisted class or collection. Here's the code: @PersistenceContext private EntityManager em; public void clearHibernateCache() { Session s = (Session)em.getDelegate(); SessionFactory sf = s.getSessionFactory(); Map classMetadata = sf.getAllClassMetadata(); for (EntityPersister ep : classMetadata.values()) { if (ep.hasCache()) { sf.evictEntity(ep.getCache().getRegionName()); } } Map collMetadata = sf.getAllCollectionMetadata(); for (AbstractCollectionPersister acp : collMetadata.values()) { if (acp.hasCache()) { sf.evictCollection(acp.getCache().getRegionName()); } } return; } Now, if we decide to switch to a different cache provider, this code will not need to be re-written. Hopefully we won't ever change to a different JPA implementaion. :) From http://mikedesjardins.us/blog/

This article introduces a presentation-tier JEE framework designed to enable the hover-over-help feature without hard coding JavaScript modules in the JSPs in your web or portal applications. The framework is packaged as a jar file for distribution and includes a server-side RESTful web service component and a set of JSP tag handlers which inserts JavaScript and Cascading Style Sheet (CSS) code into HTML files at the page rendering phrase. The targeted users are java developers who only have preliminary experience on writing JavaScript code. 1. Introduction Mouseover is a standard JavaScript event that is raised when the user hovers the cursor over a particular HTML element on a web page. This event has been widely used in web applications for navigation or causing an image or text to change. Hover-over-help, also called hover-over bubble, refers to the process of showing a small popup window when a mouseover event occurs in the browser. The window contains a message to either help the user to use the application or provide additional explanation and data. It is a useful feature which can make your web pages more intuitive and user-friendly and can carry more information on a single page in rich internet applications (RIAs). There are some tips and samples to enable the feature on the internet. However, they are not effective in developing large-scale web applications. Some of caveats include the following: The message contents are directly hard-coded in JavaScript. They are tied-coupled with graphic user interface components, such as text labels in web pages. The re-usability is low. If the same message needs to appear on several pages, the message and the pertaining JavaScript code have to be copied and pasted to each of these pages. It is hard to maintain these duplications in multiple places. The messages are designed to be static and are typically created when the page is designed. It is difficult to insert runtime data into messages on the fly. Portal applications are not completely supported. The framework introduced in this article is designed to address these issues and provides a comprehensive but easy-to-use solution to java developers who don’t have extensive JavaScript experiences. It leverages the JSP taglibary technology, the Dojo framework, and RESTful web services. Reusability in both web and portal environments, performance, and reliability are the factors that have been taken into consideration. 2. Message bubbles and messages 2.1 Message bubbles A message bubble is a rectangle information window containing a message. Each bubble has one color-coded title compartment and one content compartment. The window is decorated by CSS definitions. The image below illustrates a sample message bubble. Figure 1 – a hover-over-help message bubble Bubbles are not viewable in the webpage until the user moves his/her mouse over action labels or images. In this case, the mouse cursor will turn into a finger-pointing hand and the pertaining bubble window will pop up near the hand. 2.2 Data structure The message contents vary from static to dynamic considerably. However, all messages can share a common data structure, which typically consists of four parts: • Message ID: This is the primary key in each message, which is represented as a unique number. Given any single message ID, the framework is able to identify one and only one message. • Message title: This is a character string displayed in the title compartment in a bubble window. • Message content: This is character string that refers to the detail of a help message. The message content can contain HTML elements. • Color code: This is a character string representing the background color scheme of a bubble window. The value must be one of the following strings: “infor”, “data”, “warning”, or “link”. 2.3 Message types Based on the dynamicity of the contents, we categorized all messages into three types. Each of the types is described in this section, with samples provided. 2.3.1 Static Messages This type of message is considered static because its contents always retain the same. A static message can be the definition of a concept, the explanation of a field, or the instruction of a user action. The same messages will appear to any user on the same page when the page is visited. Valid examples include: • This is a example of a static message. • Click on the button below to submit your request. 2.3.2 Variable Messages These messages contain replaceable variables which are represented by tokens. A token is a non-whitespace character string surrounded by “${” and “}”. The token will be completely replaced by its actual value at the page rendering time on the server. The value is based on user data, and normally will not change for a longer-than-user-session period. From users’ perspectives, the same user will see the same message with his customized values when browsing the same page, but different users may see different messages. The following are examples of valid messages in this category: • Your first name ${firstname}. • Your annual goal is to sell ${yourgoalnumber} cars. 2.3.3 Dynamic Messages The messages in this category are the most dynamic ones and contain variables represented by tokens, as well. However, the actual values are populated based on the data associated to the user session. If it happens that a user session is shared by multiple applications, these values may be changed even without a page refresh. This situation typically occurs in portal applications where multiple portlets can access the same user session. It is possible that the same user will read different messages at a different time on the same page. The examples are – • You have talked to ${anumber} clients today. • It is ${servertimestamp} now. 3. Design and implementation In the design, messages are cached at server-side to gain the maximum performance. Two strategies have been implemented to support the hover-over-help feature for each of the message types described in the previous section. 3.1 Message caching Messages can be persisted in a database or flat text file, but regardless of where they are physically stored, they will be loaded and cached at the web container when it starts. The framework includes a class – CacheIntializer which implements the ServerContextListener interface to perform the job. All you need to develop is your own message loader class to retrieve your messages from storage. Your class must implement the com.myuan.tags.bubblemsg.serverside.MessageLoader interface in the framework, and its name must be added as a ContextParameter in the web descriptor. Please refer to the installation section for more details. 3.2 Dojo and CSS Strategy This strategy is designed to support static and variable messages. It can be referred as the push strategy, since help messages are embedded as html elements and pushed to users’ browsers along with the whole web page. No client-server communication is needed once the page download is done. The values will be kept the same until the page is re-loaded again. This strategy relies on a Dojo module to recognize particular “span” elements (listed in list 1) in html files. For each individual message bubble, two span elements are required. The first one represents a visible graphical component in a page, while the second one is the message bubble which isn’t visible for most of the time. When you move the mouse over the first “span” area, an action will be triggered by the browser, and a Dojo method will make the message bubble popped up (illustrated in Figure 1). The “id” attribute in the first “span” element and the “connectid” attribute in the second one are the keys to tie the pair together. These two attributes must have the same value. The value is randomly generated by the custom tags in the framework, which guarantees that the strategy can support both web and portal applications. Households Household A household includes all the persons who occupy a housing unit. Four tag handlers have been developed to support static message and variable message scenarios, respectively. At page-rendering time, the handlers can retrieve help messages from the cache, replace variable tokens in the messages if any, and create and insert value-matched “span” html elements into the web pages. The complete process is detailed in the sequence diagram in figure 2. Figure 2 – sequence diagram for the Dojo and CSS strategy 3.2.1 hohcsstag This tag inserts CSS definitions in JSP pages at the rendering time. It should be placed in the page head element. In the WebSphere Portal environment, this tag should be added in the Default.jsp file. 3.2.2 hohstatictag hohstatictag is a custom tag built for the static message scenario. It has five attributes: msgid: This is the primary key used to identify a message from the cache. This attribute is mandatory. label: This is the text which will be associated with a mouse-over action to display the message. style: This is the style definition that will be used to decorate the label above. This is the place where the user could overwrite CSS arributes for the label. bubblestyle: This is the place where the user could overwrite CSS attributes for the message bubble. img: If you need to enable the hover-over on an image instead of a text label, you can use this attribute and pass the path to your image. If this attribute appears in the tag, the value in the “label” and the “style” attributes will be ignored. A static message example -- Msg_id Msg_title Msg_content Color_cd 1 Household A household includes all the persons who occupy a housing unit. Infor JSP Fragment where the hohstatictag is used – //text //image 3.2.3 hohvariabletag and hohparamtag hohvariabletag and hohparamtag work together to support variable messages. The “hohvariabletag” has the same four attributes as the “hohstatictag” tag. One “hohparamtag” tag holds one name-value pair. The tokens in the message will be replaced with the values passed in from the hohparamtag when html elements are generated. The following is an example of how to use the custom tag. A variable message example-- Msg_id Msg_title Msg_content Color_cd 2 Recognition My retention rate is ${rate} and my goal is ${goal}. data JSP Fragment where the hohvariabletag and hohparamtag are used together – 3.2.4 hohgenerictag This tag has been created to provide a unified API for both static and variable messages. This tag can replace the “hohstatictag” or “hohvariabletag” without any syntax change. But there will be a minor performance cost if you use this tag on the static-message scenario instead of the hohstatictag. 3.3 AJAX strategy AJAX (Asynchronous JavaScript and XML) is a powerful web development technique in creating interactive web applications. The AJAX strategy was developed for the dynamic message scenario. It is a pull-based model, since messages are retrieved by an AJAX module at runtime from the server. This approach can guarantee that the message contains the latest data. When a mouseover event is triggered from a web page, the AJAX module invokes the server-side RESTful web service endpoint. The server-side component picks up the correct message from the message cache, replaces all variable tokens in it with the most current user-session data, and sends the final message back to your browser in the XML format. Upon receiving the response, the AJAX module populates the pertaining information window and pops it up. The complete process is illustrated in the sequence diagram in figure 3. Figure 3 – Sequence diagram for the AJAX strategy One servlet class and three custom tags have been created to support this strategy, and they must be used together in the same page. 3.3.1 HelpMessagesServiceServlet This is an extension of the HTTPSerlvet class. It serves as the RESTful web service endpoint at the server-side. It processes the HTTP request from the client-side AJAX module, constructs the message with the latest data in user’s session, and sends the response in XML format back to the browser. A sample response is listed below. Household infor Household A household includes all the persons who occupy a housing unit. 3.3.2 hohajaxtag This tag inserts AJAX methods in a JSP which will be invoked by the hohdynatag below. It has two attributes. The namespace can be used to pass a portlet’s namespace into the tag in the portal environment. In a web application the value of the attribute can be left blank. The serviceurl attribute must be the valid URL for the HelpMessagesServiceServlet. In the WebSphere Portal environment, this tag should be added in the Default.jsp file. // Portal environment // Web environment 3.3.3 hohdynatag and hohdynaparamtag The hohdynatag has four attributes as same as the “hohstatictag” tag, and it will generate a “span” element. Each hohdynaparamtag establishes a mapping between one token in the message and one key used in user’s session to refer to the actual value. These mappings will be sent to the RESTful endpoint as HTTP parameters. When a user’s mouse moves over the area in a page represented by the span tag, the following events will occur sequentially at the client’s browser: • OnMouseOver events will be fired by the browser. • The Ajax method generated by the hohajaxtag will be invoked. The method will make an HTTP request to the RESTful service endpoint and will be waiting for the response. • Upon receiving the response, the AJAX method will parse it to get the actual help message. • The AJAX method will display the message bubble in the browser. Below is a valid utilization of these tags. 4. Installation The installation procedure is fairly straight forward. After adding the jar file – MYTagLib.jar -- into the /WEB-INF/lib directory in your web project, you can use the deployment descriptor editor in RAD/RSA to complete the installation: Develop your own message loader class and add a context parameter with the name “BubbleMsgLoaderClass” and the value as the fully qualified name of your class. Figure 4 – adding your class name as a Server Context Parameter Create a listener. The class name is: com.myuan.tags.bubblemsg.serverside.CacheInitializer, and the class is shipped in the TagLib.jar file. Figure 5 – creating the listener with the shipped class Add the servlet class in the framework into the deployment descriptor in your web project. The servlet class is also shipped in the MYTagLib.jar. Figure 6 – creating a servlet with the shipped class Define the taglib element in the /WEB-INF/web.xml file. Figure 7 – adding the tag lib references Define the tag extension in your JSP pages. The and the uri directive must match. The prefix identifies the tags in the tag library within the jsp page. For example: 5 Conclusion The framework packaged in the MYTagLib.jar can enable the hover-over-help feature in a web or portal application without adding any JavaScript/CSS code into JSP pages during the development phrase. This approach can make it simpler to create and maintain these pages. The framework has been tested in web applications running on WebSphere Application Server (WAS) 6.0 and 6.1, as well as in portal applications running on WebSphere Portal 5.1 and 6.0.

For inserting into a SQLite table, use the code as follows: //DB Connection private var dbconn:SQLConnection; //Query Statement private var sqlQuery:SQLStatement; //Create Table Statement private var sqlCreateTable:SQLStatement; //Insert Statement private var sqlInsert:SQLStatement; //Import Statement private var sqlImport:SQLStatement; /** * This is for importing xml data to a SQLite table * @param node xml node * @param user the user whos data this is * */ public function importPostXML( node:XMLNode, user:User ):void { var query:String = "INSERT INTO posts (" + "post_url," + "post_hash," + "post_desc," + "post_tags," + "post_time," + "post_extended," + "post_shared," + "post_replace," + "post_user)" + "VALUES ( " + ":post_url," + ":post_hash," + ":post_desc," + ":post_tags," + ":post_time," + ":post_extended," + ":post_shared," + ":post_replace," + ":post_user)"; sqlImport = new SQLStatement(); sqlImport.sqlConnection = dbconn; sqlImport.addEventListener( SQLEvent.RESULT, onSQLSave ); sqlImport.addEventListener( SQLErrorEvent.ERROR, onSQLError ); sqlImport.text = query; sqlImport.parameters[":post_url"] = node.attributes.href; sqlImport.parameters[":post_hash"] = node.attributes.hash; sqlImport.parameters[":post_desc"] = node.attributes.description; sqlImport.parameters[":post_tags"] = node.attributes.tag; sqlImport.parameters[":post_time"] = node.attributes.time; sqlImport.parameters[":post_extended"] = node.attributes.extended; sqlImport.parameters[":post_shared"] = node.attributes.shared; sqlImport.parameters[":post_replace"] = node.attributes.replace; sqlImport.parameters[":post_user"] = user.user_name; sqlImport.execute(); trace( "Importing XML to SQLite Database" ); }

This article shows how easy and simple it is to include UML diagrams within your Javadoc and also keep them updated with every change in the source code repository.

Discussion of functional programming concepts, focusing on fold operations and their implementation in C# using LINQ and expression trees.

Object-oriented programming languages and techniques provide a powerful means for designing and building applications. These techniques do not always translate well into a service oriented paradigm. Service orientation demands a different set of design guidelines and requirements than an object-oriented application. Understanding how an object-oriented design can negatively impact a service-oriented design is key to building services that support an agile enterprise. This article examines where the two designs impact each other as well as methods for addressing the incompatibilities between the two while still leveraging the power of both. by Larry Guger Introduction Object orientation is a good thing. I would like to believe that I write code in a well-defined object oriented manner, taking advantage of all the goodness that is provided, such as encapsulation, polymorphism and inheritance. These are important concepts that make modern software applications easier to develop, enhance and maintain. I’m sold. Service-orientation is a good thing too. As the industry moves toward service-orientation we naturally take along a lot of what we have learned over the years and apply this to the new way of doing things. Visual Studio, the .NET framework, and especially Windows Communication Foundation (WCF) support the development of service-oriented applications. This was one of the core design goals behind WCF, but moving from object-oriented design techniques to service-oriented design techniques is not without its challenges. Part of the reason can be apportioned towards the tooling. We have very mature tools to support object-oriented design and development but fewer tools that emphasize service-oriented design. This is partly because we, as an industry, are still really figuring out what service-orientation really means. This article explores what I am referring to as the “impedance mismatch” between the two design paradigms. Note: Most of the concepts and ideas presented are not specific to .NET or Visual Studio until I refer to the namespace generation problem later in the discussion (as it manifests itself in Visual Studio). However, it is worth noting that this problem can present itself on any platform. Designing an OO System Here is an example of one model that would make sense in the object-oriented world: Figure 1 Figure 1 is a simplified model designed to support some form of purchasing functionality provided by the application. A customer contains a mailing address and a shipping address and the customer can also hold many contracts with the company that is supplying products. The customer is able to place orders against these contracts with any given order containing one or more line items each of which is an order for a product. In addition, the model permits the developer to navigate from a PurchaseOrder object to the Contract under which the order was placed by using an object reference. Likewise, a Contract will contain a collection of all of the PurchaseOrders placed under it. This model is also repeated between the Customer and its Contracts as well as PurchaseOrders and OrderLineItems. We now have a nice object model that permits navigation between related objects in any direction. Service Enablement In a distributed computing environment such as is found in almost every enterprise today there is a business logic/service tier that resides on some central server farm that exposes services for working with the contained business functionality. This service tier is accessed by a client tier, whether the client is a Web application, a rich client application or a B2B service implementation. To support the object model above, one can imagine a collection of services that are targeted at a handful of business needs: customer services, contract services and order services. Each of these services has its own endpoint with a few methods to support working with each of the primary business types identified. To be specific, a service could be developed to support working with customer data that would contain methods such as CreateCustomer, SearchCustomers, and GetCustomer. Each of these methods would either accept or return customer objects and if you retrieved a customer object using the GetCustomer service you could inspect the contracts that the customer has as well as the orders placed under each contract. Chances are that if you retrieved a customer using the GetCustomer method you would not be getting the populated contract objects along with it at that time. You would need to make additional calls to retrieve individual contracts and associated orders if that was the information you were after. The same concept should hold for working with contracts or orders. As you can see, the object hierarchy is maintained. Assuming that this is the approach taken and the GetCustomer method returns a serialized object of type Customer once that customer object is deserialized in the client application it is easy enough to create contract objects, attach them to the contracts collection on the customer and create order objects and attach them to the contract objects and we have the same object oriented goodness on the client as we have on the server. This is a standard approach when first building service enabled applications. Unfortunately this does not work well for service-oriented applications that are intended to be reused throughout the enterprise for other purposes beyond the initial application. Here’s why. Service Referencing Let’s think about developing the client side portion of our application, whether it is a web, WinForms or WPF application does not matter. To begin, we create a user interface for dealing with all things related to customers. We can create new customers, modify existing ones and search for customers based on various criteria. Once we have the user interface defined we add a service reference, using Visual Studio, to our previously created service which in turn generates our classes and proxies. We instantiate objects, add data supplied by the user and submit these objects to our services. Pretty standard stuff. Next we move on to developing the portion of the user interface that deals with contracts. We follow the same pattern and things are working well until we get to a namespace collision. When we added a reference to the customer related service, Visual Studio generated code for the classes that make up the return types and the request types our service supports. This will include all of the serializable types in the customer object graph. When we add a reference to the contract service, Visual Studio will generate the code for the classes that make up the return and request types that this service supports. This will also include all of the serializable types in the contract object graph. In other words we end up with generated code for all of the classes described above twice! This is because each reference generates the classes in a distinct namespace. Even if you use the same reference name Visual Studio will alter them slightly to make them distinct. For example if both the first and second service references are given the name “localhost”, Visual Studio will append a “1” to the end of the first reference making the namespace begin with “localhost1”. You now have two Customer classes, localhost.Customer and localhost1.Customer, as well as two of every class in the respective object graphs. Now your code is duplicated and stored in different types. You cannot create an instance of a localhost.Customer object and assign it to a variable of type localhost1.Customer. Not only do you not get object compatibility but you also end up with a whole bunch of equivalent classes under different namespaces. There are a few commonly used ways to deal with this problem: 1. Add a reference to the assembly that contains your objects to your UI projects, and alter the service references to use that/those assemblies rather than generating the code. 2. Alter the generated code to remove the duplicates. 3. Alter the code generation process to reference the assemblies containing your data objects. 4. Develop mapping code to translate from one type to another. There are challenges with all of these. The first and third options may not be possible if you don’t have access to the assemblies, perhaps you are referencing services that you did not develop, and perhaps the objects contain code that shouldn’t reside on the UI side of things such as database access logic. The second option is simply fraught with perils as the code will be updated and need re-altering after every reference update, and if this is in mid development there may be many updates. The fourth option adds extra work and who needs extra work? The Service-oriented Approach The correct approach is to avoid these problems completely when developing your services. Here’s how. A Customer service should know about customers and data directly related to a customer only. Your Customer service methods should return a slightly different object graph than the object graph defined above. You will still have the customer object and you will still have the addresses for that customer but that’s it. Break the graph at the collection of contracts. When the client requires the contracts for a customer they need to submit a request to the Contract service asking for the contracts for a particular customer. This should actually be the same approach regardless of the object graph in use. Whether the customer explicitly asks for the contracts or the system hides the implementation details and makes the call to retrieve contracts are simply implementation details. The fact that the object graph does not contain direct links to the contracts would not impact the user experience. Let me explain. Regardless of the size of the object graph in use it should be a rare case in which the entire graph is populated and returned by a service call. Generally you will find that only a portion of the objects are in use for any given user action. To minimize the amount of data that is sent over a network only the relevant objects should be populated and returned. The code that is developed on the client side takes the responsibility for calling the appropriate services to populate further objects in the graph as the user requests them - this is often termed “lazy loading”. The goal of “lazy loading” is to retrieve only the data that is required so as to improve performance of the application. In fact, the simplified object graph better supports this design approach than the more complex graph does. With the complex graph, if you have a Contract object and need to perform some work with the related Customer for that contract you still need a sparsely populated Customer object that contains, at a minimum, the customer Id that can be used to retrieve the full customer object from the service. With the simplified graph the Contract class contains a customer Id directly. The relations between the objects are still maintained, however with the simplified version the relationships are more explicit than implicit, as they are with the complex version. To bring this back to the user experience, the user should not know whether the underlying code has been developed using the simplified or complex graph. They should be able to navigate from a contract to the related customer just as easily. It is up to you, the developer, to make this experience seemless. Figure 2 Again the object graph is kept simple as shown in Figure 2. As with the customer, contracts would not maintain a full customer object reference as part of the contract definition on the client side of the equation. A Contract object passed from the service would consist of only itself, no customer, and no PurchaseOrders. In place of the customer reference each contract object would maintain the customer identifier so as to be able to uniquely identify which customer the contract belongs to and provide the means to “navigate” to the customer object when required. As a side note, when requesting the collection of contracts for any given customer the collection of data returned should only consist of enough data in each object to uniquely identify the contract being sought, whether these objects are sparsely populated contract objects or a “light” version of the contract class does not really matter. You can then query for the full contract object based on the unique identifier that would be part of the collection of query results from the first request that returned the collection. Again, these are implementation details that are hidden from the user experience and need to be determined based on application needs. The End Result The end results of using this approach are: • Returned result data is kept to the relevant bits. Even though this goal can still be achieved with a more complex object graph this approach enforces it. • When adding a service reference using tools like Visual Studio the generated classes have a smaller object graph which avoids having multiple identical classes in different namespaces. • Cleaner separation of duties. Once you have adjusted to using this approach you will find that you need to create a mapping layer just behind the services - to map to and from the interfaces exposed by the services and your more complex object graphs. Either that or you can use simpler object graphs on the server side. However, these simple object graphs may not provide the functionality needed by the consumer of the service, especially if the consumer is a rich client application. In that case, a more complex object model can be designed and mapped to the simpler objects returned by the service. This keeps the service architecture simple while allowing the ability to use all of the OO principles that we’ve learned over the years. When it’s not needed, the simpler objects can simply be used as is with no additional work required. By keeping the server side object graphs at the same simplicity as the service interfaces you will find that your code becomes cleaner, more modular, your classes become more cohesive and there is less coupling between your objects. In addition, the flexibility to reuse the customer service with other services which rely on customer information, but are sourced from a different repository, is easier to achieve. Merging multiple customer data systems into a single customer service also becomes much easier if the customer data is de-coupled from any other data. This now leads to a potential increase in service-orientation reuse, and a happier enterprise. Conclusion Both object oriented and service-oriented design and develop techniques have their place in modern systems development. Object oriented systems fit well in a stateful environment while a service-oriented approach requires a stateless environment. There is nothing wrong with the strong object oriented approach as described at the start of this paper however it will not serve you well if you try and expose those object graphs through a service. With years of OO experience it’s easy to fall into OO design by default, but when designing systems we need to shift our mindset and think about what we are designing for. If it’s an SOA system, a traditional OO approach may not be the best. The tight coupling will get you in trouble as you expand the reach and reuse of your services throughout your enterprise. Keep the interfaces into your services simple and focused and you will find that your services become much easier to manage and become much more scalable. To summarize, OO is, by its nature, stateful while SOA is, by its nature, stateless. This is where the impedance mismatch shows itself.

in a nutshell, grid computing is a way to distribute your computations across multiple computers (nodes). however, even jms does that, but jms is not a grid computing product - it's a messaging protocol. to correctly classify grid computing products we have to split them into 2 categories: compute grids and data grids. compute grid compute grids allow you to take a computation, optionally split it into multiple parts, and execute them on different grid nodes in parallel. the obvious benefit here is that your computation will perform faster as it now can use resources from all grid nodes in parallel. one of the most common design patterns for parallel execution is mapreduce . however, compute grids are useful even if you don't need to split your computation - they help you improve overall scalability and fault-tolerance of your system by offloading your computations onto most available nodes. some of the "must have" compute grid features are: automatic deployment - allows for automatic deployment of classes and resources onto grid without any extra steps from user. this feature alone provides one of the largest productivity boosts in distributed systems. users usually are able to simply execute a task from one grid node and as task execution penetrates the grid, all classes and resources are also automatically deployed. topology resolution - allows to provision nodes based on any node characteristic or user-specific configuration. for example, you can decide to only include linux nodes for execution, or to only include a certain group of nodes within certain time window. you should also be able to choose all nodes with cpu loaded, say, under 50% that have more than 2gb of available heap memory. collision resolution - allows users to control which jobs get executed, which jobs get rejected, how many jobs can be executed in parallel, order of overall execution, etc. load balancing - allows to balance properly balance your system load within grid. usually range of load balancing policies varies within products. some of the most common ones are round robin, random, or adaptive. more advanced vendors also provide affinity load balancing where grid jobs always end up on the same node based on job's affinity key. this policy works well with data grids described below. fail-over - grid jobs should automatically fail-over onto other nodes in case of node crash or some other job failure. checkpoints - long running jobs should be able to periodically store their intermediate state. this is useful for fail-overs, when a failed job should be able to pick up its execution from the latest checkpoint, rather than start from scratch. grid events - a querying mechanism for all grid events is essential. any grid node should be able to query all events that happened on remote grid nodes during grid task execution. node metrics - a good compute grid solution should be able to provide dynamic grid metrics for all grid nodes. metrics should include vital node statistics, from cpu load to average job execution time. this is especially useful for load balancing, when the system or user need to pick the least loaded node for execution. pluggability - in order to blend into any environment a good compute grid should have well thought out pluggability points. for example, if running on top of jboss, a compute grid should totally reuse jboss communication and discovery protocols. data grid integration - it is important that compute grid are able to natively integrate with data grids as quite often businesses will need both, computational and data features working within same application. some compute grid vendors: - gridgain - professional open source - jppf - open source data grid data grids allow you to distribute your data across the grid. most of us are used to the term distributed cache rather than data grid (data grid does sound more savvy though). the main goal of data grid is to provide as much data as possible from memory on every grid node and to ensure data coherency. some of the important data grid features include: data replication - all data is fully replicated to all nodes in the grid. this strategy consumes the most resources, however it is the most effective solution for read-mostly scenarios, as data is available everywhere for immediate access. data invalidation - in this scenario, nodes load data on demand. whenever data changes on one of the nodes, then the same data on all other nodes is purged (invalidated). then this data will be loaded on-demand the next time it is accessed. distributed transactions - transactions are required to ensure data coherency. cache updates must work just like database updates - whenever an update failed, then the whole transaction must be rolled back. most data grid support various transaction policies, such as read committed, write committed, serializable, etc... data backups - useful for fail-over. some data grid products provide ability to assign backup nodes for the data. this way whenever a node crashes, the data is immediately available from another node. data affinity/partitioning - data affinity allows you to split/partition your whole data set into multiple subsets and assign every subset to a grid node. in the purest form, data is not replicated between nodes at all, every node is only responsible for it's own subset of data. however, various data grid products may provide different flavors of data affinity, such as replication only to back up nodes for example. data affinity is one of the more advanced features, and is not provided by every vendor. to my knowledge, according to product websites, out of commercial vendors oracle coherence and gemstone have it (there may be others). in professional open source space you can take a look at combination of gridgain with affinity load balancing and jbosscache . some data grid/cache vendors: - oracle coherence - commercial - gemstone - commercial - gigaspaces - commercial - jbosscache - professional open source - ehcache - open source

Any input provided by a user in a GUI application must typically be validated in one way or another. There is a number of ways this gets done, while some applications have just ignored the matter altogether. When crafting an Eclipse RCP application, there are some help provided by SWT and JFace. We can add ModifyListeners and VerifyListeners to certain SWT widgets. JFace also provides ControlDecorations to help us indicate to the user where a problem with a specific input value exists. The problem is that these are at a low level, and we need to do a lot of "monkey"-coding just to add basic validation and error indication to a widget, and then we're not even touching the world of input masks. If you're like me, you want to concentrate on solving your business problem, and don't want to write lots of basic UI code over and over. This is where the RCP Toolbox is very useful. It provides a light-weight validation framework (among other features) that makes it much easier to add validation and input masks to SWT Text, Combo and CCombo widgets. The goal Let us have a look at how to define a basic wizard for creating a new Booking. This wizard must capture the following fields from the user: Name: the name of the booking, typically the name of the person making the booking. May not be empty, and preferably not less than three characters. Date: the date and time of the booking. Must be any time from the current time to the end of the year. Number of Persons: the number of persons to book for. Must be a number from 1 to 10. Telephone Number: the telephone number of the person making the booking. Must be in the form +(country code) (area code) number, e.g. +44 (33) 555-1111. And of course we want indicators next to each field when an error or warning condition exists in the field, as well as a message being written to the WizardDialog's message area. For fun we want the user to be able to get a quick-fix option on the date field for setting it to the current time. The Validation framework The RCP Toolbox provides a number of custom widgets and a easy to use validation framework. Adding validation starts with the ValidationToolkit class. This class gets instantiated to work with a specific type of contents, and is then used to create ValidatingField instances that can handle that type of contents. The rest of the framework deals with interfaces and default implementations to facilitate the validation of contents, definition of input masks, provision of quick-fixes, error-handling and conversion of the input text to specific class types. The WizardPage and the ValidationToolkits We start by first defining our BookingWizardPage class and instantiating the necessary ValidationToolkit instances. //Not all imports are shown import com.richclientgui.toolbox.validation.IFieldErrorMessageHandler; import com.richclientgui.toolbox.validation.ValidationToolkit; import com.richclientgui.toolbox.validation.converter.DateStringConverter; import com.richclientgui.toolbox.validation.converter.IntegerStringConverter; import com.richclientgui.toolbox.validation.string.StringValidationToolkit; public class BookingWizardPage extends WizardPage { private static final int DECORATOR_POSITION = SWT.TOP | SWT.LEFT; private static final int DECORATOR_MARGIN_WIDTH = 1; private static final int DEFAULT_WIDTH_HINT = 150; private StringValidationToolkit strValToolkit = null; private ValidationToolkit dateValToolkit = null; private ValidationToolkit intValToolkit = null; private final IFieldErrorMessageHandler errorMessageHandler; public BookingWizardPage() { super("booking.pageone","New Booking Entry", null); errorMessageHandler = new WizardPageErrorHandler(); } public void createControl(Composite parent) { final Composite composite = new Composite(parent, SWT.NONE); composite.setLayout(new GridLayout(2, false)); strValToolkit = new StringValidationToolkit(DECORATOR_POSITION, DECORATOR_MARGIN_WIDTH, true); strValToolkit.setDefaultErrorMessageHandler(errorMessageHandler); intValToolkit = new ValidationToolkit(new IntegerStringConverter(), DECORATOR_POSITION, DECORATOR_MARGIN_WIDTH, true); intValToolkit.setDefaultErrorMessageHandler(errorMessageHandler); dateValToolkit = new ValidationToolkit(new DateStringConverter(), DECORATOR_POSITION, DECORATOR_MARGIN_WIDTH, true); dateValToolkit.setDefaultErrorMessageHandler(errorMessageHandler); //TODO: create ValidatingFields setControl(composite); } } The StringValidationToolkit class we instantiate in line 28 is a ValidationToolkit that deals specifically with ValidatingFields that have normal String contents. In line 32 we instantiate a typed instance of ValidationToolkit that will create ValidatingFields that only takes Integers as input. We must provide a way that the contents of the fields are converted from a String to the correct content type. This is done with a set of coverter classes provided by the framework. In lines 32 and 36 we specify a IntegerStringConverter and a DateStringConverter to convert Integer and java.util.Date values respectively. The framework makes use of the JFace org.eclipse.jface.fieldassist.ControlDecoration and related classes to indicate whether a field has an error or warning condition, whether it is a required field, and if there is a quick-fix available (by right-clicking on the decorator icon) for the current error or warning condition. The position of these decorator icons relative to the input widgets as well as the margin width between the decorator icon and the widget can be specified when constructing a ValidationToolkit. All the fields created by this ValidationToolkit instance will use the same settings for there decorator icons. In lines 9 - 10 we have defined some constants for the decorator position and margins, and we use this for constructing all the ValidationToolkit instances. Handling the error messages We also make use of an IFieldErrorMessageHandler to get feedback from the validation process. The validation framework will call these error handlers when error or warning conditions occur, and allow us to do something with those messages. By default these messages are only displayed in the tooltips of the decorator icons. A default error handler can be specified for each toolkit instance, or a separate handler can be set for each ValidatingField if so required. The inner class WizardPageErrorHandler implements the IFieldErrorMessageHandler interface and basically just set the messages on the WizardPage's message area. //inner class of BookingWizardPage class WizardPageErrorHandler implements IFieldErrorMessageHandler { public void handleErrorMessage(String message, String input) { setMessage(null, DialogPage.WARNING); setErrorMessage(message); } public void handleWarningMessage(String message, String input) { setErrorMessage(null); setMessage(message, DialogPage.WARNING); } public void clearMessage() { setErrorMessage(null); setMessage(null, DialogPage.WARNING); } } The actual error or warning messages are generated by the various IFieldValidator implementations (we'll get to those), and can easily be customized by implementing custom validators. Creating a simple ValidatingField Of course just having some toolkit instances does not help us much. We need actual input widgets that are being validated. The first step is to update the createControl method. public void createControl(Composite parent) { final Composite composite = new Composite(parent, SWT.NONE); composite.setLayout(new GridLayout(2, false)); strValToolkit = new StringValidationToolkit(DECORATOR_POSITION, DECORATOR_MARGIN_WIDTH, true); strValToolkit.setDefaultErrorMessageHandler(errorMessageHandler); intValToolkit = new ValidationToolkit(new IntegerStringConverter(), DECORATOR_POSITION, DECORATOR_MARGIN_WIDTH, true); intValToolkit.setDefaultErrorMessageHandler(errorMessageHandler); dateValToolkit = new ValidationToolkit(new DateStringConverter(), DECORATOR_POSITION, DECORATOR_MARGIN_WIDTH, true); dateValToolkit.setDefaultErrorMessageHandler(errorMessageHandler); createNameField(composite); createDateField(composite); createNumberPersonsField(composite); createTelephoneNumberField(composite); setControl(composite); } Then we can look at creating our first validated input field that makes use of a SWT Text widget to capture the name of the person doing the booking. private void createNameField(Composite composite) { new Label(composite, SWT.NONE).setText("Booking Name:"); final ValidatingField nameField = strValToolkit.createTextField( composite, new IFieldValidator(){ public String getErrorMessage() { return "Name may not be empty."; } public String getWarningMessage() { return "That's a very short name..."; } public boolean isValid(String contents) { return !(contents.length()==0); } public boolean warningExist(String contents) { return contents.length() < 3; } }, true, ""); GridData gd = new GridData(SWT.LEFT, SWT.CENTER, false, false); gd.widthHint = DEFAULT_WIDTH_HINT; nameField.getControl().setLayoutData(gd); } Since this field works with String contents, we make use of the strValToolkit instance to create the field in line 4 above. We specify the parent composite that the input widget must be added to, the IFieldValidator that will be used to validate the field contents, whether this is a required field or not (thus whether the required decorator icon must be shown or not) and an initial empty string value for the field. Note that this call will also create a Text widget to be used for the field, but the API allows that you can create your own Text, Combo or CCombo instance and pass that to the toolkit to use when creating a new ValidatingField. An anonymous inner class implementation of IFieldValidator is specified in lines 5 - 23. We're doing some very basic validation checks in this example, but it is easy to implement validators that makes use of other heavy-weight business validation frameworks. Our validator will indicate an error condition if the contents of the field is empty (line 16), in which case the error message "Name may not be empty." will be displayed (line 8). This validator will also indicate a warning condition if the name field contains less than 3 characters (line 20) with the message "That's a very short name..." (line 12). In lines 24 - 26 we set the layout of the input widget on the composite. Dating an input mask Dates have always been a difficult input type to deal with. The easiest way for us developers to deal with them are to use widgets that pop up a calendar from where the user can choose a day, and possibly a time as well. However, this way of dealing with dates are not always a favourite with touch-typing end-users. They prefer some masked field where they only need to fill in the bits of the date that matter. Using the mouse should be restricted as far as possible. Luckily the RCP Toolbox provides a way of specifying input masks, as well as specific implementations of validators and converters for dealing with Dates. We want to create a field that only takes dates as input, where the date entered must be of the form yyyy-MM-dd HH:mm (e.g 2008-07-19 21:00), and fall in the date range starting at the current time and ending at the end of the year 2008. private void createDateField(Composite composite) { new Label(composite, SWT.NONE).setText("Booking Time:"); final Date endYear = getEndYearDate(); //we create a Date field that takes input of form yyyy-MM-dd HH:mm //and only allows values from now till the end of the year final ValidatingField rangedDateField = dateValToolkit.createTextField(composite, new RangedDateFieldValidator( DateFieldValidator.DATE_TIME_HHMM_DASH, dateValToolkit.getStringConverter(), new Date(), endYear), true, new Date()); GridData gd = new GridData(SWT.LEFT, SWT.CENTER, false, false); gd.widthHint = DEFAULT_WIDTH_HINT; rangedDateField.getControl().setLayoutData(gd); } Here we used the dateValToolkit instance to create the field as the contents of the field must be a java.util.Date. We specify an instance of RangedDateFieldValidator (provided by the framework) that makes use of the specified Date input mask pattern DateFieldValidator.DATE_TIME_HHMM_DASH (line 9) to validate the contents of the field. Other patterns are available, or custom ones can also be defined. The DateStringConverter specified when dateValToolkit was constructed will be used to convert from Dates to Strings and vice versa. In line 11 we specify the valid date range for the field, from the current date and time to the end of the year, and in line 13 we set the initial value of the field to the current time. Providing quick-fixes I found that developers using Eclipse RCP to develop their applications like to make the experience for the end-user as good as possible. So we should not stop at just validating input; we must also try and help them quickly fix mistakes, where possible. In this example we can do that by specifying a IQuickFixProvider. //add at end of createDateField(..) method //we add a quickfix that will set it to the current date rangedDateField.setQuickFixProvider(new IQuickFixProvider(){ public boolean doQuickFix(ValidatingField field) { field.setContents(new Date()); return true; } public String getQuickFixMenuText() { return "Set to current time"; } public boolean hasQuickFix(Date contents) { //would typically first check contents to determine if quickfix //is possible return true; } }); The above is a very simple quick-fixer. It always says it has a quick-fix available (line 17), where a more complex provider will first check the contents of the field to determine if there is a quick-fix. When the user performs the quick-fix, it just sets the contents of the field to the current date and time (line 6). When the validation framework detects there is an error condition on a field, it will see if there is a IQuickFixProvider available with a quick-fix. If this is the case, it will add the quick-fix option to a context-menu on the decorator icon with the text specified in line 11. All the user then needs to do is right-click on the decorator icon and select the quick-fix to perform. Validating Combos A Combo widget would be just the thing to use for capturing the number of persons for the booking. Our requirements say we must limit the number to a maximum of 10 people (and a minimum of 1 goes without saying). Once again we do not want to force the user to use numerous mouse-clicks or keystrokes to select the number, so we do not make the Combo read-only, and rather decide to add validation to it. private void createNumberPersonsField(Composite composite) { new Label(composite, SWT.NONE).setText("Number of persons:"); final ValidatingField numberPersonsField = intValToolkit.createComboField( composite, new StrictRangedNumberFieldValidator(1, 10){ public String getErrorMessage() { return "Bookings for groups bigger than 10 not allowed"; } public String getWarningMessage() { return null; } public boolean warningExist(Integer contents) { return false; } }, true, 2, new Integer[]{1,2,3,4,5,6,7,8,9,10}); GridData gd = new GridData(SWT.LEFT, SWT.CENTER, false, false); gd.widthHint = DEFAULT_WIDTH_HINT; numberPersonsField.getControl().setLayoutData(gd); } Here we make use of the intValToolkit.createComboField method to create a field containing a Combo widget with contents of type Integer. We specify a StrictRangedNumberFieldValidator (line 6) to ensure that the entered value only consists of digits and falls in the range 1 to 10. No warning conditions are checked. In line 22 we populate the Combo with a list of Integers from 1 to 10, and in line 21 we select a default value of 2. As easy as counting to 5. And don't forget the telephone number Freeform telephone number fields are used a lot, but unfortunately end-users can easily make mistakes in such fields. We want to force our user to input the telephone number in a specific form, thus at least preventing the cases where digits are missed. To do this, we make use of the framework's TelephoneNumberValidator. This validator allows telephone number to be entered in either international format (e.g. +44 (55) 555-5555) or in domestic format (e.g. (055) 555-5555). private void createTelephoneNumberField(Composite composite) { new Label(composite, SWT.NONE).setText("Contact Telephone Nr:"); final ValidatingField telephoneField = strValToolkit.createTextField( composite, new TelephoneNumberValidator(true), true, "+44 (55) 555-4321"); GridData gd = new GridData(SWT.LEFT, SWT.CENTER, false, false); gd.widthHint = DEFAULT_WIDTH_HINT; telephoneField.getControl().setLayoutData(gd); } We are using strValToolkit to create the field, since the contents will be managed as a String. Then we specify a TelephoneNumberValidator as the validator in line 7, with the true parameter indicating that we want to use the international format. In line 9 we provide an initial value. Conclusion This article describes a very simple example of how to add validation to SWT widgets using the RCP Toolbox. In a real-world application the actual business validations to be done might be more complex, but if this validation framework is used, the UI code related to validation would remain as simple as the code in these examples. This validation framework really made our development much easier, allowing us to concentrate on the business code. It is very easy to extend the framework with custom validators, converters, quick-fix providers and error handlers that ties into existing business code or other validation code, rules engines etc. Note that the examples in this article need Eclipse RCP 3.3 or 3.4 as well as RCP Toolbox v1.0.1, created and distributed by www.richclientgui.com.