when studying both the java nio and io api's, a question quickly pops into mind: when should i use io and when should i use nio? in this text i will try to shed some light on the differences between java nio and io, their use cases, and how they affect the design of your code. main differences of java nio and io the table below summarizes the main differences between java nio and io. i will get into more detail about each difference in the sections following the table. io nio stream oriented buffer oriented blocking io non blocking io selectors stream oriented vs. buffer oriented the first big difference between java nio and io is that io is stream oriented, where nio is buffer oriented. so, what does that mean? java io being stream oriented means that you read one or more bytes at a time, from a stream. what you do with the read bytes is up to you. they are not cached anywhere. furthermore, you cannot move forth and back in the data in a stream. if you need to move forth and back in the data read from a stream, you will need to cache it in a buffer first. java nio's buffer oriented approach is slightly different. data is read into a buffer from which it is later processed. you can move forth and back in the buffer as you need to. this gives you a bit more flexibility during processing. however, you also need to check if the buffer contains all the data you need in order to fully process it. and, you need to make sure that when reading more data into the buffer, you do not overwrite data in the buffer you have not yet processed. blocking vs. non-blocking io java io's various streams are blocking. that means, that when a thread invokes a read() or write(), that thread is blocked until there is some data to read, or the data is fully written. the thread can do nothing else in the meantime. java nio's non-blocking mode enables a thread to request reading data from a channel, and only get what is currently available, or nothing at all, if no data is currently available. rather than remain blocked until data becomes available for reading, the thread can go on with something else. the same is true for non-blocking writing. a thread can request that some data be written to a channel, but not wait for it to be fully written. the thread can then go on and do something else in the mean time. what threads spend their idle time on when not blocked in io calls, is usually performing io on other channels in the meantime. that is, a single thread can now manage multiple channels of input and output. selectors java nio's selectors allow a single thread to monitor multiple channels of input. you can register multiple channels with a selector, then use a single thread to "select" the channels that have input available for processing, or select the channels that are ready for writing. this selector mechanism makes it easy for a single thread to manage multiple channels. how nio and io influences application design whether you choose nio or io as your io toolkit may impact the following aspects of your application design: the api calls to the nio or io classes. the processing of data. the number of thread used to process the data. the api calls of course the api calls when using nio look different than when using io. this is no surprise. rather than just read the data byte for byte from e.g. an inputstream, the data must first be read into a buffer, and then be processed from there. the processing of data the processing of the data is also affected when using a pure nio design, vs. an io design. in an io design you read the data byte for byte from an inputstream or a reader. imagine you were processing a stream of line based textual data. for instance: name: anna age: 25 email: [email protected] phone: 1234567890 this stream of text lines could be processed like this: inputstream input = ... ; // get the inputstream from the client socket bufferedreader reader = new bufferedreader(new inputstreamreader(input)); string nameline = reader.readline(); string ageline = reader.readline(); string emailline = reader.readline(); string phoneline = reader.readline(); notice how the processing state is determined by how far the program has executed. in other words, once the first reader.readline() method returns, you know for sure that a full line of text has been read. the readline() blocks until a full line is read, that's why. you also know that this line contains the name. similarly, when the second readline() call returns, you know that this line contains the age etc. as you can see, the program progresses only when there is new data to read, and for each step you know what that data is. once the executing thread have progressed past reading a certain piece of data in the code, the thread is not going backwards in the data (mostly not). this principle is also illustrated in this diagram: java io: reading data from a blocking stream. a nio implementation would look different. here is a simplified example: bytebuffer buffer = bytebuffer.allocate(48); int bytesread = inchannel.read(buffer); notice the second line which reads bytes from the channel into the bytebuffer. when that method call returns you don't know if all the data you need is inside the buffer. all you know is that the buffer contains some bytes. this makes processing somewhat harder. imagine if, after the first read(buffer) call, that all what was read into the buffer was half a line. for instance, "name: an". can you process that data? not really. you need to wait until at leas a full line of data has been into the buffer, before it makes sense to process any of the data at all. so how do you know if the buffer contains enough data for it to make sense to be processed? well, you don't. the only way to find out, is to look at the data in the buffer. the result is, that you may have to inspect the data in the buffer several times before you know if all the data is inthere. this is both inefficient, and can become messy in terms of program design. for instance: bytebuffer buffer = bytebuffer.allocate(48); int bytesread = inchannel.read(buffer); while(! bufferfull(bytesread) ) { bytesread = inchannel.read(buffer); } the bufferfull() method has to keep track of how much data is read into the buffer, and return either true or false, depending on whether the buffer is full. in other words, if the buffer is ready for processing, it is considered full. the bufferfull() method scans through the buffer, but must leave the buffer in the same state as before the bufferfull() method was called. if not, the next data read into the buffer might not be read in at the correct location. this is not impossible, but it is yet another issue to watch out for. if the buffer is full, it can be processed. if it is not full, you might be able to partially process whatever data is there, if that makes sense in your particular case. in many cases it doesn't. the is-data-in-buffer-ready loop is illustrated in this diagram: java nio: reading data from a channel until all needed data is in buffer. summary nio allows you to manage multiple channels (network connections or files) using only a single (or few) threads, but the cost is that parsing the data might be somewhat more complicated than when reading data from a blocking stream. if you need to manage thousands of open connections simultanously, which each only send a little data, for instance a chat server, implementing the server in nio is probably an advantage. similarly, if you need to keep a lot of open connections to other computers, e.g. in a p2p network, using a single thread to manage all of your outbound connections might be an advantage. this one thread, multiple connections design is illustrated in this diagram: java nio: a single thread managing multiple connections. if you have fewer connections with very high bandwidth, sending a lot of data at a time, perhaps a classic io server implementation might be the best fit. this diagram illustrates a classic io server design: java io: a classic io server design - one connection handled by one thread. from http://tutorials.jenkov.com/java-nio/nio-vs-io.html

In Eclipse, when you press Ctrl button and click on any Class names, the IDE will take you to the source file for that class. This is the normal behavior for the classes you have in your project. But, in case you want the same behavior for Java’s core classes too, you can have it by attaching the Java source with the Eclipse IDE. Once you attach the source, thereafter when you Ctrl+Click any Java class names (String for example), Eclipse will open the source code of that class. To attach the Java source code with Eclipse, When you install the JDK, you must have selected the option to install the Java source files too. This will copy the src.zip file in the installation directory. In Eclipse, go to Window -> Preferences -> Java -> Installed JREs -> Add and choose the JDK you have in your system. Eclipse will now list the JARs found in the dialog box. There, select the rt.jar and choose Source Attachment. By default, this will be pointing to the correct src.zip. If not, choose the src.zip file which you have in your java installation directory. Similarly, if you have the javadoc downloaded in your machine, you can configure that too in this dialog box. Done! Here after, for all the projects for which you are using the above JDK, you’ll be able to browse the Java’s source code just like how you browse your own code. From http://veerasundar.com/blog/2011/08/attaching-java-source-with-eclipse-ide

This article shows *one* way to mock the JMS infrastructure in a Spring JMS application. This allows us to test our JMS infrastructure without actually having to depend on a physical connection being available. If you are reading this article, chances are that you are also frustrated with failing tests in your continuous integration environment due to a JMS server being (temporarily) unavailable. By mocking the JMS provider, developers are left free to test not only the functionality of their API (unit tests) but also the plumbing of the different components, e.g. in a Spring container. In this article I show how a Spring JMS Hello World application can be fully tested without the need of a physical JMS connection. I would like to stress the fact that the code in this article is by no means meant for production and that the approach shown is just one of many. The infrastructure For this article I use the following infrastructure: Apache ActiveMQ, an open source JMS provider, running on an Ubuntu installation Spring 3 Java 6 MockRunner Eclipse as development environment, running on Windows 7 The Spring configuration It's my belief that using what I define as Spring Configuration Strategy Pattern (SCSP) is the right solution in almost all cases when there is the need for a sound testing infrastructure. I will dedicate an entire article to SCSP, for now this is how it looks: The Spring application context Here follows the content of jemosJms-appContext.xml The only important thing to note here is that there are some services which rely on an existing bean named jmsConnectionFactory but that such bean is not defined in this file. This is key to the SCSP and I will illustrate this in one of my future articles. The Spring application context implementation Here follows the content of jemosJms-appContextImpl.xml which could be seen as an implementation of the Spring application context defined above This Spring context file imports the Spring application context defined above and it is this application context which declared the connection factory. This decoupling of the bean requirement (in the super context) from its actual declaration (Spring application context implementation) represents the cornerstore of SCSP. Mocking the JMS provider - The Spring Test application context and MockRunner Following the same approach I used above, I can now declare a fake connection factory which does not require a physical connection to a JMS provider. Here follows the content of jemosJmsTest-appContext.xml. Please note that this file should reside in the test resources of your project, i.e. it should never make it to production. Here the Spring test application context file imports the Spring application context (not its implementation) and it declares a fake connection factory, thanks to the MockRunner MockQueueConnectionFactory class. A POJO listener The job of handling the message is delegated to a simple POJO, which happens to be declared also as a bean: package uk.co.jemos.experiments; public class HelloWorldHandler { /** The application logger */ private static final org.apache.log4j.Logger LOG = org.apache.log4j.Logger .getLogger(HelloWorldHandler.class); public void handleHelloWorld(String msg) { LOG.info("Received message: " + msg); } } There is nothing glamorous about this class. In real life this should have probably be the implementation of an interface, but here I wanted to keep things simple. A simple JMS message producer Here follows an example of a JMS message producer, which would use the real JMS infrastructure to send messages: package uk.co.jemos.experiments; import org.springframework.context.ApplicationContext; import org.springframework.context.support.ClassPathXmlApplicationContext; import org.springframework.jms.core.JmsTemplate; public class JmsTest { /** The application logger */ private static final org.apache.log4j.Logger LOG = org.apache.log4j.Logger .getLogger(JmsTest.class); /** * @param args */ public static void main(String[] args) { ApplicationContext ctx = new ClassPathXmlApplicationContext( "classpath:jemosJms-appContextImpl.xml"); JmsTemplate jmsTemplate = ctx.getBean(JmsTemplate.class); jmsTemplate.send("jemos.tests", new HelloWorldMessageCreator()); LOG.info("Message sent successfully"); } } The only thing of interest here is that this class retrieves the real JmsTemplate to send a message to the queue. Now if I was to run this class as is, I would obtain the following: 2011-07-31 17:09:46 ClassPathXmlApplicationContext [INFO] Refreshing org.springframework.context.support.ClassPathXmlApplicationContext@19e0ff2f: startup date [Sun Jul 31 17:09:46 BST 2011]; root of context hierarchy 2011-07-31 17:09:46 XmlBeanDefinitionReader [INFO] Loading XML bean definitions from class path resource [jemosJms-appContextImpl.xml] 2011-07-31 17:09:46 XmlBeanDefinitionReader [INFO] Loading XML bean definitions from class path resource [jemosJms-appContext.xml] 2011-07-31 17:09:46 DefaultListableBeanFactory [INFO] Pre-instantiating singletons in org.springframework.beans.factory.support.DefaultListableBeanFactory@3479e304: defining beans [helloWorldConsumer,jmsTemplate,org.springframework.jms.listener.DefaultMessageListenerContainer#0,jmsConnectionFactory]; root of factory hierarchy 2011-07-31 17:09:46 DefaultLifecycleProcessor [INFO] Starting beans in phase 2147483647 2011-07-31 17:09:47 HelloWorldHandler [INFO] Received message: Hello World 2011-07-31 17:09:47 JmsTest [INFO] Message sent successfully Writing the integration test There are various interpretations as to what different types of tests mean and I don't pretend to have the only answer; my interpreation is that an integration test is a functional test which also wires up different components together but which does not interact with real external infrastructure (e.g. a Dao integration test fakes data, a JMS integration test fakes the JMS physical connection, an HTTP integration test fakes the remote Web host, etc). Whereas in my opinion, the main purpose of a unit (aka functional) test is to let the API emerge from the tests, the main goal of an integration test is to test that the plumbing amongst components works as expected so as to avoid surprises in a production environment. Both unit (functional) and integration tests should run very fast (e.g. under 10 minutes) as they constitute what can be considered the "development token". If unit and integration tests are green one should feel pretty confident that 90% of the functionality works as expected; in my projects when both unit and integration tests are green I let developers free to release the token. This does not mean that the other 10% (e.g. the interaction with the real infrastructure) should not be tested, but this can be delegated to system tests which run nightly and don't require the development token. Because unit and integration tests need to run fast, interaction with external infrastructure should be mocked whenever possible. Here follows an integration test for the Hello World handler: package uk.co.jemos.experiments.test.integration; import javax.annotation.Resource; import javax.jms.TextMessage; import junit.framework.Assert; import org.junit.Before; import org.junit.Test; import org.springframework.jms.core.JmsTemplate; import org.springframework.test.context.ContextConfiguration; import org.springframework.test.context.junit4.AbstractJUnit4SpringContextTests; import uk.co.jemos.experiments.HelloWorldHandler; import uk.co.jemos.experiments.HelloWorldMessageCreator; import com.mockrunner.jms.DestinationManager; import com.mockrunner.mock.jms.MockQueue; /** * @author mtedone * */ @ContextConfiguration(locations = { "classpath:jemosJmsTest-appContextImpl.xml" }) public class HelloWorldHandlerIntegrationTest extends AbstractJUnit4SpringContextTests { @Resource private JmsTemplate jmsTemplate; @Resource private DestinationManager mockDestinationManager; @Resource private HelloWorldHandler helloWorldHandler; @Before public void init() { Assert.assertNotNull(jmsTemplate); Assert.assertNotNull(mockDestinationManager); Assert.assertNotNull(helloWorldHandler); } @Test public void helloWorld() throws Exception { MockQueue mockQueue = mockDestinationManager.createQueue("jemos.tests"); jmsTemplate.send(mockQueue, new HelloWorldMessageCreator()); TextMessage message = (TextMessage) jmsTemplate.receive(mockQueue); Assert.assertNotNull("The text message cannot be null!", message.getText()); helloWorldHandler.handleHelloWorld(message.getText()); } } And here follows the output: 2011-07-31 17:17:26 XmlBeanDefinitionReader [INFO] Loading XML bean definitions from class path resource [jemosJmsTest-appContextImpl.xml] 2011-07-31 17:17:26 XmlBeanDefinitionReader [INFO] Loading XML bean definitions from class path resource [jemosJms-appContext.xml] 2011-07-31 17:17:26 GenericApplicationContext [INFO] Refreshing org.springframework.context.support.GenericApplicationContext@f01a1e: startup date [Sun Jul 31 17:17:26 BST 2011]; root of context hierarchy 2011-07-31 17:17:27 DefaultListableBeanFactory [INFO] Pre-instantiating singletons in org.springframework.beans.factory.support. DefaultListableBeanFactory@39478a43: defining beans [helloWorldConsumer,jmsTemplate,org.springframework.jms.listener.DefaultMessageListener Container#0,destinationManager,configurationManager,jmsConnectionFactory,org.springframework.context.annotation.internalConfigurationAnnotation Processor,org.springframework.context.annotation.internalAutowiredAnnotationProcessor,org.springframework.context.annotation.internalRequired AnnotationProcessor,org.springframework.context.annotation.internalCommonAnnotationProcessor]; root of factory hierarchy 2011-07-31 17:17:27 DefaultLifecycleProcessor [INFO] Starting beans in phase 2147483647 2011-07-31 17:17:27 HelloWorldHandler [INFO] Received message: Hello World 2011-07-31 17:17:27 GenericApplicationContext [INFO] Closing org.springframework.context.support.GenericApplicationContext@f01a1e: startup date [Sun Jul 31 17:17:26 BST 2011]; root of context hierarchy 2011-07-31 17:17:27 DefaultLifecycleProcessor [INFO] Stopping beans in phase 2147483647 2011-07-31 17:17:32 DefaultMessageListenerContainer [WARN] Setup of JMS message listener invoker failed for destination 'jemos.tests' - trying to recover. Cause: Queue with name jemos.tests not found 2011-07-31 17:17:32 DefaultListableBeanFactory [INFO] Destroying singletons in org.springframework.beans.factory.support. DefaultListableBeanFactory@39478a43: defining beans [helloWorldConsumer,jmsTemplate,org.springframework.jms.listener.DefaultMessageListener Container#0,destinationManager,configurationManager,jmsConnectionFactory,org.springframework.context.annotation.internalConfigurationAnnotationProcessor ,org.springframework.context.annotation.internalAutowiredAnnotationProcessor,org.springframework.context.annotation.internalRequiredAnnotationProcessor,org.springframework.context. annotation.internalCommonAnnotationProcessor]; root of factory hierarchy In this test, although we simulated a message roundtrip to a JMS queue, the message never left the current JVM and it the whole execution did not depend on a JMS infrastructure being up. This gives us the power to simulate the JMS infrastructure, to test the integration of our business components without having to fear a red from time to time due to JMS infrastructure being down or inaccessible. Please note that in the output there are some warnings because the JMS listener container declared in the jemosJms-appContext.xml does not find a queue named "jemos.test" in the fake connection factory, but this is fine; it's a warning and does not impede the test from running successfully. The Maven configuration Here follows the Maven pom.xml to compile the example: 4.0.0 uk.co.jemos.experiments jmx-experiments 0.0.1-SNAPSHOT Jemos JMS experiments junit junit 4.8.2 test com.mockrunner mockrunner 0.3.1 test log4j log4j 1.2.16 compile org.slf4j slf4j-api 1.6.1 compile org.slf4j slf4j-simple 1.6.1 compile org.apache.activemq activemq-all 5.5.0 compile org.springframework spring-beans 3.0.5.RELEASE org.springframework spring-context 3.0.5.RELEASE org.springframework spring-core 3.0.5.RELEASE org.springframework spring-jms 3.0.5.RELEASE org.springframework spring-test 3.0.5.RELEASE test From http://tedone.typepad.com/blog/2011/07/mocking-spring-jms-with-mockrunner.html

i often get asked about ‘rest to soap’ transformation use cases these days. using an soa gateway like securespan to perform this type of transformation at runtime is trivial to setup. with securespan in front of any existing web service (in the dmz for example), you can virtualize a rest version of this same service. using an example, here is a description of the steps to perform this conversion. imagine the geoloc web service for recording geographical locations. it has two methods, one for setting a location and one for getting a location. see below what this would look like in soap. request: 34802398402 response: 52.37706 4.889721 request: 34802398402 52.37706 4.889721 response: ok here is the equivalent rest target that i want to support at the edge. payloads could be xml, but let’s use json to make it more interesting. get /position/34802398402 http 200 ok content-type: text/json { 'latitude' : 52.37706 'longitude' : 4.889721 } post /position/34802398402 content-type: text/json { 'latitude' : 52.37706 'longitude' : 4.889721 } http 200 ok ok now let’s implement this rest version of the service using securespan. i’m assuming that you already have a securespan gateway deployed between the potential rest requesters and the existing soap web service. first, i will create a new service endpoint on the gateway for this service and assign anything that comes at the uri pattern /position/* to this service. i will also allow the http verbs get and post for this service. rest geoloc service properties next, let’s isolate the resource id from the uri and save this as a context variable named ‘trackerid’. we can use a simple regex assertion to accomplish this. also, i will branch on the incoming http verb using an or statement. i am just focusing on get and post for this example but you could add additional logic for other http verbs that you want to support for this rest service. regex for rest service resource identification policy branching for get vs post for get requests, the transformation is very simple, we just declare a message variable using a soap skeleton into which we refer to the trackerid variable. soap request template this soap message is routed to the existing web service and the essential elements are isolated using xpath assertions. processing soap response the rest response is then constructed back using a template response. template json response a similar logic is performed for the post message. see below for the full policy logic. complete policy you’re done for virtualizing the rest service. setting this up with securespan took less than an hour, did not require any change on the existing soap web service and did not require the deployment of an additional component. from there, you would probably enrich the policy to perform some json schema validation , some url and query parameter validation, perhaps some authentication, authorization , etc.

martin fowler has written a really good article describing not only the disruptor , but also how it fits into the architecture at lmax . this gives some of the context that has been missing so far, but the most frequently asked question is still "what is the disruptor?". i'm working up to answering that. i'm currently on question number two: "why is it so fast?". these questions do go hand in hand, however, because i can't talk about why it's fast without saying what it does, and i can't talk about what it is without saying why it is that way. so i'm trapped in a circular dependency. a circular dependency of blogging. to break the dependency, i'm going to answer question one with the simplest answer, and with any luck i'll come back to it in a later post if it still needs explanation: the disruptor is a way to pass information between threads. as a developer, already my alarm bells are going off because the word "thread" was just mentioned, which means this is about concurrency, and concurrency is hard. concurrency 101 imagine two threads are trying to change the same value. case one: thread 1 gets there first: the value changes to "blah" then the value changes to "blahy" when thread 2 gets there. case two: thread 2 gets there first: the value changes to "fluffy" then the value changes to "blah" when thread 1 gets there. case three: thread 1 interrupts thread 2: thread 2 gets the value "fluff" and stores it as myvalue thread 1 goes in and updates value to "blah" then thread 2 wakes up and sets the value to "fluffy". case three is probably the only one which is definitely wrong, unless you think the naive approach to wiki editing is ok ( google code wiki, i'm looking at you...). in the other two cases it's all about intentions and predictability. thread 2 might not care what's in value, the intention might be to append "y" to whatever is in there regardless. in this circumstance, cases one and two are both correct. but if thread 2 only wanted to change "fluff" to "fluffy", then both cases two and three are incorrect. assuming that thread 2 wants to set the value to "fluffy", there are some different approaches to solving the problem. approach one: pessimistic locking (does the "no entry" sign make sense to people who don't drive in britain?) the terms pessimistic and optimistic locking seem to be more commonly used when talking about database reads and writes, but the principal applies to getting a lock on an object. thread 2 grabs a lock on entry as soon as it knows it needs it and stops anything from setting it. then it does its thing, sets the value, and lets everything else carry on. you can imagine this gets quite expensive, with threads hanging around all over the place trying to get hold of objects and being blocked. the more threads you have, the more chance that things are going to grind to a halt. approach two: optimistic locking in this case thread 2 will only lock entry when it needs to write to it. in order to make this work, it needs to check if entry has changed since it first looked at it. if thread 1 came in and changed the value to "blah" after thread 2 had read the value, thread 2 couldn't write "fluffy" to the entry and trample all over the change from thread 1. thread 2 could either re-try (go back, read the value, and append "y" onto the end of the new value), which you would do if thread 2 didn't care what the value it was changing was; or it could throw an exception or return some sort of failed update flag if it was expecting to change "fluff" to "fluffy". an example of this latter case might be if you have two users trying to update a wiki page, and you tell the user on the other end of thread 2 they'll need to load the new changes from thread 1 and then reapply their changes. potential problem: deadlock locking can lead to all sorts of issues, for example deadlock. imagine two threads that need access to two resources to do whatever they need to do: if you've used an over-zealous locking technique, both threads are going to sit there forever waiting for the other one to release its lock on the resource. that's when you reboot windows your computer. definite problem: locks are sloooow... the thing about locks is that they need the operating system to arbitrate the argument. the threads are like siblings squabbling over a toy, and the os kernel is the parent that decides which one gets it. it's like when you run to your dad to tell him your sister has nicked the transformer when you wanted to play with it - he's got bigger things to worry about than you two fighting, and he might finish off loading the dishwasher and putting on the laundry before settling the argument. if you draw attention to yourself with a lock, not only does it take time to get the operating system to arbitrate, the os might decide the cpu has better things to do than servicing your thread. the disruptor paper talks about an experiment we did. the test calls a function incrementing a 64-bit counter in a loop 500 million times. for a single thread with no locking, the test takes 300ms. if you add a lock (and this is for a single thread, no contention, and no additional complexity other than the lock) the test takes 10,000ms. that's, like, two orders of magnitude slower. even more astounding, if you add a second thread (which logic suggests should take maybe half the time of the single thread with a lock) it takes 224,000ms. incrementing a counter 500 million times takes nearly a thousand times longer when you split it over two threads instead of running it on one with no lock. concurrency is hard and locks are bad i'm just touching the surface of the problem, and obviously i'm using very simple examples. but the point is, if your code is meant to work in a multi-threaded environment, your job as a developer just got a lot more difficult: naive code can have unintended consequences. case three above is an example of how things can go horribly wrong if you don't realise you have multiple threads accessing and writing to the same data. selfish code is going to slow your system down. using locks to protect your code from the problem in case three can lead to things like deadlock or simply poor performance. this is why many organisations have some sort of concurrency problems in their interview process (certainly for java interviews). unfortunately it's very easy to learn how to answer the questions without really understanding the problem, or possible solutions to it. how does the disruptor address these issues? for a start, it doesn't use locks. at all. instead, where we need to make sure that operations are thread-safe (specifically, updating the next available sequence number in the case of multiple producers ), we use a cas (compare and swap/set) operation. this is a cpu-level instruction, and in my mind it works a bit like optimistic locking - the cpu goes to update a value, but if the value it's changing it from is not the one it expects, the operation fails because clearly something else got in there first. note this could be two different cores rather than two separate cpus. cas operations are much cheaper than locks because they don't involve the operating system, they go straight to the cpu. but they're not cost-free - in the experiment i mentioned above, where a lock-free thread takes 300ms and a thread with a lock takes 10,000ms, a single thread using cas takes 5,700ms. so it takes less time than using a lock, but more time than a single thread that doesn't worry about contention at all. back to the disruptor - i talked about the claimstrategy when i went over the producers . in the code you'll see two strategies, a singlethreadedstrategy and a multithreadedstrategy. you could argue, why not just use the multi-threaded one with only a single producer? surely it can handle that case? and it can. but the multi-threaded one uses an atomiclong (java's way of providing cas operations), and the single-threaded one uses a simple long with no locks and no cas. this means the single-threaded claim strategy is as fast as possible, given that it knows there is only one producer and therefore no contention on the sequence number. i know what you're thinking: turning one single number into an atomiclong can't possibly have been the only thing that is the secret to the disruptor's speed. and of course, it's not - otherwise this wouldn't be called "why it's so fast (part one )". but this is an important point - there's only one place in the code where multiple threads might be trying to update the same value. only one place in the whole of this complicated data-structure-slash-framework. and that's the secret. remember everything has its own sequence number? if you only have one producer then every sequence number in the system is only ever written to by one thread. that means there is no contention. no need for locks. no need even for cas. the only sequence number that is ever written to by more than one thread is the one on the claimstrategy if there is more than one producer. this is also why each variable in the entry can only be written to by one consumer . it ensures there's no write contention, therefore no need for locks or cas. back to why queues aren't up to the job so you start to see why queues, which may implemented as a ring buffer under the covers, still can't match the performance of the disruptor. the queue, and the basic ring buffer , only has two pointers - one to the front of the queue and one to the end: if more than one producer wants to place something on the queue, the tail pointer will be a point of contention as more than one thing wants to write to it. if there's more than one consumer, then the head pointer is contended, because this is not just a read operation but a write, as the pointer is updated when the item is consumed from the queue. but wait, i hear you cry foul! because we already knew this, so queues are usually single producer and single consumer (or at least they are in all the queue comparisons in our performance tests). there's another thing to bear in mind with queues/buffers. the whole point is to provide a place for things to hang out between producers and consumers, to help buffer bursts of messages from one to the other. this means the buffer is usually full (the producer is out-pacing the consumer) or empty (the consumer is out-pacing the producer). it's rare that the producer and consumer will be so evenly-matched that the buffer has items in it but the producers and consumers are keeping pace with each other. so this is how things really look. an empty queue: ...and a full queue: the queue needs a size so that it can tell the difference between empty and full. or, if it doesn't, it might determine that based on the contents of that entry, in which case reading an entry will require a write to erase it or mark it as consumed. whichever implementation is chosen, there's quite a bit of contention around the tail, head and size variables, or the entry itself if a consume operation also includes a write to remove it. on top of this, these three variables are often in the same cache line , leading to false sharing . so, not only do you have to worry about the producer and the consumer both causing a write to the size variable (or the entry), updating the tail pointer could lead to a cache-miss when the head pointer is updated because they're sat in the same place. i'm going to duck out of going into that in detail because this post is quite long enough as it is. so this is what we mean when we talk about "teasing apart the concerns" or a queue's "conflated concerns". by giving everything its own sequence number and by allowing only one consumer to write to each variable in the entry, the only case the disruptor needs to manage contention is where more than one producer is writing to the ring buffer. in summary the disruptor a number of advantages over traditional approaches: no contention = no locks = it's very fast. having everything track its own sequence number allows multiple producers and multiple consumers to use the same data structure. tracking sequence numbers at each individual place (ring buffer, claim strategy, producers and consumers), plus the magic cache line padding , means no false sharing and no unexpected contention. from http://mechanitis.blogspot.com/2011/07/dissecting-disruptor-why-its-so-fast.html

I’m currently working on a project that is converted from being a Mainframe application, to a Java web/batch application. We don’t ‘big bang’ into production, so the Mainframe and the Java code will work next to each other for a fairly amount of time. Since we have multiple batch processes and many simultaneous users, we start seeing deadlock errors in certain parts of the application. Some specific parts have to take a pessimistic lock, this is where it goes wrong. Since a deadlock is an error that can be solved by repeating the action, we decide to build in a retry mechanism to restart the transaction if it got rolled back. I started of with creating an Annotation. This annotation will mark the entry point that we want to retry in case of a deadlock. @Retention(RetentionPolicy.RUNTIME) @Target(ElementType.METHOD) public @interface DeadLockRetry { /** * Retry count. default value 3 */ int retryCount() default 3; } The retry count is a value you can supply together with your annotation, so you can specify the number of times we want to retry our operation. Using AOP we can pick up this annotation an let us surround the method call with a retry mechanism. @Around(value = "@annotation(deadLockRetry)", argNames = "deadLockRetry") So lets view the aspect, we start with adding an @Aspect annotation on top of our class, this way it is configured to be an Aspect. We also want to implement the Ordered interface. This interface lets us order our aspect. We need this to surround our Transactional aspect. If we don’t surround our Transaction, we will never be able to retry in a new transaction, we would be working in the same (marked as rollback only) transaction. The rest of the code is pretty straight forward. We create a loop where we loop until we have more retries than we should have. Inside that loop we proceed our ProceedingJoinPoint and catch the PersistenceException that JPA would throw when a deadlock would occur. Inside the catch block we check if the error code is a deadlock error code. Off course we could not directly configure the database specific error codes inside our aspect, so I’ve created an interface. /** * Interface that marks a dialect aware of certain error codes. When you have to * do a low level check of the exception you are trying to handle, you can * implement this in this interface, so you can encapsulate the specific error * codes for the specific dialects. * * @author Jelle Victoor * @version 05-jul-2011 */ public interface ErrorCodeAware { Set getDeadlockErrorCodes(); } We already have custom hibernate dialects for our database and database to be, so this let me configure the error codes in the Dialect implementations. It was a bit tricky to get the current dialect. I injected the persistence unit, since we are outside a transaction, and made some casts to get my dialect. The alternative was to use a custom implementation of the ErrorCodeAware interface, not using the dialects. We could inject the needed ErrorCodeAware implementation based on our application context. This added another database specific injection, which added another point of configuration. This is why I chose to store it in our custom dialect. private Dialect getDialect() { final SessionFactory sessionFactory = ((HibernateEntityManagerFactory) emf).getSessionFactory(); return ((SessionFactoryImplementor) sessionFactory).getDialect(); } The only thing left is to configure the aspect, mind the order of the transaction manager and the retry aspect Now when I have a deadlock exception, and I’ve added this annotation, the transaction will rollback and will be reexecuted. /** * This Aspect will cause methods to retry if there is a notion of a deadlock. * * Note that the aspect implements the Ordered interface so we can set the * precedence of the aspect higher than the transaction advice (we want a fresh * transaction each time we retry). * * @author Jelle Victoor * @version 04-jul-2011 handles deadlocks */ @Aspect public class DeadLockRetryAspect implements Ordered { private static final Logger LOGGER = LoggerFactory.getLogger(DeadLockRetryAspect.class); private int order = -1; @PersistenceUnit private EntityManagerFactory emf; /** * Deadlock retry. The aspect applies to every service method with the * annotation {@link DeadLockRetry} * * @param pjp * the joinpoint * @param deadLockRetry * the concurrency retry * @return * * @throws Throwable * the throwable */ @Around(value = "@annotation(deadLockRetry)", argNames = "deadLockRetry") public Object concurrencyRetry(final ProceedingJoinPoint pjp, final DeadLockRetry deadLockRetry) throws Throwable { final Integer retryCount = deadLockRetry.retryCount(); Integer deadlockCounter = 0; Object result = null; while (deadlockCounter < retryCount) { try { result = pjp.proceed(); break; } catch (final PersistenceException exception) { deadlockCounter = handleException(exception, deadlockCounter, retryCount); } } return result; } /** * handles the persistence exception. Performs checks to see if the * exception is a deadlock and check the retry count. * * @param exception * the persistence exception that could be a deadlock * @param deadlockCounter * the counter of occured deadlocks * @param retryCount * the max retry count * @return the deadlockCounter that is incremented */ private Integer handleException(final PersistenceException exception, Integer deadlockCounter, final Integer retryCount) { if (isDeadlock(exception)) { deadlockCounter++; LOGGER.error("Deadlocked ", exception.getMessage()); if (deadlockCounter == (retryCount - 1)) { throw exception; } } else { throw exception; } return deadlockCounter; } /** * check if the exception is a deadlock error. * * @param exception * the persitence error * @return is a deadlock error */ private Boolean isDeadlock(final PersistenceException exception) { Boolean isDeadlock = Boolean.FALSE; final Dialect dialect = getDialect(); if (dialect instanceof ErrorCodeAware && exception.getCause() instanceof GenericJDBCException) { if (((ErrorCodeAware) dialect).getDeadlockErrorCodes().contains(getSQLErrorCode(exception))) { isDeadlock = Boolean.TRUE; } } return isDeadlock; } /** * Returns the currently used dialect * * @return the dialect */ private Dialect getDialect() { final SessionFactory sessionFactory = ((HibernateEntityManagerFactory) emf).getSessionFactory(); return ((SessionFactoryImplementor) sessionFactory).getDialect(); } /** * extracts the low level sql error code from the * {@link PersistenceException} * * @param exception * the persistence exception * @return the low level sql error code */ private int getSQLErrorCode(final PersistenceException exception) { return ((GenericJDBCException) exception.getCause()).getSQLException().getErrorCode(); } /** {@inheritDoc} */ public int getOrder() { return order; } /** * Sets the order. * * @param order * the order to set */ public void setOrder(final int order) { this.order = order; } } From http://styledideas.be/blog/2011/07/05/automatic-deadlock-retry-aspect-with-spring-and-jpahibernate/

This article describes how to create a simple HTML5 chat application using WebSockets to connect to a Java back-end.

For the eight successive year, the latest iteration of the Eclipse release train, Indigo, is now available for developers everywhere. And once again, the Eclipse community have shown that it is possible to coordinate software to be released on time. The scale of Indigo is huge - it contains 62 projects, 46 million lines of code contributed by 408 committers. “We are very proud to celebrate another on-time annual release train from the Eclipse community,” states Mike Milinkovich, executive director of the Eclipse Foundation. “This release has a long list of new features, especially for Java developers. Features such as Git support, Maven and Hudson integration, a great GUI builder in WindowBuilder, and our new Jubula testing tool will, I am sure, motivate developers to try Indigo.” Yesterday I listed some of the excellent tooling additions that are available in Indigo. Once again, the latest Eclipse release provides something for everyone. Download it now and find out for yourself. For Java Developers EGit 1.0 provides first-class support support for Java developers using Git for source code management WindowBuilder, a world-class Eclipse-based GUI builder, is now available as an Eclipse open source project Automated functional GUI testing for Java and HTML applications is included via Jubula m2eclipse brings tight integration with Maven and the Eclipse workspace, enabling developers to work with Maven projects directly from Eclipse Mylyn 3.6 supports Hudson build monitoring directly from the Eclipse workspace Eclipse Marketplace Client now supports drag and drop installation of Eclipse-based solutions directly into Eclipse making it significantly easier to install new solutions. New Innovation in Eclipse Modeling Xtext 2.0 has added significant new features for domain-specific languages (DSLs): 1) the ability to create DSLs with embedded Java-like expressions; 2) Xtend, a new template language that allows tightly integrated code generation into the Eclipse tooling environment; and 3) a new refactoring framework for DSLs. Acceleo 3.1 integrates code generation into Ant and Maven build chains, and includes improved generator editing facilities. CDO Model Repository 4.0 integrates with several NoSQL databases such as Objectivity/DB, MongoDB, and DB4O. Cache optimizations and many other enhancements allow for models of several gigabytes. EMF 2.7 makes it easy to replicate changes across distributed systems in an optimal way: a client can send back to the server a minimal description of what's been changed rather than sending back the whole, arbitrarily-large, new instance. Eclipse Extended Editing Framework (EEF) 1.0 generates advanced and good-looking EMF editors in one click. EMF Compare 1.2 brings dedicated UML support and is more fully integrated with the SCM. EMF Facet, a new project, allows extension of an existing Ecore metamodel without modification. EclipseRT Advancements EclipseLink 2.3 supports multi-tenant JPA Entities, making it possible to incorporate JPA persistency into SaaS-style applications. Equinox 3.7 now implements the OSGi 4.3 specification, including use of generic signatures, generic capabilities, and requirements for bundles. Eclipse Communication Framework (ECF) implements OSGi 4.2 Remote Service and Remote Service Admin standards.

The Eclipse Communication Framework has been a steady participant in the Eclipse release trains, continuously adding to its impressive list of features. This year’s inclusion of ECF 3.5 in the Indigo release train is no exception. In this article, I'll take a look at five key features of the release: OSGi 4.2 Remote Services/RSA Standards Support ECF Indigo implements two recently-completed OSGi standards: OSGi remote services and OSGi Remote Service Admin (RSA). The OSGi Remote Services spec provides a simple, standardized way to expose OSGi services for network discovery and remote access. ECF Indigo also implements the Enterprise specification for remote services management known as Remote Services Admin (RSA). The RSA specification defines a management agent to allow for enterprise-application control of the discovery and distribution of remote services via a standardized API. Also included in the RSA specification is a standardized format for communicating meta-data about remote services, advanced handling of security, discovery and distribution event notification, and advanced handling of remote service versioning. ECF has run its implementation of RS/RSA through the OSGi Test Compatability Kit to ensure that it is compliant with the OSGi specification. Extensibility through Provider Architecture ECF has a provider architecture, that allows major components of the OSGi remote services/RSA implementation to be extended, enhanced, or replaced as needed. For example, for interoperability with existing services and applications, it’s frequently desirable to be able to substitute the wire protocol/transport to one that is already being used. With the ECF provider architecture, it’s possible to substitute the underlying protocol...and use other frameworks based upon REST, SOAP, JMS, XML-RPC, XMPP, and/or others. If you wish, you can even define and use a proprietary provider and use it to expose your remote services. Or you can use one provider for remote services development and testing, and another for deployment. Asynchronous Proxies ECF has support for remote service access via asynchronous proxies. This allows client consumers of remote services to avoid the reliability problems that are frequent when synchronous proxies are used over a relatively slow and unreliable network. The choice of whether to use synchronous or asynchronous proxies is up to the programmer, and can be made at runtime. Here is more information about this feature of ECF’s remote services implementation. XML-RPC provider ECF Indigo has an XML-RPC-based provider, which implements the remote services API. Remote Service invocation through a proxy and/or async proxy is supported too. In addition to being usable for interoperability with existing XML-RPC-based services, it can also be used as an example of how to easily use an existing framework to create a remote service provider. Google wave provider Although discontinued by Google, Wave is an open protocol with an open source implementation of the Wave server available. This means you can still build applications that take advantage of the real time shared editing functionality from within your Eclipse environment using this provider. Already, ECF provides real time shared editing using cola. This is limited to two users on a a document at a time - using the Wave provider, you could have multiple authors collaborating on the same document. Mustafa and Sebastian created a multiplayer Android phone game for EclipseCon this year, using the Wave protocol for concurrency control. Take a look at the results in the video below. ECF on Other OSGi Frameworks You're not limited to running ECF on Equinox anymore: ECF4Felix allows ECF to run on the Felix OSGi framework. So far testing has only been done on Felix. But if you are willing to help with testing ECF Remote Services/RSA on another framework, please send an email to the ecf-dev mailing list. ECF Documentation Project ECF recently started the ECF Documentation Project. This project is an approach to improve the amount and quality of the ECF documentation with the help of the committer, contributor, and consumer communities. It also aims to use of ECF for new and existing consumers. Currently this includes a Users Guide and an Integrators Guide. As a user of ECF, the documentation effort is a huge help in getting ECF to work right within your application. Great credit is due to the ECF team for this, and all other features listed here. ECF wiki: http://wiki.eclipse.org/ECF Remote services section of ECF wiki: http://wiki.eclipse.org/ECF#OSGi_Remote_Services OSGi compendium specification (Chap 13 is Remote Services): http://www.osgi.org/download/r4v42/r4.cmpn.pdf OSGi Enterprise Specification (Chap 122 is RSA): http://www.osgi.org/download/r4v42/r4.enterprise.pdf RSA wiki pages: http://wiki.eclipse.org/Remote_Services_Admin Getting Started with Remote Services: http://wiki.eclipse.org/EIG:Getting_Started_with_OSGi_Remote_Services Asynchronous Proxies (examples): http://wiki.eclipse.org/Asynchronous_Proxies_for_Remote_Services ECF Builder: https://build.ecf-project.org/jenkins/ ECF Github site (other providers, examples, Wave, and Newsreader) : https://github.com/ECF ECF4Felix: https://github.com/ECF/ECF4Felix

A common question relating to REST security is whether or not one can achieve message level integrity in the context of a RESTful web service exchange. Security at the message level (as opposed to transport level security such as HTTPS) presents a number of advantages and is essential for achieving a number of advanced security related goals. When faced with the question of how to achieve message level integrity in REST, the typical reaction of an architect with a WS-* background is to incorporate an XML digital signature in the payload. Technically, including an XML dSig inside a REST payload is certainly possible. After all, XML dSig can be used independently of WS-Security. However there are a number of reasons why this approach is awkward. First, REST is not bound to XML. XML signatures only sign XML, not JSON, and other content types popular with RESTful web services. Also, it is practical to separate the signatures from the payload. This is why WS-Security defines signatures located in SOAP headers as opposed to using enveloped signatures. And most importantly, a REST ‘payload’ by itself has limited meaning without its associated network level entities such as the HTTP verb and the HTTP URI. This is a fundamental difference between REST and WS-*, let me explain further. Below, I illustrate a REST message and a WS-* (SOAP) message. Notice how the SOAP messages has it’s own SOAP headers in addition to transport level headers such as HTTP headers. The reason is simple: WS-* specifications go out of their way to be transport independent. You can take a soap message and send it over HTTP, FTP, SMTP, JMS, whatever. The ‘W’ in WS-* does stand for ‘Web’ but this etymology does not reflect today’s reality. In WS-*, the SOAP envelope can be isolated. All the necessary information needed is in there including the action. In REST, you cannot separate the payload from the HTTP verb because this is what defines the action. You can’t separate the payload from the HTTP URI either because this defines the resource which is being acted upon. Any signature based integrity mechanism for REST needs to have the signature not only cover the payload but also cover those HTTP URIs and HTTP verbs as well. And since you can’t separate the payload from those HTTP entities, you might as well include the signature in the HTTP headers. This is what is achieved by a number of proprietary authentication schemes today. For example Amazon S3 REST authentication and Windows Azure Platform both use HMAC based signatures located in the HTTP Authorization header. Those signatures cover the payload as well as the verb, the URI and other key headers. OAuth v1 also defined a standard signature based token which does just this: it covers the verb, the uri, the payload, and other crucial headers. This is an elegant way to achieve integrity for REST. Unfortunately, OAuth v2 dropped this signature component of the specification. Bearer type tokens are also useful but, as explained by Eran Hammer-Lahav in this post, dropping payload signatures completely from OAuth is very unfortunate.

When to use Apache Camel, a popular JVM/Java environment, and when to use other alternatives.

JmsTemplate is easy for simple message sending. What if we want to add headers, intercept or transform the message? Then we have to write more code. So, how do we solve this common task with more configurability in lieu of more code? First, lets review JMS in Spring. Spring JMS Options JmsTemplate – either to send and receive messages inline Use send()/convertAndSend() methods to send messages Use receive()/receiveAndConvert() methods to receive messages. BEWARE: these are blocking methods! If there is no message on the Destination, it will wait until a message is received or times out. MessageListenerContainer – Async JMS message receipt by polling JMS Destinations and directing messages to service methods or MDBs Both JmsTemplate and MessageListenerContainer have been successfully implemented in Spring applications, if we have to do something a little different, we introduce new code. What could possibly go wrong? Future Extensibility? On many projects new use-cases arise, such as: Route messages to different destinations, based on header values or contents? Log the message contents? Add header values? Buffer the messages? Improved response and error handling? Make configuration changes without having to recompile? and more… Now we have to refactor code and introduce new code and test cases, run it through QA, etc. etc. A More Configurable Solution! It is time to graduate Spring JmsTemplate and play with the big kids. We can easily do this with a Spring Integration flow. How it is done with Spring Integration Here we have a diagram illustrating the 3 simple components to Spring Integration replacing the JmsTemplate send. Create a Gateway interface – an interface defining method(s) that accept the type of data you wish to send and any optional header values. Define a Channel – the pipe connecting our endpoints Define an Outbound JMS Adapter – sends the message to your JMS provider (ActiveMQ, RabbitMQ, etc.) Simply inject this into our service classes and invoke the methods. Immediate Gains Add header & header values via the methods defined in the interface Simple invokation of Gateway methods from our service classes Multiple Gateway methods Configure method level or class level destinations Future Gains Change the JMS Adapter (one-way) to a JMS Gateway (two-way) to processes responses from JMS We can change the channel to a queue (buffered) channel We can wire in a transformer for message transformation We can wire in additional destinations, and wire in a “header (key), header value, or content based” router and add another adapter We can wire in other inbound adapters receiving data from another source, such as SMTP, FTP, File, etc. Wiretap the channel to send a copy of the message elsewhere Change the channel to a logging adapter channel which would provide us with logging of the messages coming through Add the “message-history” option to our SI configuration to track the message along its route and more… Optimal JMS Send Solution The Spring Integration Gateway Interface Gateway provides a one or two way communication with Spring Integration. If the method returns void, it is inherently one-way. The interface MyJmsGateway, has one Gateway method declared sendMyMessage(). When this method is invoked by your service class, the first argument will go into a message header field named “myHeaderKey”, the second argument goes into the payload. package com.gordondickens.sijms; import org.springframework.integration.annotation.Gateway;import org.springframework.integration.annotation.Header; public interface MyJmsGateway { @Gateway public void sendMyMessage(@Header("myHeaderKey") String s, Object o);} Spring Integration Configuration Because the interface is proxied at runtime, we need to configure in the Gateway via XML. Sending the Message package com.gordondickens.sijms; import org.junit.Test;import org.junit.runner.RunWith;import org.springframework.beans.factory.annotation.Autowired;import org.springframework.test.context.ContextConfiguration;import org.springframework.test.context.junit4.SpringJUnit4ClassRunner; @ContextConfiguration("classpath:/com/gordondickens/sijms/JmsSenderTests-context.xml")@RunWith(SpringJUnit4ClassRunner.class)public class JmsSenderTests { @Autowired MyJmsGateway myJmsGateway; @Test public void testJmsSend() { myJmsGateway.sendMyMessage("myHeaderValue", "MY PayLoad"); } Summary Simple implementation Invoke a method to send a message to JMS – Very SOA eh? Flexible configuration Reconfigure & restart WITHOUT recompiling – SWEET!

this tutorial will walk you through how to setup ibatis ( mybatis ) in a simple java project and will present how to work with stored procedures using mysql.the goal os this tutorial is to demonstrate how to execute/call stored procedures using ibatis/ mybatis . pre-requisites for this tutorial i am using: ide: eclipse (you can use your favorite one) database: mysql libs/jars: mybatis , mysql conector and junit (for testing) this is how your project should look like: sample database please run the script into your database before getting started with the project implementation. you will find the script (with dummy data) inside the sql folder. as we are going to work with stored procedures, you will also have to execute a script with procedures. here are the procedures: use `blog_ibatis`;drop procedure if exists `gettotalcity`;delimiter $$use `blog_ibatis`$$create procedure `blog_ibatis`.`gettotalcity` (out total integer)begin select count(*) into total from city;end$$delimiter ; -- -------------------------------------------------------------------------------- use `blog_ibatis`;drop procedure if exists `gettotalcitystateid`;delimiter $$use `blog_ibatis`$$create procedure `blog_ibatis`.`gettotalcitystateid` (in stateid smallint, out total integer)begin select count(*) into total from city where state_id = stateid;end$$delimiter ; -- -------------------------------------------------------------------------------- use `blog_ibatis`;drop procedure if exists `getstates`;delimiter $$use `blog_ibatis`$$create procedure `blog_ibatis`.`getstates` ()begin select state_id, state_code, state_name from state;end$$delimiter ; 1 – spmapper – xml i did not find anything on the user manual about how to call stored procedures, so i decided to search on the mailing list. and i found some tips of how to call stores procedures. on the previous version, ibatis has a special xml tag for stored procedures. but there is no xml tag for it on current mybatis version (version 3). to call a stored procedure usgin mybatis/ibatis 3 you will have to follow some tips: must set the statement type to callable must use the jdbc standard escape sequence for stored procedures: { call xxx (parm1, parm2) } must set the mode of all parameters ( in, out, inout ) all in, out, and inout parameters must be a part of the parametertype or parametermap (discouraged). the only exception is if you are using a map as a parameter object. in that case you do not need to add out parameters to the map before calling , mybatis will add them for you automatically. resulttype or resultmap (more typically) is only used if the procedure returns a result set. important : oracle ref cursors are usually returned as parameters, not directly from the stored proc. so with ref cursors, resultmap and/or resulttype is usually not used. first example: we want to call the procedure gettotalcity and this procedure only have one out parameter, and no in/inout parameter. how to do it? we are going to ser inline parameters in this first example. to use inline parameters, create a pojo class to represent your parameters, set the parametertype to the class you created and you are going to use this notation to represent each parameter: #{parametername, mode=out, jdbctype=integer} mode can be in, out, inout and specify the jdbctype of your parameter to create the mybatis xml configuration, you can use the select ou update tag. do not forget to set the statementtype to callable . here is how our mybatis statement is going to look like: { call gettotalcity(#{total, mode=out, jdbctype=integer})} and this is the pojo class which represents the parameter for gettotalcity procedure: package com.loiane.model; public class param { private int total; public int gettotal() { return total; } public void settotal(int total) { this.total = total; } second example: now we are going to try to call the same stored procedure we demonstrated on the first example, but we are going to use a parametermap, like you used to do in version 2.x. a very important note: this is discouraged, please use inline parameters. let’s declare the param pojo class as a parametermap: and the stored procedure statment: { call gettotalcity(?) } note that now we use “ ? ” (question mark) to represent each parameter. third example: now we are going to call a stored procedure with in and out parameters. let’s follow the same rules as the fisrt example. we are going to use inline parameters and we are going to create a pojo class to represent our parameter. mybatis code: { call gettotalcitystateid( #{stateid, mode=in, jdbctype=integer}, #{total, mode=out, jdbctype=integer})} param2 pojo: package com.loiane.model; public class param2 { private int total; private int stateid; public int gettotal() { return total; } public void settotal(int total) { this.total = total; } public int getstateid() { return stateid; } public void setstateid(int stateid) { this.stateid = stateid; } fourth example: now let’s try to retrieve a resultset from the stored procedure. for this we are going to use a resultmap. { call getstates()} state pojo class: package com.loiane.model; public class state { private int id; private string code; private string name; public int getid() { return id; } public void setid(int id) { this.id = id; } public string getcode() { return code; } public void setcode(string code) { this.code = code; } public string getname() { return name; } public void setname(string name) { this.name = name; } 2- spmapper – annotations now let’s try to do the same thing we did using xml config. annotation for first example (xml): @select(value= "{ call gettotalcity( #{total, mode=out, jdbctype=integer} )}")@options(statementtype = statementtype.callable)object callgettotalcityannotations(param param); it is very similiar to a simple select statement, but we have to set the statement type to callable. to do it, we can use the annotation @options . with annotations, we can only use inline parameters, so we will not be able to represent the second exemple using annotations. annotation for third example (xml): the explanation is the same as first example, i am just going to list the code: @select(value= "{ call gettotalcitystateid( #{stateid, mode=in, jdbctype=integer}, #{total, mode=out, jdbctype=integer})}")@options(statementtype = statementtype.callable)object callgettotalcitystateidannotations(param2 param2); annotation for fourth example (xml): i tried to set the fourth example with annotation, but the only thing i’ve got is this: //todo: set resultmap with annotations/*@select(value= "{ call gettotalcitystateid()}")@options(statementtype = statementtype.callable)/*@results(value = { @result(property="id", column="state_id"), @result(property="name", column="state_name"), @result(property="code", column="state_code"),})*/list callgetstatesannotations(); and it does not work. i tried to search on the mailing list, no luck. i could not find a way to represent a resultmap with annotation and stored procedures. i don’t know if it is a limitation. if you have any clue how to do it, please leave a comment, i will appreciate it! download if you want to download the complete sample project, you can get it from my github account: https://github.com/loiane/ibatis-stored-procedures if you want to download the zip file of the project, just click on download: there are more articles about ibatis to come. stay tooned! from http://loianegroner.com/2011/03/ibatis-mybatis-working-with-stored-procedures/

this tutorial will walk you through how to setup ibatis ( mybatis ) in a simple java project and will present how to work with dynamic queries (sql). pre-requisites for this tutorial i am using: ide: eclipse (you can use your favorite one) database: mysql libs/jars: mybatis , mysql conector and junit (for testing) this is how your project should look like: sample database please run the script into your database before getting started with the project implementation. you will find the script (with dummy data) inside the sql folder. 1 – article pojo i represented the pojo we are going to use in this tutorial with a uml diagram, but you can download the complete source code in the end of this article. the goal of this tutorial is to demonstrate how to retrieve the article information from database using dynamic sql to filter the data. 2 – article mapper – xml one of the most powerful features of mybatis has always been its dynamic sql capabilities. if you have any experience with jdbc or any similar framework, you understand how painful it is to conditionally concatenate strings of sql together, making sure not to forget spaces or to omit a comma at the end of a list of columns. dynamic sql can be downright painful to deal with. while working with dynamic sql will never be a party, mybatis certainly improves the situation with a powerful dynamic sql language that can be used within any mapped sql statement. the dynamic sql elements should be familiar to anyone who has used jstl or any similar xml based text processors. in previous versions of mybatis, there were a lot of elements to know and understand. mybatis 3 greatly improves upon this, and now there are less than half of those elements to work with. mybatis employs powerful ognl based expressions to eliminate most of the other elements. if choose (when, otherwise) trim (where, set) foreach let’s explain each one with examples. 1 – first scenario : we want to retrieve all the articles from database with an optional filter: title. in other words, if user specify an article title, we are going to retrieve the articles that match with the title, otherwise we are going to retrieve all the articles from database. so we are going to implement a condition (if) : select id, title, author from article where id_status = 1 and title like #{title} 2 – second scenario : now we have two optional filters: article title and author. the user can specify both, none or only one filter. so we are going to implement two conditions: select id, title, author from article where id_status = 1 and title like #{title} and author like #{author} 3 – third scenario : now we want to give the user only one option: the user will have to specify only one of the following filters: title, author or retrieve all the articles from ibatis category. so we are going to use a choose element: select id, title, author from article where id_status = 1 and title like #{title} and author like #{author} and id_category = 3 4 – fourth scenario : take a look at all three statements above. they all have a condition in common: where id_status = 1. it means we are already filtering the active articles let’s remove this condition to make it more interesting. select id, title, author from article where title like #{title} and author like #{author} what if both title and author are null? we are going to have the following statement: select id, title, authorfrom articlewhere and what if only the author is not null? we are going to have the fololwing statement: select id, title, authorfrom articlewhereand author like #{author} and both fails! how to fix it? 5 – fifth scenario : we want to retrieve all the articles with two optional filters: title and author. to avoid the 4th scenatio, we are going to use a where element: select id, title, author from article title like #{title} and author like #{author} mybatis has a simple answer that will likely work in 90% of the cases. and in cases where it doesn’t, you can customize it so that it does. the where element knows to only insert “where” if there is any content returned by the containing tags. furthermore, if that content begins with “and” or “or”, it knows to strip it off. if the where element does not behave exactly as you like, you can customize it by defining your own trim element. for example,the trim equivalent to the where element is: select id, title, author from article title like #{title} and author like #{author} the overrides attribute takes a pipe delimited list of text to override, where whitespace is relevant. the result is the removal of anything specified in the overrides attribute, and the insertion of anything in the with attribute. you can also use the trim element with set. 6 – sixth scenario : the user will choose all the categories an article can belong to. so in this case, we have a list (a collection), and we have to interate this collection and we are going to use a foreach element: select id, title, author from article title like #{title} and author like #{author} the foreach element is very powerful, and allows you to specify a collection, declare item and index variables that can be used inside the body of the element. it also allows you to specify opening and closing strings, and add a separator to place in between iterations. the element is smart in that it won’t accidentally append extra separators. note : you can pass a list instance or an array to mybatis as a parameter object. when you do, mybatis will automatically wrap it in a map, and key it by name. list instances will be keyed to the name “list” and array instances will be keyed to the name “array”. the complete article.xml file looks like this: select id, title, author from article where id_status = 1 and title like #{title} select id, title, author from article where id_status = 1 and title like #{title} and author like #{author} select id, title, author from article where id_status = 1 and title like #{title} and author like #{author} and id_category = 3 select id, title, author from article title like #{title} and author like #{author} select id, title, author from article title like #{title} and author like #{author} select id, title, author from article where id_category in #{category} download if you want to download the complete sample project, you can get it from my github account: https://github.com/loiane/ibatis-dynamic-sql if you want to download the zip file of the project, just click on download: there are more articles about ibatis to come. stay tooned! happy coding! from http://loianegroner.com/2011/03/ibatis-mybatis-working-with-dynamic-queries-sql/

This tutorial will walk you through how to setup iBatis (MyBatis) in a simple Java project and will present an example using a discriminator column, in another words it is a inheritance mapping tutorial. Pre-Requisites For this tutorial I am using: IDE: Eclipse (you can use your favorite one) DataBase: MySQL Libs/jars: Mybatis, MySQL conector and JUnit (for testing) This is how your project should look like: Sample Database Please run the script into your database before getting started with the project implementation. You will find the script (with dummy data) inside the sql folder. 1 – POJOs – Beans I represented the beans here with a UML model, but you can download the complete source code in the end of this article. As you can see on the Data Modeling Diagram and the UML diagram above, we have a class Employee and two subclasses: Developer and Manager. The goal of this tutorial is to retrieve all the Employees from the database, but these employees can be an instance of Developer or Manager, and we are going to use a discriminator column to see which class we are going to instanciate. 2 – Employee Mapper – XML Sometimes a single database query might return result sets of many different (but hopefully somewhat related) data types. The discriminator element was designed to deal with this situation, and others, including class inheritance hierarchies. The discriminator is pretty simple to understand, as it behaves much like a switch statement in Java. A discriminator definition specifies column and javaType attributes. The column is where MyBatis will look for the value to compare. The javaType is required to ensure the proper kind of equality test is performed (although String would probably work for almost any situation). SELECT id, name, employee_type, manager_id, info, developer_id, product FROM employee E left join manager M on M.employee_id = E.id left join developer D on D.employee_id = E.id In this example, MyBatis would retrieve each record from the result set and compare its employee type value. If it matches any of the discriminator cases, then it will use the resultMap specified by the case. This is done exclusively, so in other words, the rest of the resultMap is ignored (unless it is extended, which we talk about in a second). If none of the cases match, then MyBatis simply uses the resultMap as defined outside of the discriminator block. So, if the managerResult was declared as follows: Now all of the properties from both the managerResult and developerResult will be loaded. Once again though, some may find this external definition of maps somewhat tedious. Thereforethere’s an alternative syntax for those that prefer a more concise mapping style. For example: SELECT id, name, employee_type, manager_id, info, developer_id, product FROM employee E left join manager M on M.employee_id = E.id left join developer D on D.employee_id = E.id Remember that these are all Result Maps, and if you don’t specify any results at all, then MyBatis willautomatically match up columns and properties for you. So most of these examples are more verbosethan they really need to be. That said, most databases are kind of complex and it’s unlikely that we’ll beable to depend on that for all cases. 3 - Employee Mapper – Annotations We did the configuration in XML, now let’s try to use annotations to do the same thing we did using XML. This is the code for EmployeeMapper.java: package com.loiane.data; import java.util.List; import org.apache.ibatis.annotations.Case;import org.apache.ibatis.annotations.Result;import org.apache.ibatis.annotations.Select;import org.apache.ibatis.annotations.TypeDiscriminator; import com.loiane.model.Developer;import com.loiane.model.Employee;import com.loiane.model.Manager; public interface EmployeeMapper { final String SELECT_EMPLOYEE = "SELECT id, name, employee_type, manager_id, info, developer_id, product " + "FROM employee E left join manager M on M.employee_id = E.id " + "left join developer D on D.employee_id = E.id "; /** * Returns the list of all Employee instances from the database. * @return the list of all Employee instances from the database. */ @Select(SELECT_EMPLOYEE) @TypeDiscriminator(column = "employee_type", cases = { @Case (value="1", type = Manager.class, results={ @Result(property="managerId", column="manager_id"), @Result(property="info"), }), @Case (value="2", type = Developer.class, results={ @Result(property="developerId", column="developer_id"), @Result(property="project", column="product"), }) }) List getAllEmployeesAnnotation();} If you are reading this blog lately, you are already familiar with the @Select and @Result annotations. So let’s skip it. Let’s talk about the @TypeDiscriminator and @Case annotations. @TypeDiscriminator A group of value cases that can be used to determine the result mapping to perform. Attributes: column, javaType, jdbcType, typeHandler, cases. The cases attribute is an array of Cases. @Case A single case of a value and its corresponding mappings. Attributes: value, type, results. The results attribute is an array of Results, thus this Case Annotation is similar to an actual ResultMap, specified by the Results annotation below. In this example: We set the column atribute for @TypeDiscriminator to determine which column MyBatis will look for the value to compare. And we set an array of @Case. For each @Case we set the value, so if the column matches the value, MyBatis will instanciate a object of type we set and we also set an array of @Result to match column with class atribute. Note one thing: using XML we set the id and name properties. We did not set these properties using annotations. It is not necessary, because the column matches the atribute name. But if you need to set, it is going to look like this: @Select(SELECT_EMPLOYEE)@Results(value = { @Result(property="id"), @Result(property="name")})@TypeDiscriminator(column = "employee_type", cases = { @Case (value="1", type = Manager.class, results={ @Result(property="managerId", column="manager_id"), @Result(property="info"), }), @Case (value="2", type = Developer.class, results={ @Result(property="developerId", column="developer_id"), @Result(property="project", column="product"), })})List getAllEmployeesAnnotation(); 4 – EmployeeDAO In the DAO, we have two methods: the first one will call the select statement from the XML and the second one will call the annotation method. Both returns the same result. package com.loiane.dao; import java.util.List; import org.apache.ibatis.session.SqlSession;import org.apache.ibatis.session.SqlSessionFactory; import com.loiane.data.EmployeeMapper;import com.loiane.model.Employee; public class EmployeeDAO { /** * Returns the list of all Employee instances from the database. * @return the list of all Employee instances from the database. */ @SuppressWarnings("unchecked") public List selectAll(){ SqlSessionFactory sqlSessionFactory = MyBatisConnectionFactory.getSqlSessionFactory(); SqlSession session = sqlSessionFactory.openSession(); try { List list = session.selectList("Employee.getAllEmployees"); return list; } finally { session.close(); } } /** * Returns the list of all Employee instances from the database. * @return the list of all Employee instances from the database. */ public List selectAllUsingAnnotations(){ SqlSessionFactory sqlSessionFactory = MyBatisConnectionFactory.getSqlSessionFactory(); SqlSession session = sqlSessionFactory.openSession(); try { EmployeeMapper mapper = session.getMapper(EmployeeMapper.class); List list = mapper.getAllEmployeesAnnotation(); return list; } finally { session.close(); } } The output if you call one of these methods and print: Employee ID = 1 Name = Kate Manager ID = 1 Info = info KateEmployee ID = 2 Name = Josh Developer ID = 1 Project = webEmployee ID = 3 Name = Peter Developer ID = 2 Project = desktopEmployee ID = 4 Name = James Manager ID = 2 Info = info JamesEmployee ID = 5 Name = Susan Developer ID = 3 Project = web Download If you want to download the complete sample project, you can get it from my GitHub account: https://github.com/loiane/ibatis-discriminator If you want to download the zip file of the project, just click on download: There are more articles about iBatis to come. Stay tooned! From http://loianegroner.com/2011/03/ibatis-mybatis-discriminator-column-example-inheritance-mapping-tutorial/

this tutorial will walk you through how to setup ibatis ( mybatis ) in a simple java project and will present an example using a class constructor with arguments. pre-requisites for this tutorial i am using: ide: eclipse (you can use your favorite one) database: mysql libs/jars: mybatis , mysql conector and junit (for testing) this is how your project should look like: sample database please run the script into your database before getting started with the project implementation. you will find the script (with dummy data) inside the sql folder. 1 – pojo i represented the beans here with a uml model, but you can download the complete source code in the end of this article. as you can see, we do not have a default construtor in this class, only a constructor with some arguments. some persistence frameworks requires a default constructor, but you have to be careful with your business logic. let’s say there are a couple of mandatory atributes in your class. nothing is going to stop you if you do not set these atributes and try to insert, update on the database. and you problably will get an exception for that. to prevent this kind of situation, you can create a constructor with the mandatory arguments. and ibatis/ mybatis can handle this situation for you, because you do not need to create a default constructor. 2 – blog mapper – xml while properties will work for most data transfer object (dto) type classes, and likely most of yourdomain model, there may be some cases where you want to use immutable classes. often tables thatcontain reference or lookup data that rarely or never changes is suited to immutable classes.constructor injection allows you to set values on a class upon instantiation, without exposing publicmethods. mybatis also supports private properties and private javabeans properties to achieve this, butsome people prefer constructor injection. the constructor element enables this. in order to inject the results into the constructor, mybatis needs to identify the constructor by the type of its parameters. java has no way to introspect (or reflect) on parameter names. so when creating a constructor element, ensure that the arguments are in order, and that the data types are specified. if you need, you can still map another attributes, such as association, collection in your resultmap. following is the blog.xml file: select idblog as id, name, url from blog 3 - blog mapper – annotations we did the configuration in xml, now let’s try to use annotations to do the same thing we did using xml. this is the code for blogmapper.java: package com.loiane.data; import java.util.list; import org.apache.ibatis.annotations.arg; import org.apache.ibatis.annotations.constructorargs; import org.apache.ibatis.annotations.select; import com.loiane.model.blog; public interface blogmapper { /** * returns the list of all blog instances from the database. * @return the list of all blog instances from the database. */ @select("select idblog as id, name, url from blog ") @constructorargs(value = { @arg(column="id",javatype=integer.class), @arg(column="url",javatype=string.class) }) list selectallblogs(); } let’s take a look at the @constructorargs and @arg annotations: @constructorargs collects a group of results to be passed to a result object constructor. attributes: value, which is an array of args. xml equivalent: constructor @arg a single constructor argument that is part of a constructorargs collection. attributes: id, column, javatype, jdbctype, typehandler. the id attribute is a boolean value that identifies the property to be used for comparisons, similar to the xml element. xml equivalent: idarg, arg we do not need to use the @results annotation because the other attributes has the same name, so mybatis knows how to map them. download if you want to download the complete sample project, you can get it from my github account: https://github.com/loiane/ibatis-constructor if you want to download the zip file of the project, just click on download: there are more articles about ibatis to come. stay tooned! happy coding! once again though, some may find this external definition of maps somewhat tedious. thereforethere’s an alternative syntax for those that prefer a more concise mapping style.

This tutorial will present examples using advanced result mappings, how to handle mappings with association, collections, the n+1 problem, and more.

java classes can get big and hairy, making it difficult to find the method you’re looking for when browsing or editing a class. there is no specific order to where methods can be in a class and different developers have different preferences about where to put them. you could use the mouse wheel and scroll ferociously until you eventually find the method or you could even use page down/page up on your keyboard. but these methods can be time-consuming and haphazard, especially when the class has lots of methods or they’re scattered in an arbitrary order. luckily, eclipse has a number of fast and easy ways to help you navigate methods in a class, especially using the keyboard. i’ll discuss some of those keyboard shortcuts and also which ones to use when. quick outline the quick outline is basically a scaled-down popup version of the outline view. the main advantage over the outline view is that it has a search box that allows you to search for a method. here’s how to use the quick outline: press ctrl+o from anywhere within the class. type a search term in the search box and eclipse will just show all methods that match the search term. by default eclipse does an exact match search, but you can use wildcards. once you see the method you’re interested in, press down to select the method (if it’s not selected already). press enter once the method is selected. eclipse will take you directly to the method’s declaration. this is an example of the popup for java’s arraylist . searching for *rem will search for all method names that contain the word rem . here’s an example: notes: sort the view using the the down arrow menu in the top right corner. it makes it easier to find methods by scanning. resize the quick outline popup to see more methods. eclipse remembers the size of the popup for the next time you open it. next member & previous member another way to move between methods is to use two features called go to next member and go to previous member. when you press ctrl+shift+down , eclipse moves the cursor to the next method in the class. pressing ctrl+shift+up moves to the previous method. here’s a video to give you a quick example of how these shortcuts work: this shortcut works best if you’re already positioned in a method or if the class has few fields. that’s because to eclipse a member can either be a method or a field. if you’re at the top of the class, you have to move through all the fields before you actually start moving through the methods themselves, a time-consuming process especially for bigger classes with lots of fields. it helps to generate getters and setters at the bottom of the class because you don’t have to navigate through them to get to the useful methods. open declaration if you’ve got lots of private methods in your class then open declaration might be the best way to navigate between them. when you’re positioned on a method call and press f3 , eclipse takes you directly to the definition of that method. for example, if you’re busy in the method process() and your cursor’s positioned on initprocessing() , pressing f3 will take you directly to the declaration for that method further down the class. public void process() { //do things... initprocessing(); //... } ... private void initprocessing() { //init something... } this feature works very well with alt+left (backward history). see the section below for more details about the backward history. navigating back to a previously viewed method while browsing code, you’ll often want to return to the previous method you were viewing once you’re done viewing the method it calls. to do this, use alt+left (backward history) to move back to the last navigation point. this feature isn’t specific to just methods, but also works for navigating between previously visited editors. but it works great if you’ve just been browsing methods within a class. quick mentions eclipse’s outline view also allows easy navigation but mostly with the mouse. you could navigate to the view using alt+shift+q, o , and you can move to methods by typing their first letter, but i’ve found the quick outline to be more keyboard friendly. also, the outline view doesn’t support wildcard searches. you can also use eclipse’s call hierarchy ( ctrl+alt+h ) especially if you’re trying to understand the flow of methods in a class and move between them easily. knowing how to navigate between views and editors with the keyboard helps a lot since you’ll be moving between the call hierarchy view and editors a lot. what should i use when? use next/previous member shortcut if the class is small or you have a good idea of where other methods are in relation to the current method (eg. are they above/below the current method). use the quick outline if you don’t know the class too well or there are lots of methods in the class. use open declaration if you’re moving between many private methods of the class. it’s normally the fastest way to move to another private method in the class, but only if you’re already positioned in a method that calls it. from http://eclipseone.wordpress.com/2011/02/21/the-easiest-ways-to-navigate-methods-in-a-class-using-eclipse-keyboard-shortcuts/

This tutorial will walk you through how to setup iBatis (MyBatis) in a simple Java project and will present examples using simple insert, update, select and delete statements using annotations. This is the third tutorial of the iBatis/MyBatis series, you can read the first 2 tutorials on the following links: Introduction to iBatis (MyBatis), An alternative to Hibernate and JDBC Getting Started with iBatis (MyBatis): XML Configuration iBatis/ MyBatis 3 offers a new feature: annotations. But it lacks examples and documentation about annotations. I started to explore and read the MyBatis mailing list archive to write this tutorial. Another thing you will notice is the limitation related to annotations. I am going to demonstrate some examples that you can do with annotations in this tutorial. All the power of iBatis is in its XMl configuration. So let’s play a little bit with annotations. It is much simpler and you can use it for simple queries in small projects. As I already mentioned, if you want something more complex, you will have to use XML configuration. One more thing before we get started: this tutorial is the same as the previous one, but instead of XML, we are going to use annotations. Pre-Requisites For this tutorial I am using: IDE: Eclipse (you can use your favorite one) DataBase: MySQL Libs/jars: Mybatis, MySQL conector and JUnit (for testing) This is how your project should look like: Sample Database Please run this script into your database before getting started with the project implementation: I will not post the sample database here again. You can get it from the previous post about iBatis or download this sample project. The files are the same. 1 – Contact POJO We will create a POJO class first to respresent a contact with id, name, phone number and email address – same as previous post. 2 – ContactMapper In this file, we are going to set up all the queries using annotations. It is the MyBatis-Interface for the SQLSessionFactory. A mapper class is simply an interface with method definitions that match up against the SqlSession methods. Mapper interfaces do not need to implement any interface or extend any class. As long as the method signature can be used to uniquely identify a corresponding mapped statement. Mapper interfaces can extend other interfaces. Be sure that you have the statements in the appropriate namespace when using XML binding to Mapper interfaces. Also, the only limitation is that you cannot have the same method signature in two interfaces in a hierarchy (a bad idea anyway). A mapperclass is simply an interface with method definitions that match up against the SqlSession methods. You can create some strings with the SQL code. Remember it has to be the same code as in XML Configuration. package com.loiane.data; import java.util.List; import org.apache.ibatis.annotations.Delete;import org.apache.ibatis.annotations.Insert;import org.apache.ibatis.annotations.Options;import org.apache.ibatis.annotations.Param;import org.apache.ibatis.annotations.Result;import org.apache.ibatis.annotations.Results;import org.apache.ibatis.annotations.Select;import org.apache.ibatis.annotations.Update; import com.loiane.model.Contact; public interface ContactMapper { final String SELECT_ALL = "SELECT * FROM CONTACT"; final String SELECT_BY_ID = "SELECT * FROM CONTACT WHERE CONTACT_ID = #{id}"; final String UPDATE = "UPDATE CONTACT SET CONTACT_EMAIL = #{email}, CONTACT_NAME = #{name}, CONTACT_PHONE = #{phone} WHERE CONTACT_ID = #{id}"; final String UPDATE_NAME = "UPDATE CONTACT SET CONTACT_NAME = #{name} WHERE CONTACT_ID = #{id}"; final String DELETE = "DELETE FROM CONTACT WHERE CONTACT_ID = #{id}"; final String INSERT = "INSERT INTO CONTACT (CONTACT_EMAIL, CONTACT_NAME, CONTACT_PHONE) VALUES (#{name}, #{phone}, #{email})"; /** * Returns the list of all Contact instances from the database. * @return the list of all Contact instances from the database. */ @Select(SELECT_ALL) @Results(value = { @Result(property="id", column="CONTACT_ID"), @Result(property="name", column="CONTACT_NAME"), @Result(property="phone", column="CONTACT_PHONE"), @Result(property="email", column="CONTACT_EMAIL") }) List selectAll(); /** * Returns a Contact instance from the database. * @param id primary key value used for lookup. * @return A Contact instance with a primary key value equals to pk. null if there is no matching row. */ @Select(SELECT_BY_ID) @Results(value = { @Result(property="id"), @Result(property="name", column="CONTACT_NAME"), @Result(property="phone", column="CONTACT_PHONE"), @Result(property="email", column="CONTACT_EMAIL") }) Contact selectById(int id); /** * Updates an instance of Contact in the database. * @param contact the instance to be updated. */ @Update(UPDATE) void update(Contact contact); /** * Updates an instance of Contact in the database. * @param name name value to be updated. * @param id primary key value used for lookup. */ void updateName(@Param("name") String name, @Param("id") int id); /** * Delete an instance of Contact from the database. * @param id primary key value of the instance to be deleted. */ @Delete(DELETE) void delete(int id); /** * Insert an instance of Contact into the database. * @param contact the instance to be persisted. */ @Insert(INSERT) @Options(useGeneratedKeys = true, keyProperty = "id") void insert(Contact contact);} @Select The @Select annotation is very simple. Let’s take a look at the first select statment of this class: selectAll. Note that you don’t need to use the mapping if your database table columns mach the name of the class atributes. I used different names to use the @Result annotation. If table columns match with atribute names, you don’t need to use the @Result annotation. Not let’s take a look on the second method: selectById. Notice that we have a parameter. It is a simple parameter – easy to use when you have a single parameter. @Update Let’s say you want to update all the columns. You can pass the object as parameter and iBatis will do all the magic for you. Remember to mach the parameter name with the atribute name, otherwise iBatis can get confused, Now let’s say you want to use 2 or 3 paramaters, and they don’t belong to an object. If you take a look at iBatis XML configuration you will see you have to set the option parameterType (remember?) and specify you parameter type in it, in another words, you can use only one parameter. If you are using annotation, you can use more than one parameter using the @Param annotation. @Delete The @Delete annotation is also very simple. It follows the previous rules related to parameters. @Insert The @Insert annotation also follows the rules related to parameters. You can use an object or use the @Param annotation to specify more than one parameter. What about the generation key? Well, if your database supports auto generation key, you can set it up using annotations with the @Options annotation. You will need to specify the option useGeneratedKeys and keyProperty. If your database does not support auto generation key, sorry, but I still did not figure out how to do it (in last case, use can do it manually and then pass as parameter to your insert query). 3 – MyBatisConnectionFactory Every MyBatis application centers around an instance of SqlSessionFactory. A SqlSessionFactory instance can be acquired by using the SqlSessionFactoryBuilder. SqlSessionFactoryBuilder can build a SqlSessionFactory instance from an XML configuration file, of from a custom prepared instance of the Configuration class. An observation about this file: on the previous example, we set the mappers on the iBatis Configuration XML file. Using annotations, we will set the mapper manually. In a future example, I’ll show you how to work with XML and Annotations together. package com.loiane.dao; import java.io.FileNotFoundException;import java.io.IOException;import java.io.Reader; import org.apache.ibatis.io.Resources;import org.apache.ibatis.session.SqlSessionFactory;import org.apache.ibatis.session.SqlSessionFactoryBuilder; import com.loiane.data.ContactMapper; public class MyBatisConnectionFactory { private static SqlSessionFactory sqlSessionFactory; static { try { String resource = "SqlMapConfig.xml"; Reader reader = Resources.getResourceAsReader(resource); if (sqlSessionFactory == null) { sqlSessionFactory = new SqlSessionFactoryBuilder().build(reader); sqlSessionFactory.getConfiguration().addMapper(ContactMapper.class); } } catch (FileNotFoundException fileNotFoundException) { fileNotFoundException.printStackTrace(); } catch (IOException iOException) { iOException.printStackTrace(); } } public static SqlSessionFactory getSqlSessionFactory() { return sqlSessionFactory; } } 4 – ContactDAO Now that we set up everything needed, let’s create our DAO. To call the sql statments, we need to do one more configuration, that is to set and get the mapper from the SqlSessionFactory. Then we just need to call the mapper method. It is a little bit different, but it does the same thing. package com.loiane.dao; import java.util.List; import org.apache.ibatis.session.SqlSession;import org.apache.ibatis.session.SqlSessionFactory; import com.loiane.data.ContactMapper;import com.loiane.model.Contact; public class ContactDAO { private SqlSessionFactory sqlSessionFactory; public ContactDAO(){ sqlSessionFactory = MyBatisConnectionFactory.getSqlSessionFactory(); } /** * Returns the list of all Contact instances from the database. * @return the list of all Contact instances from the database. */ public List selectAll(){ SqlSession session = sqlSessionFactory.openSession(); try { ContactMapper mapper = session.getMapper(ContactMapper.class); List list = mapper.selectAll(); return list; } finally { session.close(); } } /** * Returns a Contact instance from the database. * @param id primary key value used for lookup. * @return A Contact instance with a primary key value equals to pk. null if there is no matching row. */ public Contact selectById(int id){ SqlSession session = sqlSessionFactory.openSession(); try { ContactMapper mapper = session.getMapper(ContactMapper.class); Contact list = mapper.selectById(id); return list; } finally { session.close(); } } /** * Updates an instance of Contact in the database. * @param contact the instance to be updated. */ public void update(Contact contact){ SqlSession session = sqlSessionFactory.openSession(); try { ContactMapper mapper = session.getMapper(ContactMapper.class); mapper.update(contact); session.commit(); } finally { session.close(); } } /** * Updates an instance of Contact in the database. * @param name name value to be updated. * @param id primary key value used for lookup. */ public void updateName(String name, int id){ SqlSession session = sqlSessionFactory.openSession(); try { ContactMapper mapper = session.getMapper(ContactMapper.class); mapper.updateName(name, id); session.commit(); } finally { session.close(); } } /** * Insert an instance of Contact into the database. * @param contact the instance to be persisted. */ public void insert(Contact contact){ SqlSession session = sqlSessionFactory.openSession(); try { ContactMapper mapper = session.getMapper(ContactMapper.class); mapper.insert(contact); session.commit(); } finally { session.close(); } } /** * Delete an instance of Contact from the database. * @param id primary key value of the instance to be deleted. */ public void delete(int id){ SqlSession session = sqlSessionFactory.openSession(); try { ContactMapper mapper = session.getMapper(ContactMapper.class); mapper.delete(id); session.commit(); } finally { session.close(); } } 5 – Mapper Configuration File The MyBatis XML configuration file contains settings and properties that have a dramatic effect on how MyBatis behaves. This time, we do not need to configure alias or xml config files. We did all the magic with annotations, so we have a simple config file with only the information about the database we want to connect with. Download I suggest you to take a look at the org.apache.ibatis.annotations package and try to find out what each annotation can do. Unfortunatelly, you won’t find much documentation or examples on MyBatis website. I also created a TestCase class. If you want to download the complete sample project, you can get it from my GitHub account: https://github.com/loiane/ibatis-annotations-helloworld If you want to download the zip file of the project, just click on download: There are more articles about iBatis to come. Stay tooned! In next articles, I’m going to demonstrate how to implement the feature using XML and then Annotations (when it is possible). Happy Coding! From http://loianegroner.com/2011/02/getting-started-with-ibatis-mybatis-annotations/

This tutorial will walk you through how to setup iBatis (MyBatis) in a simple Java project and will present examples using simple insert, update, select and delete statements.