Grails 3.1 allows us to build a runnable WAR file for our application with the package command. We can run this WAR file with Java using the -jar option. In Grails 3.0 the package command also created a JAR file that could be executed as standalone application. Let's see how we can still create the JAR with Grails 3.1.
First we use the package command to create the WAR file. The file is generated in the directory build/libs. The WAR file can be run with the command java -jar sample-0.1.war if the file name of our WAR file is sample-0.1.war. It is important to run this command in the same directory as where the WAR file is, otherwise we get an ServletException when we open the application in our web browser (javax.servlet.ServletException: Could not resolve view with name '/index' in servlet with name 'grailsDispatcherServlet').
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Interesting links for week 5 2016:
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In a previous post we learned how to save the application PID in a file when we start our Grails application. We can also save the port number the application uses in a file when we run our Grails application. We must use the class EmbeddedServerPortFileWriter and add it as a listener to the GrailsApp instance. By default the server port is saved in a file application.port. But we can pass a custom file name or File object to the constructor of the EmbeddedServerPortFileWriter class.
In the following example we use the file name application.server.port to store the port number:
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The Spring Cloud project has several sub projects. One of them is the Spring Cloud Config Server. With the Config Server we have a central place to manage external properties for applications with support for different environments. Configuration files in several formats like YAML or properties are added to a Git repository. The server provides an REST API to get configuration values. But there is also a good integration for client applications written with Spring Boot. And because Grails (3) depends on Spring Boot we can leverage the same integration support. Because of the Spring Boot auto configuration we only have to add a dependency to our build file and add some configuration.
Before we look at how to use a Spring Cloud Config server in our Grails application we start our own server for testing. We use a local Git repository as backend for the configuration. And we use the Spring Boot CLI to start the server. We have the following Groovy source file to enable the configuration server:
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Recently I wanted to use the Tuckey UrlRewriteFilter. It is described as: A Java Web Filter for any compliant web application server, which allows you to rewrite URLs before they get to your code.
I wanted to load my urlrewrite.xml as a Spring (classpath) resource, instead of loading it from the default location provided by the UrlRewriteFilter. The default behavior loads the configuration file from /WEB-INF/ulrewrite.xml. In my case I wanted to load it from the /src/main/resources folder, which is the root of my classpath.
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To get objects from the registry or context we specify the type of the object we want. Ratpack will find the object(s) that match the given type. If we use the get method then the last object added to the registry with the given type is returned. To get multiple objects we use the getAll method. The methods returns an Iterable with the found objects where the last added objects are returned as first elements.
In the following example specification we have a Registry with some objects, of which two are of type User. Next we use the get and getAll methods to get the objects.
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We can use the wiretap method of the Promise interface to listen in on results. We write an Action implementation which has the result of a Promise encapsulated in a Result object. The wiretap method can be used to do something with a Promise value without interrupting a method chain.
In the following example we tap in on Promise results:
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I have seen several projects where the developers had implemented caching all over the place. Caches were causing a large increase of heap usage, and users were always complaining that they were not seeing the latest data. My opinion on this is that a decision to add caching should not be taken lightly. Adding a cache means adding a lot of additional (or so-called accidental) complexity and also has a functional impact on the users. Adding a cache raises a lot of questions that need to be answered:
- What if cached data is updated, should the cached record be updated or evicted too?
- What should we do in a distributed environment, use a distributed cache? Is this distributed cache scalable?
- Do we get the performance improvements we're expecting?
- What is an acceptable delay for users to see the updated data?
- How many elements should we store in the cache?
- What eviction policy do we need when not all data fits in the cache?
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In a Spock specification we write our assertion in the then: or expect: blocks. If we need to write multiple assertions for an object we can group those with the with method. We specify the object we want write assertions for as argument followed by a closure with the real assertions. We don't need to use the assert keyword inside the closure, just as we don't have to use the assert keyword in an expect: or then: block.
In the following example specification we have a very simple implementation for finding an User object. We want to check that the properties username and name have the correct value.
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Interesting links for week 4 2016:
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