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To gain access to the data layer, we need to create a service layer bean to inject data into and call the data access layer. To do so, we need to create an interface that is implemented by the e-commerce service. This code will reside in the service layer and not change when you migrate to a different ORM solution. By keeping code in the proper application layers, you eliminate the need for rework by building components in Spring that serve a separate purpose than the data access layer. Listings 8-8 and 8-9 show the EcommerceService and EcommerceServiceImpl that will be wired into the ApplicationContext for this application. Listing 8-8. EcommerceService package com.af.core.services; import com.af.core.domain.Product; import java.util.List; public interface EcommerceService { public abstract List<Product> getProducts() throws Exception; public abstract int insertProduct(Product product) throws Exception; public abstract int deleteProduct(Product product) throws Exception; public abstract int updateProduct(Product product) throws Exception; } Listing 8-9. EcommerceServiceImpl package com.af.core.services; import com.af.core.dao.EcommerceDao; import com.af.core.domain.Product; import java.util.List; import java.io.Serializable; public class EcommerceServiceImpl implements Serializable, EcommerceService { // Injected by Spring EcommerceDao ecommerceDao; public EcommerceDao getEcommerceDao() { return ecommerceDao; }

Figure 22-1. Alternative PHP Cache (APC) comes with an interface that displays memory allocation and the files currently within the cache. Application Profiling Often custom code and modules that have performed reasonably well for small-scale sites can become a bottleneck when moved into production. CPU-intensive code loops, memory-hungry algorithms, and large database retrievals can be identified by profiling your code to determine where PHP is spending most of its time and thus where you ought to spend most of your time debugging. See 21 for more information on PHP debuggers and profilers. If, even after adding an opcode cache and optimizing your code, your web server cannot handle the load, it is time to get a beefier box with more or faster CPUs or to move to a different architecture with multiple web server frontends.

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The RAM footprint of the web server process serving the request includes all of the modules loaded by the web server (such as Apache s mod_mime, mod_rewrite, etc.) as well as the memory used by the PHP interpreter. The more web server and Drupal modules that are enabled, the more RAM used per request.

public void setEcommerceDao(EcommerceDao ecommerceDao) { this.ecommerceDao = ecommerceDao; } // Products public List<Product> getProducts() throws Exception { return ecommerceDao.getProducts(); } public int insertProduct(Product product) throws Exception { return ((Integer)ecommerceDao.insertProduct(product)); } public int deleteProduct(Product product) throws Exception { return ((Integer)ecommerceDao.deleteProduct(product)); } public int updateProduct(Product product) throws Exception { return ((Integer)ecommerceDao.updateProduct(product)); } } Again, this bean will not change if there are any changes to this application s ORM solutions. The only upgrade we will need for these beans is to make them transactional. The properties in Table 8-2 are held in the application.properties file, which is read into context during the initialization of the application when your web server starts. You can see the application.properties file in Listing 8-10.

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Because RAM is a finite resource, you should determine how much is being used on each request and how many requests your web server is configured to handle. To see how much real RAM is being used on average for each request, use a program like top to see your list of processes. In Apache, the maximum number of simultaneous requests that will be served is set using the MaxClients directive. A common mistake is thinking the solution to a saturated web server is to increase the value of MaxClients. This only complicates the problem, since you ll be hit by too many requests at once. That means RAM will be exhausted, and your server will start disk swapping and become unresponsive. Let s assume, for example, that your web server has 2GB of RAM and each Apache request is using roughly 20MB (you can check the actual value by using top on Unix or Task Manager on Windows). You can calculate a good value for MaxClients by using the following formula; keep in mind the fact that you will need to reserve memory for your operating system and other processes: 2GB RAM / 20MB per process = 100 MaxClients If your server consistently runs out of RAM even after disabling unneeded web server modules and profiling any custom modules or code, your next step is to make sure the database and the operating system are not the causes of the bottleneck. If they are, then add more RAM. If the database and operating system are not causing the bottlenecks, you simply have more requests than you can serve; the solution is to add more web server boxes.

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