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We will start with poor performance of the data selection code, particularly DefaultInvoiceService. It is not handling paging; in fact, if we used the command s 1-1 Supplier% to display one invoice, our code will select all rows from the t_invoice table. But that s not all it will also select the appropriate rows from tables t_supplier, t_invoice_line, and t_discount. In total, using our test data set, our application will create 50 Supplier, 5,000 Invoice, 25,000 InvoiceLine, and 50,000 Discount objects only to throw away virtually all of them. The memory profile in Figure 22-4 clearly shows the steep increase in heap usage.

Figure 2-12 Teamprise Team Explorer in Mac OS X You will see in 6 that VSTS has these features embedded out of the box Microsoft uses Microsoft Office SharePoint Server/Windows SharePoint Services for collaboration among team members, for example Active Directory is used for authentication and security SQL Server obviously is the data repository giving us access to tools such as SQL Server Analysis Services for analytics and SQL Server Report Builder for reports Here Microsoft has done a good job in giving us tools that will help us get the job done Forrester Research also mentions that ALM 20 should be repository neutral They say that there should not be a single repository but many, so we are not required to use the storage solution that the vendor proposes.

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Figure 22-4. Inefficient memory usage You can see that the heap usage has shot up from under 20MB to almost 100MB during the call to DefaultInvoiceService.findBySupplierName. We need to move paging to the services and data access tiers. Let s refactor the InvoiceService.findBySupplierName method to support paging; Listing 22-3 shows the InvoiceService and InvoiceDao interfaces with support for paging. Listing 22-3. Support for Paging in InvoiceService and InvoiceDao InvoiceService.java: public interface InvoiceService { List<Invoice> findBySupplierName(String name, int firstResult, int maxResults); void save(Invoice invoice); Invoice findById(Long id);

To create policy categories, right-click Policy Management in SQL Server Management Studio Object Explorer and select Manage Categories from the context menu. This will display the Manage Policy Categories dialog box, shown in Figure 2-17.

} InvoiceDao.java: public interface InvoiceDao { void save(Invoice invoice); Invoice getById(Long id); List<Invoice> getBySupplierName(String name, int firstResult, int maxResults); } We needed to modify both the InvoiceService and InvoiceDao interfaces and their appropriate implementations. If we had only modified the InvoiceService, the code would not be too different from paging on the client side. The DefaultInvoiceService implementation of the InvoiceService is simply going to pass the paging information to the HibernateInvoiceDao (see Listing 22-4). Listing 22-4. Paging in HibernateInvoiceDao public class HibernateInvoiceDao extends HibernateDaoSupport implements InvoiceDao { public void save(Invoice invoice) { getHibernateTemplate().saveOrUpdate(invoice); } public Invoice getById(Long id) { return (Invoice) DataAccessUtils.uniqueResult(getHibernateTemplate(). find("from Invoice where id= ", id)); } @SuppressWarnings({"unchecked"}) public List<Invoice> getBySupplierName( final String name, final int firstResult, final int maxResults) { return (List<Invoice>) getHibernateTemplate().execute(new HibernateCallback() { public Object doInHibernate(Session session) throws HibernateException, SQLException { Query query = session.createQuery( "from Invoice where supplier.name like :name"); query.setString("name", name); query.setFirstResult(firstResult); query.setMaxResults(maxResults); return query.list(); } }); } } With this modification, running s 1-1 Supplier% in the CLI application completes in 182 milliseconds, which is a significant improvement over the previous 10,900 milliseconds! However, it still performs three select statements, even though we only need the data from the Invoice objects. We have configured Hibernate to eagerly load all associations. We need to modify the Hibernate mapping files and enable lazy loading for all classes. Listing 22-5 shows the required modification in the Invoice.hbm.xml mapping file.

Listing 22-5. Hibernate Mapping Files < xml version="1.0" > <!DOCTYPE hibernate-mapping PUBLIC "-//Hibernate/Hibernate Mapping DTD 3.0//EN" "http://hibernate.sourceforge.net/hibernate-mapping-3.0.dtd"> <hibernate-mapping default-lazy="true"> <class name="com.apress.prospring2.ch23.domain.Invoice" table="t_invoice"> ... </class> </hibernate-mapping> To enable lazy loading for all mapped classes, we need to change the value of the default-lazy to true in all mapping files. Alternatively, we can simply remove the default-lazy attribute, because Hibernate by default considers all associations to be lazily loaded. We then run the profiler again to find out how it improved the performance of our application. And indeed, the profiler shows another significant decrease in the required time: from 182 milliseconds down to 6 milliseconds (see Figure 22-5).

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