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Using LINQ to Entities, we query for all the poets, and for each poet we print out the poet s name and the details for each of their poems The code is pretty simple, but it does use a couple of nested for loops The last block of code uses the vwLibrary entity This entity is based on our vwLibrary view This view joins the tables together to flatten things out a bit and provide a cleaner perspective When we query for each poet against the vwLibraries entity set, we can get by with just one for loop The output is a little different because we repeat the poet s name for each poem There is one last thing to note in this example We didn t insert the poets, poems, and meters using the vwLibrary entity because views are always read-only in most database systems.

The list gets bound upon the first request of the page. protected void Page_Load(object sender, EventArgs e) { if (!IsPostBack) { SqlConnection cn = new SqlConnection( ConfigurationManager.ConnectionStrings ["localPubs"].ToString()); string sql = "select state from authors group by state order by state"; SqlCommand cm = new SqlCommand(sql, cn); cn.Open(); ddlState.DataSource = cm.ExecuteReader(); ddlState.DataTextField = "state"; ddlState.DataBind(); cn.Close(); ddlState.Items.Insert(0, ""); } } All postbacks are then fired by a change made to the DropDownList. Here s where you ll use a cached DataView that already has an index prepared for the state column of the authors table. By applying a row filter to the view, you re leveraging the index on the column you sorted by when creating the view. By keeping it in the cache you are once again using only a single instance of the data instead of returning to the database each time the user selects a state. private DataView GetAuthors() { DataSet ds; DataView dv; dv = (DataView)Cache["AuthorData"]; if (dv == null) { ds = new DataSet(); SqlConnection cn = new SqlConnection( ConfigurationManager.ConnectionStrings ["localPubs"].ToString());

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So, with DDT you don t drive the design from the unit tests. This is not to say that the design in a DDT project isn t affected by the tests. Inevitably you ll end up basing the design around testability. As we ll explore in 3, code that hasn t been written with testability in mind is an absolute pig to test. Therefore, it s important to build testability into your designs from as early a stage as possible. It s no coincidence that code that is easily tested also generally happens to be well-designed code. To put it another way, the qualities of a code design that result in it being easy to unit-test are also the same qualities that make the code clear, maintainable, flexible, malleable, well factored, and highly modular. It s also no coincidence that the ICONIX Process and DDT place their primary emphasis on creating designs that have these exact qualities.

In Entity Framework, we can t insert (or update, or delete) entities that are based on views Of course, we ll show you exactly how to overcome this little challenge in many of the recipes in this book!.

SqlCommand cm = new SqlCommand("select * from authors", cn); new SqlDataAdapter(cm).Fill(ds); dv = new DataView (ds.Tables[0], "", "state", DataViewRowState.CurrentRows); Cache.Insert("AuthorData", dv); } return dv; } protected void ddlState_SelectedIndexChanged(object sender, EventArgs e) { DataView dv = GetAuthors(); dv.RowFilter = string.Format("state = '{0}'", ddlState.SelectedValue); gvAuthors.DataSource = dv; gvAuthors.DataBind(); } Here again, you could go back to the database with each request that comes into the server, but you ll be much better off keeping a cache of this data in memory and using the DataView to create an index on the data you ll be querying upon. If the users can choose the column they want to apply the filter to, you can apply a strategy similar to the one you used in the sorting example, creating a cached DataView per column being queried upon. The problem with an in-memory cache is, of course, concurrency and dirty data. When someone comes along and makes a change to the data, the cache entry is no longer useful to you. In 11, we take a look at the new facility that s been added to 2.0 to create a dependency between a cache entry and the relational database where the entry came from, the SqlCacheDependency. We also examine some overall strategies for managing latency and concurrency when modifying data.

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