Working with Data Sets in .NET framework

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62 Working with Data Sets
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require SQL Server CE, DataSet objects are still the best way to display the data to the user and to persist all of the data (or subsets of it) as XML files
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DataSet Class Limitations
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DataSet objects do not have an ad hoc query capability Instead, the data in a DataSet object is accessed programmatically, not through a SELECT statement Properties and methods of the data objects are used to access the data Thus, you access all rows of a data table by iterating through its Rows collection with a For Each statement; you access all rows of a data table that meet a certain criteria through the table s Select method; and you access the rows of a relationship by using the parent row s GetChildRows method
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621 Creating and Accessing DataSet, DataTable, and DataView Objects Creating a DataSet object is easy: You simply new it, with the option of specifying a name, as follows:
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dsetDB = new DataSet("AnyName");
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Within a DataSet object, you can create a DataTable object and populate it from scratch, as shown in Listing 61
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Listing 61: Building a DataTable Object from Scratch
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private void CreateTable() { // Create an empty table DataTable dtabCustomers = new DataTable("Customers"); // Create three columns DataColumn dcolID = new DataColumn("ID"); dcolIDDataType = typeof(int); dcolIDAutoIncrement = true; dcolIDAutoIncrementSeed = 1; dcolIDAutoIncrementStep = 1; DataColumn dcolName = new DataColumn("Name"); dcolNameDataType = typeof(string ); DataColumn dcolAddress = new DataColumn("Address"); dcolAddressDataType = typeof(string ); // Add the columns to the table
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dtabCustomersColumnsAdd(dcolID); dtabCustomersColumnsAdd(dcolName); dtabCustomersColumnsAdd(dcolAddress); // Add a primary key constraint dtabCustomersConstraintsAdd("PKCust", dcolID, true); // Add two rows to the table DataRow drowCust; drowCust = dtabCustomersNewRow(); drowCust["Name"] = "Amalgamated United"; drowCust["Address"] = "PO Box 123, 98765"; dtabCustomersRowsAdd(drowCust); drowCust = dtabCustomersNewRow(); drowCust["Name"] = "United Amalgamated"; drowCust["Address"] = "PO Box 987, 12345"; dtabCustomersRowsAdd(drowCust); } }
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However, the most common way to create and populate a data table is to execute a SELECT statement against a database and place the results into a DataTable object These SELECT statements can be as simple as SELECT * FROM Products or as complex as a multitable join with an aggregate function and grouping Different data tables in the same data set can be drawn from different databases We cover the details of moving data between a data set and a database in the Microsoft SQL Server CE and Microsoft SQL Server sections later in this chapter For now, we are only interested in accessing the data as it resides in the data set and in the movement of data between the data set and the user
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6211 Understanding Data Tables
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A data table consists of a collection of columns and a collection of rows DataRow objects are a collection of Items, which are the fields of the row To access a value in a data table you must specify the row number and column identifier (either column name or number), as shown in the following code, which sets the CategoryName column of the second row in the dtabCategories data table to Muzzy:
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dtabCategoriesRows[1]["CategoryName"] = "Muzzy";
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You can also use the DataTable class s Select method to access rows by value The following code returns the array of rows whose CategoryName is Widgets:
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62 Working with Data Sets
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dsetDBTables["Categories"]Select("CategoryName = 'Widgets'");
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To save the reference to the first row in the array, you would code the following line (Remember that arrays are zero-based; the first row of this array is row 0)
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drowX = dsetDBTables["Categories"]Select( "CategoryName = 'Widgets'")[0];
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Accessing columns by name makes your code more readable, but the code will execute more quickly if you access columns by index value rather than by name A good performance strategy is to look up the row index value for the name once and thereafter access the column by index value We often think of a data table as a two-dimensional object, but we should think of it as a three-dimensional object Each data element (ie, each field) in a data table can have up to four values, referred to as versions: Current, Original, Proposed, and Default Having four possible values for each field does not necessarily make the data table four times as large, because values exist only when necessary The Default version, for instance, applies at the column level, not the individual field level There is at most one Default value per column, not one for each field In addition to multiple possible field versions, individual rows have a status value, such as Unchanged, Modified, Added, or Deleted Understanding the meaning of the versions and status codes, and the relationship between them, is essential when programming for data sets To illustrate this, we focus on two field versions, Original and Current, and two row statuses, Unchanged and Modified When new rows are added to a data table, the Original and Current values are equal to each other and the status is set to Unchanged When field values change in a data table either because of changes done by your code or from user actions on a data-bound control the new value becomes the Current value, the old value remains the Original value, and the state is set to Modified At some point in the execution of the program, you decide that you have completed your changes, that new values are no longer new That is, you want the Original value thrown away and replaced with the Current value, and you want the row status set back to Unchanged Normally, this desire to shuffle versions and statuses occurs because you have pushed the changes back to the underlying database, but it could occur for a variety of other reasons as well