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SQL Server transaction boundaries help you to identify when SQL Server transactions start and end by using API functions and methods: Transact-SQL statements: Use the BEGIN TRANSACTION, COMMIT TRANSACTION, COMMIT WORK, ROLLBACK TRANSACTION, ROLLBACK WORK, and SET IMPLICIT_TRANSACTIONS statements to delineate transactions. These are primarily used in DB-Library applications and in T-SQL scripts, such as the scripts that are run using the osql command-prompt utility. API functions and methods: Database APIs such as ODBC, OLE DB, ADO, and the .NET Framework SQLClient namespace contain functions or methods used to delineate transactions. These are the primary mechanisms used to control transactions in a database engine application.

org.hibernate.search.FullTextQuery hibQuery = session.createFullTextQuery(query, Dvd.class); List<Dvd> results = hibQuery.list(); assert results.size() == 2: "incorrect hit count"; assert results.get(0).getDescription() .equals("the fifth season of star trek"); for (Dvd dvd : results) { System.out.println(dvd.getDescription()); }

So, you can create a data adapter in four ways: You can use its parameterless constructor (assigning SQL and the connection later). You can pass its constructor a command (here, cmd is a SqlCommand object). You can pass a SQL string and a connection. You can pass a SQL string and a connection string. You ll see all this working in action shortly. For now, we ll move on and show how to use data tables, data columns, and data rows. You ll use these in upcoming sections.

Dvd.class.getName()).list())

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A data table is an instance of the class System.Data.DataTable. It s conceptually analogous to a relational table. As shown in Figure 8-1, a data table has collections of data rows and data columns. You can access these nested collections via the Rows and Columns properties of the data table. A data table can represent a stand-alone independent table, either inside a dataset as you ll see in this chapter or as an object created by another method, as you saw in the previous chapter when a data table was returned by calling the GetSchemaTable method on a data reader. A data column represents the schema of a column within a data table and can then be used to set or get column properties. For example, you could use it to set the default value of a column by assigning a value to the DefaultValue property of the data column. You obtain the collection of data columns using the data table s Columns property, whose indexer accepts either a column name or a zero-based index, for example (where dt is a data table):

} finally { session.close(); } }

Each transaction must be managed by only one of these methods. Using both methods on the same transaction can lead to undefined results. For example, you should not start a transaction using the ODBC API functions, and then use the T-SQL COMMIT statement to complete the transaction. This would not notify the SQL Server ODBC driver that the transaction was committed. In this case, use the ODBC SQLEndTran function to end the transaction.

for (Object element : session.createQuery("from " + session.delete(element); tx.commit();

Dim col as DataColumn = dt.Columns("ContactName") Dim col as DataColumn = dt.Columns(2)

private void buildIndex(FullTextSession session, Transaction tx) { for (int x = 0; x < descs.length; x++) { Dvd dvd = new Dvd(); dvd.setDescription(descs[x]); dvd.setId(x);

You can use all T-SQL statements in a transaction, except for the following statements: ALTER DATABASE, RECONFIGURE, BACKUP, RESTORE, CREATE DATABASE, UPDATE STATISTICS, and DROP DATABASE. Also, you cannot use sp_dboption to set database options or use any system procedures that modify the master database inside explicit or implicit transactions.

A data row represents the data in a row. You can programmatically add, update, or delete rows in a data table. To access rows in a data table, you use its Rows property, whose indexer accepts a zero-based index, for example (where dt is a data table):

CHAPTER 7 session.save(dvd); } tx.commit(); session.clear(); } }

Dim row as DataRow = dt.Rows(2)

B we add the third term, season, to our query and increase the slop factor to 4 at C. Decreasing the slop factor makes things more strict and results in a lower number

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