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From the early days of XML, developers have tried to map data stored in XML documents to relational data structures. The subtle but fundamental differences between the two data models, however, create an impedance mismatch that is trumped only by the object/relational mismatch. Attempts to marry the two models fall into one of the following techniques. Storing as a varchar: In this case, the entire XML document is simply copied whole into a varchar typed column. However, from the database perspective, this varchar is nothing more than a blob of unstructured data, which means it can t be indexed nor can you query for individual pieces of information within the XML. XML decomposition: This approach, sometimes referred to as shredding, entails decomposing the XML document into one or usually more database tables. Although this technique is most faithful to the relational model, some of the XML goodness is stripped away in the process. Namely, XML document order is not preserved, which is extremely important in cases where the XML truly represents a document rather than a collection of data. Partial decomposition: This approach is a combination of the first two. It involves storing the entire XML document in a large varchar column and also copying some of the data from the XML into relational tables. This provides indexing and querying abilities on the extracted data plus preserves the document order in the original XML. However, choosing which part of the XML to decompose can be a difficult decision that requires a large amount of foresight. Who knows how future applications may need to use and query the data

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this defaults to 14 lines. I find that they just clutter my screen so this setting effectively disables them for all intents and purposes - except for the first page of course pagesize 9999

Furthermore, you should be aware that SQL Server does not support detached databases (mdf files); therefore, if you are migrating from a SQL Express instance (for example when your hosting provider supports only SQL Server), you will need to manually import the contents of the detached database file into a SQL Server database (either by attaching it from the hosting.

REM here is how I set my signature prompt in sqlplus to REM username@database> I use the NEW_VALUE concept to format REM a nice prompt string that defaults to IDLE (useful for those REM of you that use sqlplus to startup their databases - the REM prompt will default to idle> if your database isn't started) define gname=idle column global_name new_value gname select lower(user) || '@' || substr( global_name, 1, decode( dot, 0, length(global_name), dot-1) ) global_name from (select global_name, instr(global_name,'.') dot from global_name ); set sqlprompt '&gname> ' REM and lastly, we'll put termout back on so sqlplus prints REM to the screen set termout on Furthermore, you can use this script to format the SQL*Plus prompt so you always know who you re logged in as and on which database. For example, as you work through this book, you ll encounter prompts of the following format: scott@ORA10G> This tells you that you re logged into the SCOTT schema on the ORA10G database. The following is the code in the login.sql script that achieves this: REM here is how I set my signature prompt in sqlplus to REM username@database> I use the NEW_VALUE concept to format REM a nice prompt string that defaults to IDLE (useful for those REM of you who use sqlplus to start up your databases - the REM prompt will default to idle> if your database isn't started) define gname=idle column global_name new_value gname select lower(user) || '@' || substr( global_name, 1, decode( dot, 0, length(global_name), dot-1) ) global_name from (select global_name, instr(global_name,'.') dot from global_name ); set sqlprompt '&gname> ' REM and lastly, we'll put termout back on so sqlplus prints REM to the screen set termout on

provider s administrative console or creating a backup from the Express database and importing it); in other words, there is no way to use the .mdf database with SQL Server directly.

Clearly, none of the earlier solutions are ideal. What you need is a way to store XML data in its native form while also providing indexing and querying capabilities on any part of the data. This is exactly what SQL Server 2005 provides with the new XML native type and an integrated XML query language called XQuery.