INFORMIX DataBlade Developers Kit Tutorial

List of Exercises

Exercise 3: Creating Distinct Data Types and Casts, continued


11

Compile your source code using your C compiler.

See " Compiling and Linking DataBlade Module Code" for detailed instructions on using the Visual C++ makefile (Mercury.mak for this exercise) to compile the source code into the dynamic link library file (Mercury.bld).

For more information about compiling on UNIX, see the DataBlade Developers Kit User's Guide.


12

Install the Mercury DataBlade module.

Install the Mercury DataBlade module in the %INFORMIXDIR%\extend\Mercury.1.0 directory.

See " Installing a DataBlade Module" for detailed installation instructions.

Ensure that the permissions on the Mercury.bld file are read-only. (If your dynamic link library or shared object file is not read-only, a database server error occurs when you try to load it.)


13

Start the database server.

See " Starting Informix Dynamic Server on Windows NT" for detailed instructions for starting Informix Dynamic Server on Windows NT.

For instructions on starting Informix Dynamic Server on UNIX, see the Administrator's Guide for your database server.


14

Create a test database.

If the database in which you plan to test the Mercury DataBlade module does not yet exist, create it using the following SQL statement:

    create database mercury_ex with buffered log; 
    
    

15

Register the Mercury DataBlade module in the mercury_ex database.

See " Registering a DataBlade Module" for detailed instructions on registering using the BladeManager graphical user interface.

For information on registering using BladeManager from the command line, see the DataBlade Module Installation and Registration Guide.


16

Run the Mercury DataBlade module.

After you install and register the DataBlade module, the Informix database accepts the new data types and routines and runs them as if they were built-in.

To test the Mercury DataBlade module, execute these SQL operations using DB-Access or SQL Editor

    1. Create the tables climate_EU and climate_USA.

    2. Insert sample data into the two tables.

    3. Run three queries against these tables.


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