Understanding Larva™ Technology
Monarca comes with a set of predefined validation and transformation functions that you can use in your database migration project to perform operations like to concatenate two or more column values, to convert a column value to upper or lower case, to use regular expressions on column values, to convert a group of column values into a date, to validate column value ranges and more.
These functions deal with several problems that you may encounter when working on complex database migration projects but what happens when they are just not enough and you need specialized functions? The answer is simple, use Larva™ Technology and integrate your own solutions.
There are three mayor concepts in Larva™ Technology:
Larva Libraries
A Larva Library is a collection of validation and transformation functions packed in a JAR file. You can create specialized libraries to deal with all migration scenarios you may have. Monarca let you load as many libraries as you need using the Monarca Larva Manager (Menu: Tools -> Configure Larvas...).
Larva Validations
A Larva Validation is a programmed function to validate a column value during a migration process. For instance, suppose you only want migrating data with:
1000 <= ID <= 5000
from the table:
PRODUCTS (ID, DESCRIPTION)
Instead of creating a new SQL VIEW in your database with the specified delimitation, you may create a simple validation rule to delimitate the required range for the ID column.
Larva Transformations
A Larva Transformation is a programmed function to transform a column value or a set of column values into another value during a migration process. For instance, suppose you want migrating data from the table:
CUST(ID, NAME, ADDRESS, DAYOFBIRTH, MONTHOFBIRTH, YEAROFBIRTH)
to the table:
CUSTOMER(ID, NAME, SECOND_NAME, LAST_NAME, ADDRESS, BIRTH)
This is a very common problem in real migration scenarios; we need to transform the NAME column of the CUST table into NAME, SECOND_NAME and LAST_NAME columns of the CUSTOMER table. Even more, we need to transform DAYOFBIRTH, MONTHOFBIRTH and YEAROFBIRTH columns of the CUST table into BIRTH column of the CUSTOMER table.
You can create a new transformation function to deal with the split name and the join birth problem or use one of the built-in transformation functions.
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