Virtual deployments¶
Deployment steps¶
Trac uses a ‘virtual deployment’ method which involved three steps.
IMPORT MODEL |
The model code is scanned by not copied. A new metadata object is created which contains the model schema and a link to the code commit in the repository |
BUILD FLOW |
Models are combined into a calculation graph where the outputs of one model become the inputs to the next. Flow exist only as trac metadata and are built from the model schemas, not the model code |
RUN FLOW |
The model code is fetched from the repository at runtime every time a Job is launched. |
Note
This short video (under 3 mins) explains the virtual deployment method.
Model schema¶
All trac models contain a custom function to declare their schema, which consists of:
INPUTS |
The schema(s) of all the input data the model needs to run |
PARAMETERS |
The schema of any parameters that govern how the model runs |
OUTPUTS |
The schema(s) of all the data objects produced when the model runs |
Note
See Modelling for how to build trac models.
Schema validation¶
This is an example of a schema (sub-type = table).

Schema validation occurs when selecting data inputs for a job and when combining models to build a flow. In both instances, TRAC applies strict schema validation.
Key things to remember about schema validation are:
It occurs between schemas, not between data content
It considers Field name, Field Type, Business key, Categorical and Not nullable
The order in which field names appear is not important
A source schema must contain all the fields needed by the target schema
The source schema can contain extra fields
Note
See Data types for supported data types.