Questions
Here are the answers to the questions in this chapter.
| Miss Vector says... |
|
Fanouts are an important part of writing data with FME, so tell me, which of these statements are true?
1. You can have both a Feature Type Fanout and a Dataset Fanout in the same workspace 2. You can use a Feature Type Fanout with a database format, but not a Dataset Fanout 3. A fanout expression can be an attribute, or a constructed string, but not a user parameter 4. A fanout cannot be based on a format attribute such as fme_color It's true you can have both types of fanout in the same workspace, but a database writer won't do a Dataset Fanout (it can create multiple tables, but not multiple databases). A Fanout Expression can be any attribute (including FME attribute or format attribute) or string, and it can be a user parameter too! |
| Miss Vector says... |
|
Now tell me which of these statements about Generic Reading/Writing are true?
1. Because you select an output folder, the Generic Writer won't write to a file format like AutoCAD DWG 2. If the feature types of the chosen format are limited to a single geometry, the Generic Writer will drop all features except a single geometry type 3. The Generic Writer does not support either type of Fanout 4. The ParameterFetcher transformer can be used to retrieve the format of data being Read/Written in order to route features in a specific way through the workspace Most of these are untrue. The Generic Writer will create files, even though you only pick the output folder, and it will create multiple feature types if it's necessary to split data because of clashing geometry types. On a similar vein, fanouts are supported. And, yes, the ParameterFetcher transformer will fetch the value of the format parameter letting you redirect data in the workspace (for example you might route data through a KMLStyler if KML is the chosen output format). |
| Miss Vector says... |
|
It's important to get the concepts correct here, and I have some more statements only some of which are true:
1. A Dynamic workspace will read/write any format of data 2. A Dynamic workspace will read/write any feature types in the source data 3. A Dynamic workspace will read/write any attributes in the source data 4. A Dynamic workspace will read/write any geometry in the source data Feature Types, Attributes, and Geometry are the three schema parts handled by dynamic workspaces. However, format is not handled. This is the role of the Generic Reader/Writer. If you don't use the Generic Reader/Writer your dynamic workspace will not handle any format. Basically, the term Generic means “any format”, while Dynamic means “any schema”. A workspace may be generic, or dynamic, or both, or neither! |
| Miss Vector says... |
|
The ability to construct a dynamic schema from attributes in a workspace has lots of possibilities. In fact, one of these FME transformers automatically creates dynamic schema attributes specifically so you can create a new schema. Which is it?
1. SchemaMapper 2. AttributePivoter 3. PythonCaller 4. Clipper The AttributePivoter creates a whole new series of attributes that are completely different to the source schema; therefore it also generates a dynamic schema to assist you in writing the data. Check it out and you will see it creates a whole series of attribute_name{} and attribute_data_type{} list attributes. |