Data mapping: Establish the mapping operation mechanism between data according to the structure information of data.
Elements of a data map:
First, the data
1, source data;
2, Target data;
3, the relationship between data;
4, the metadata of the data (structure information).
5, the corresponding relationship of the element type.
Second, the acquisition of meta-data:
1, description file: CoreData of the MOMD file, the table structure of the database;
2. Structure information: Use the run-time reflection or the format information of the memory read get.
Third, map operation:
1, hard-coded for format conversion.
2, according to the metadata information direct memory write;
3, according to meta-data information KVC write;
Iv. Non-matching mappings
1, the mapped data between the one by one corresponding relationship, but the key values do not match
2. A mapping that contains a relationship or nested data;
3, the collection of data mapping.
4, chain-type data mapping.
Data Mapping: Given two data models, the corresponding relationship between the data elements is established between the models, which is called the data map.
Data mapping is the first step in a number of data integration tasks, such as data migration, data cleaning, data integration, semantic network construction, and peer information systems.
There are two ways to map data: Manual encoding (hand-coded) and visual operations (graphical manual). Manual coding is to define data correspondence directly in a programming language like xslt,java,c++. Visualizations typically enable users to draw a line between data items to define the correspondence between data items. Some tools that support visual operations can automatically establish this correspondence. This auto-established correspondence typically requires that data items have the same name. Whether you use manual or automatic relationships, you ultimately need tools to automatically convert graphical representations into executable programs such as xslt,java,c++.
Data mapping-Map