Data Exchange Mappings

Each Data Exchange mapping is an XML file describing the structure of particular formats (like JSON, XML, CSV, Excel or Parquet) being mapped. Below you find the elements specific for each of the mapping types. The attributes that you can specify for each element are shared. In this How-To article you can find some simple examples on the usages.

JSON Mapping elements

The following are the elements allowed in a JSON mapping

• the AimmsJSONMapping element, the mandatory root of a JSON mapping

• the ObjectMapping element, a mapping element used to map a JSON object value (enclosed in curly brackets { and })

• the ArrayMapping element, a mapping element used to map a JSON array value (enclosed in square brackets [ and ]). A JSON array mapping can only have a single child mapping, specifying the type of every element in the array.

• the ValueMapping element, a mapping element used to map a integer, double or string value in a JSON file

• the RowMapping element (underneath an ObjectMapping), a mapping element used to map all underlying mapping nodes as an array of row arrays (containing heterogeneous value types)

• the RowMapping element (underneath a ColumnMapping), a mapping element used to map the value of a particular element in a ColumnMapping to a specific identifier in the model.

• the ColumnMapping element (underneath an ObjectMapping), a mapping element used to map all underlying mapping nodes as an array of column arrays (containing homogeneous value types)

• the ColumnMapping element (underneath a RowMapping), a mapping element used to map the value of a particular element in a RowMapping to a specific identifier in the model.

The represent row-oriented data, the RowMapping and ColumnMapping will provide the most compact JSON representations and will execute the fastest.

XML Mapping elements

The following are the elements allowed in a XML mapping

• the AimmsXMLMapping element, the mandatory root of a XML mapping

• the ElementObjectMapping element, a mapping element used to map an XML element that holds child elements, but no value

• the ElementValueMapping element, a mapping element used to map an XML element that holds a value, but no child elements

• the AttributeMapping element, a mapping element used to map the value of an attribute of an XML element

Row-based Table mapping elements

For files types like CSV, Parquet, Excel and SQLite, data is organized in tables or collection of tables. This makes these table-based mapping simple and the same for all these file types.

The root of the mapping specifies the file type. These are the possible roots of a row based table mappings

• the AimmsCSVMapping element for CSV files

• the AimmsParquetMapping element for Parquet files

• the AimmsExcelMapping element for Excel files (.xlsx)

• the AimmsDatabaseMapping element for SQLite files (.db)

The child elements of these root nodes are

• the TableMapping element is always directly underneath the root and represents the meta information of the table, like it’s name.

• the RowMapping element a single child element of the TableMapping and maps the rows

• the ColumnMapping element maps a column and is always underneath a RowMapping element

For CSV and Parquet each table is stored as one file, so if a TableMapping is specified then it will determine the name of the file. Therefore the first argument of Procedures dex::WriteToFile() and dex::ReadFromFile() is interpreted as a folder containing the files. When no TableMapping is specified the first argument of Procedures dex::WriteToFile() and dex::ReadFromFile() is the file name and only one single table can be written.

The AimmsDatabaseMapping is not exclusive for SQLite, but this is the only database format that is a file and can be used with Procedures dex::WriteToFile() and dex::ReadFromFile(). For other databases see Application Database.

Note

In older versions of DataExchange each file type had their own child element mapping nodes, like SheetMapping or CSVColumnMapping. When reading the mapping these old style elements are automatically converted to the corresponding TableMapping, RowMapping and ColumnMapping.

Mapping attributes

The attributes of the elements in a Data Exchange mapping are shared among the different types of mappings, although not all attributes are supported by every type of mapping element.

The available mapping attributes are:

• name

• alt-name

• binds-to

• name-binds-to

• name-regex

• name-regex-from

• name-regex-prefix

• name-regex-postfix

• iterative-binds-to

• iterative-prefix

• iterative-existing

• iterative-reset

• implicit-binds-to

• binds-existing

• skip-non-existing

• skip-empty-rows

• maps-to

• max-string-size

• range-existing

• value

• write-defaults

• write-filter

• force-dense

• dense-children

• included-mapping

• embedded-mapping

• base64-encoded

• read-normalize

• write-normalize

The name and alt-name attributes

The name attribute specifies the name of the mapped element in the format. Not every element needs a name, for instance to root value in a JSON file, or the child mapping of a JSON array. With the alt-name attribute you can indicate an alternative name for the mapping element when reading a file, e.g. when the name has been recently altered, and there are still data files that use the old name. When writing, the Data Exchange library will always use the name attribute.

The binds-to attribute

The binds-to attribute, which can be added to the mapping of any value-holding element. The binds-to attribute will also provide an index binding for all sibling mapping elements of mapping element for which it is specified, or for the parent element in case the binds-to attribute is applied to an AttributeMapping element.

The name-binds-to attribute

The name-binds-to attribute provides a way of binding the name of an element in a JSON or XML file to an index in your AIMMS model. You would typically use this if a JSON or XML file holds elements with different names but with the same structure. Rather than creating a mapping for each of the elements you can create a mapping where the element names serves as an extra index in the binding of the multi-dimensional identifiers mapped to the values contained in each of the elements.

The name-regex attribute should be used in conjunction with a name-binds-to attribute, to specify a regular expression to restrict the element to which the name-binds-to attribute should be applied. Alternatively, you can use the name-regex-from attribute to let the Data Exchange library dynamically create a regular expression for you, when you call dex::AddMapping for the given mapping, that exactly matches all elements from a simple set or index in your model that you can specify through this attribute.

As the name suggests, you can use any accepted regular expression within these attributes’ definitions. For example, using name-regex=".*" in your ColumnMapping will accept any column name, which makes it a very useful expression if you’re iterating over data with different column names binding to the same index.

With the name-regex-prefix attribute you can specify a prefix that is used in the JSON, XML, CSV, Excel, Parquet file or database, but which should not be included in the element names in the model. Note that the value of the name-regex-prefix attribute is automatically prepended to the regular expression specified in the name-regex attribute, and subsequently removed from the match if a match has been found.

By default, when writing CSV files, Excel sheets, Parquet files and databases, AIMMS will first generate columns generated on the basis of the current contents associated with the name-binds-to index. Subsequently, it will fill individual fields, on a row-per-row basis, based on the presence of data in the maps-to identifier. If that identifier contains data for tuples which do not currently lie in the set associated with the name-binds-to index, such data will not be written, and may potentially lead to rows without any data.

The iterative-binds-to attribute

The iterative-binds-to attribute can be used if the given JSON or XML format does not hold an explicit value which can be bound to an index in your model. The iterative-binds-to attribute will generate elements using an increasing integer counter.

The iterative-prefix attribute can be used alongside the iterative-binds-to attribute. All elements created in the model will be prefixed with the prefix specified here. If you don’t specify a prefix, the element names will be just increasing integer values.

Assigning a value of 1 to the the iterative-existing attribute causes the iterative-binds-to attribute to not generate new elements, but instead to use existing elements of the set bound to the index specified in the iterative-binds-to attribute, starting at the element with ordinal 1. If a generated element is not present, the reading will stop with an error.

The iterative-reset attribute can be specified at a particular element of your mapping. If attribute value is “1”, it will cause the integer counter associated with the of iterative-binds-to attributes of all direct child mappings to be reset to 1. If it contains a comma-separated list of indices used in the mapping or in any of its included mappings, then the integer counter associated with each of these indices will be reset to 1. The indices specified in an iterative-reset attribute do not have to be bound at that node.

The implicit-binds-to attribute

By default, if a node in a mapping has sibling nodes, any index bound via a binds-to attribute at such a node n can be used in any attribute of all nodes in the subtree starting at the parent node of n. Via the implicit-binds-to attribute you can make such an index available for use in subtrees starting at even higher parent nodes. You can use this, for instance, if an id of a JSON/XML data structure, that you intend to use as the index value for all data in such a data structure, is stored deeper in such a data structure. By means of the implicit-binds-to attribute you can make sure that the Data Exchange library will first read the entire subtree containing the index value, prior to reading the subtrees where this index is referenced in e.g. a maps-to attribute.

The binds-existing and skip-non-existing attribute

The binds-existing attribute can be used in conjunction with the binds-to, name-binds-to and iterative-binds-to attribute to indicate that, when reading a data file, no new set elements will be created based on node values or names. If a newly read or generated element is not present in the set, any data value underneath the node to which the element is bound will be skipped or lead to an error depending on the value of the skip-non-existing attribute. This allows for a filtering mechanism where a data file can only be partially read for all nodes that correspond to existing set elements in the model. This option behaves slightly different than the iterative-existing attribute for iterative bindings which will always return with an error in such a case.

The skip-non-existing attribute specifies the desired behavior when the Data Exchange library encounters a non-existing element for a binds-to, name-binds-to, iterative-binds-to, or attribute. If you specify a value of 0, an error will be returned, while with the default value of 1 all data dependent on the empty value for the binds-to, name-binds-to or iterative-binds-to attribute will be silently skipped. A value of 2 will skip the value, but will also issue a warning. You can use this attribute to skip objects or rows that are indexed by empty labels in the data file, but also by non-empty labels that cannot be added to e.g. a defined set in the model.

The skip-empty-rows attribute

With the skip-empty-rows attribute you can let the Data Exchange library skip completely empty rows in row-based mappings. When specified, all columns present in the mapping will be checked, while non-mapped columns will be not be checked. You can use this to allow reading data from e.g. Excel sheets where the user inserted empty lines in between data. When skip-non-existing is set to 0, the Data Exchange library will still pick up empty fields for columns that bind to indices in your model on non-empty lines.

External bindings in mappings

Directly underneath the root node of any mapping you can specify one or more ExternalBinding nodes. An external mapping node has two attributes:

• binds-to

• binding

Through the binds-to attribute you can specify the index which should be bound externally to the scalar element parameter specified through the binding attribute.

As a result of an ExternalBinding, any externally bound index cannot be bound any longer within the document, and any use of an externally bound index in multi-dimensional identifiers used in e.g. a maps-to attribute will refer to the slice of that identifier associated with the element parameter specified through the binding attribute.

You can use an ExternalBinding node to read or write a document only for the slice associated with the specified element parameter. Alternatively, you can use it to bind it in an included-mapping to the current value of an index bound in an outer mapping at the node containing the included-mapping.

The maps-to attribute

You can assign the maps-to attribute to any value-holding mapping element. Its value should be a reference to an identifier in your model, including the indices bound at this location in the mapping tree in the exact order in which they are bound in the mapping, including any external bindings present. Note that this implies that the dimension of the identifier must be matched exactly with the number of bound indices, and that the root domain of the identifier should match the root domains of the indices. Also this requirement prevents you from permuting the bound indices bound in the identifier reference specified in the maps-to attribute.

The write-filter attribute can be specified at any node in the mapping tree, and should be a reference to an identifier in the model including the bound indices at this location as for the maps-to attribute. For any tuple of bound indices for which the write-filter attribute does not hold a non-default value, the corresponding part of the generate JSON, XML or CSV file will be skipped.

By default, the Data Exchange library assumes that all string values will hold up to 1024 characters. Through the max-string-size attribute a maximum string size up to 1 MB can be specified.

The write-defaults attribute

For all row-based formats (CSV, Excel, Parquet or database), cells for which no data is present in the maps-to identifier will be left empty by default. With the write-defaults attribute you can indicate that you want the default value of that identifier to be written to such cells instead. You can specify the value 1 to the write-defaults attribute on a ColumnMapping, or on the RowMapping or ExcelSheetMapping. For the latter, the write-defaults attribute will be applied to all underlying ColumnMappings. The default value for the write-defaults attribute is 0.

Similarly, for JSON and XML mappings, you can set the write-defaults attribute for any value-holding mapping element. On its own it will never cause an element which contains a value with the write-defaults attribute set to generated, but if such an element is generated because another child holds a non-default value, then the value with `` write-defaults`` attribute will also be generated, even if it holds no non-default value.

The range-existing attribute

If the identifier associated with a maps-to attribute is an element parameter, the range-existing attribute can be used to that any values encountered that do not correspond to an existing element in the range set, should be skipped, rather than creating a new element in the range set for such a value. When an non-existing element is encountered, the Data Exchange library will follow the skip-non-existing attribute to determine whether to raise an error, to skip the value, or to skip the value but raise a warning to the model.

The force-dense attribute

The force-dense attribute should also contain a reference to an identifier plus bound indices as for the maps-to attribute. Through this attribute you can force a specific density pattern by specifying a domain for which nodes should be generated, regardless of whether non-default data is present to fill such nodes, e.g. because the identifier specified in the maps-to attribute of the node itself, or any of its sub-nodes, holds no non-default data. Note that a density pattern enforced through the force-dense attribute is still subject to a write filter specified in a write-filter attribute.

Enforcing a density pattern may be important when the bound indices are generated through the iterative-binds-to attribute, and not explicitly represented through data-holding node bound to a regular binds-to attribute. In such cases, not writing nodes that hold no non-default data, may lead to inconsistent numbering of generated elements when reading the generated JSON or XML files back in. When reading a JSON, XML, CSV, Excel, Parquet file or database, the library will assign a value of 1 for the identifier specified in the force-dense attribute to any tuple encountered, such that the same file will be generated when writing back the file using the same mapping based on the data just read in.

Note

None of the maps-to, write-filter and force-dense attributes may contain an identifier slice, but must be bound to indices in the mapping for all dimensions of the given identifier. Thus, for instance, specifying a value of 1 to the force-dense attribute to enforce full density is not allowed. Instead you should create a full-dimensional parameter holding 1 for every tuple in its domain and assign that to the force-dense attribute.

To enforce slicing for a particular index, you can specify an ExternalBinding node directly underneath the root node of the mapping.

The dense-children attribute

With the dense-children you can indicate that when a node will be written, because of the density pattern of all of its children, all direct value-holding child elements with the same bound indices as the parent node, will be written in a dense manner. For example, with this attribute you can cause all columns in a table row to be written to a CSV, Excel, Parquet file or database, whenever at least one of the columns holds a non-default value.

With this attribute you cannot cause an array to be written in a dense manner, as the array elements need to bind an additional index. To enforce writing an array in a dense manner, you have to use the force-dense attribute.

The value attribute

With the value attribute you can specify that, when writing a file, the value of a value-holding mapping element should become the static string value specified through this attribute. When reading a file, a node with a value attribute will be silently ignored.

Note

Any value-holding mapping element may have only one of the binds-to, maps-to or value attributes specified.

The included-mapping attribute

Through the included-mapping attribute, you can indicate that the contents of an object or array element in a given JSON or XML file should be read/written using a mapping, the name of which is contained in the string parameter specified in this attribute. The dimension of the string parameter should match the indices already bound at the given node. With this attribute you can specify a data-driven mapping name for a certain sub-tree of a JSON or XML file, e.g., to specify a table-specific mapping, where the table name is already bound in a parent node of the node at hand.

Alternatively, if the string value of the included-mapping attribute starts with the @ character, the remainder of the value will be interpreted as the fixed name of a mapping to be applied for the node at hand, instead of as a string parameter holding mapping names.

Note that when reading the contents of the node associated with the included mapping you cannot refer to the indices already bound at that node in the containing mapping, i.e., the contents of the tree node should be able to be read/written as if read from/written to a completely separate JSON/XML file.

It is possible, however, to externally bind the values of bound indices to indices used in the included mapping by specifying an ExternalBinding node underneath the node containing the included-mapping attribute. To this end, the included mapping itself should have an possess an ExternalBinding for the index you want to bind to. In addition, you should specify an ExternalBinding node underneath the node with included-mapping attribute, with the binds-to attribute set to the externally bound index in the included mapping, and the binding attribute set to the bound index in the outer mapping you want to bind to.

You can use external bindings in combination with included mappings to break a longer mapping into its constituting components. Note, however, that breaking up mappings this way will carry a performance penalty, especially if there is a lot of repetition in the nodes using an included mapping.

The embedded-mapping attribute

Through the embedded-mapping attribute, you can indicate that a value-holding element in the given JSON or XML file should hold a string that can be read or written using the mapping specified in this attribute. Note that the mapping element to which this attribute is attached may not have bound indices. The mapping specified in this attribute may be of any type (e.g. XML, JSON, CSV or Excel) and will be represented as a single (base64 encoded) string.

Assigning a value of 1 to the base64-encoded attribute indicates whether embedded mapped string is or should be base64 encoded.

Unicode normalization

The Data Exchange library can read and write the text-based formats JSON, XML and CSV files which are encoded as UTF-8. However, in Unicode there multiple ways to represent composed characters such as characters with accents. In the Unicode standard these representations are considered equivalent, although their binary representations are different (see for instance Unicode equivalence) When you are reading data from multiple data sources, this may present a problem in your AIMMS model. Set elements may be read from a data source using one representation, while data defined over these sets may come from data sources using another representation.

The Unicode standard provides several normalization procedures to normalize different text representations to various normalized forms. By itself, AIMMS will not normalize any incoming Unicode characters, as this may lead to problems when, for instance, you are trying to write back data to a database which was read in a different normalized form and then re-normalized in AIMMS. Instead the Data Exchange library offers support for normalizing Unicode data from and to the NFC (representing composed characters as a single character, preferred) and the NFD representation (representing composed characters decomposed as the character itself and separate characters for the accents). In addition, it offers an option to remove all diacritics completely, as well as trim the string from leading and trailing spaces.

In a mapping you can specify a normalization to apply before writing any string data to AIMMS through the read-normalize attribute, while the attribute write-normalize indicates the normalization to apply when writing out data to a data source. You can specify these attributes for any string-valued tree node in the mapping that binds to an index or maps to a string or element parameter. The value of these attributes can be nfc, nfd or no-diacritics, indicating whether to apply the NFC or NFD normalization or to remove all diacritics before reading the data from or writing the data to a data source. For additional trimming it also supports the values trim, nfc-trim, nfd-trim and no-diacritics-trim.

In addition, the Data Exchange library offers the functions dex::NormalizeString() and dex::NormalizeSet() to normalize strings and set elements that are already present in the model.

How does the mapping work for reading and writing?

In this section we will explain how the Data Exchange library uses the mapping to read or write a given format.

During read

When reading a file or database using a specified mapping, the Data Exchange library will iterate over the entire tree.

If reading a particular node in the data file, it will first try to bind any indices specified

• at the node itself through the name-binds-to or iterative-binds-to attributes,

• at direct child nodes through the binds-to attribute, or

• at deeper child nodes that make their indices available through implicit-binds-to attributes.

All elements associated with indices bound this way will be maintained in a stack of bound indices.

Subsequently the Data Exchange library will examine all other child nodes. If such a node is a structural or iterative node, it will recursively try to read the data associated with the child node. If the examined node is a value-holding node mapped to an multi-dimensional identifier, the value will be assigned to that identifier. Finally, if the node itself is a value-holding node mapped onto an identifier, it will also assign this value.

If a node in the mapping contains an included mapping, all externally bound indices bound to the values of bound indices in the outer mapping, will be carried over to the included mapping, prior to reading the subtree associated with the included mapping.

During write

When generating a file or database for a given mapping, at any given node, the Data Exchange library will examine all multi-dimensional identifiers associated with the node or any of its sub-nodes through either the maps-to, write-filter or force-dense attributes, and will try to find the lowest sub-tuple associated with all these identifiers, for all indices bound at this level (through the binds-to, name-binds-to, iterative-binds-to, or implicit-binds-to attributes) while fixing the indices already found at a previous level. If such a sub-tuple can be found, the new indices at this level will be stored, and any mapped value-holding nodes at this level will be written the associated values of any multi-dimensional identifiers matching with the value of the currently bound indices, and the Data Exchange library will iterate over all any structural or iterative child nodes recursively. If no further multi-dimensional data can be found for a particular node, the Data Exchange library will track back to the parent node, and try to progress there.

The message here is that an JSON, XML, CSV, Excel sheet, Parquet file tree or database is generated solely on the basis of multi-dimensional identifiers in the mapping, and never on the basis of any of the binds-to attributes. Such nodes will be generated based on indices bound by iterating over multi-dimensional data.

Thus, for instance, to generate a JSON array containing only all element names of a set in your model, you must combine a binds-to attribute, together with a force-dense attribute consisting an identifier over the index you want to generate the elements for, holding a value of 1 for every element you want to be contained in the array.

If a node in the mapping contains an included mapping, all externally bound indices bound to the values of bound indices in the outer mapping, will be carried over to the included mapping, resulting in the Data Exchange library to use the identifier slices corresponding to the externally bound indices to generate the node contents.