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The gSOAP tools convert C/C++ data types to/from XML schema data types. Since C does not support namespaces and struct/class member names cannot be namespace-qualified in C++, the use of identifier naming conventions in gSOAP allow for binding this structure and its members to an XML schema complexType that is auto-generated as follows:
Schema-IDL? Standard APIs Supports zero-copy operations Apache Arrow: Apache Software Foundation — De facto: Arrow Columnar Format: Yes No Yes Built-in C, C++, C#, Go, Java, JavaScript, Julia, Matlab, Python, R, Ruby, Rust, Swift Yes Apache Avro: Apache Software Foundation — No Apache Avro™ Specification: Yes Partial g — Built-in C, C# ...
File metadata, including the schema definition. The 16-byte, randomly-generated sync marker for this file. For data blocks Avro specifies two serialization encodings: [6] binary and JSON. Most applications will use the binary encoding, as it is smaller and faster. For debugging and web-based applications, the JSON encoding may sometimes be ...
Semi-structured data [1] is a form of structured data that does not obey the tabular structure of data models associated with relational databases or other forms of data tables, but nonetheless contains tags or other markers to separate semantic elements and enforce hierarchies of records and fields within the data.
JSON-LD is designed around the concept of a "context" to provide additional mappings from JSON to an RDF model. The context links object properties in a JSON document to concepts in an ontology. In order to map the JSON-LD syntax to RDF, JSON-LD allows values to be coerced to a specified type or to be tagged with a language.
Another example can be when dealing with structs. In the code snippet below, we have a struct student which contains some variables describing the information about a student. The function register_student leaks memory contents because it fails to fully initialize the members of struct student new_student .
Compared to JSON, BSON is designed to be efficient both in storage space and scan-speed. Large elements in a BSON document are prefixed with a length field to facilitate scanning. In some cases, BSON will use more space than JSON due to the length prefixes and explicit array indices.
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