Semi-structured data is defined as irregular data with structure that may change rapidly or unpredictably. An example of such data can be found inside the World-Wide Web. Since the data is irregular, the user may not know the complete structure of the database. Thus, querying such data becomes a difficult issue. In order to write meaningful queries on semi-structured data, there is a need for a query language that will support the features that are presented by this data. Standard query languages, such as SQL for relational databases and OQL for object databases, are too constraining for querying semi-structured data, because they require data to conform to a fixed schema before any data is stored into the database. This paper introduces Lorel, a query language developed particularly for querying semi-structured data. Furthermore, it investigates if the standardised query languages support any of the criteria presented for semi-structured data. The result is an evaluation of three query languages, SQL, OQL and Lorel against these criteria.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:bth-4332 |
| Date | January 2003 |
| Creators | Maksimovic, Gordana |
| Publisher | Blekinge Tekniska Högskola, Institutionen för programvaruteknik och datavetenskap |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
Page generated in 0.0016 seconds