X^ 3: A Cube Operator for XML OLAP

With increasing amounts of data being exchanged and even generated or stored in XML, a natural question is how to perform OLAP on XML data, which can be structurally heterogeneous (e.g., parse trees) and/or marked-up text documents. A core operator for OLAP is the data cube. While the relational cube can be extended in a straightforward way to XML, we argue such an extension would not address the specific issues posed by XML. While in a relational warehouse, facts are flat records and dimensions may have hierarchies, in an XML warehouse, both facts and dimensions may be hierarchical. Second, XML is flexible: (a) an element may have missing or repeated subelements; (b) different instances of the same element type may have different structure. We identify the challenges introduced by these features of XML for cube definition and computation. We propose a definition for cube adapted for XML data warehouse, including a suitably generalized specification mechanism. We define a cube lattice over the aggregates so defined. We then identify properties of this cube lattice that can be leveraged to allow optimized computation of the cube. Finally, we present the results of an extensive performance evaluation experiment gauging the behavior of alternative algorithms for cube computation.