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Hypertree Decompositions
- Invited Talk on Hypertree Decompositions: Questions and Answers by Georg Gottlob
- Chair: Nysret Musliu
Abstract
Hypertree decompositions (HTDs) are a database optimization technique used to represent complex graphs hierarchically in order to improve query performance. HTDs represent a graph as a hierarchy of hypertrees, which are trees composed of hyperedges that correspond to subsets of nodes in the graph.
HTDs are constructed recursively, by dividing the nodes of a graph into disjoint subsets, and creating a hypertree for each subset. The process is repeated on each subset until a single node is reached. The resulting hierarchy of hypertrees provides a compact and efficient representation of the original graph that can be used for query processing.
HTDs are useful because they allow for efficient evaluation of graph queries by exploiting the structure of the data. The hierarchical nature of the hypertree representation enables the use of more efficient algorithms for query processing, and reduces the amount of data that needs to be accessed during query evaluation. For example, queries that would be difficult to process on the original graph can be evaluated more efficiently on the hypertree representation.
One important feature of HTDs is that they can be customized to optimize query processing for a specific application or query. This is because the partitioning of the nodes in the graph can be tailored to the specific characteristics of the data and the query. For example, if a query only involves a subset of nodes in the graph, the HTD can be constructed to minimize the number of hypertrees that need to be accessed during query evaluation.
However, constructing an optimal HTD is a complex and computationally expensive task. Therefore, heuristic algorithms are often used to generate approximate HTDs that can be constructed efficiently. These algorithms typically use techniques such as dynamic programming and branch-and-bound search to generate HTDs that are near-optimal.
In summary, HTDs are a database optimization technique that represent complex graphs hierarchically using hypertrees. They are constructed recursively by dividing nodes into disjoint subsets, and provide a compact and efficient representation of the original graph that can be used for query processing. HTDs can be customized to optimize query processing for a specific application or query, and heuristic algorithms are often used to generate approximate HTDs that can be constructed efficiently.