In the introductory part of this thesis, we outlined the long-term objective to enable strategical query optimization for evaluating XPath expressions. The present work did not solve this problem entirely, but provided a large set of required models and methods. We will conclude this work by taking a look at the tasks that still remain open.
We suggested to constrain the optimization problem to single step expressions.
Hence, the solution space of imaginable query plans is highly limited. In fact, there are not just two, as shown in the introduction, but three possible plans when considerations include the additional key join due to Monet’s vertically fragmented data model (Fig. 5.1):
(a) Independent execution: the axis step and the name test are executed on the entire node set followed by a key join on both results.
./
Figure 5.1: Possible query plans for single step expressions combining an axis step , a key join./, and name test selectionσ.
(b) Axis step first: the axis step is performed on the entire node set, followed by the join and the name test on the intermediary result.
(c) Name test first: the name test is performed on the entire node set, followed by the join and the axis step over the restricted node set resulting from the first two.
Obviously, the three plans shown above involve issues of tactical optimization as well. Whereas (a) and (b) enable application of thevoidaxis step, the third variant falls back to the less efficientoid-version. Similarly, the key join in (a) require the usage of the sort-merge join implementation due to its oid-operands. The faster fetch-join, however, can be applied in both other query plans as it is associated there with at least one operand of typevoid.
Experiments considering scenarios that differ with respect to the chosen context nodes, axis steps, and node tests might in advance disqualify one of the three plans, if it is outperformed in all tests by one of the other two. However, query optimization will not become obsolete this way. First tests already showed that at least the plans (b) and (c) will pass this preselection.
When calculating costs for entire step expressions, we further have to analyze how the proposed axis step cost models could be combined with those of the involved standard database operations. Using the number of cache misses for cost indication, we would expect that the cache misses of all three involved operations could be simply summed up to represent the total costs of a step expression. Comparison of the three (respectively, two) calculated results enables the query optimizer to choose the optimal plan in any given situation.
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