Abstract: In processing a query including a selection criterion on one or more attributes of a relation, a prior statistic generated for a prior different selection criterion on the same one or more attributes of the relation, may be revalidated for use in processing the query, based upon a measure of the entropy of the one or more attributes of the relation. In this way, the re-validation of statistics may be performed more efficiently. Furthermore, attribute groups of a relation for which multi-dimensional indexes are to be formed, are identified by evaluating the correlation of attribute values within tuples of the relation and determining that the correlation of attribute values within tuples of the relation exceeds a threshold.

Abstract: Statistics for a pattern matching predicate are generated using stored character statistics. A first structure stores, for each of a plurality of character positions, frequently occurring characters in that character position, and a count of the number of occurrences of that character. A second structure stores frequently occurring characters that are subsequent to the frequently occurring characters stored in the first structure, and a probability of occurrence of each frequently occurring subsequent character. To form an estimate of the number of tuples matching a pattern matching predicate, statistics are retrieved for the matching characters in each matching position in the predicate, and then combined to produce the estimate. In the event a statistic is not stored for a desired character, the available statistics are used to make an estimate by accumulating statistics for other characters, and then calculating average frequency of occurrence of characters that do not have stored statistics.

Abstract: A relational database system analyzes each potential join in a query, to determine whether a relation involved in the join is subject to a selection criterion, and evaluate whether that selection criterion or the join per se effects a join reduction. The computational expense of generating a look-ahead predicate comprising the tuples of the second relation matching any applicable selection criterion, is compared to the computational savings that result from the join reduction. The most beneficial look-ahead predicate among all potential joins of relations in the query is identified through iterative analysis of all possible joins.

Abstract: A cardinality estimator computes an estimated cardinality for a database column using a formula that accounts for skew in the data in the column. The result is an estimate of cardinality that more closely resembles the actual cardinality in the column. The improved cardinality estimate may then be used to make better query optimizations.