Abstract: In some examples, a system identifies sub-portions of a database query, assigns identifiers to the identified sub-portions, and adds the identifiers to a data structure. The system generates a fingerprint representing the database query based on applying a fingerprint function on the data structure including the identifiers.

Abstract: A process includes accessing a query that is associated with joining a fact table with a plurality of dimension tables. The fact table includes a primary key that includes a set of columns, which are covered by the dimension tables. The process includes determining a query plan for processing the query. The query plan has an associated join order. Determining the query plan includes determining a plurality of sets of the plurality of dimension tables, where each set includes dimension tables, which cover the set of columns of the primary key. Determining the query plan includes evaluating costs that are associated with joining subsets of the plurality of sets with the fact table. Based on the costs, a given subset of the plurality of subsets is selected. Determining the query plan includes constraining the join order based on the given subset so that the dimension tables of the given subset are joined before the fact table.

Abstract: In some examples, a system identifies sub-portions of a database query, assigns identifiers to the identified sub-portions, and adds the identifiers to a data structure. The system generates a fingerprint representing the database query based on applying a fingerprint function on the data structure including the identifiers.

Abstract: In some examples, a system identifies sub-portions of a database query, assigns identifiers to the identified sub-portions, and adds the identifiers to a data structure. The system generates a fingerprint representing the database query based on applying a fingerprint function on the data structure including the identifiers.

Abstract: A process includes accessing a query that is associated with joining a fact table with a plurality of dimension tables. The fact table includes a primary key that includes a set of columns, which are covered by the dimension tables. The process includes determining a query plan for processing the query. The query plan has an associated join order. Determining the query plan includes determining a plurality of sets of the plurality of dimension tables, where each set includes dimension tables, which cover the set of columns of the primary key. Determining the query plan includes evaluating costs that are associated with joining subsets of the plurality of sets with the fact table. Based on the costs, a given subset of the plurality of subsets is selected. Determining the query plan includes constraining the join order based on the given subset so that the dimension tables of the given subset are joined before the fact table.

Abstract: A relational database system for performing a join operation between a first table and a second table may include a query analyzer and an optimization engine. The query analyzer may compare predicates of a join operation query for an American National Standards Institute (ANSI) compliant database. The optimization engine, based upon comparison of the predicates, is to bypass a scan of the second table as part of outputting semantically correct results for the join operation.

Abstract: A relational database system for performing a join operation between a first table and a second table may include a query analyzer and an optimization engine. The query analyzer may compare predicates of a join operation query for an American National Standards Institute (ANSI) compliant database. The optimization engine, based upon comparison of the predicates, is to bypass a scan of the second table as part of outputting semantically correct results for the join operation.