Abstract: An enterprise data warehouse or business intelligence system having a plurality of processors and memory resources. The system includes at least a database server, a workload management system, a query compiler, and a query executor. The database server configured to receive a database query from an application at a database client system. The query compiler configured to prepare the execution plan for the query and compute the number of executive server processes (ESPs) in each ESP layer of the query. The workload management system is configured to generate an affinity value, and the query executor is configured to execute the query. As disclosed herein, placement of the executive server process layers of the query onto processors of the computing system is determined using the affinity value. Other embodiments, aspects and features are also disclosed.

Abstract: Optimized query plans are partitioned into equivalence groups that each include equivalence classes. Each equivalence group corresponds to a particular compiled, normalized, and parameterized query plan prior to optimization. Each equivalence class within an equivalence group corresponds to a different query plan corresponding to the particular compiled, normalized, and parameterized query plan represented by the equivalence group that has been optimized with respect to the selectivity of one or more predicate clauses of the query that is compiled to produce the particular compiled, normalized, and parameterized query plan. Optimized query plans are cached according to their respective equivalence groups and equivalence classes.

Abstract: There is provided a computer-implemented method of executing a query. An exemplary method comprises optimizing the query. The query may specify multiple operations on corresponding multiple column sets of a table in a database. The exemplary method further comprises partitioning data of the table based on the operations within a single pass of the table. Additionally, the exemplary method comprises performing the operations on the partitioned data in parallel.

Abstract: One embodiment includes dimensional columns of a database table that are mapped to filter columns. The filter columns are used to build an index which provides multi-dimensional access to the database table.

Abstract: Embodiments of the present invention partition optimized query plans into equivalence groups, each comprising one or more equivalence classes. Each equivalence group corresponds to a particular compiled, normalized, and parameterized query plan prior to optimization. Each equivalence class within an equivalence group corresponds to a different query plan corresponding to the particular compiled, normalized, and parameterized query plan represented by the equivalence group that has been optimized with respect to the selectivity of one or more predicate clauses of the query that is compiled to produce the particular compiled, normalized, and parameterized query plan. Optimized query plans are cached according to their respective equivalence groups and equivalence classes.

Abstract: An enterprise data warehouse or business intelligence system having a plurality of processors and memory resources. The system includes at least a database server, a workload management system, a query compiler, and a query executor. The database server configured to receive a database query from an application at a database client system. The query compiler configured to prepare the execution plan for the query and compute the number of executive server processes (ESPs) in each ESP layer of the query. The workload management system is configured to generate an affinity value, and the query executor is configured to execute the query. As disclosed herein, placement of the executive server process layers of the query onto processors of the computing system is determined using the affinity value. Other embodiments, aspects and features are also disclosed.

Abstract: A database query compiler and compilation method has special facilities for compiling a query that includes one or more of a predefined set of running and moving sequence functions. The compiler converts the query into a predefined normalized form suitable for compilation using a running and moving function normalizer. The running and moving function normalizer converts each running and moving sequence function in the set into a corresponding ordered set of one or more executable statements, which include at least one Offset sequence function that accesses data in an auxiliary field of a row of a table. An offset sequence function compiler, compiles each Offset sequence function, Offset(argument, index), in the normalized database query into a compiled set of instructions, including instructions for storing and reading the auxiliary fields to and from a buffer that is separate from the table. The buffer is preferably stored in volatile, main memory.

Abstract: A database query compiler and compilation method has special facilities for compiling a query that includes an Offset sequence function, Offset(argument, index). During execution of the query, while the cursor for a table is pointing to a current row, the Offset function is used to access information from a previously accessed row. The argument of the Offset sequence function is a specified function of information associated with the previously accessed row of the table. The previously accessed row has a position that is index rows before the current row referenced by the cursor for the table. During compilation, the argument of the Offset sequence function is parsed to determine a set of auxiliary fields for each row of the table. Each auxiliary field of a row contains information that may be accessed during execution of the Offset sequence function while the cursor for that table is pointing to a subsequent row.

Abstract: A database query compiler and compilation method has special facilities for compiling a query that includes a Rows Since sequence function, Rows Since (search condition). A query normalizer includes a Rows Since function normalizer for normalizing the Rows Since sequence function. The Rows Since function normalizer parses the search condition of the Rows Since function to identify each reference to information from a previously access row and converts each such identified reference into an Offset sequence function, Offset(argument, index). The argument of the Offset sequence function is a specified function of the identified information from a previously accessed row of the table. The previously accessed row has a position that is index rows before the current row referenced by the cursor for the table. The query compiler places the resulting normalized search condition in a search loop that traverses successively earlier rows in the table until it finds a row that satisfies the search condition.