Abstract: In accordance with aspects of the present invention, provided are methods for incrementally estimating the cardinality of a derived relation including statistically correlated partially applicable predicates for a range-partitioned table. During the generation of a QEP a cardinality estimate is calculated in which one or more partially applicable predicates is correlated to another partially applicable predicate and/or to one or more fully applicable predicates. The cardinality includes a number of rows expected to be returned by the QEP and is computed in an incremental fashion for each operator of the QEP.

Abstract: A method and system for accurately estimating a result size of a Group-By operation in a relational database. The estimate utilizes the probability of union of the columns involved in the operation, as well as the relative cardinality of each column with respect to the other columns in the operation. In addition, the estimate incorporates the use of table filters when indicated such that table filters are applied prior to determining the size of the tables in the operation, as well as including equivalent columns into the list of columns that are a part of the Group-By operation. Accordingly, the estimate of the result size of the operation includes influencing factors that provide an accurate estimation of system memory requirements.

Abstract: A choose tree is generated at compile time to facilitate a determination if any partition of a range partitioned database table includes a particular key at runtime. To generate the choose tree at compile time, a query compiler receives a source code indicative of each partition of the range partitioned database table, and generates the choose tree from the source code at compile time where the choose tree is representative of a pre-computed binary search of the range partitioned database table. Thereafter, the choose tree can be interpreted/executed at runtime to facilitate a traversal of the choose tree for determining if any partition of the range partitioned database table includes the particular key.

Abstract: In accordance with aspects of the present invention, provided are methods for incrementally estimating the cardinality of a derived relation including statistically correlated partially applicable predicates for a range-partitioned table. During the generation of a QEP a cardinality estimate is calculated in which one or more partially applicable predicates is correlated to another partially applicable predicate and/or to one or more fully applicable predicates. The cardinality includes a number of rows expected to be returned by the QEP and is computed in an incremental fashion for each operator of the QEP.

Abstract: In accordance with aspects of the present invention, provided are methods for incrementally estimating the cardinality of a derived relation including statistically correlated partially applicable predicates for a range-partitioned table. During the generation of a QEP a cardinality estimate is calculated in which one or more partially applicable predicates is correlated to another partially applicable predicate and/or to one or more fully applicable predicates. The cardinality includes a number of rows expected to be returned by the QEP and is computed in an incremental fashion for each operator of the QEP.

Abstract: A method and system for accurately estimating a result size of a Group-By operation in a relational database. The estimate utilizes the probability of union of the columns involved in the operation, as well as the relative cardinality of each column with respect to the other columns in the operation. In addition, the estimate incorporates the use of table filters when indicated such that table filters are applied prior to determining the size of the tables in the operation, as well as including equivalent columns into the list of columns that are a part of the Group-By operation. Accordingly, the estimate of the result size of the operation includes influencing factors that provide an accurate estimation of system memory requirements.

Abstract: A method and system for accurately estimating a result size of a Group-By operation in a relational database. The estimate utilizes the probability of union of the columns involved in the operation, as well as the relative cardinality of each column with respect to the other columns in the operation. In addition, the estimate incorporates the use of table filters when indicated such that table filters are applied prior to determining the size of the tables in the operation, as well as including equivalent columns into the list of columns that are a part of the Group-By operation. Accordingly, the estimate of the result size of the operation includes influencing factors that provide an accurate estimation of system memory requirements.

Abstract: A method of searching for information within a database that includes: identifying a set of leading index key columns, from among a plurality of index key columns, that has a limited number of unique values; utilizing the identified set of leading index key columns to perform an index scan in order to retrieve each unique value from the set of leading index key columns; and utilizing each of the retrieved unique values from the set of leading index key columns to perform an index lead key self-join operation, such that predicates on the non-leading index key columns are utilized to position an index scan operation.

Abstract: A method and system for accurately estimating a result size of a Group-By operation in a relational database. The estimate utilizes the probability of union of the columns involved in the operation, as well as the relative cardinality of each column with respect to the other columns in the operation. In addition, the estimate incorporates the use of table filters when indicated such that table filters are applied prior to determining the size of the tables in the operation, as well as including equivalent columns into the list of columns that are a part of the Group-By operation. Accordingly, the estimate of the result size of the operation includes influencing factors that provide an accurate estimation of system memory requirements.

Abstract: In accordance with aspects of the present invention, provided are methods, systems, and computer program products for incrementally estimating the cardinality of a derived relation including statistically correlated partially applicable predicates for a range-partitioned table. During the generation of a QEP a cardinality estimate is calculated in which one or more partially applicable predicates is correlated to another partially applicable predicate and/or to one or more fully applicable predicates. The cardinality includes a number of rows expected to be returned by the QEP and is computed in an incremental fashion for each operator of the QEP.

Abstract: A method and system are provided for optimizing a query migrated from a source database system to a possibly dissimilar target database system, wherein the execution plan chosen for the migrated query is communicated from the source database system. Explain facilities of the source database system are used to gather information describing the execution plan used in the source database system for the migrated query. The explain information is then used to obtain plan directives for communicating the execution plan to the optimizer of the target system. If the obtained plan directives require auxiliary data structures, the source system catalogs are queried to determine the attributes of these auxiliary structures. These attributes are then used to create equivalent auxiliary structures in the target system.

Abstract: A method and system for optimizing a query in a snow flake schema (60) within a relational database. The schema (60) includes a fact table (12) and multiple dimension tables and a plurality of dimension levels, with at least one dimension table at each level. A logical node (310) comprised of a level one child dimension table (32) and all dimension tables (62) rooted at this level one child dimension table is created based upon the cumulative selectivity calculation for all of the dimension tables at each level of the database (210). Creation of the logical node reduces a snow flake schema to a star schema, thereby mitigating search space traversal.

Abstract: A choose tree is generated at compile time to facilitate a determination if any partition of a range partitioned database table includes a particular key at runtime. To generate the choose tree at compile time, a query compiler receives a source code indicative of each partition of the range partitioned database table, and generates the choose tree from the source code at compile time where the choose tree is representative of a pre-computed binary search of the range partitioned database table. Thereafter, the choose tree can be interpreted/executed at runtime to facilitate a traversal of the choose tree for determining if any partition of the range partitioned database table includes the particular key.

Abstract: A method and system for accurately estimating a result size of a Group-By operation in a relational database. The estimate utilizes the probability of union of the columns involved in the operation, as well as the relative cardinality of each column with respect to the other columns in the operation. In addition, the estimate incorporates the use of table filters when indicated such that table filters are applied prior to determining the size of the tables in the operation, as well as including equivalent columns into the list of columns that are a part of the Group-By operation. Accordingly, the estimate of the result size of the operation includes influencing factors that provide an accurate estimation of system memory requirements.

Abstract: A method and system for optimizing a query in a snow flake schema (60) within a relational database. The schema (60) includes a fact table (12) and multiple dimension tables and a plurality of dimension levels, with at least one dimension table at each level. A logical node (310) comprised of a level one child dimension table (32) and all dimension tables (62) rooted at this level one child dimension table is created based upon the cumulative selectivity calculation for all of the dimension tables at each level of the database (210). Creation of the logical node reduces a snow flake schema to a star schema, thereby mitigating search space traversal.