Abstract: A database system may implement resource management for redistribution of stored database information in additional database resources. Resource management may include detection of the presence of additional database resources, such as storage and processing resources. Based on conditions associated with the additional resources and database information selected for potential redistribution, resource management may include a determination as to whether or not redistribution of the database information is to be performed. Resource management may include a cost-benefit analysis to determine if redistribution of database information is to be performed. The cost-benefit analysis may be based on factors related to both the additional resources and the database information being considered for redistribution.

Abstract: Table rows are mapped to corresponding characters, where the mapping produces a collection of the characters. A query is received to identify a pattern in the table rows. The collection of the characters is accessed to process the query.

Abstract: In a database system having processing units, a request is received to calculate aggregates of multiple combinations of a given set of columns. The processing units are divided into multiple groups, where each of the multiple groups includes a corresponding subset of the processing units. Within each of the groups, data of each processing unit in the group is replicated to other one or more processing units in the group. Within each of the groups, aggregates of at least some of the multiple combinations of the given set of columns are calculated by the processing units in the group using the replicated data.

Abstract: A query to perform an ordered analytic function contains a clause specifying creation of dynamic partitions, where the clause contains a partitioning condition to specify the dynamic partitions. During processing of the query, dynamic partitions are identified based on evaluating the partitioning condition. To identify the dynamic partitions, a first table is created that contains a first column to track rows of an input table for indicating whether the partitioning condition evaluates to true. The first column of the first table is used to identify the dynamic partitions.

Abstract: A system, method, and computer-readable medium that facilitate counting the number of distinct values in several columns of a table utilizing parallel aggregation mechanisms.

Abstract: In a database system, a query to perforin an ordered analytic function is received. The query contains a clause specifying creation of dynamic partitions, where the clause contains a partitioning condition to specify the dynamic partitions. During processing of the query, the dynamic partitions are identified based on evaluating the partitioning condition.

Abstract: The cost of running a query (having a query range) on a multidimensional database may be estimated using a process factors criteria beyond merely the number of affected records. First, a materialized view of the database may be represented as a container of tuples, sorted by key. Then keys may be stepped through, each key representing a mapping of a combination of tuples from the container. At each step, the process may request the next smallest key in the query range greater than or equal to the key of the current step, which results in the tuple in the database whose key is the smallest, greater than or equal to the requested key, and determine if the resulting is in the query range. The cost of the query may then be estimated as the number of tuples upon which the range check was performed.

Abstract: A database system includes a storage to store a view containing results of a cube-based operation on at least one base table, with the view containing a first result set for a group-by on a first grouping set, and a second result set for a group-by on a second grouping set. In response to a change to the at least one base table, a controller updates the first result set by computing a change to the first result set based on a change in the at least one base table, and updates the second result set by computing a change to the second result set based on the change to the first result set.

Abstract: A multi-dimensional table having plural dimensions is stored in a database system, where plural grouping combinations of the plural dimensions define corresponding subsets of the multi-dimensional table. An aggregate measure for each of at least some of the plural subsets is computed, where the aggregate measure for a particular subset represents a relationship of the particular subset to one or more parents of the particular subset. Less than all of the at least some subsets are selected to materialize based on the aggregate measures.

Abstract: A database system computes an aggregate on distinct values of at least one attribute for each of plural groups specified by multiple levels of grouping sets. Distinct values of the at least one attribute are identified and stored in a first table. The first table is used to compute aggregates for groups specified by a first grouping set and for groups specified by a second grouping set.

Abstract: Selection of certain views of a multidimensional database to materialize may be accomplished using an efficient and effective solution. A set of all potential views may be stored in a structure. A path in the structure may then be traversed in an indicated direction through the structure, the path including two or more potential views and beginning at an indicated view. Then two or more immaterialized views in the path may be compared to each other to determine which immaterialized view is the optimum choice for maximizing benefit if selected to be materialized. Then the traversing and comparing may be continually iterated through, each iteration utilizing an indicated direction different than the last, each iteration also utilizing an indicated view set at the optimum choice determined by the last iteration, the iterating continuing until it converges on a single view. That single view may then be selected for materialization.

Abstract: The cost of running a query (having a query range) on a multidimensional database may be estimated using a process factors criteria beyond merely the number of affected records. First, a materialized view of the database may be represented as a container of tuples, sorted by key. Then keys may be stepped through, each key representing a mapping of a combination of tuples from the container. At each step, the process may request the next smallest key in the query range greater than or equal to the key of the current step, which results in the tuple in the database whose key is the smallest, greater than or equal to the requested key, and determine if the resulting tuple is in the query range. The cost of the query may then be estimated as the number of tuples upon which the range check was performed.

Abstract: A database system is capable of performing interpolation (e.g., temporal interpolation) of data in response to receiving a database query. In one implementation, the database query contains an interpolation function. The database system in one example configuration is a parallel database system that has plural processing units that are capable of performing interpolation of data in parallel.

Abstract: A method and apparatus is provided in a parallel database system having a plurality of nodes for computing a moving aggregate of an attribute of a relation having multiple tuples. Portions of the relation are distributed across the plurality of nodes of the database system. For each node i, the database system identifies one or more other nodes that contain tuples of the relation which are covered by a moving window of each tuple of the relation at node i. For each such identified node, a value representing an aggregate of the tuples at each such identified node is communicated to node i. The moving aggregate is then calculated using at least tuples of the relation at node i as well as the value from each of the identified one or more nodes.

Abstract: A stratified sampling mechanism is provided in a database system. The stratified sampling mechanism includes defining a clause in a query that indicates stratified sampling is desired. Data from a source table is stratified into different subgroups based on stratification conditions in the query. Sampling is performed within each subgroup.

Abstract: A method and apparatus is provided in a parallel database system having a plurality of nodes for computing a moving aggregate of an attribute of a relation having multiple tuples. Portions of the relation are distributed across the plurality of nodes of the database system. For each node i, the database system identifies one or more other nodes that contain tuples of the relation which are covered by a moving window of each tuple of the relation at node i. For each such identified node, a value representing an aggregate of the tuples at each such identified node is communicated to node i. The moving aggregate is then calculated using at least tuples of the relation at node i as well as the value from each of the identified one or more nodes.

Abstract: A parallel database system includes multiple processing units and associated storage modules. To achieve even distribution of workload, rows of a table are distributed as evenly as possible across the multiple processing units using a predefined partitioning algorithm. The predefined partitioning algorithm defines groups and probabilities assigned to boundary points defining the groups. Partitioning of data is based on the boundary points and the assigned probabilities.

Abstract: A parallel random sampling algorithm (such as a parallel simple random sampling algorithm) utilizes the parallelism of a parallel relational database management system. A random number generator in one node generates random number seeds for a second random number generator in each of the nodes. Random numbers generated by the second random number generators in parallel are used to obtain random sample tuples in each of the nodes.

Abstract: A method, apparatus, and article of manufacture for selecting one or more of the highest ranking records in a database system that has one or more processing units. At each processing unit, a candidate list of records is generated in a memory space of the processing unit. Each record contains a field value. The generated candidate list of records is ranked based on the field value as each new candidate is added to the generated candidate list. When the memory space of the processing unit is insufficient, the ranked candidate list of records are transferred from the memory space of the processing unit to a data store. At the data store, a predefined number of extrema values are identified by using the transferred candidate list of records.

Abstract: A method, apparatus, and article of manufacture for random sampling of rows stored in a table, wherein the table has a plurality of partitions. A row count is determined for each of the partitions of the table and a total number of rows in the table is determined from the row count for each of the partitions of the table. A proportional allocation of a sample size is computed for each of the partitions based on the row count and the total number of rows. A sample set of rows of the sample size is retrieved from the table, wherein each of the partitions of the table contributes its proportional allocation of rows to the sample set of rows. Preferably, the computer system is a parallel processing database system, wherein each of its processing units manages a partition of the table, and some of the above steps can be performed in parallel by the processing units.