Abstract: The retrieval of distinct tuples in a relational database management system. In response to a request from a consumer process for distinct tuples in a relational database table matching a defined criteria, a distinct operator component sequentially requests tuples from a source component. The source component access the database table and returns a tuple in the sequence to the distinct operator component. The distinct operator component passes each tuple in the sequence to an auxiliary logger. The auxiliary component receives a tuples from the distinct component and determines if it is distinct from other previously received tuples in the sequence to verify its uniqueness to the distinct operator. Tuples that are verified as unique by the auxiliary logger are returned to the consumer process by the distinct operator upon verification.

Abstract: The retrieval of distinct tuples in a relational database management system. In response to a request from a consumer process for distinct tuples in a relational database table matching a defined criteria, a distinct operator component sequentially requests tuples from a source component. The source component access the database table and returns a tuple in the sequence to the distinct operator component. The distinct operator component passes each tuple in the sequence to an auxiliary logger. The auxiliary component receives a tuples from the distinct component and determines if it is distinct from other previously received tuples in the sequence to verify its uniqueness to the distinct operator. Tuples that are verified as unique by the auxiliary logger are returned to the consumer process by the distinct operator upon verification.

Abstract: Multidimensional clustered tables are provided for efficient processing and management in a relational database management system. A multidimensional clustered table is one whose data is simultaneously clustered along one or more independent dimensions, or clustering keys, and physically organized into blocks or pages on disk. When such a table is created, one can specify one or more keys as dimensions along which to cluster the table's data. Each of the dimensions can consist of one or more columns. Further provided are efficient query processing and maintenance techniques for use in conjunction with multidimensional clustered tables.

Abstract: A method to process a query for information stored in a relational database using indexes which have different granularity and/or composition is provided. The method involves selecting indexes of various granularity and/or composition based on the query, ordering and combining them (if necessary) in order to subset the data from a relational table to be optimally scanned. The ability to combine indexes is very useful to answer ad hoc queries for which no specific index exists. This requirement may be met by using index ANDing and index ORing techniques.

Abstract: Multidimensional clustered tables are provided for efficient processing and management in a relational database management system. A multidimensional clustered table is one whose data is simultaneously clustered along one or more independent dimensions, or clustering keys, and physically organized into blocks or pages on disk. When such a table is created, one can specify one or more keys as dimensions along which to cluster the table's data. Each of the dimensions can consist of one or more columns. Further provided are efficient query processing and maintenance techniques for use in conjunction with multidimensional clustered tables.

Abstract: A method to process a query for information stored in a relational database using indexes which have different granularity and/or composition is provided. The method involves selecting indexes of various granularity and/or composition based on the query, ordering and combining them (if necessary) in order to subset the data from a relational table to be optimally scanned. The ability to combine indexes is very useful to answer ad hoc queries for which no specific index exists. This requirement may be met by using index ANDing and index ORing techniques.

Abstract: A method and computer program product for analyzing data retrieval using index scanning in a database management system. The method involves scanning an index associated with a table in the database management system and selecting pages in the index. For each of the selected pages, the index entries are extracted and ranked. A distance parameter is then determined for each of the ranked index entries. The number of page transfers is estimated based on the distance parameters and the number of consecutive index entries which can be stored in the buffer pool.

Abstract: The retrieval of distinct tuples in a relational database management system. In response to a request from a consumer process for distinct tuples in a relational database table matching a defined criteria, a distinct operator component sequentially requests tuples from a source component. The source component access the database table and returns a tuple in the sequence to the distinct operator component. The distinct operator component passes each tuple in the sequence to an auxiliary logger. The auxiliary component receives a tuples from the distinct component and determines if it is distinct from other previously received tuples in the sequence to verify its uniqueness to the distinct operator. Tuples that are verified as unique by the auxiliary logger are returned to the consumer process by the distinct operator upon verification.