INDEPENDENT DEFERRED INCREMENTAL REFRESH OF MATERIALIZED VIEWS

    公开(公告)号:CA2414983A1

    公开(公告)日:2004-06-23

    申请号:CA2414983

    申请日:2002-12-23

    Applicant: IBM CANADA

    Abstract: A system and method for flexible execution in the order of operations for loading data into base tables, for checking the base tables for constraint violations, an d for refreshing the materialized views. The system and method maintains the ability to perform a ny of these operations incrementally. Materialized views may be incrementally refreshed at different points in time independently of one another and independently of the load append operations performed on the base tables. The system and method includes load appending data to on e base table, incrementally refreshing of just one associated materialized view (and makin g the materialized view available immediately thereafter) and deferring refresh of the other materialized views, load appending more data into other base tables, and incrementally refreshing all materialized views with respect to all load append operations. Advantageously, the system and method handles combinations of multiple materialized views associated with a single base table as well as multiple base tables referenced or associated with one materialized view.

    METHOD OF QUERY TRANSFORMATION USING WINDOW AGGREGATION

    公开(公告)号:CA2418163A1

    公开(公告)日:2004-07-31

    申请号:CA2418163

    申请日:2003-01-31

    Applicant: IBM CANADA

    Abstract: A method of query transformation using window aggregation to transform queri es involving subqueries. An optimizer in a relational database management system transfor ms queries to optimize their efficiency and speed. The method transforms queries that have a subquery, replacing the subquery with a window aggregation function. In the case of a correlated subquery, the window aggregation function is partitioned by a correlated column of a correlated table. All data in the main select, or outer block, of the query that was obtained through references to the correlated table is instead obtained through the new window aggregation subquery. By using windo w aggregation, the aggregation is performed at the same time as the selection of relevant data from the correlated table, thereby compiling all needed data in a single pass through the table or view . Reducing the number of times that tables or views are accessed reduces the computational demands of a query.

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