IDENTIFYING A WORKLOAD TYPE FOR A GIVEN WORKLOAD OF DATABASEREQUESTS

    公开(公告)号:CA2426439A1

    公开(公告)日:2004-10-23

    申请号:CA2426439

    申请日:2003-04-23

    Applicant: IBM CANADA

    Abstract: Workload type to be managed by a database management system (DBMS) is a key consideration in tuning the DBMS. Allocations for resources, such as main memory, can be very different depending on whether the workload type is Online Transaction Processing (OLTP) or Decision Support System (DSS). The DBMS also experiences changes in workload type during the normal processing cycle of the DBMS. Database administrators must therefore recognize the significant shift s of workload type that demand reconfiguring the DBMS in order to maintain acceptable levels of performance. Disclosed is a workload type classifier module, used by a DBMS, for recognizing workload types so that the DBMS may then manage or adjust its performance and reconfiguring its resources accordingly. The classifier may be constructed based on the most significant workload characteristics th at differentiate OLTP from DSS; then, the classifier is used for identifying changes in workload types contained in a workload. One aspect, there is provided, for an information retrieval system, a method of identifying a workload type for a given workload, including selecting a sample of the given workload, and predicting identification of the workload type based on a comparison between the selected sample and a set of rules.

    HEURISTIC-BASED CONDITIONAL DATA INDEXING

    公开(公告)号:CA2279119C

    公开(公告)日:2004-10-19

    申请号:CA2279119

    申请日:1999-07-29

    Applicant: IBM CANADA

    Abstract: A computer system for the indexing of data in which a heuristic determinatio n function is applied to predict an efficient index updating approach. The system is able to updat e an index relating to a first data set by incrementally updating the index or by a rebuild of the index at the completion of the addition of a second set of data to the first set of data. The system applies a heuristic determination function to the characteristics of the first set of data, its index, and the second set of data, to predict whether an incremental update or a rebuild update of the index will result in a more efficient rebuild of the data. The system applies this approach to a restore and rollforward recovery or a data load operation to improve the efficiency of these operations.

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