Abstract: A method, system, and computer program product for a multi-resolution storage scheme for historical data are provided. The method includes dividing the historical data into a plurality of time frames and determining an amount of compression for each of the time frames, where at least two of the time frames have a different amount of compression. The method further includes applying the amount of compression to each of the time frames, resulting in multi-resolution historical data, and storing the multi-resolution historical data.

Abstract: A window size for outlier detection in a time series of a database system is determined. Strength values are calculated for data points using a set of window sizes, resulting at least in one set of strength values for each window size. The strength values increase as a distance between a value of a respective data point and a local mean value increases. For each set of strength values, a weighted sum is calculated based on the respective set of strength values. A weighting function is used to suppress the effect of largest strength values and a window size is selected based on the weighted sums.

Abstract: A technique for dynamic integration and semantic analysis of structured data and unstructured textual data including: defining and selecting static attributes and dynamic attribute from structured data, embedding static and dynamic views of the selected corresponding attributes in an annotated document, linking the unstructured textual data with the structured data using the defined static and dynamic attributes, populating an annotated document structure of multiple annotated documents, performing semantic analysis of a query across the unstructured textual data and structured data, querying the annotated document structure to provide query results satisfying static part of the query, processing static and dynamic parts of the query by querying structured data and the annotated document structure, as appropriate, and providing a combined query processing result satisfying the dynamic and static part the query. Other embodiments are also disclosed.

Abstract: A method for scheduling a workload comprising a plurality of transactions relating to a database management system is disclosed. The method comprises the steps of determining a log space amount required by each transaction in the workload, estimating the total log space required for executing the workload based on the log space amounts required by each transaction, and scheduling execution of the workload based on the estimated total log space.

Abstract: A method, system, and computer program product for a multi-resolution storage scheme for historical data are provided. The method includes dividing the historical data into a plurality of time frames and determining an amount of compression for each of the time frames, where at least two of the time frames have a different amount of compression. The method further includes applying the amount of compression to each of the time frames, resulting in multi-resolution historical data, and storing the multi-resolution historical data.

Abstract: A method, system, and computer program product for a multi-resolution storage scheme for historical data are provided. The method includes dividing the historical data into a plurality of time frames and determining an amount of compression for each of the time frames, where at least two of the time frames have a different amount of compression. The method further includes applying the amount of compression to each of the time frames, resulting in multi-resolution historical data, and storing the multi-resolution historical data.

Abstract: A method for scheduling a workload comprising a plurality of transactions relating to a database management system is disclosed. The method comprises the steps of determining a log space amount required by each transaction in the workload, estimating the total log space required for executing the workload based on the log space amounts required by each transaction, and scheduling execution of the workload based on the estimated total log space.

Abstract: A window size for outlier detection in a time series of a database system is determined. Strength values are calculated for data points using a set of window sizes, resulting at least in one set of strength values for each window size. The strength values increase as a distance between a value of a respective data point and a local mean value increases. For each set of strength values, a weighted sum is calculated based on the respective set of strength values. A weighting function is used to suppress the effect of largest strength values and a window size is selected based on the weighted sums.

Abstract: A method for scheduling a workload comprising a plurality of transactions relating to a database management system is disclosed. The method comprises the steps of determining a log space amount required by each transaction in the workload, estimating the total log space required for executing the workload based on the log space amounts required by each transaction, and scheduling execution of the workload based on the estimated total log space.

Abstract: A method and system to predict future performance of a database management system (DBMS) is disclosed. The invention uses a time series of historical data of operating parameters to predict future values of the operating parameters. The predicted future values of the operating are used to predict the future performance of the DBMS.