International Business Machines Corporation

Mark William Theuer

Rafal Przemyslaw Konik

Roger Alan Mittelstadt

Brian Robert Muras

Michael Alan Venz

Randy Lynn Egan

Paul Reuben Day

Cary Lee Bates

Mark John Anderson

Kyle Gilbertson

Kathryn Rose Steinbrink

Randy Keith Rolfe

Jane Ann Vold

Jonathan Lee Triebenbach

Ritchie Lee Nyland

Richard Donald Parrott

Kevin Robert Brettin

Renee Kristin Saxman

Russell Edward Bruhnke

Kathy Lynn Passe

Susan Liisa Romano

A method, system, and computer program product to manage a database is disclosed. The method, system, and computer program product may include structuring the database to have a first table having an index and a second table. A first key of the first table may be related to a second key of the second table. The method, system, and computer program product may include creating an entry locator in the index. The method, system, and computer program product may include maintaining an association between the second key of the second table and the entry locator of the index.

Management of a database system

An index shared between a plurality of tables is used to access a data sharing space (DSS) storing a set of rows from a base table having a plurality of rows with stored data. First data values of the index are identified in response to a query for a table. A subset of rows is then retrieved from the DSS using the index elements corresponding to the first data values. Second data values and some of the first data values are then identified in response to a second query for a table. A second subset of rows are then retrieved from the DSS using the index elements corresponding to the second data values and some of the first data values and the query is then applied to the subset of rows.

Generating and accessing a data table

A computer system can generate a materialized query table (MQT) for data from a base table that has a plurality of rows and columns that each contain stored data. The computer system can receive a query to data stored in a row from the base table. The system can identify a column in the row and determine that data from a cell in the row and the column is above a threshold memory size. The system can generate, in response to determining that the data being above the threshold memory size, an MQT that includes data for the row and that includes a reference pointer that points to a location shared with another table.

Materialized query tables with shared data

A respective volatility attribute associated with each of one or more tables of a computerized database is used to determine circumstances under which a page of table data is paged out of memory, by preferentially retaining pages from volatile database tables in memory. Various optional additional uses of a volatility attribute to manage a database are disclosed. Preferably, database parameters are automatically monitored over time and database table volatility state is automatically determined and periodically adjusted.

Preferentially retaining memory pages using a volatile database table attribute

A respective volatility attribute associated with each of one or more tables of a computerized database is used in any of various aspects to (a) determine how table data is stored in a physical storage device; (b) regulate the use of a materialized query table using database table data; and/or (c) influence circumstances under which indexes are created or advised by database analytic software. Various optional additional uses of a volatility attribute to manage a database are disclosed. Preferably, database parameters are automatically monitored over time and database table volatility state is automatically determined and periodically adjusted.

Managing a computerized database using a volatile database table attribute

In an embodiment, a first key value is received. A plurality of candidate rows are found in a database table, wherein the plurality of candidate rows are deleted. For the plurality of candidate rows, a plurality of respective impacts on a plurality of respective densities of each of other key values that are stored within a first key range of the first key value are calculated. For the plurality of candidate rows, a plurality of function results of the plurality of respective impacts on the plurality of respective densities are calculated. A selected candidate row of the plurality of candidate rows with a smallest function result of the plurality of function results of the plurality of respective impacts on the plurality of respective densities is selected. The first key value is stored to the selected candidate row.

Storing a key value to a deleted row based on key range density

Systems, methods, and computer program products to perform an operation comprising upon determining that a received query requests values of sensitive data stored in a secure database table of a database, computing a security score for the received query based on a determined specificity of a selection predicate of the received query, and upon determining that the security score exceeds a security threshold, performing a predefined operation to restrict access to the requested values of the sensitive data.

Intelligent database with secure tables

A computer-implemented method for improving database management includes selecting one or more database records that are requested based on a query statement. The one or more database records may are read from a first database file. The one or more database records are copied from the first database file and stored to a memory. The one or more database records are deleted from the first database file at substantially the same time as the reading the one or more database records. The reading and the deleting occur through a single read and delete input/output (I/O) operation.

Read and delete input/output operation for database management

A database table is monitored to automatically determine its volatility, and at least one volatility attribute expressing volatility state is saved. The volatility attribute is used to manage the database, e.g., to determine an optimum query execution strategy for a query involving data in the table, and/or for determining whether to re-optimize a previously saved query execution strategy and/or for managing storage and retrieval of table data. Preferably, parameters of the database table are captured at regular sampling intervals and a figure of merit representing volatility is computed from the parameter values. Preferably, the database supports the SQL database language, and the volatility attribute is or includes the SQL VOLATILE attribute. In an additional embodiment, the database manager may express volatility of a database table as a value within a range.

Autonomic regulation of a volatile database table attribute

Methods to perform an operation comprising upon determining that a received query requests values of sensitive data stored in a secure database table of a database, computing a security score for the received query based on a determined specificity of a selection predicate of the received query, and upon determining that the security score exceeds a security threshold, performing a predefined operation to restrict access to the requested values of the sensitive data.

A respective volatility attribute associated with each of one or more tables of a computerized database is used to adjust an extension file size value associated with a database table file space. Various optional additional uses of a volatility attribute to manage a database are disclosed. Preferably, database parameters are automatically monitored over time and database table volatility state is automatically determined and periodically adjusted.

Growing community of inventors

Rochester, MN, United States of America

Mark William Theuer