Abstract: Techniques are disclosed for selecting between query execution plans in part based on VM mirroring costs. In one embodiment, a query optimizer determines runtimes for multiple query execution plans, and modifies these runtimes based on flashing cost, which is itself determined based on the amount of memory which needs to be flashed to the secondary memory if each execution plan is executed. In so doing, the query optimizer may select a execution plan which takes a longer to run, but incurs less flashing cost. By considering both the query runtime itself and the flashing cost, the query optimizer may be better able to determine the fastest query execution plan to execute.

Abstract: 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.

Abstract: A method, a system, and a computer program product for managing a database are disclosed. Managing the database includes managing an index of a table of the database. Managing the index includes determining the table includes a first field having a first input value configured to identify a first dynamic data function utilized to determine a first output value for the first field. In embodiments, managing the index includes determining the first dynamic data function is deterministic, determining the first output value for the first field using the first dynamic data function, and storing the first output value for the first field. In embodiments, managing the index includes determining the first dynamic data function is nondeterministic, determining a first special value to represent the first output value for the first field, and storing the first special value for the first field.

Abstract: A method, a system, and a computer program product for managing a database are disclosed. Managing the database includes managing an index of a table of the database. Managing the index includes determining the table includes a first field having a first input value configured to identify a first dynamic data function utilized to determine a first output value for the first field. In embodiments, managing the index includes determining the first dynamic data function is deterministic, determining the first output value for the first field using the first dynamic data function, and storing the first output value for the first field. In embodiments, managing the index includes determining the first dynamic data function is nondeterministic, determining a first special value to represent the first output value for the first field, and storing the first special value for the first field.

Abstract: An apparatus and method utilize partitioned database tables divided into data allocation containers (DACs) where data is placed into the DACs based on usage of the data in past queries. Records that are used most often are placed together and records that are used less often are placed together to improve database performance. In preferred embodiments, a database manager determines where to place data into the DACs based on how often the data is selected by a database query using a DAC selection ratio (DSR). The database manager may determine when to perform table maintenance to move rows of data to the appropriate DACs based on a timestamp or last check date (LCD) stored in the database.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

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

Abstract: A partially built index is used in a computer database system. When a database index is being built, or rebuilt, the database manager keeps track of the records processed using a relative row number (RRN) to track what part of the partially built index is complete. Queries are optimized by a query optimizer associated with the database manager that uses the portion of the index that is complete with reference to the RRN. The remainder of the database table beyond the RRN can be estimated or implemented using the completed data or can be determined by searching the relevant portion of the database table.

Abstract: 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.