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: 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: In an embodiment, a query plan is compressed to data in a cache at a high compression level if a runtime of a query that the query plan implements is greater than a high time threshold. The query plan is compressed to the data in the cache at a medium compression level if the runtime of the query that the query plan implements is less than the high time threshold and greater than a low time threshold. The query plan is stored to the data in the cache at an uncompressed level if the runtime of the query that the query plan implements is less than the low time threshold.

Abstract: In an embodiment, a request is received that specifies a function and a specified key value. Rows from all tables that are accessible from the specified key value are transitively searched, wherein the transitively searching further comprises finding values in a plurality of pairs of columns, wherein found rows that are found by the transitively searching comprise values in a respective first column of the plurality of pairs of columns that satisfy a dependency relationship with values in a respective second column of the plurality of pairs of columns. The function is executed against only the found rows.

Abstract: In an embodiment, a query plan is compressed to data in a cache at a high compression level if a runtime of a query that the query plan implements is greater than a high time threshold. The query plan is compressed to the data in the cache at a medium compression level if the runtime of the query that the query plan implements is less than the high time threshold and greater than a low time threshold. The query plan is stored to the data in the cache at an uncompressed level if the runtime of the query that the query plan implements is less than the low time threshold.

Abstract: In an embodiment, a request is received that specifies a function and a specified key value. Rows from all tables that are accessible from the specified key value are transitively searched, wherein the transitively searching further comprises finding values in a plurality of pairs of columns, wherein found rows that are found by the transitively searching comprise values in a respective first column of the plurality of pairs of columns that satisfy a dependency relationship with values in a respective second column of the plurality of pairs of columns. The function is executed against only the found rows.

Abstract: In an embodiment, a first plurality of rows of a first table are read from memory in an order of page addresses of pages in the memory that comprise the first plurality of rows. First selected rows from the first plurality of rows that meet a query predicate are stored into a result set. After the reading the first plurality of rows in the order of the page addresses, a second plurality of rows of the first table are read from secondary storage, in an order of row identifiers of the second plurality of the rows in the first table. Second selected rows from the second plurality of rows that meet the query predicate are stored into the result set.

Abstract: A data sharing space (DSS) is generated for a base table having a set of rows with stored data. Requests are received to generate tables, each request including a query to the base table. A row from the set of rows is then accessed. The query is then applied to the row to generate results. An index value is then determined and a portion of the row is stored in the DSS based on the index value.

Abstract: 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.

Abstract: 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.

Abstract: A data sharing space (DSS) is generated for a base table having a set of rows with stored data. Requests are received to generate tables, each request including a query to the base table. A row from the set of rows is then accessed. The query is then applied to the row to generate results. An index value is then determined and a portion of the row is stored in the DSS based on the index value.

Abstract: A method, system, and computer program product to create an access control bit mapping (ACBM) structure for a corresponding database table are disclosed. The ACBM structure may include a relative record number (RRN) bit map. The RRN bit map may describe the access rights for a parameter. The computer-implemented method may maintain one or more statistics describing the RRN bit map. The method may additionally provide for updating the ACBM structure. The method may also provide for using the ACBM structure to process a database query.

Abstract: A wireless access point receives a set of invalid passwords from at least one wireless device attempting to connect to a network through the wireless access point. The wireless access point reduces RF signal power in response to receiving the set of invalid passwords.

Abstract: A method, a system, and a computer program product for managing a database are disclosed. Managing the database includes managing a table of the database, the table having a set of fields including a first field in a first row of the table. Managing the table includes selecting, in the first field, a first input value configured to identify a first dynamic data function utilized to determine a first output value for the first field. Managing the table includes determining the first output value for the first field using the first dynamic data function. Managing the table includes returning (for a read request) the first output 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: A method, a system, and a computer program product for managing a database are disclosed. Managing the database includes managing a table of the database, the table having a set of fields including a first field in a first row of the table. Managing the table includes selecting, in the first field, a first input value configured to identify a first dynamic data function utilized to determine a first output value for the first field. Managing the table includes determining the first output value for the first field using the first dynamic data function. Managing the table includes returning (for a read request) the first output 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: A wireless access point receives a set of invalid passwords from at least one wireless device attempting to connect to a network through the wireless access point. The wireless access point reduces RF signal power in response to receiving the set of invalid passwords.

Abstract: 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.

Abstract: 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.