Abstract: Disclosed aspects relate to query plan management associated with a shared pool of configurable computing resources. A query, which relates to a set of data located on the shared pool of configurable computing resources, is detected. A virtual machine includes the set of data. With respect to the virtual machine, a set of burden values of performing a set of asset actions is determined. Based on the set of burden values, a query plan to access the set of data is established. Using at least one asset action of the set of asset actions, the query plan is processed.

Abstract: In various embodiments, a computer-implemented method includes collecting, using biometric sensors, stress data associated with a user of a virtual reality device. The method may also include determining a stress level of the user based on the stress data. The method may also include retrieving historical data of the user. The method may also include monitoring a current environment of the user during a current virtual session. The method may also include identifying a safety hazard during the current virtual session based on the stress data and the current environment. The method may also include determining, using the historical data, virtual scenarios that affect the stress level of the user. The method may also include generating, using the determined virtual scenarios, a safe virtual scenario to eliminate the safety hazard.

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: 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.

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 remote visual experience application which transmits real-time video remotely includes a filter which obscures one or more previously identified regions in space when the regions come within the camera's field of vision. The application may be a shared visual experience application, in which the camera is mounted to a wearable appliance of a local user. The application may include a function for mapping regions of a space in which the application will be used, and defining different levels of remote access for different regions of the space. A space map may be generated before or during transmission of video to a remote user. Exemplary embodiments include a virtual vendor house call application or a game. The application may further include an audio filter for filtering an audio signal.

Abstract: A computer detects a user computing device when the user enters the store and receives the user's purchase history and preference information from a database. The computer receives a list and/or recipe that the user inputs into the application. This list and/or recipe is a list of items that the user plans to purchase. The computer identifies an item on the list, determines whether the item is in stock, and generates a route through the store so the user will reach each item on his list. The computer transmits the route to the user's computing device to be displayed.

Abstract: A computer detects a user computing device when the user enters the store and receives the user's purchase history and preference information from a database. The computer receives a list and/or recipe that the user inputs into the application. This list and/or recipe is a list of items that the user plans to purchase. The computer identifies an item on the list, determines whether the item is in stock, and generates a route through the store so the user will reach each item on his list. The computer transmits the route to the user's computing device to be displayed.

Abstract: A computer detects a user computing device when the user enters the store and receives the user's purchase history and preference information from a database. The computer receives a list and/or recipe that the user inputs into the application. This list and/or recipe is a list of items that the user plans to purchase. The computer identifies an item on the list, determines whether the item is in stock, and generates a route through the store so the user will reach each item on his list. The computer transmits the route to the user's computing device to be displayed.

Abstract: A computer detects a user computing device when the user enters the store and receives the user's purchase history and preference information from a database. The computer receives a list and/or recipe that the user inputs into the application. This list and/or recipe is a list of items that the user plans to purchase. The computer identifies an item on the list, determines whether the item is in stock, and generates a route through the store so the user will reach each item on his list. The computer transmits the route to the user's computing device to be displayed.

Abstract: A remote visual experience application which transmits real-time video remotely includes a filter which obscures one or more previously identified regions in space when the regions come within the camera's field of vision. The application may be a shared visual experience application, in which the camera is mounted to a wearable appliance of a local user. The application may include a function for mapping regions of a space in which the application will be used, and defining different levels of remote access for different regions of the space. A space map may be generated before or during transmission of video to a remote user. Exemplary embodiments include a virtual vendor house call application or a game. The application may further include an audio filter for filtering an audio signal.

Abstract: A query is received. Based on statistics for a database, a first query access plan is generated for executing the query on the database. A first result set for the query is obtained by implementing the first query access plan on the database. Based on at least one trend in the statistics, a target time after which implementing the first query access plan will fail a set of criteria is forecasted. In response to the forecasting and based on the statistics, a replacement query access plan is generated prior to the target time. After the target time, a second result set for the query is obtained by implementing the replacement query access plan rather than the first query access plan.

Abstract: Disclosed aspects relate to query hint learning in a database management system. A hint in a first query is detected by the database management system. The first query has a first signature. A second query is received by the database management system. The second query has a second signature. A determination is made by the database management system that the second signature correlates with the first signature. A query plan is established by the database management system. The query plan is based on the second query and uses the hint in the first query. In response to receiving the second query, the database management system processes the query plan.

Abstract: Disclosed aspects relate to query hint learning in a database management system. A hint in a first query is detected by the database management system. The first query has a first signature. A second query is received by the database management system. The second query has a second signature. A determination is made by the database management system that the second signature correlates with the first signature. A query plan is established by the database management system. The query plan is based on the second query and uses the hint in the first query. In response to receiving the second query, the database management system processes the query plan.

Abstract: Disclosed aspects relate to query hint management for a database management system. With respect to a hint for a query, a set of hint profile data is established. The database management system detects a triggering event. Based on the set of hint profile data, the database management system determines to perform a hint action in response to the triggering event. Performance of the hint action is initiated.

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 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.

Abstract: A first database management system (DBMS) running on first computer having a first set of computing resources determines that with respect to the first set of computing resources a first query access plan for executing a query satisfies a set of query optimization criteria. A determination is then made that with respect to a second set of computing resources the first query access plan fails a set of preliminary criteria. In response to this failure determination, a second query access plan for executing the query is generated. Prior to having a second DBMS running on a second computer having the second set of computing resources receive a request to execute the query, a determination is made that with respect to the second set of computing resources the second query access plan satisfies the set query optimization criteria.

Abstract: A first database management system (DBMS) running on first computer having a first set of computing resources determines that with respect to the first set of computing resources a first query access plan for executing a query satisfies a set of query optimization criteria. A determination is then made that with respect to a second set of computing resources the first query access plan fails a set of preliminary criteria. In response to this failure determination, a second query access plan for executing the query is generated. Prior to having a second DBMS running on a second computer having the second set of computing resources receive a request to execute the query, a determination is made that with respect to the second set of computing resources the second query access plan satisfies the set query optimization criteria.