Abstract: A computer system displays a data visualization in a data visualization user interface. In response to detecting a user input that selects a subset of visual data marks from the data visualization, the computer system displays a summary of the selected subset of visual data marks in a summary tab of a view data window. When the computer system determines that the selected subset of visual marks (1) corresponds to a plurality of data fields and (2) references a row-level calculation that uses logical fields from at least two logical tables of a plurality of logical tables of a data model, the computer system (i) generates a representation of the row-level calculation and (ii) displays the representation of the row-level calculation as a first tab in the view data window, distinct from the summary tab.

Abstract: A user selects a data source, and a computer displays a data visualization in a data visualization user interface according to the data source. The data visualization includes visual data marks representing data from the data source. The user selects a subset of the visual data marks. In response, the computer displays a view data window having a summary of the selected data marks. The computer obtains a data model encoding the data source as a tree of logical tables. The computer identifies aggregate measures corresponding to the selected data marks, where each aggregate measure is aggregated from logical tables of the data model. The computer displays each aggregate measure in the view data window. The computer also displays, in the view data window, one or more level of detail calculations referenced in the selected subset of visual data marks.

Abstract: A user selects a data source, and a computer displays a data visualization in a data visualization user interface according to the data source. The data visualization includes visual data marks representing data from the data source. The user selects a subset of the visual data marks. In response, the computer displays a view data window having a summary of the selected data marks. The computer obtains a data model encoding the data source as a tree of logical tables. The computer identifies aggregate measures corresponding to the selected data marks, where each aggregate measure is aggregated from logical tables of the data model. The computer displays each aggregate measure in the view data window. The computer also displays, in the view data window, one or more level of detail calculations referenced in the selected subset of visual data marks.

Abstract: A user selects a data source, and a computer displays a data visualization in a data visualization user interface according to the data source. The data visualization includes visual data marks representing data from the data source. The user selects a subset of the visual data marks. In response, the computer displaying a view data window having a summary of the selected data marks. The computer obtains a data model encoding the data source as a tree of logical tables, each including one or more logical fields. Each logical field corresponds to either a data field or a calculation that spans one or more logical tables. Each edge of the tree connects two logical tables that are related. The computer identifies aggregate measures corresponding to the selected data marks, and displays each aggregate measure in the view data window.

Abstract: A user selects a data source, and a computer displays a data visualization in a data visualization user interface according to the data source. The data visualization includes visual data marks representing data from the data source. The user selects a subset of the visual data marks. In response, the computer displaying a view data window having a summary of the selected data marks. The computer obtains a data model encoding the data source as a tree of logical tables, each including one or more logical fields. Each logical field corresponds to either a data field or a calculation that spans one or more logical tables. Each edge of the tree connects two logical tables that are related. The computer identifies aggregate measures corresponding to the selected data marks, and displays each aggregate measure in the view data window.

Abstract: To identify objects shared by entities and to, in turn, identify free space in nonvolatile storage, a computer system uses a probabilistic data structure which tests whether an element is a member of a set. Such probabilistic data structures are created for entities in the storage system that share objects. The probabilistic data structure for an entity represents the objects that are used by that entity. When an entity is deleted, each object used by that entity is compared to the probabilistic data structures of other entities to determine if there is a likelihood that the object is used by one or more of the other entities. If the likelihood determined for an object is above an acceptable threshold, then the object is not deleted. If the likelihood determined for an object is below the set threshold, then the object can be deleted and the corresponding storage locations can be marked as free.

Abstract: A computer system supports measuring execution time of concurrent threads. A thread allocates a timing buffer in thread local storage. During execution, the thread also has access to a system timer which it can sample with microsecond or better precision with a single instruction. For any sequence of instructions within the thread for which execution time is to be measured, the sequence of instructions has an identifier and includes two commands, herein called a start command and an end command. The start command samples the system timer to obtain a start time, and stores the identifier and the start time in the timing buffer in the thread local storage. The end command samples the system timer to obtain an end time, and updates the data for the corresponding identifier in the timing buffer, to indicate an elapsed time for execution of the sequence of instructions. The start command and end command each can be implemented as a single executable instruction.

Abstract: To identify objects shared by entities and to, in turn, identify free space in nonvolatile storage, a computer system uses a probabilistic data structure which tests whether an element is a member of a set. Such probabilistic data structures are created for entities in the storage system that share objects. The probabilistic data structure for an entity represents the objects that are used by that entity. When an entity is deleted, each object used by that entity is compared to the probabilistic data structures of other entities to determine if there is a likelihood that the object is used by one or more of the other entities. If the likelihood determined for an object is above an acceptable threshold, then the object is not deleted. If the likelihood determined for an object is below the set threshold, then the object can be deleted and the corresponding storage locations can be marked as free.