Abstract: A computer receives a visual specification, which specifies a data source, visual variables, and data fields from the data source. Each visual variable is associated with either data fields (e.g., dimension and/or measures) or filters. The computer obtains a data model encoding the data source as a tree of related logical tables. Each logical table includes logical fields, each of which corresponds to either a data field or a calculation that spans logical tables. The computer generates a dimension subquery for the dimensions and the filters. The computer also generates, for each measure, an aggregated measure subquery grouped by the dimensions. The computer forms a final query by joining the dimension subquery to each of the aggregated measure subqueries. The computer subsequently executes the final query and displays a data visualization according to the results of the final query.

Abstract: The method receives a visual specification, which specifies a data source, visual variables, and data fields from the data source. Each visual variable is associated with data fields and each data field is either a dimension or a measure. From an object model of the data source, the method identifies a minimal subtree that includes all of the dimension data fields and constructs a query from the minimal subtree. The method executes the query against the data source to retrieve a set of tuples, each tuple comprising a unique ordered combination of data values for the dimension data fields. For each tuple, the method forms an extended tuple by appending aggregated data values corresponding to each measure data field. The method then builds and displays a data visualization according to the data fields in the extended tuples and according to the visual variables to which the data fields are associated.

Abstract: A user selects a node that specifies an operation for a dataset. In response, a computer system displays data values for the dataset, in a grid in a data pane. The grid includes a first column and a second column. In the grid, the user edits a first data value in the first column in a first row. The user input changes the first data value to a replacement data value. The computer system identifies a second data value in the second column in the first row, and identifies one or more additional rows in the grid, whose data values for the first column and the second column match the first data value and the second data value. The computer system then updates the data value in the first column for a second row in the grid to the replacement data value.

Abstract: A method uses natural language for visual analysis of a dataset. A data visualization application displays a data visualization, at a computer, based on a dataset retrieved from a database using a set of one or more queries. A user specifies a natural language command related to the displayed data visualization, and the computer extracts an analytic phrase from the natural language command. The computer computes semantic relatedness between the analytic phrase and numeric data fields in the dataset. The computer identifies numeric data fields having highest semantic relatedness to the analytic phrase, and also selects a relevant numerical function. The numerical function compares data values in the numeric data fields to a threshold value. The computer retrieves an updated dataset that filters the identified numeric data fields according to the numeric function. The computer then displays an updated data visualization using the updated dataset.

Abstract: A computer system concurrently displays a plurality of panes in a user interface. The panes include a first pane that displays a flow diagram having one or more nodes. Each node contains one or more icons. Each icon represents a respective data transformation operation. The panes include a second pane that displays a plurality of data rows and/or data columns for an intermediate dataset corresponding to a user-selected node. The computer system receives a user input, in the first pane, to perform a first data transformation operation at a selected node. In response to receiving the user input, the computer system performs the first data transformation operation. The computer system displays, in the first pane, an additional icon corresponding to the first data transformation operation at the selected node. The computer system updates the second pane in accordance with the first data transformation operation.

Abstract: A method uses natural language for visual analysis of a dataset, and is performed at a computer having a display, processors, and memory. The computer displays a data visualization based on a dataset retrieved from a database and receives a first user input to specify a natural language command related to the displayed data visualization. Based on the displayed data visualization and the natural language command, the computer identifies an initial range of values for a first data field in the dataset and displays an editable user interface control showing the initial range of values. The computer receives a second user input, at the user interface control, specifying a modified range of values for the first data field and retrieves an updated dataset from the database using the modified range of values for the first data field. The computer then updates the displayed data visualization using the updated dataset.

Abstract: An electronic device displays a chart in accordance with contents of a plurality of shelf regions of a data visualization interface. The chart includes visual marks representing a set of data. The electronic device generates a visual analytic object by applying a first analytic operation to the set of data represented by the visual marks, and displays the visual analytic object superimposed over the chart. The device detects user input to select the displayed visual analytic object and place an icon representing the visual analytic object onto a first shelf region of the plurality of shelf regions. In response to the user input, the electronic device updates content of the first shelf region to include an association with the first analytic operation corresponding to the visual analytic object.

Abstract: A computer system displays a user interface that includes a flow pane, a tool pane, a profile pane, and a data pane. The flow pane displays a node/link flow diagram that identifies data sources, operations, and output datasets. The tool pane includes a data source selector that enables users to add data sources to the flow diagram, and includes an operation palette that enables users to insert nodes into the flow diagram for performing specific transformation operations. The profile pane displays schemas corresponding to selected nodes in the flow diagram, including information about data fields and statistical information about data values for the data fields and enables users to modify the flow diagram by interacting with individual data elements. The data pane displays rows of data corresponding to selected nodes in the flow diagram, and enables users to modify the flow diagram by interacting with individual data values.

Abstract: A computer system obtains a data model that encodes a data source as a tree of logical tables. Each logical table includes respective data fields of the data source. For each data field in the logical tables, the system automatically assigns a semantic role to the data field based on a concept obtained from a concept graph. The system determines hierarchies between the data field and other data fields in the first data source based on a respective semantic role of the data field and semantic roles of the other data fields. The system validates the data field based on the assigned semantic role and the determined hierarchies. The system displays transformations to clean the data field based on the assigned semantic role. The system transforms data values for the data field according to a user input and updates the logical tables according to the transformed data values.

Abstract: A computer device receives, via a graphical user interface, a first user input specifying a first data field of the dataset. The first data field has a first data type. In response to receiving the first user input, the device selects a first visualization type of a data visualization, for visualizing a portion of the dataset based on the first data type, and displays the data visualization. The device receives, via the graphical user interface, a second user input specifying a second data field of the dataset. The second data field is distinct from the first data field and has a second data type. In response to receiving the second user input, the device selects a second visualization type based at least in part on the first data type and the second data type, and displays an updated data visualization, having the second visualization type, in the graphical user interface.

Abstract: A method implements data visualization collaboration. The method displays, for a second user, an interface with a comment pane that displays a first comment text and a first thumbnail image of a data visualization generated according to a first visual specification, from a first user. In response to detecting an input from the second user to select the first thumbnail image, the method generates and displays the data visualization. The method receives, from the second user, input modifying the data visualization, and input specifying a second comment that refers to the data visualization. In response, the method generates a second thumbnail image and a second visual specification corresponding to the modified data visualization, and transmits that information along with the second comment text to the first user.

Abstract: A method uses natural language processing for visual analysis of a dataset by a computer. The computer displays a data visualization based on a dataset retrieved from a database. The computer computes an initial visualization state that includes elements corresponding to data attributes of the data visualization. The computer receives user input to specify a natural language command related to the displayed data visualization. The computer extracts cue phrases from the natural language command. The computer also determines a transitional goal, to transform the data visualization, based on the cue phrases. The computer derives an updated visualization state based on the transitional goal, by applying transitional rules to each element of the initial visualization state. The computer subsequently computes analytical functions associated with the visualization states, thereby creating functional phrases. The computer then updates the data visualization based on the functional phrases.

Abstract: A method is executed at a computer system to retrieve data from a database. Upon receiving a database query, a database engine of the computer system parses the query to form an operator tree including a plurality of join operators. For one of the plurality of clauses, the database engine adds to the operator tree a respective node that specifies a mark join operator, a single join operator, an inner join operator, or an outer join operator. Specifically, the database engine adds the mark join operator when the clause includes one of a predetermined set of predicate subqueries, and adds the single join operator when the clause includes a scalar subquery. The database engine performs one or more optimization passes on the operator tree to form an optimized execution plan, and executes the optimized execution plan to retrieve a result set from the database.

Abstract: A computing device receives a user input to specify a natural language command directed to a data source. The device identifies a first keyword, corresponding to a first data field from the data source, in the natural language command. The device identifies a second keyword in the natural language command. The second keyword comprises an adjective that provides context for the first data field. The device generates a visual specification based on the first and second keywords. The visual specification specifies the data source, a plurality of visual variables, and a plurality of data fields from the data source, including the first data field. The visual variables include a first visual variable that specifies filtering of the first data field according to the second keyword. The device generates and displays a data visualization based on the visual specification.

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 method dynamically selects query execution operators. A database engine receives a query, parses the query to form a query execution tree, and compiles the tree to form a first executable plan that includes in-memory operators. The database engine executes the first plan, including executing in-memory operators in parallel. While executing a first in-memory operator, insufficient memory is detected. In response, the database engine aborts the execution, and recompiles the query tree in two ways, forming a second executable plan that replaces the first in-memory operator with a first spooling operator. The first spooling operator executes within a fixed volatile memory budget and swaps to non-volatile memory according to the budget. A third executable plan retains the first in-memory operator, but schedules it to run serially. The database engine selects either the second plan or the third plan, and executes the selected plan to return results for the query.

Abstract: A device displays a chart representing data from a dataset. The chart has a first region displaying labels corresponding to data values of a first data field, a second region displaying labels corresponding to data values of a second data field, and a third region displaying visual marks representing aggregated data corresponding to pairs of data values from the first and second data fields. In response to a user input, the device removes visual marks from the chart. When the input location is the first region, the device removes visual marks in the first chart corresponding to a first data value of the first data field. When the input location is the second region, the device removes visual marks corresponding to a second data value of the second data field. Otherwise, the device removes only one visual mark. This updates the displayed chart.

Abstract: An electronic device displays a chart, which includes a first set of visual marks that represent values derived from a set of data. The device concurrently displays a chart-calculations-options area. The chart-calculations-options area displays a first plurality of options for type of calculation. The device detects user selection of (i) a first option, from the first plurality of options, for type of calculation and (ii) a second option corresponding to a parameter for the selected first option. In response to detecting the user selection, the device visually distinguishes visual marks in a second set of visual marks in the chart. The second set of visual marks is distinct from the first set of visual marks and corresponds to the first option for type of calculation and the second option corresponding to the parameter for the selected first option.

Abstract: A method executes at a computer system to retrieve data from a database. Upon receiving a database query, the computer system translates the query into an intermediate representation, and estimates a compilation time to compile the intermediate representation into machine executable code. The query execution time to retrieve a result set is also estimated. In accordance with a determination that the query execution time and compilation time satisfy an interpretation criterion, the computer system invokes a byte code interpreter to interpret the intermediate representation and retrieve the result set from the database. In accordance with a determination that the query execution and compilation times satisfy one of a plurality of compilation criteria, the computer system compiles the intermediate representation to form machine code and executes the machine code to retrieve the result set from the database. In some cases, the query intermediate representation is optimized prior to compilation.

Abstract: A method executes at a computing device that includes a display. The device displays a user interface that includes a data flow pane and a calculation pane, the data flow pane including a node/link diagram for a data prep flow. A user selects a node in the diagram, and the device populates affordances in the calculation pane according to data fields of a data set associated with the selected node. A first user input specifies grouping on a first data field, and a second user input specifies an aggregation function on a second data field. In response to the user inputs, for each distinct value of the first data field, the device aggregates corresponding values of the second data field according to the aggregation function. Calculated data values are displayed in the calculation pane. The device saves rows of data displayed in the calculation pane as a new data source.