Abstract: A computer-navigable trie structure used in order to represent predicates for matching foreign keys to primary rows in a primary table. The predicates may be wide ranging, and each may be represented by a corresponding descendant path of the trie structure, and defines which foreign keys are to be mapped to the particular row. The trie structure is built by incrementally augmenting the trie structure as each predicate is analyzed. During later use of the trie structure, each foreign key that is a candidate for mapping to one or more parent rows are evaluated. The foreign key is used to navigate through a set of one or more descendant paths of the computer-navigable trie structure. Matching parent rows may then be identified based on the identity of the navigated descendant paths. The foreign key may then be mapped to each of the one or more matching parent rows.

Abstract: Reusing data in a memory. A method includes determining to revalidate a first set of data stored in a first, invalidated, portion of the memory. An amount of data in a second set of data in the free portion of the memory that will also be revalidated by revalidating the first portion of the memory is determined. As a result, an action to perform is determined and performed. The action includes either revalidating the first portion of the memory if the amount of data in the second set of data is at or below a predetermined threshold or copying the first set of data in the first portion of the memory, and re-writing the first set of data to the active valid portion of the memory, if the amount of data in the second set of data is above the predetermined threshold.

Abstract: A scalable analysis system is described herein that performs common data analysis operations such as distinct counts and data grouping in a more scalable and efficient manner. The system allows distinct counts and data grouping to be applied to large datasets with predictable growth in the cost of the operation. The system dynamically partitions data based on the actual data distribution, which provides both scalability and uncompromised performance. The system sets a budget of available memory or other resources to use for the operation. As the operation progresses, the system determines whether the budget of memory is nearing exhaustion. Upon detecting that the memory used is near the limit, the system dynamically partitions the data. If the system still detects memory pressure, then the system partitions again, until a partition level is identified that fits within the memory budget.

Abstract: Implementing a database system using a plurality of sequentially ordered drives to store sequential portions of columns of the database, but where the database system is usable by a system configured for use with in-memory database systems. The method includes loading one or more columns of a database into main memory of a computing system as a table based database. The method further includes dividing a column of the database into sequential portions. Each of the sequential portions is of sufficient size to create efficient transfers using hard disk controllers to transfer an entire sequential portion. The method further includes writing each of the sequential portions sequentially onto sequentially ordered drives in a round robin fashion such that sequential portions of the column are on sequential drives.

Abstract: Linking of a child table to a parent table in a database system. For a given parent table row, an expression associated with the particular row is identified. The expression may be a semantic expression that comprises something different than or more than an equals expression or a contains expression. The expression might also take as input a field of the parent table other than the primary key of the parent table. For each of multiple (and potentially all) rows of a child table, the expression is evaluated against a foreign key of the corresponding row of the child table. If the foreign key matches the expression, an association is created, and perhaps saved, between the foreign key and the particular row of the parent table. The expressions may differ even down to the granularity of a single row in the parent table, thereby enabling perhaps custom per-row expressions.

Abstract: Reusing data in a memory buffer. A method includes reading data into a first portion of memory of a buffer implemented in the memory. The method further includes invalidating the data and marking the first portion of memory as free such that the first portion of memory is marked as being usable for storing other data, but where the data is not yet overwritten. The method further includes reusing the data in the first portion of memory after the data has been invalidated and the first portion of the memory is marked as free.

Abstract: The creation and updating of an association index that defines a linking between a child table and a parent table in a database system, and in which each of at least some of the parent table rows have an associated expression defining rules for mapping child table rows to the associated parent table row. The association index may be constructed with one pass of the parent table by evaluating the mapping definition to identifying associated child table rows. If there are such associations for a given parent table row, the linking module may record that association in an association index. If there are changes made that potentially invalidate an association status (whether an association or lack thereof), a re-evaluation module then determines which mapping definitions for which parent rows need to be re-evaluated, and potentially for which child table rows, rather than perform the entire process again.

Abstract: Methods and systems are disclosed for receiving and processing data analysis expressions. A particular method includes receiving a data analysis expression at a pivot table of a spreadsheet. The data analysis expression is executed for a particular cell of the pivot table by determining a context associated with the particular cell, calculating a value of the data analysis expression based on the context, and outputting the calculated value at the particular cell.

Abstract: Performing a distributed data operation. A method includes receiving a request for one or more data operations from a first computing system, such as a client. The method further includes determining a number of node endpoints that can be used to satisfy the query. Based on the number of node endpoints, the method further includes selecting a plan from the group consisting essentially of a flat data operation plan, a hierarchical data operation plan or a combination of partially flat/partially hierarchical data operation plan. The request for one or more data operations is serviced using the selected data operation plan.

Abstract: Job execution can be scheduled and monitored. Execution of a job results in generation of one or more data slices, which can be consumed as input by one or more related jobs. Data slices can be presented in an interactive view. Selection of a data slice in the view can trigger automatic identification of related data slices based on dependencies between data slices. Each data slice can also include and be presented with a status indicating the availability of corresponding data, such as pending, ready, or failed. Furthermore, selection of a data slice that failed to generate successfully can trigger identification of related data slices that failed or are predicted to fail to generate successfully.

Abstract: The description relates to a shared digital workspace. One example includes a display device and sensors. The sensors are configured to detect users proximate the display device and to detect that an individual user is performing an individual user command relative to the display device. The system also includes a graphical user interface configured to be presented on the display device that allows multiple detected users to simultaneously interact with the graphical user interface via user commands.

Abstract: The description relates to a shared digital workspace. One example includes a display device and sensors. The sensors are configured to detect users proximate the display device and to detect that an individual user is performing an individual user command relative to the display device. The system also includes a graphical user interface configured to be presented on the display device that allows multiple detected users to simultaneously interact with the graphical user interface via user commands.

Abstract: The description relates to a shared digital workspace. One example includes a display device and sensors. The sensors are configured to detect users proximate the display device and to detect that an individual user is performing an individual user command relative to the display device. The system also includes a graphical user interface configured to be presented on the display device that allows multiple detected users to simultaneously interact with the graphical user interface via user commands.

Abstract: Performing a distributed data operation. A method includes receiving a request for one or more data operations from a first computing system, such as a client. The method further includes determining a number of node endpoints that can be used to satisfy the query. Based on the number of node endpoints, the method further includes selecting a plan from the group consisting essentially of a flat data operation plan, a hierarchical data operation plan or a combination of partially flat/partially hierarchical data operation plan. The request for one or more data operations is serviced using the selected data operation plan.

Abstract: The present invention extends to methods, systems, and computer program products for using cinematic techniques to present data. Embodiments of the invention can be used to infer and generate cinematic techniques or combinations thereof based on a model and user action. Cinematic techniques can be used to meet the data exploration and analysis requirements of a user. As such, embodiments of the invention permit users (including non-programmers) to employ cinematic techniques (possibly in combination with other techniques) to gain insights into their data and also convey appropriate emotional messages.

Abstract: A view of data transformation jobs can be presented by way of a user interface. Related jobs can subsequently be identified automatically after a job is selected based on data dependencies between jobs. Execution status can also be determined and presented such that successful and failed execution of jobs, for example, can be differentiated. Furthermore, selection of a job run that failed to execute successfully can trigger identification of related jobs runs that failed or are predicted to fail to execute successfully.

Abstract: Methods and systems are disclosed for receiving and processing data analysis expressions. A particular method includes receiving a data analysis expression at a pivot table of a spreadsheet. The data analysis expression is executed for a particular cell of the pivot table by determining a context associated with the particular cell, calculating a value of the data analysis expression based on the context, and outputting the calculated value at the particular cell.

Abstract: The description relates to an interactive digital display. One example includes a display device configured to receive user input and recognize commands relative to data visualizations. The system also includes a graphical user interface configured to be presented on the display device that allows users to interact with the data visualizations via the user commands.

Abstract: The present invention extends to methods, systems, and computer program products for using cinematic techniques to present data. Embodiments of the invention can be used to infer and generate cinematic techniques or combinations thereof based on a model and user action. Cinematic techniques can be used to meet the data exploration and analysis requirements of a user. As such, embodiments of the invention permit users (including non-programmers) to employ cinematic techniques (possibly in combination with other techniques) to gain insights into their data and also convey appropriate emotional messages.

Abstract: A scalable analysis system is described herein that performs common data analysis operations such as distinct counts and data grouping in a more scalable and efficient manner. The system allows distinct counts and data grouping to be applied to large datasets with predictable growth in the cost of the operation. The system dynamically partitions data based on the actual data distribution, which provides both scalability and uncompromised performance. The system sets a budget of available memory or other resources to use for the operation. As the operation progresses, the system determines whether the budget of memory is nearing exhaustion. Upon detecting that the memory used is near the limit, the system dynamically partitions the data. If the system still detects memory pressure, then the system partitions again, until a partition level is identified that fits within the memory budget.