A battery charging apparatus for device charging in a vehicle includes a charging device compartment, a housing, a blower, a charger, and a duct. The charging device compartment is configured to retain at least one device. The housing includes a top member, a bottom member, and an accommodating space. The housing further includes an air-return port. The blower is in the housing and has an input port and an output port. The charger is in the housing and between the top member of the housing and the blower. The duct has an input port and an output port. The input port of the duct is coupled to the output port of the blower, and the output port of the duct is coupled to the air-return port of the housing. The duct forms a barrier between the accommodating space and the air-return port of the housing.

One method includes receiving a database query, receiving information about a database table in data storage populated with data elements, producing a structural representation of the database table that includes a formatted data organization reflective of the database table and is absent the data elements of the database table, and providing the structural representation and the database query to a plan generator capable of producing a query plan representing operations for executing the database query on the database table. Another method includes receiving a query plan from a plan generator, the plan representing operations for executing a database query on a database table, and producing a dataflow graph from the query plan, wherein the dataflow graph includes at least one node that represents at least one operation represented by the query plan, and includes at least one link that represents at least one dataflow associated with the query plan.

Techniques for splitting a time-range query into sub-queries for serial execution are provided. In one embodiment, a user query is received requesting items within a time range from a database. The time range is divided into a plurality of time periods within the time range. Sub-queries defining respective time periods of the plurality of time periods are generated from the user query, and a first sub-query is executed. The first sub-query defines a first time period of the plurality of time periods, where the first time period is a most-recent time period or a least-recent time period among the plurality of time periods. If it is determined that a number of items obtained from executing the first sub-query is greater than or equal to a predetermined result target, then the items obtained from executing the first sub-query are provided and subsequent sub-queries are not executed.

An empirical approach to providing differential privacy includes applying a common statistical query to a set of databases to produce sample values, both with and without any particular entity's data. The probability density is empirically estimated by sorting the sample values to generate an empirical cumulative distribution function. The cumulative distribution function is differenced across approximately the square root of the number of sample points to get an empirical density function. The statistical query is empirically (ε,δ)-private if the empirical densities with and without any particular individual differ by a factor of no more than exp(ε), with the exception of a set for which the densities exceed that bound by a total of no more than δ.

Systems, apparatus, methods, and articles of manufacture provide for evaluation of and prediction for data queries (e.g., SQL statements). In one example implementation, a controller device trains a data model for classifying input SQL queries. The controller classifies each input SQL query by testing it against the data model, without requiring actual execution of the SQL query.

Methods, systems, and computer readable mediums for command engine execution are disclosed. One method for command engine execution includes receiving free-form information for requesting or modifying information about a computing system. The method also includes identifying a portion in the free-form information that is unsupported by a command engine. The method further includes converting, using a grammar module that supports the portion, the free-form information into at least one compatible command for interacting with at least one data set. The method also includes requesting or modifying the information about the computing system by interacting with the at least one data set using the at least one compatible command.

Techniques are introduced herein for maintaining geometry-type data on persistent storage and in memory. Specifically, a DBMS that maintains a database table, which includes at least one column storing spatial data objects (SDOs), also maintains metadata for the database table that includes definition data for one or more virtual columns of the table. According to an embodiment, the definition data includes one or more expressions that calculate minimum bounding box values for SDOs stored in the geometry-type column in the table. The one or more expressions in the metadata maintained for the table are used to create one or more in-memory columns that materialize the bounding box data for the represented SDOs. When a query that uses spatial-type operators to perform spatial filtering over data in the geometry-type column is received, the DBMS replaces the spatial-type operators with operators that operate over the scalar bounding box information materialized in memory.

Techniques for communicating with a third-party management database are described herein. According to an embodiment, a computer receives a search-style query, searches the third-party management database, retrieves multiple computer-readable database search strings, displays the computer-readable database search strings, and receives a selected computer-readable database search string. The computer may receive data associated with one or more third party surveys, and questions and answer options may be displayed according to various metadata attributes associated with previously-selected answer options.

Computer databases can be searched for relevant data values using an advanced search process. For example, a system can receive a search query indicating an attribute and a condition of a target client. The search query can be for searching one or more databases for data values relevant to the target client. The system can determine other clients described in the databases that are similar to the target client based on the attribute. The system can then filter the other clients to determine which of them has been treated for the condition. The system can identify candidate providers that treated said clients for the condition based on relationships in the databases. The system can then generate an ordered list of the candidate providers based on corresponding treatment metrics and transmit the ordered list of the candidate providers as search results in response to the search query.

A computer system may be configured to: execute a first query associated with a first panel; display the first panel in a user interface based on first display settings of the first panel, the first panel displaying at least a portion of the result of the first query, the result of the first query associated with a variable; execute a second query associated with a second panel, wherein the second query refers to the variable associated with the first query; display the second panel in the user interface based on second display settings of the second panel, the second panel displaying at least a portion of the result of the second query; and in response to user input changing the displayed result in the first panel: re-execute the second query; and update the display of the second panel in the user interface based on results of the re-executed second query.