Vertex/edge table rows are mapped to unique integer identifiers, to enable construction of in-memory representation of a graph from existing, unmodified RDBMS tables. The unique integer identifiers are based on an encoding of primary key values of the table rows. The unique integer identifiers are used as graph indexes of the in-memory representation.

A code base is parsed to identify methods having changes in a code base since a last code commit. Thereafter, a call graph is traversed to identify test cases implicated by the identified methods having changes in the code base. The call graph can be a directed call graph comprising a plurality of connected nodes in which a first subset of the connected nodes are method nodes representing each method in the code base in which unidirectional edges connecting method nodes correspond to invocations by a calling method to a callee method, and in which a second subset of the connected nodes are test case nodes representing each of a plurality of available test cases to test the code base. The test case nodes are each coupled to one or more method nodes by unidirectional edges that correspond to the test case coverage of the method.

Interacting with a computing device can include registering a plurality of commands from a plurality of applications, wherein the plurality of commands specify entity types that are accepted as parameters, determining a first entity having a first entity type, wherein the first entity is independent of the plurality of applications, and determining a selected command from the plurality of commands registered by the plurality of applications that accepts the first entity type as a parameter. The first entity and the selected command can be provided, using a processor, to a first application of the plurality of applications that supports the selected command for execution.

Systems and methods are provided for enhanced processing of time series data via parallelization of instructions. An example method includes receiving a query indicating time series datasets and operations to be performed on the time series datasets. Nodes associated with the query are identified, with each node associated with a time series dataset. Nodes associated with operations to be performed are generated. The nodes are assembled into query tree, with parent nodes of the query tree indicating operations that are to be applied to children nodes. Instructions for processing the query tree are generated. At least a subset of the instructions is provided to one or more compute systems for processing in parallel. Results are received, and presented in a user interface.

Compiling a database query including receiving, by a query compiler from a client computing system, a state specification of a graphical user interface comprising a worksheet, wherein the worksheet is a presentation of a data set from a data warehouse; converting, by the query compiler, the state specification into a database query including determining a first order of operations for elements within the state specification; and sending the database query to the data warehouse.

Performing database queries. A method includes receiving a particular database query. The method further includes accessing a query plan based on the particular database query. The query plan has operators and specific operational parameters associated with each of the operators. The association of operators and specific operational parameters is specific to the particular database query. From the query plan, the method further includes instantiating a plurality of compiled code templates. Each code template includes executable code that when executed performs functionality of one of the operators from the query plan with the specific operational parameters applied in the compilation. The method further includes binding the code templates together using programmatic control flow to create a functioning program.

Techniques are provided for processing a database command in a sharded database. The processing of the database command may include generating or otherwise accessing a shard key expression, and evaluating the shard key expression to identify one or more target shards that contain data used to execute the database command.

A method includes accessing a schema that specifies relationships among datasets, computations on the datasets, or transformations of the datasets, selecting a dataset from among the datasets, and identifying, from the schema, other datasets that are related to the selected dataset. Attributes of the datasets are identified, and logical data representing the identified attributes and relationships among the attributes is generated. The logical data is provided to a development environment, which provides access to portions of the logical data representing the identified attributes. A specification that specifies at least one of the identified attributes in performing an operation is received from the development environment. Based on the specification and the relationships among the identified attributes represented by the logical data, a computer program is generated to perform the operation by accessing, from storage, at least one dataset having the at least one of the attributes specified in the specification.

Disclosed is a method of accessing a network of relationship instances and data field values of entity instances in a combined entity relationship- and relational-model database management system. The method comprises the steps of receiving a query that natively references relationship types including data fields to be accessed; parsing the query into a parse tree; converting the parse tree to a query graph; optimising the query graph by consolidating equivalent nodes in the query graph; analysing the nodes in the optimised query graph; codifying each node of the optimised query graph into a first table of state transition rules; codifying the data fields to be accessed into a second table of field rules; preparing a query that includes the first and second tables; identifying entity instances to be accessed by the prepared query by iteratively following relationship instances according to the first table; and loading data fields of the identified entity instances according to the second table.

A method for performing data encryption and application-agnostic querying of encrypted data includes identifying, via a processor, selected data for encryption. Encryption is applied to the selected data, to produce encrypted data. A query is received at the processor, the query originating from a software application. The query is translated into a modified query compatible with the encrypted data. The processor causes execution of the modified query, to produce query results. The query results include a subset of the encrypted data. The query results are sent to the software application without decrypting the subset of the encrypted data.