A method of improving computing efficiency of a computing device for language-independent problem solving and reasoning includes receiving a query from a user, which is decomposed into one or more sub-queries arranged according to a tree structure. The one or more sub-queries are executed in a knowledge base. The results of the executed one or more sub-queries are received and composed into a query response. The query response is transmitted to the user.

The disclosed technologies are capable of decentralized query evaluation for a distributed graph database. In one technique, a query is divided into first and second sets of operations. The query comprises variables and constraints that correspond to at least two nodes and at least one edge of a graph in a graph database. The first set of operations for processing the query is assigned to multiple shards. A limit is communicated to the shards. The second set of operations for processing the query is executed. A list of completed operations is received from each shard. The lists of operations received from the shards are merged into a merged set of operations, which is used to determine whether query processing is finished. If query processing is not finished, then an updated limit is communicated to the shards; otherwise, query results are provided in response to the query.

A system for processing database data includes an interface and a processor. The interface is configured to receive a query for the database data comprising a date range and a data selection criterion. The processor is configured to determine a set of fields of the database data corresponding to a most recent date of the date range; determine a subset of the set of fields of the database data specified by the data selection criterion; determine a set of transformations, where each transformation of the set of transformations corresponds to a field of the subset and a sub-range of the date range; transform the database data to determine transformed database data using the set of transformations; and select data from the transformed database data using the data selection criterion to determine a query response.

A system and method for processing of queries including receiving a query including a set operation and a sort operation, wherein the set operation includes a first data structure and a second data structure and the sort operation requests a result set that is sorted based on a column or attribute of the first data structure and a column or attribute of the second data structure; generating a query plan in which a sort operation occurs prior to the set operation; determining a first, partial set of one or more resultant rows responsive to the query; sending the first, partial set of one or more resultant rows responsive to the query to a client; determining a second, partial set of one or more resultant rows responsive to the query; and sending the second, partial set of one or more resultant rows to the client.

Data warehousing solutions utilize lengthy and complex SQL instructions. These SQL instructions are difficult to parse and understand underlying logic/transformations performed. Conventionally, extensive analysis, time and effort needs to be spent to understand such SQL instructions and detect any data abnormalities in the SQL instructions. This technical challenge is exacerbated in high-volume production systems that include multiple systems that each utilize their own sets of SQL instructions. Apparatus and methods described herein take as input a natural language inquiry received from a user. The system attempts to parse the natural language inquiry to identify one or more relevant SQL instructions. Apparatus and methods may utilize AI and natural language processing to locate relevant SQL instructions, deconstruct them into subqueries and map a logical operational flow. Based on the mapped logic flow, a natural language response may be formulated to the user inquiry.

In one embodiment, a computing device includes a memory device storing instructions, and a processing device communicatively coupled to the memory device. The processing device executes the instructions to execute a computer-implemented system configured to manage items in a self-describing data model, and generate a representation of a federated system in the self-describing data model. The representation includes logical model items having logical model item types associated with data in an external object model used by a third-party computer-implemented system. The processing device may enable communication of the items and the logical model items between a client computer-implemented system and the third-party computer-implemented system.

A method, a system, and a computer program product for querying graph data. A graph workspace object is identified. One or more parameters for executing a declarative language query are identified. Using the identified parameters, the declarative language query is executed on the identified graph workspace object. Based on the executed declarative language query, one or more tables responsive to a request to access graph data stored in a relational database are processed.

The present disclosure is directed to a leader-based partially synchronous BFT SMR protocol that improves upon existing protocols by exhibiting two rounds of communication latency, linear authenticator complexity, and optimistic responsiveness. This is achieved through the novel use of an aggregate signature scheme as part of the protocol's view-change procedure.

A database system includes: a distributed processing apparatus 1; and a plurality of database apparatuses 2, in which the distributed processing apparatus 1 includes: a generation unit 12 that generates an execution plan for a query related to the database apparatuses 2 based on a security policy; a transmission unit 13 that divides the query in accordance with the execution plan and transmits instructions to the corresponding database apparatuses 2, the instructions including divided queries obtained by dividing the query and transfer destinations of execution results of the divided queries; and an output unit 14 that receives the execution result of the query, from the database apparatus 2, and outputs the execution result, the database apparatuses 2 each include an execution unit 22 that executes the divided query included in the instruction received from the distributed processing apparatus 1, and transmits the execution result to another database apparatus or the distributed processing apparatus serving as the transfer destination included in the instruction, and at least one of the output unit 14 and the execution unit 22 encrypts the execution result in accordance with the security policy.

Source data rendered as a string of hexadecimal data representing a set of Extended Binary Coded Decimal Interchange Code (EBCDIC) data, and a data layout description defining a record in the source data that includes a plurality of fields, are obtained. Respective hexadecimal lengths of the fields based on a source data length of each field and a source datatype of each field are determined. Hexadecimal sub-strings are extracted from the hexadecimal string based on the hexadecimal lengths and source datatypes of the fields. At least some of the hexadecimal sub-strings are converted to a target format. The sub-strings are output in the target format.