G06F16/2438

SQL INTERFACE FOR EMBEDDED GRAPH SUBQUERIES

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.

AUTOMATIC GENERATION OF MATERIALIZED VIEWS
20210026847 · 2021-01-28 ·

Definitions of material views are automatically generated. In general, Automated MV generation identifies a set of candidates MVs by examining a working set of query blocks. Once the candidates are formed, the candidate MVs are further evaluated to calculate a benefit to the candidate MVs. An improved approach for generating a candidate set of MVs is described herein. The improved approach is referred to as the extended covering subexpression technique (ECSE). Under ECSE, various relationships between join sets other than strict equivalence are used to generate new resultant join sets. Such relationships include subset, intersection, superset, and union, which shall be described in further detail below. In some cases, relationships among resultant join sets and initial join sets are considered to generate new resultant join sets. The final resultant join sets are then used to form a candidate set of MVs.

Machine learning system and method to map keywords and records into an embedding space

In some embodiments, a method includes determining a position for a search query and a position for each audience record from multiple audience records in an embedding space. The method further includes receiving multiple device records, each associated with an audience record. The method further includes determining multiple keywords, each associated with an audience record and determining a position for each keyword in the embedding space. The method further includes calculating a first distance between the position of the search query in the embedding space and the position of each audience record in the embedding space. The method further includes calculating a second distance between the position of the search query in the embedding space and the position of each keyword in the embedding space. The method further includes ranking each audience record based on the first distance and the second distance.

Integrated Application Server and Data Server Processes with Matching Data Formats

In one embodiment, the present invention includes a computer-implemented method comprising storing data in an application using an application custom data type and application custom data structure. The data is stored in a database using the application custom data type and the application custom data structure. In one embodiment, a request is sent to access the data from the application to the database. The data is retrieved from the database in response to the request in the application custom data type and the application custom data structure. In one embodiment, the data is sent from the database to a shared memory in the application custom data type and the application custom data structure and the data is retrieved by the application from the shared memory in the application custom data type and the application custom data structure.

DATA MANIPULATION RECORD STORAGE METHOD, SYSTEM, APPARATUS, AND DEVICE
20200372037 · 2020-11-26 · ·

Computer-implemented methods, computer-implemented systems, and non-transitory, computer-readable media for data manipulation record storage. One computer-implemented method includes: sending, by a server, one or more manipulation instructions to a database, wherein the one or more manipulation instructions are in a structured query language (SQL) format; receiving, by the server from the database, an execution result of the one or more manipulation instructions; generating, by the server, one or more data records comprising the one or more manipulation instructions and the execution result; and determining, by the server, that a predetermined condition of generating a data block is satisfied; and generating, by the server, the data block that includes at least a portion of the data records.

SOLUTION FOR IMPLEMENTING COMPUTING SERVICE BASED ON STRUCTURED QUERY LANGUAGE STATEMENT

Syntax parsing on a SQL statement is performed to determine whether an extended syntax identifier exists in the SQL statement, where the extended syntax identifier indicates a target computing service for the SQL statement. It is determined that the extended syntax identifier exists in the SQL statement. A computing service description statement in a first statement format is generated based on the SQL statement, where the first statement format is a statement format that can be recognized by a target computing framework. The computing service description statement is submitted to the target computing framework. Data queried by the SQL statement is invoked, in the target computing framework based on the computing service description statement, to perform target computation, where the SQL statement includes a computing element needed by the target computing service.

Integrated application server and data server processes with matching data formats

In one embodiment, the present invention includes a computer-implemented method comprising storing data in an application using an application custom data type and application custom data structure. The data is stored in a database using the application custom data type and the application custom data structure. In one embodiment, a request is sent to access the data from the application to the database. The data is retrieved from the database in response to the request in the application custom data type and the application custom data structure. In one embodiment, the data is sent from the database to a shared memory in the application custom data type and the application custom data structure and the data is retrieved by the application from the shared memory in the application custom data type and the application custom data structure.

Statement based migration for adaptively building and updating a column store database from a row store database based on query demands using disparate database systems

A method for updating a column store database and includes establishing a row store database, wherein each row comprises a plurality of attributes. The method includes establishing a column store database including attribute vectors corresponding to at least one attribute in the row store, wherein each attribute vector includes data used to satisfy at least one of previously received analytic queries. The method includes collecting a SQL change statements beginning from a synchronization point indicating when the row store database and the column store database are synchronized, and continuing until an analytic query is received. The method includes sending the plurality of SQL change statements to the column store database upon receipt of the analytic query for updating the column store database for purposes of satisfying the query, wherein the analytic query is directed to a queried range of primary key attributes in the plurality of attributes.

COMPILATION FRAMEWORK FOR DYNAMIC INLINING

Disclosed embodiments include generating code from a database query and providing a framework to develop complex data structures and the functions that access those data structures outside of the generated code to access the complex data structures. These data structure functions can be precompiled in order to save compilation time at query runtime, and linked to the generated code in a way that the framework can still inline function calls and apply various optimizations on the linked code.

Systems and methods for indexing and searching rule-based models

The present disclosure relates to systems and methods for indexing and clustering machine learned models. Moreover, the present disclosure relates to systems and methods for searching indexed machine learned models and receiving suggested models based on the clustering of the same.