Embodiments of the present invention are directed to identifying related data, in particular, data associated with different source types. In embodiments, a first source type related to a second source type associated with a search query is identified. Field set pairs are identified from a first data set associated with the first source type and a second data set associated with the second source type. Each field set pair can include one field set associated with the first source type and another field set associated with the second source type. For each field set pair, an extent of similarity is determined between the corresponding field sets. Based on the extent of similarities between the corresponding field sets, at least one pair of related field sets is identified. An indication of the at least one pair of related field sets is provided, for example, for presentation to a user.

A system, program product, and method for use with an artificial intelligence (AI) platform to dynamically amend a knowledge base responsive to query evaluating and processing. A received or detected query is subject to natural language processing to identify, annotate, and map one or more query tokens against a knowledge base. The query tokens are evaluated against the knowledge base to identify one or more query tokens absent from the knowledge base and leverage a neural network to predict a probability relationship between the query tokens absent from the knowledge base and one or more tokens populated in the knowledge base. The natural language (NL) query is translated to a structured query language (SQL) and the SQL query is executed and evaluated, and the knowledge base is selectively and dynamically amended subject to the SQL evaluation.

Compiled portions of code generated to perform a query plan at a query engine may be shared with other query engines. A data store, separate from the query engines, may store compiled portions of query code generated for different queries. If a query engine does not have a locally stored compiled portion of query code, then the separate data store may be accessed in order to obtain a compiled portion of query code, allowing reuse of compiled query code across different queries engines for queries directed to different databases.

SCAN operations for databases where scan time is dependent on a payload size consume too much memory space and computing time as payload sizes increase. A database table is configured to include an additional index mapping column that stores bitmaps related to the corresponding row of the table. Each bit in the bitmap corresponds to a column and indicates whether that column stores a value. Inclusion of an index column in a table decouples the time it takes to perform the SCAN operation on a column from the payload size of data stored in the column. The bitmaps stored in the index column are relatively small and uniform in size, so the SCAN operation on such a database requires only for the bitmap values of the applicable rows to be obtained from the index column and inspected.

A statement parsing method for a database statement comprises: conducting lexical analysis on a database statement inputted into a database, to obtain an inputted word sequence; looking up a statement similarity table according to the inputted word sequence to determine whether there is an existing word sequence similar to the inputted word sequence in the statement similarity table; if yes, obtaining the parsed data corresponding to the existing word sequence from the statement similarity table; otherwise, parsing the inputted word sequence to obtain parsed data corresponding thereto, and storing the inputted word sequence and the corresponding parsed data in the statement similarity table; and executing the database statement inputted to the database based on the parsed data corresponding to the existing or inputted word sequence. The method can quickly parse a database statement and is favorable for improving the response speed and the working efficiency of a database.

A Sort Lists instruction is provided to perform a sort and/or a merge operation. The instruction is an architected machine instruction of an instruction set architecture and is executed by a general-purpose processor of the computing environment. The executing includes sorting a plurality of input lists to obtain one or more sorted output lists, which are output.

The present invention relates to a system and methodology to facilitate the automated creation of an XML object model which overlays a standard relational database to allow both saving and retrieval of data via hierarchical XML objects from within the actual database server itself. The Automated Database Object Model (ADOM) process generates a set of log tables, triggers, stored procedures, functions, and views for all objects as determined by a database schema interrogation process. The result is a select query for every hierarchical object in the database, and a single point of entry stored procedure for all inserts, updates, and deletes. A managed application programming interface (API) is also provided to automatically generate a class object library in the application layer which matches the automated database object model, thus abstracting the application developer from directly managing the underlying database structure.

Systems and methods for embodiments of artificial intelligence systems for identity management are disclosed. Embodiments of the identity management systems disclosed herein may support the creation, association, searching, or visualization of any relevant context to identity management assets for a variety of purposes, including for informing the identity management systems' manual or automated decisions, processes or workflows.

A server in a cloud-based environment is interfaced with storage devices that store shared content accessible by two or more user devices that interact with the cloud-based service platform over a network. A virtual file system module is delivered to a user device, which user device hosts one or more applications. The virtual file system module detects a plurality of application calls issued by processes or threads operating on the user device. The plurality of application calls are mapped into one coalesced cloud call. The coalesced cloud call is delivered to the cloud-based service platform to facilitate access to the shared content by the application. The mapping of application calls to the coalesced cloud call is based on pattern rules that are applied over a stream of incoming application calls. A delay may be observed after mapping to a first pattern, and before making a mapping to a second pattern.

Implementations of the present specification provide a method for deploying a smart contract. According to one implementation the method includes: receiving a transaction request for invoking a first contract; obtaining a first instruction code and a function index table, wherein the function index table is used to indicate a memory address of an instruction code corresponding to each of import and export functions in the first contract; determining a first memory address corresponding to the invocation function based on the function index table; and executing the first instruction code in the first memory address based on the determined first memory address.