A system may determine one or more data sources which the system is configured to access. The system may provide a set of application programming interfaces (APIs) for interacting with data stored in one or more data sources. The APIs may be accessible to one or more web applications which the system is configured to serve. The system may determine that a web application has requested an operation for interacting with the data through one or more APIs in the set of APIs. The system may determine one or more responses based at least in part on the operation requested by the web application. The system may provide the response(s) to the web application.

This invention is a system for integrating relational databases into a semantic web framework utilizing a simple mapping process and the SQL query optimizer present in the SQL database engine.

A system may determine one or more data sources which the system is configured to access. The system may provide a set of application programming interfaces (APIs) for interacting with data stored in one or more data sources. The APIs may be accessible to one or more web applications which the system is configured to serve. The system may determine that a web application has requested an operation for interacting with the data through one or more APIs in the set of APIs. The system may determine one or more responses based at least in part on the operation requested by the web application. The system may provide the response(s) to the web application.

A computer processor determines a schema that enables splitting of one or more elements of an XML file. The computer processor determines an XML file as a split candidate, based on one or more attributes of the one or more elements of the XML file. The computer processor splits the XML file at run-time into a plurality of subsets of the XML file, based on the one or more attributes of the one or more elements of the XML file, and the computer processor distributes the plurality of subsets of the XML file to a plurality of computing nodes of a computer processing system.

Approaches presented herein enable optimization of a cache of compiled XML Path Language (XPath) expressions by removing variability from XPath expressions. More specifically, XPath expressions are identified that are the same but for one or more hardcoded values. These hardcoded values are identified and replaced in an identified XPath expression with an identifier to form a cache optimized XPath expression that lacks the hardcoded value variability of the identified XPath expressions. This cache optimized XPath expression is inserted into a cache optimized function that receives the hardcoded value as arguments and assigns the received hardcoded value to the identifier in the cache optimized XPath expression. The identified XPath expressions are then rewritten as calls to the cache optimized function or to another function wrapping the cache optimized function. Therefore, only the cache optimized XPath expression, instead of several of the identified XPath expressions, is stored in the XPath expression cache.

Embodiments implement a plug-in architecture supporting adding new data sources to a legacy federated database without the need to recode a federated database manager software module. The federated database manager software module includes an administrative tool and a plug-in framework for interfacing with a data source cartridge. The data source cartridge supplies metadata including a feature table of a newly added data source to the framework and creates a physical query for the newly added data source based on an execution plan generated by the federated database manager software module. The administrative tool generates presentation panes including new data sources added to the legacy federated database.

A node of a database system is operable to determine a plurality of query operator execution flows for execution of a plurality of queries. Execution of the plurality of queries is facilitated based on performing a plurality of sequential operator execution steps based on power. At least one of the plurality of sequential operator execution steps includes selecting one of the plurality of queries for execution at the each of the plurality of sequential operator execution steps, selecting one of the plurality of operators of the one of the plurality of query operator execution flows corresponding to the one of the plurality of queries, facilitating execution of the one of the plurality of operators on a queued set of data blocks of the one of the plurality of operators to generate at least one output data block, and advancing to a next one of the plurality of sequential operator execution steps.

A method of dynamically computing an optimal materialization schedule for each column in a column oriented RDBMS. Dynamic column-specific materialization scheduling in a distributed column oriented RDBMS is optimized by choosing a materialization strategy based on execution cost including central processing unit (CPU), disk, and network costs for each individual exchange operator. The dynamic programming approach is computationally feasible because the optimal schedule for a sub-plan is path independent.

Data Brick is a state of the art solution to access the data through high speed data access mechanism that is exceptionally fast and is associated with low CPU consumption cost. The Data Brick stores relatively static reference data in the form of a programming language Load Module. The Load module contains the data can be launched into the application program memory and this data can be accessed very efficiently in a programming language program. Static application data that is accessed by multiple applications in a mainframe Batch environment is a prime candidate for the Data Brick.

Computer systems and methods allow users to annotate content items found in a corpus such as the World Wide Web Annotations, which can include any descriptive and/or evaluative metadata related to a document, are collected from a user and stored in association with that user. Users are able to annotate and view their annotations for any document they encounter while interacting with the corpus, including hits returned in a search of the corpus. Users are also able to search their annotations or to limit searches to documents they have annotated. Metadata from annotations can also be aggregated across users and aggregated metadata applied in generating search results.