An embodiment includes causing elements to be recognized that correspond to one or more browser-supported programming languages in an application. The recognized elements are those elements that can be converted to native user interface elements in the operating system and rendered on a display of a computing device. The elements in the one or more browser-supported programming languages are converted to native user interface elements. The native user interface elements are caused to be rendered on the display of the computing device. Methods, apparatus, software, and computer program products are disclosed.

Automatically rendering web or hybrid applications natively

Methods, systems, and techniques for managing groups of entities, such as individuals, employees, or systems, and providing entitlement and access to computer resources based on group membership are provided. Example embodiments provide a Group Management System having a Group Management Engine “GME,” an Entitlement Engine, and a Provisioning Engine, which work together to allow simplified grouping of entities and providing entitlement and access to the entities based upon the group membership. In one embodiment, the GME leverages dynamic programming techniques to enable accurate, scalable systems that can manage near real time updates and changes to the group's status or to the entities' status. These components cooperate to enable provisioning of applications based upon current entitlement.

Dynamic Management Of Groups For Entitlement And Provisioning Of Computer Resources

Systems and methods for accessing data stored in a data array, mapping the data using a bitmap index, and processing data queries by determining positions of query attributes in the bitmap index and locating values corresponding to the positions in the data array are described herein

Systems and methods for querying column oriented databases

The invention discloses a multi-dimensional OLAP (On Line Analytical Processing) inquiry processing method facing a column storage data warehouse. In the multi-dimensional OLAP inquiry processing method, the OLAP inquiry is decomposed into a bitmap filtering operation, a grouping operation and an aggregation operation. In the bitmap filtering operation, firstly, the predication is executed on a dimension table and a predicate vector bitmap is generated; and a connection operation is converted into a direct dimension table record access operation by surrogate key address mapping so as to implement access according to the positions. In the grouping operation, the pre-generation of grouping units is carried out on fact table records which meet the filtering conditions according to grouping attributes in an SQL (Structured Query Language) command and increasing IDs (identity) are distributed. In the aggregation operation, the grouping aggregation calculation which is carried out according to a grouping item of a grouping filtering vector of a fact table is implemented by carrying out column scanning on the metric attribute of the fact table for once. According to the invention, all OLAP processing tasks can be completed only by carrying out column scanning on the fact table for once, so that the cost of repeatedly scanning is avoided.

Multi-dimensional OLAP (On Line Analytical Processing) inquiry processing method facing column storage data warehouse

Methods and systems for automatic table schema generation are disclosed. A description of a data source is received. A table definition is determined based on the description of the data source, wherein the table definition maps the data source to one or more columns of an output table. A parser for the data source is selected from a set of predefined parsers based on the description of the data source. A query against the data source is received. One or more elements of data responsive to the query are retrieved from the data source using the selected parser. The one or more elements are transformed into the output table based on the table definition.

Automatic table schema generation

A database access model and storage structure that efficiently support concurrent OLTP and OLAP activity independently of the data model or schema used, are described. The storage structure and access model presented avoid the need to design schemas for particular workloads or query patterns and avoid the need to design or implement indexing to support specific queries. Indeed, the access model presented is independent of the database model used and can equally support relational, object and hierarchical models amongst others.

Apparatus, systems and methods for data storage and/or retrieval based on a database model-agnostic, schema-agnostic and workload-agnostic data storage and access models

Duncan Gunther Pauly

Papers

Apparatus, systems and methods for data storage and/or retrieval based on a database model-agnostic, schema-agnostic and workload-agnostic data storage and access models

Data storage and/or retrieval based on a database model-agnostic, schema-agnostic and workload-agnostic data strorage and access models