Abstract: method for querying a data storage includes receiving queries for execution in the data storage, and deriving from the queries one or more table-scans over one or more tables of the data storage. Candidate sparse indexes, for pruning the table-scans, are specified based on the queries. Pruning-power measures, indicative of as effectiveness of the candidate sparse indexes in pruning the table-scans, are evaluated. One or more of the candidate sparse indexes are converted into actual sparse indexes, depending on the pruning-power measures. The queries are executed by performing the table-scans, including pruning the table-scans using the actual sparse indexes.

Abstract: Disclosed herein are system, method, and computer tangible medium embodiments for generating a relational database model from a model view that provides an estimate for generating query plan for a query on the model view, according to an embodiment. A join model of a model view set on one or more database tables is received. At least one index conversion of the join model is performed, where the index conversion converts at least one index in the join model into at least one leaf node in a relational model tree. At least one join conversion of the join model is performed where the at least one join conversion generates a node in the relational model tree that joins a first and second leaf nodes in the relational model tree. A requested parameter conversion is performed, where the requested parameter conversion includes an attribute or key figure requested by a query.

Abstract: Creating a model data set using a spreadsheet interface including generating the model data set using the spreadsheet interface and a first data source from a data warehouse, wherein the model data set is a reusable modeling layer comprising at least a portion of the first data source, and wherein generating the model data set comprises: creating a first worksheet using the spreadsheet interface and the first data source; receiving an indication that the first worksheet is a model data set; and generating model data set metadata for the first worksheet; and providing, as a second data source for a second worksheet, the model data set generated from the model data set metadata.

Abstract: Enabling editable tables on a cloud-based data warehouse including receiving, by a query manager, a client-provided table; receiving, by the query manager from a query manager client, a request to create a referencing worksheet using, as data sources, the client-provided table and a database table on a cloud-based data warehouse; storing, by the query manager, the client-provided table in the schema storage location on the cloud-based data warehouse, wherein the schema storage location is a storage location on the cloud-based data warehouse to which the query manager has read and write access, and wherein the database table is external to the schema storage location; generating, by the query manager, a database query to create the referencing worksheet, wherein the database query targets the client-provided table in the schema storage location and the database table; and issuing, by the query manager, the database query to the cloud-based data warehouse.

Abstract: A system and method for processing a database query is described. In response to detection that a database query involves a star or snowflake join operation, a join operator in a preliminary query plan can be split into a build operator and a probe operator. The probe operator can be placed in a final query plan in the same place as the join operator in the preliminary query plan, while the build operator can be placed beneath the probe operator in the final query plan, between an exchange operator and the exchange operator's child from the preliminary query plan.

Abstract: A method may include generating a first hash value that is representative of a current configuration of a database storing a plurality of data records. A change in the configuration of the database may be detected based on the first hash value and a second hash value representative of a previous configuration of the database. The configuration of the database may include a plurality of database tables available for storing the plurality of data records. In response to detecting the change in the configuration of the database, the database may be updated by at least transforming the plurality of data records in accordance with the current configuration of the database. Related methods and articles of manufacture, including computer program products, are also disclosed.

Abstract: A distributed in-memory query processor may utilize a remote data store. Column segments may be retrieved from the remote data store and loaded into system memory of a computing node. The query processor may, in response to receiving a request to perform a query, identify columns and ranges of column values required to process the query. Partition-level schemas and cross-partition schemas may be formed for computing nodes holding column segments in memory. Computing nodes may be selected for processing the query based on a degree to which a partition or set of partitions matches data requirements of the query.

Abstract: Methods, systems, and computer-readable media for transforming or modifying domain data are provided. A master control table may be generating including data from a plurality of domain data tables and a configuration associated with each domain data table. A user may modify a domain data table (or associated domain data) via the master control table. A user interface may be generated having a first portion, listing domain data tables in the master control table, and a second portion. Upon selection of a domain data table from the first portion, the second portion may be populated with the data and associated configuration of the selected domain data table. Modifications to the domain data table (and/or domain data) may be made via the second portion.

Abstract: Automatic generation of logical database schemas from physical database tables and metadata is disclosed. One exemplary method for automatic generation of logical database schemas from physical database tables and metadata includes identifying physical fact tables in a data repository. The method further includes identifying physical dimension tables in the data repository. The method includes mapping the physical fact tables to logical fact tables. The method further includes mapping the physical dimension tables to logical dimension tables. The method further includes determining relationships between the physical fact and dimension tables. The method further includes logically joining the logical tables based on the identified relationships between the physical tables to form a logical database schema. The method further includes outputting the logical database schema to the user.

Abstract: SQL queries are optimized to operate directly on compressed data (and obtain the correct result) rather than requiring that the data be first decompressed prior to processing a query. Certain characteristic pattern trees are mapped against a logical input query plan that includes certain logical operators such as a DECOMPRESS that precedes a JOIN or a GROUPBY in association with a COUNT to identify instances in the plan that match a characteristic pattern. Upon locating a match, the input query plan is transformed into a logically equivalent plan that operates correctly on compressed data, by analyzing the interplay of the semantics of logical query operations with the compressed data and substituting less costly structures and operations. DECOMPRESS operations are moved to operate subsequent to a JOIN or eliminated altogether, and COUNT operations are replaced by a different operation, such as SUM, that is logically equivalent for compressed data.

Abstract: Embodiments of the present disclosure may provide a system and method for processing an online transactional processing (OLTP) transaction on a column-based storage of a database. The method may include receiving a request of the OLTP transaction to access data on the column-based storage. A determination may be made whether a cache associated with the database includes column information for the OLTP transaction. If the cache includes the column information for the OLTP transaction, the method may include processing the OLTP transaction with the column information in the cache. If the cache does not include the column information for the OLTP transaction, the method may include selecting columns from the column-based storage of the database.

Abstract: A machine implemented method for collecting business intelligence data including providing a master database table on a computer readable medium and accessible by an analytics server, accessing rows in the master database table by the analytics server, with each row in the master database table containing at least a partial set of measures for a plurality of dimensions, identifying by the analytics server a set of one or more dimensions from the plurality of dimensions subject to a query by one or more computing devices in communication with the analytics server, extracting the set of one or more dimensions and associated measures for each of the one or more dimensions from the master database table, and forming a baby fact table such that each row in the baby fact table contains the set of one or more dimensions subject to the query and the associated measures derived from the extracting step.

Abstract: A system, computer-implemented method, and computer-program product embodiments for determining a cardinality estimate for a query. A cardinality estimator identifies a predicate in a query, where the predicate is split into a plurality of equivalence classes. The cardinality estimator then generates a plurality of equivalence graphs from the plurality of equivalence classes, one equivalence graph for an equivalence class. Spanning trees are identified from the plurality of equivalence graphs, and the cardinality estimator then determines the cardinality estimate for the query from the spanning trees.

Abstract: As disclosed herein a method, executed by a computer, for avoiding double counting in the presence of many-to-many relationships in database data includes receiving a report definition from a data management system, detecting a bridge table defining many-to-many relationships between at least two datasets, generating a query plan with layered sub-queries, and executing the query plan including the layered sub-queries to provide query results corresponding to the report definition. A query plan with layered sub-queries may include instructions to join, partition, normalize, group, and summarize tabular data. Additionally, a conditional selection operation may be used to detect and eliminate duplicated data from a field specified in the report definition. The resulting query plan may be executed as a single query language. A computer program product and an apparatus corresponding to the described method are also disclosed herein.

Abstract: SQL queries are optimized to operate directly on compressed data (and obtain the correct result) rather than requiring that the data be first decompressed prior to processing a query. Certain characteristic pattern trees are mapped against a logical input query plan that includes certain logical operators such as a DECOMPRESS that precedes a JOIN or a GROUPBY in association with a COUNT to identify instances in the plan that match a characteristic pattern. Upon locating a match, the input query plan is transformed into a logically equivalent plan that operates correctly on compressed data, by analyzing the interplay of the semantics of logical query operations with the compressed data and substituting less costly structures and operations. DECOMPRESS operations are moved to operate subsequent to a JOIN or eliminated altogether, and COUNT operations are replaced by a different operation, such as SUM, that is logically equivalent for compressed data.

Abstract: Disclosed is a system allowing to query data warehouses using SPARQL. An aspect of the system may support the representation of multidimensional data as virtual graphs. Another aspect of the system may provide mapping of SPARQL queries directed against multidimensional data vis-à-vis the graphs to native queries directed against the multidimensional data. Responses from the native queries may then be translated to a SPARQL response format.

Abstract: A data warehouse includes plurality of master data tables, a plurality of dimension tables and a fact table. The master data tables including surrogate identifiers. The dimension tables use the surrogate identifiers to link to the master data table domains within the master data tables. The fact table stores dimension identifiers that provide links to the master data tables. A cloud storage area includes a plurality of cloud dimension tables and a cloud fact table. Each cloud dimension table stores summary characteristics. Each cloud dimension table associates a separate cloud identifier with each entry of summary characteristics. The cloud fact table stores aggregated data representing key performance indicators. The cloud fact table includes a plurality of cloud identifier columns in which cloud identifiers are stored.

Abstract: In a data warehouse, a master table includes surrogate identifiers. Each surrogate identifier (SID) uniquely identifies a master table domain within the master table. A dimension table uses the surrogate identifiers to link to the master table domains. A SID generator uses first data supplied in a user query to generate a first SID indicating location of a particular master table domain in the master table. The SID generator generates the first SID without accessing the master table.

Abstract: Disclosed is a system allowing to query data warehouses using SPARQL. An aspect of the system may support the representation of multidimensional data as virtual graphs. Another aspect of the system may provide mapping of SPARQL queries directed against multidimensional data vis-à-vis the graphs to native queries directed against the multidimensional data. Responses from the native queries may then be translated to a SPARQL response format.

Abstract: For a database query that defines a plurality of separate snowflake schemas, a query optimizer computes separately for each of the snowflake schemas a logical access plan for obtaining from that schema's tables a respective record set that includes the data requested from those tables by that query. The query optimizer also computes a logical access plan for obtaining the query's results from the record sets in which execution of the logical access plans thus computed will result.

Abstract: A node in a computer network is enabled to form a hypercube comprising stored metadata. The node is enabled to exchange the hypercube metadata with neighboring nodes and any hypercube metadata therein. Upon receipt of a query at a node, metadata discovery is initiated using the hypercube metadata, and an overlay is built using results from the metadata discovery.

Abstract: Aspects of the current subject matter can provide a background job repository that stores a background job template specifying a background job comprising a maintenance task that affects a customized software platform. The background job template can also include metadata defining a purpose of the background job, triggering information indicating when the background job should be executed, and a prerequisite feature of the customized software platform that indicates a need for the background job in the customized software platform. A previous set of background jobs that run in the customized software platform can be updated to a current set by comparing the previous set with the background job template and including the background job in the current set of background jobs when the customized software platform includes the prerequisite feature.

Abstract: A method, computer program, and system-model converter for converting system model. The method includes the steps of: receiving input of a conversion processing description about a structure of a multi-dimensional data model and extraction queries, where the multi-dimensional data model and the extraction queries extract at least one element from a plurality of model elements; and generating a hierarchical multi-dimensional data model from a graph model stored in a graph model storage unit on the basis of the inputted conversion processing description, where the hierarchical multi-dimensional data model includes dimensions having a hierarchical relationship.

Abstract: A computing system for intelligence gathering and analysis includes a computer-based remote avatar rendering and maintenance module, a self-directed data gathering and communication module, a remote personalized data stream analysis module, and a database. The avatar rendering and maintenance module provides an indicator for users to select targeted data streams presented as weapon icons that includes user-selected analysis priorities and threshold attributes of the targeted data. The self-directed data gathering and communication module provides administration programs that coordinate and control the timing and execution of commercially available web search, crawler, and messaging applications. The personalized data stream analysis module provides administration programs that coordinate and control the timing and execution of data consolidation, workflow and scoring programs related to the analysis module.

Abstract: A data warehouse includes a plurality of master data tables. The master data tables include surrogate identifiers. Each surrogate identifier (SID) identifies a master data table domain inside a master data table from the plurality of master data tables. A plurality of dimension tables use the surrogate identifiers to link to the master data table domains within the master data tables. A fact table stores dimension identifiers (DIM IDs) that provide links to the dimension tables. A domain fact table stores aggregated data aggregated from data stored in the master data tables. The aggregated data is accessible from the domain fact table using surrogate identifiers, without using DIM IDs stored in the fact table.

Abstract: Methods and apparatus for improving data warehouse performance are disclosed. An example method to transform a first database into a second database includes analyzing a structure of the first database, generating a hierarchical file path structure reflecting the structure of the first database, and associating a mapping file with a fact table, the mapping file stored in a first hierarchical directory file path of the hierarchical file path structure. The example method also includes copying data from the first database to form the second database, the copied data being accessible from the second database via the mapping file and the fact table, receiving a request to access data in the first database, using the mapping file and the fact table to retrieve the data responsive to the analysis instruction from the second database, and outputting the retrieved data.

Abstract: The present invention automatically generates an object model from a dimensional model. The object model can then be queried using object oriented expressions.

Abstract: [Object] To provide a system model conversion method, a computer program, and a system model converter which facilitate analysis and editing of the system model by using information indicating a hierarchical relationship. [Solving Means] A model converter 1 includes a graph model storage unit 2 storing therein a graph model which is the system model having a graph-type data structure and including a plurality of model elements. A conversion processing description input unit 6 receives input of a conversion processing description including a description about a structure of a multi-dimensional data model and extraction queries that each extract any of the model elements. A data converter 4 generates a table 32 of the multi-dimensional data model in which dimensions have a hierarchical relationship, from the graph model 20 stored in the graph model storage unit 2, on the basis of the inputted conversion processing description.

Abstract: Methods, program products and systems for determining, for a database query that does not represent a snowflake schema, a graph comprising vertices each representing a table joined in the query, a directed edge between each pair of vertices of which a first vertex represents a first table and a second vertex represents a second table that is joined in the query with the first table, each of the edges representing one of an outer join and an inner join. Further determining, for the graph, a directed spanning tree that represents an ordering of joins in the query and includes all outer join edges in the graph.

Abstract: Provided are, inter alia, systems, methods and techniques for facilitating identification of a skilled resource's skill set. Initially, a master set of previously identified skills is filtered in order to identify a subset of skills that appear to be potentially applicable to a skilled resource. Then, based on the identified subset, a query regarding skills actually possessed by the skilled resource is created and presented. A response that designates skills possessed by the skilled resource is received and incorporated into a user skills database. The above-referenced filtering is performed by utilizing an automated tool to analyze content from a set of computer files.

Abstract: An aspect of the present invention simplifies generating a star schema from a snowflake schema. In an embodiment, a user first specifies fact tables to be included in a star schema, and a synchronization tool inspects the snowflake schema to determine the dimension tables linked to the specified fact tables. The determined dimension tables are included in the star schema sought to be generated.

Abstract: A data extraction tool is provided for cataloging information in an information source for searching by a user. The tool mines information from the information source and organizes the information, or the locations of that information, within a database. A user may then query the tool for a desired type of information. The tool filters the database to provide a set of pinpoint site locations with information of the type requested in the query. These pinpoint site locations are presented to a user and indexed for future reference. The index of site locations may be updated automatically by the tool. A context system is provided for manually or automatically determining the proper context for a user's query. Thus, the data extraction tool provides information with a high probability of relevance to the user. The user obtains the information without expending much effort to refine the search.

Abstract: The subject invention pertains to systems and methods that facilitate generation of a database to support a multidimensional model. A database schema is generated in a top-down fashion. In particular, multidimensional structures and attributes such as cubes and dimensions can be defined. From such definition, a proposed database schema can be produced. This schema can subsequently be modified prior to or after populating the database. For example, a table or column could be added. Thereafter, the cubes and dimensions could be altered and a modified schema generated that preserves changes made to the schema. Accordingly, the subject systems and methods disclose an iterative approach that supports both top-down and bottom-up multidimensional database design.

Abstract: The subject invention pertains to systems and methods for interacting with fact dimensions. In particular, systems and methods are disclosed that optimize performance and scalability with respect to processing queries that involve fact dimensions. Furthermore, queries involving fact dimensions can be evaluated in distinct manners. For instance, queries can be processed such that regular dimensions restrict the scope of the data and only fact dimension members that are relevant to that scope are exposed.

Abstract: A data warehouse comprises a multidimensional data storage area to store multidimensional data and a transactional data storage area to store underlying transactional data from which the multidimensional data is generated. The data warehouse also comprises a multidimensional query processor to provide one or more interfaces to issue a first set of queries conforming to one or more multidimensional query languages to retrieve the multidimensional data from the multidimensional data storage area. Furthermore, the data warehouse comprises a dynamic query engine to provide an additional interface to issue a second set of queries that bypass the interfaces provided by the multidimensional query processor to retrieve the transactional data from the transactional data storage area, wherein the second set of queries do not conform to any of the one or more multidimensional query languages.