Abstract: Embodiments may provide methods and systems for intelligent capture and fast transformation of granulated data summaries. An engine may be used to transform input data summaries into result sets representing query outcomes. The data summaries contain enough knowledge about the original data to accurately perform operations on the summaries without needing to access the original data. In an embodiment, the contents of data summaries are accessible via an SQL approximate engine which retrieves summaries stored on disk and utilizes them for its operations. Alternatively, the contents of data summaries are accessible via virtual tables which give users direct access to the summary contents and allow for the creation and implementation of algorithms to work with the data summaries independently from the SQL approximate engine.

Abstract: Embodiments may provide methods and systems for intelligent capture and fast transformation of granulated data summaries. An engine may be used to transform input data summaries into result sets representing query outcomes. The data summaries contain enough knowledge about the original data to accurately perform operations on the summaries without needing to access the original data. In an embodiment, the contents of data summaries are accessible via an SQL approximate engine which retrieves summaries stored on disk and utilizes them for its operations. Alternatively, the contents of data summaries are accessible via virtual tables which give users direct access to the summary contents and allow for the creation and implementation of algorithms to work with the data summaries independently from the SQL approximate engine.

Abstract: In a method for storing data in a relational database system using a processor, a collection of values is assigned to a structure dictionary, each of the values represents the value of a row for an attribute and has a unique ordinal number within the collection. and the structure dictionary contains structures defined based on at least one of interaction with a user of the system via an interface, automatic detection of structures occurring in data, automatic detection of frequencies of values occurring in data, analysis of a history of queries, and predetermined information about structures relevant to data content that is stored in the system. For each structure, forming a structure match list from ordinal numbers of values matching the structure, and a structure sub-collection from values matching the structure, using the processor.

Abstract: In a method for managing metadata in a relational database system using a processor, the metadata is created in a form of rough values corresponding to collections of values, wherein each rough value represents summarized information about values, the values are elements of the corresponding collection of values, and each rough value is substantially smaller than the corresponding collection of values. A collection of values is assigned to a structure dictionary, wherein each of the values represents the value of a row for an attribute and has a unique ordinal number within the collection, and wherein the structure dictionary contains structures defined based on at least one of interaction with a user of the system via an interface, automatic detection of structures occurring in data, and predetermined information about structures relevant to data content that is stored in the system. A match granule is formed, and for each structure in the structure dictionary, a structure granule is formed.

Abstract: In a method for storing data in a relational database system using a processor, a collection of values is assigned to a structure dictionary, wherein each of the values represents the value of a row for an attribute and has a unique ordinal number within the collection, and wherein the structure dictionary contains structures defined based on at least one of interaction with a user of the system via an interface, automatic detection of structures occurring in data, and predetermined information about structures relevant to data content that is stored in the system. For each structure in the structure dictionary, a structure match list is formed from ordinal numbers of values matching the structure, and a structure sub-collection from values matching the structure, using the processor.

Abstract: In a method for storing data in a relational database system using a processor, a collection of values is assigned to a structure dictionary, wherein each of the values represents the value of a row for an attribute and has a unique ordinal number within the collection, and wherein the structure dictionary contains structures defined based on at least one of interaction with a user of the system via an interface, automatic detection of structures occurring in data, and predetermined information about structures relevant to data content that is stored in the system. For each structure in the structure dictionary, a structure match list is formed from ordinal numbers of values matching the structure, and a structure sub-collection from values matching the structure, using the processor.

Abstract: In a method for storing data in a relational database system using a processor, a collection of values is assigned to a structure dictionary, wherein each of the values represents the value of a row for an attribute and has a unique ordinal number within the collection, and wherein the structure dictionary contains structures defined based on at least one of interaction with a user of the system via an interface, automatic detection of structures occurring in data, and predetermined information about structures relevant to data content that is stored in the system. For each structure in the structure dictionary, a structure match list is formed from ordinal numbers of values matching the structure, and a structure sub-collection from values matching the structure, using the processor.