Abstract: A system is configured for automatic recognition of data store architecture and tracking dynamic changes and evolution in data store architecture. The system is a complementary system, which can be added onto an existing data store system using the existing interfaces or can be integrated with a data store system. The system comprises three main components that are configured to compose an approximation of the data store architecture. The first of these components is adapted to execute an analysis of the architecture of the data store; the second of the components is adapted to collect and compile statistics from said data store; and the third of the components is adapted to compose an approximation of the architecture of said data store.

Abstract: A system is configured for automatic recognition of data store architecture and tracking dynamic changes and evolution in data store architecture. The system ef is a complementary system, which can be added onto an existing data store system using the existing interfaces or can be integrated with a data store system. The system comprises three main components that are configured to compose an approximation of the data store architecture. The first of these components is adapted to execute an analysis of the architecture of the data store; the second of the components is adapted to collect and compile statistics from said data store; and the third of the components is adapted to compose an approximation of the architecture of said data store.

Abstract: System and methods for obtaining frequent terms in a set of data is provided. The method comprises obtaining the set of data comprising a stream of terms; analyzing the stream of terms using a modified data streaming generator to find a set of frequent terms; forming a dictionary of terms based on the set of most frequent terms; identifying one or more of the set of frequent terms in the set of data; and analyzing the one or more of the set of frequent terms in the set of data to determine a context and/or structure based on neighboring terms in the set of data; providing a visualization tool for the interactions with the frequent terms and the application at hand.

Abstract: The present invention is a system for automatic recognition of data store architecture and tracking dynamic changes and evolution in data store architecture. The system of the invention is a complementary system, which can be added onto an existing data store system using the existing interfaces or can be integrated with a data store system. The system comprises three main components that are configured to compose an approximation of the data store architecture. The first of these components is adapted to execute an analysis of the architecture of the data store; the second of the components is adapted to collect and compile statistics from said data store; and the third of the components is adapted to compose an approximation of the architecture of said data store. Methods for using the system of the invention are also described.

Abstract: The present invention is a system for automatic recognition of data store architecture and tracking dynamic changes and evolution in data store architecture. The system of the invention is a complementary system, which can be added onto an existing data store system using the existing interfaces or can be integrated with a data store system. The system comprises three main components that are configured to compose an approximation of the data store architecture. The first of these components is adapted to execute an analysis of the architecture of the data store; the second of the components is adapted to collect and compile statistics from said data store; and the third of the components is adapted to compose an approximation of the architecture of said data store. Methods for using the system of the invention are also described.

Abstract: System and methods for obtaining frequent terms in a set of data is provided. The method comprises obtaining the set of data comprising a stream of terms; analyzing the stream of terms using a modified data streaming generator to find a set of frequent terms; forming a dictionary of terms based on the set of most frequent terms; identifying one or more of the set of frequent terms in the set of data; and analyzing the one or more of the set of frequent terms in the set of data to determine a context and/or structure based on neighboring terms in the set of data; providing a visualization toot for the interactions with the frequent terms and the application at hand.

Abstract: The present invention is a system for automatic recognition of data store architecture and tracking dynamic changes and evolution in data store architecture. The system of the invention is a complementary system, which can be added onto an existing data store system using the existing interfaces or can be integrated with a data store system. The system comprises three main components that are configured to compose an approximation of the data store architecture. The first of these components is adapted to execute an analysis of the architecture of the data store; the second of the components is adapted to collect and compile statistics from said data store; and the third of the components is adapted to compose an approximation of the architecture of said data store. Methods for using the system of the invention are also described.

Abstract: A database system includes an input to a database server configured to deliver a data stream formed of a sequence of elements, D={p1, p2, . . . , pm} of size m of numbers from {1, . . . , n} to the database server. The system further includes a computer program that causes a processor to approximate frequency moments (Fk) in the data stream, such that a frequency of an element (i) is defined as fi=|{j:pj=i}| and a k-th frequency moment of D is defined as F k = ? i = 1 n ? m i k in a single pass through the data stream. The processor is caused to carry out the steps of locating elements (i) with a frequency ?Fk in the data stream as heavy elements and approximating fi as ? a fraction of fi to limit memory resources used by the processor to estimate Fk to O(n1?2/k log(n)) bits.

Abstract: A database system includes an input to a database server configured to deliver a data stream formed of a sequence of elements, D={p1, p2, . . . , pm} of size m of numbers from {1, . . . , n} to the database server. The system further includes a computer program that causes a processor to approximate frequency moments (Fk) in the data stream, such that a frequency of an element (i) is defined as fi=|{j:pj=i}| and a k-th frequency moment of D is defined as F k = ? i = 1 n ? m i k ? ? in ? ? a single pass through the data stream. The processor is caused to carry out the steps of locating elements (i) with a frequency ?Fk in the data stream as heavy elements and approximating fi as ? a fraction of fi to limit memory resources used by the processor to estimate Fk to O(n1?2/k log(n)) bits.

Abstract: A method of effectively representing and processing data sets with time series is disclosed. The method may comprise representing time series as a virtual part of data in a data store layer of a user system, thereby allowing processing of time-series related queries in said data store layer of said user system.

Abstract: A database system includes an input to a database server configured to deliver a data stream formed of a sequence of elements, D={p1, p2, . . . , pm} of size m of numbers from {1, . . . , n} to the database server. The system further includes a computer program that causes a processor to approximate frequency moments (Fk) in the data stream, such that a frequency of an element (i) is defined as fi=|{j:pj=i}| and a k-th frequency moment of D is defined as F k = ? i = 1 n ? m i k ? ? in ? ? a single pass through the data stream. The processor is caused to carry out the steps of locating elements (i) with a frequency ?Fk in the data stream as heavy elements and approximating fi as ? a fraction of fi to limit memory resources used by the processor to estimate Fk to O(n1?2/k log(n)) bits.

Abstract: The current invention is a method and a system for analyzing templates of queries, with different levels of precision. When the system of the current invention takes a decision to arrange data, these templates are used, and a single data arrangement object (HRBlob) is designed which may serve a single template or several templates and not just a single query. This approach has an important impact on data arrangement performance and on queries performance, since this approach may help many more queries to be handled using less data arrangement objects.

Abstract: A method of effectively representing and processing data sets with time series is disclosed. The method may comprise representing time series as a virtual part of data in a data store layer of a user system, thereby allowing processing of time-series related queries in said data store layer of said user system.

Abstract: The current invention is a method and a system for analyzing templates of queries, with different levels of precision. When the system of the current invention takes a decision to arrange data, these templates are used, and a single data arrangement object (HRBlob) is designed which may serve a single template or several templates and not just a single query. This approach has an important impact on data arrangement performance and on queries performance, since this approach may help many more queries to be handled using less data arrangement objects.