Abstract: A method, system and computer program product for providing early diagnosis of hardware, software or configuration problems in a data warehouse system. A received query is parsed to determine the properties of the query. The query may then be joined to existing groups of queries if those groups have shared properties of the query. After executing the query according to an execution plan, results from the execution of the query is received, which may include problem(s) that occurred during execution of the query. For those problems that reach a pre-defined threshold of becoming a “group problem” in those groups joined by the query, the problem is reported to the end user concerning those groups where the problem exceeds the pre-defined threshold. In this manner, an early diagnosis of the problems in the data warehouse system that can cause delay and failure of the processing of queries is able to occur.

Abstract: The present disclosure relates to a computer-implemented method for joining two data tables on a join attribute. The data tables have at least a first and a second attribute. The second attribute is the join attribute. The method comprises providing a function for associating a computing node to a given record. The function may be used to determine the associated computing node. The records of the two data tables may be distributed to the respective determined computing nodes. The relationship between the values of the first and second attributes may be modelled using a predefined dataset. For each record of the two data tables the values of the first attribute may be re-determined using the corresponding values of the second attribute. The function may be used to re-determine the associated computing node.

Abstract: A method, system and computer program product for providing early diagnosis of hardware, software or configuration problems in a data warehouse system. A received query is parsed to determine the properties of the query. The query may then be joined to existing groups of queries if those groups have shared properties of the query. After executing the query according to an execution plan, results from the execution of the query is received, which may include problem(s) that occurred during execution of the query. For those problems that reach a pre-defined threshold of becoming a “group problem” in those groups joined by the query, the problem is reported to the end user concerning those groups where the problem exceeds the pre-defined threshold. In this manner, an early diagnosis of the problems in the data warehouse system that can cause delay and failure of the processing of queries is able to occur.

Abstract: The present disclosure relates to a computer-implemented method for joining two data tables on a join attribute. The data tables have at least a first and a second attribute. The second attribute is the join attribute. The method includes providing a function for associating a computing node to a given record. The function may be used to determine the associated computing node. The records of the two data tables may be distributed to the respective determined computing nodes. The relationship between the values of the first and second attributes may be modelled using a predefined dataset. For each record of the two data tables the values of the first attribute may be re-determined using the corresponding values of the second attribute. The function may be used to re-determine the associated computing node.

Abstract: The invention relates to a method, computer program product and computer system for providing attribute value information for a data extent comprising a set of data entries.

Abstract: Embodiments of the present invention provide a method, computer program product, and a computer system for storing data records in extents. According to one embodiment a data record comprising an attribute value is received. One or more data records stored in a first extent, are identified, wherein the stored one or more data records in the first extent have at least one attribute value. The attribute value of the received data record is compared to the attribute values of the identified data records stored in the first extent. It is then determined whether to store the received data record in the first extent. Responsive to determining, not to store the received data record in the first extent, the received data record is stored in a second extent. If the first received data record is stored in a second extent, determining, an attribute value information of the second extent.

Abstract: Embodiments of the present invention provide a method, computer program product, and a computer system for storing data records in extents. According to one embodiment a data record comprising an attribute value is received. One or more data records stored in a first extent, are identified, wherein the stored one or more data records in the first extent have at least one attribute value. The attribute value of the received data record is compared to the attribute values of the identified data records stored in the first extent. It is then determined whether to store the received data record in the first extent. Responsive to determining, not to store the received data record in the first extent, the received data record is stored in a second extent. If the first received data record is stored in a second extent, determining, an attribute value information of the second extent.

Abstract: The present disclosure relates to a method for recording user activity on a computer. The method includes creating a video file for a video sequence of a user interface of an application of the computer. Video frames may be recorded in the video file, wherein a video frame comprises data indicative of the visual representation of the user interface and corresponding timestamp, wherein the data of the video frame is parsable.

Abstract: The invention relates to a method, computer program product and computer system for providing attribute value information for a data extent having a set of data entries.

Abstract: The present disclosure relates to a computer-implemented method, computer program product, and computer system, for optimization of query processing a set of data extents on which a table is stored. Attribute value information may be maintained for each data extent. The attribute value information indicate as ranges the minimum and maximum values of an attribute of the entries stored in the respective extent. A first metric of a first data extent of the set may determine splitting the first data extent into sub-extents increases query processing efficiency. A second metric of a second data extent and a third data extent may determine merging the second data extent and the third data extent increases query processing efficiency.

Abstract: A computer-implemented method for partitioning data for a query operation of one table of the database system is provided. The computer-implemented method comprises estimating a value distribution of the attribute in the result table based on a first value distribution of the attribute in the first column of the first table. The computer-implemented method further comprises determining boundaries for partitioning ranges of the attribute, based on the estimated value distribution, wherein the partitioning ranges correspond to a same number of rows of the result table. The computer-implemented method further comprises partitioning the first table with processing nodes of the query operation, based on the determined boundaries of partitioning ranges.

Abstract: The present disclosure relates to a computer-implemented method for joining two data tables on a join attribute. The data tables have at least a first and a second attribute. The second attribute is the join attribute. The method comprises providing a function for associating a computing node to a given record. The function may be used to determine the associated computing node. The records of the two data tables may be distributed to the respective determined computing nodes. The relationship between the values of the first and second attributes may be modelled using a predefined dataset. For each record of the two data tables the values of the first attribute may be re-determined using the corresponding values of the second attribute. The function may be used to re-determine the associated computing node.

Abstract: A computer-implemented method of estimating selectivity of a query may include generating, for data stored in a database in a memory, a one-dimensional value distribution for each of a plurality of attributes of the data. A multidimensional histogram may be generated, wherein the multidimensional histogram includes the one-dimensional value distributions for the plurality of attributes of the data. The multidimensional histogram may be converted to a one-dimensional histogram by assigning each bucket of the multidimensional histogram to corresponding buckets of the one-dimensional histogram and ordering the corresponding buckets according to a space-filling curve. One or more bucket ranges of the one-dimensional histogram may be determined by mapping the query conditions on the one-dimensional histogram. The selectivity of the query may be estimated by estimating how many data values in the one or more bucket ranges will meet the query conditions.

Abstract: A computer-implemented method of estimating selectivity of a query may include generating, for data stored in a database in a memory, a one-dimensional value distribution for each of a plurality of attributes of the data. A multidimensional histogram may be generated, wherein the multidimensional histogram includes the one-dimensional value distributions for the plurality of attributes of the data. The multidimensional histogram may be converted to a one-dimensional histogram by assigning each bucket of the multidimensional histogram to corresponding buckets of the one-dimensional histogram and ordering the corresponding buckets according to a space-filling curve. One or more bucket ranges of the one-dimensional histogram may be determined by mapping the query conditions on the one-dimensional histogram. The selectivity of the query may be estimated by estimating how many data values in the one or more bucket ranges will meet the query conditions.

Abstract: In an approach to preparing a query execution plan, a host node receives a query implicating one or more data tables. The host node broadcasts one or more implicated data tables to one or more processing nodes. The host node receives a set of node-specific query execution plans and execution cost estimates associated with each of the node-specific query execution plans, which have been prepared in parallel based on global statistics and node-specific low level statistics. The host node selects an optimal query execution plan based on minimized execution cost.

Abstract: A method for determining when to send monitoring data to a server within a monitoring infrastructure. The method includes a first agent computer collecting a first instance of monitoring data relating to an alert on a computer system, wherein the collecting is based, at least in part, on a set of instructions received from a monitoring server, wherein the set of instructions includes instructions for determining whether the monitoring data is relevant to triggering the alert. The first agent then receives at least one second instance of monitoring data from a set of second agents. The first agent then determines whether the first instance of monitoring data is relevant to triggering the alert based, at least in part, on the first instance of monitoring data and the second instance of monitoring data. The first agent then determines whether to send the first instance of monitoring data to the monitoring server.

Abstract: A method for determining when to send monitoring data to a server within a monitoring infrastructure. The method includes a first agent computer collecting a first instance of monitoring data relating to an alert on a computer system, wherein the collecting is based, at least in part, on a set of instructions received from a monitoring server, wherein the set of instructions includes instructions for determining whether the monitoring data is relevant to triggering the alert. The first agent then receives at least one second instance of monitoring data from a set of second agents. The first agent then determines whether the first instance of monitoring data is relevant to triggering the alert based, at least in part, on the first instance of monitoring data and the second instance of monitoring data. The first agent then determines whether to send the first instance of monitoring data to the monitoring server.

Abstract: Software for processing a database query that includes: (i) receiving a query of a database including a search value; (ii) determining a distance between the search value and at least one reference value; (iii) determining a maximum distance from the search value to be used in searching a plurality of datasets of the database, wherein the maximum distance from the search value defines a search range and is based, at least in part, on the determined distance between the search value and the at least one reference value; (iv) determining a subset of datasets from the plurality of datasets that includes datasets for which a data range with respect to each reference value overlaps with the search range; and (v) performing approximate string matching for the search value on the subset of datasets.

Abstract: Software for processing a database query that includes: (i) receiving a query of a database including a search value; (ii) determining a distance between the search value and at least one reference value; (iii) determining a maximum distance from the search value to be used in searching a plurality of datasets of the database, wherein the maximum distance from the search value defines a search range and is based, at least in part, on the determined distance between the search value and the at least one reference value; (iv) determining a subset of datasets from the plurality of datasets that includes datasets for which a data range with respect to each reference value overlaps with the search range; and (v) performing approximate string matching for the search value on the subset of datasets.

Abstract: A computer-implemented method, system, and/or computer program product optimizes an order of execution of column join operations. A first partitioning of the first data column splits the first data column into first subsets of rows. A second partitioning of the second data column splits the second data column into a second subsets of rows. Cardinalities of sub-tables derived by a respective joining of the subsets of rows of the first and second data columns are estimated, based on the first and second value frequency information. An order of execution of multiple join operations is then optimized based on the estimated cardinalities of the sub-tables.