Abstract: According to embodiments of the present invention, methods, systems and computer-readable media are presented for scanning a plurality of storage regions within memory for a specified quantity of results, wherein each storage region is associated with an interval including first and second interval values indicating a value range for values within that storage region. The techniques comprise sorting the first interval values into an order, wherein the order of the first interval values determines a scanning order for the plurality of storage regions, determining a result value, wherein the result value is an upper bound, a lower bound, or is outside of the specified quantity of results, and examining the sorted first interval values and scanning corresponding individual storage regions in response to a comparison of the determined result value with the first interval value of that storage region.

Abstract: According to embodiments of the present invention, methods, systems and computer-readable media are presented for scanning a plurality of storage regions within memory for a specified quantity of results, wherein each storage region is associated with an interval including first and second interval values indicating a value range for values within that storage region. The techniques comprise sorting the first interval values into an order, wherein the order of the first interval values determines a scanning order for the plurality of storage regions, determining a result value, wherein the result value is an upper bound, a lower bound, or is outside of the specified quantity of results, and examining the sorted first interval values and scanning corresponding individual storage regions in response to a comparison of the determined result value with the first interval value of that storage region.

Abstract: Elements of a database object are stored among a plurality of different storage regions, each storage region being associated with a first value range indicating upper and lower range values for element values within that storage region. An index is generated and maintained for one or more second value ranges that include range values that comprise subsets of the first value ranges. A query is processed that includes a query value and one or more storage regions to be read is determined by using one of the index and the first value ranges based on the query value relative to a second value range.

Abstract: According to one embodiment of the present invention, a system for processes a query for accessing data within one or more database objects stores an element of a database object among a plurality of different storage regions. Each storage region is associated with first and second range values indicating a value range for element values within that storage region. The system examines the first and second range values for the storage regions of each database object element and determines an effectiveness value representing a degree of overlap between the storage regions of that database object element. The system determines a selectivity model for the storage regions for each database object utilizing the effectiveness value, determines a query plan based on the selectivity model, and executes the query plan. Embodiments of the present invention further include a method and computer program product for processing a query in substantially the same manners.

Abstract: According to one embodiment of the present invention, a system for processes a query for accessing data within one or more database objects stores an element of a database object among a plurality of different storage regions. Each storage region is associated with first and second range values indicating a value range for element values within that storage region. The system examines the first and second range values for the storage regions of each database object element and determines an effectiveness value representing a degree of overlap between the storage regions of that database object element. The system determines a selectivity model for the storage regions for each database object utilizing the effectiveness value, determines a query plan based on the selectivity model, and executes the query plan. Embodiments of the present invention further include a method and computer program product for processing a query in substantially the same manners.

Abstract: According to one embodiment of the present invention, a system for sorting data records generates a plurality of data structures associated with corresponding record fields used to sort the data records, and inserts values of the record fields into the corresponding data structures. Each of the data structures comprises one or more ordered parts, and each inserted value is inserted into a part of the corresponding data structure. Each part of a data structure corresponding to a record field having a sort priority immediately below another record field corresponds to a distinct value inserted into a part of the data structure corresponding to the other record field. The system processes the generated data structures to determine sorted data records. Embodiments of the present invention further include a method and computer program product for sorting data records in substantially the same manners described above.

Abstract: To perform a join operation on database objects, data structures contained in a first database object are distributed across database partitions in accordance with a partitioning scheme. Data structures of the first database object are associated with respective indices computed complementarily to the partitioning scheme. Other indices are computed from the respective data structures of a second database object. The join operation is performed at each of the database partitions on the data structures in the respective first and second database objects having the indices and the other indices in common.

Abstract: According to one embodiment of the present invention, a system may execute database queries and may comprise a computer system including at least one processor. The system may select a column of a first table as a candidate column for creating a dictionary, create tokens for a foreign key in a second table that corresponds to a primary key in the first table, generate the dictionary for the selected column using the created tokens as indexes in the dictionary and modify a query accessing the column of the first table to retrieve column values based on the dictionary. Embodiments of the present invention further include a method and computer program product executing database queries in substantially the same manner described above.

Abstract: Data within a database object are accessed based on a query with a predicate including a plurality of conditional expressions. Elements of the database object are stored among a plurality of different storage regions along with range values for element values within each storage region. Each conditional expression of the query predicate is applied to the range values for each storage region to produce evaluation results of that conditional expression for each storage region. The evaluation result of each conditional expression for a corresponding storage region is combined to produce aggregated results for each of the storage regions, where the aggregated result for a corresponding storage region indicates results of a tri-state evaluation (e.g., true/false or unknown) of the conditional expressions for that storage region. One or more corresponding individual storage regions are scanned based on the aggregated results for those storage regions when the tri-state evaluation is unknown.

Abstract: According to one embodiment of the present invention, a system may execute database queries and may comprise a computer system including at least one processor. The system may select a column of a first table as a candidate column for creating a dictionary, create tokens for a foreign key in a second table that corresponds to a primary key in the first table, generate the dictionary for the selected column using the created tokens as indexes in the dictionary and modify a query accessing the column of the first table to retrieve column values based on the dictionary. Embodiments of the present invention further include a method and computer program product executing database queries in substantially the same manner described above.

Abstract: Each binary floating-point value in a set of binary floating-point values is converted to a decimal floating-point value. Data are determined including an exponent, a mantissa and a quantity of decimal digits of the mantissa for each decimal floating-point value. The exponents, the mantissas and the quantity of decimal digits are individually compressed to produce compressed floating-point values based on the individual compressions.

Abstract: According to embodiments of the present invention, apparatus, systems, methods and computer program products for sorting and compressing an unordered set of data records from a structured database are provided. Fields of the unordered set of data records are prioritized based on an impact of those fields to a compression scheme for column-oriented compression. The unordered set of data records are sorted based on the prioritized field(s) with a greatest impact on the performance metric. Data of the sorted data records are compressed according to a compression scheme. In some embodiments, prioritizing the fields may be based on an anticipated level of usage of data within those fields and/or a cost function associated with a performance metric as well as optimization of compression. A performance metric may include a faster computational time, reduced I/O computation, faster scan time, etc.

Abstract: According to embodiments of the present invention, machines, systems, methods and computer program products for hardware acceleration are presented. A plurality of computational nodes for processing data is provided, each node performing a corresponding operation for data received at that node. A metric module is used to determine a compression benefit metric pertaining to performance of the corresponding operations of one or more computational nodes with recompressed data. An accelerator module recompresses data for processing by the one or more computational nodes based on the compression benefit metric indicating a benefit gained by using the recompressed data. A distribution function may be used to distribute data among a plurality of nodes.

Abstract: Data within a database object are accessed based on a query with a predicate including a plurality of conditional expressions. Elements of the database object are stored among a plurality of different storage regions along with range values for element values within each storage region. Each conditional expression of the query predicate is applied to the range values for each storage region to produce evaluation results of that conditional expression for each storage region. The evaluation result of each conditional expression for a corresponding storage region is combined to produce aggregated results for each of the storage regions, where the aggregated result for a corresponding storage region indicates results of a tri-state evaluation (e.g., true/false or unknown) of the conditional expressions for that storage region. One or more corresponding individual storage regions are scanned based on the aggregated results for those storage regions when the tri-state evaluation is unknown.

Abstract: According to embodiments of the present invention, machines, systems, methods and computer program products for hardware acceleration are presented. A plurality of computational nodes for processing data is provided, each node performing a corresponding operation for data received at that node. A metric module is used to determine a compression benefit metric pertaining to performance of the corresponding operations of one or more computational nodes with recompressed data. An accelerator module recompresses data for processing by the one or more computational nodes based on the compression benefit metric indicating a benefit gained by using the recompressed data. A distribution function may be used to distribute data among a plurality of nodes.

Abstract: According to embodiments of the present invention, machines, systems, methods and computer program products for hardware acceleration are presented. A plurality of computational nodes for processing data is provided, each node performing a corresponding operation for data received at that node. A metric module is used to determine a compression benefit metric pertaining to performance of the corresponding operations of one or more computational nodes with recompressed data. An accelerator module recompresses data for processing by the one or more computational nodes based on the compression benefit metric indicating a benefit gained by using the recompressed data. A distribution function may be used to distribute data among a plurality of nodes.

Abstract: According to embodiments of the present invention, apparatus, systems, methods and computer program products for sorting and compressing an unordered set of data records from a structured database are provided. Fields of the unordered set of data records are prioritized based on an impact of those fields to a compression scheme for column-oriented compression. The unordered set of data records are sorted based on the prioritized field(s) with a greatest impact on the performance metric. Data of the sorted data records are compressed according to a compression scheme. In some embodiments, prioritizing the fields may be based on an anticipated level of usage of data within those fields and/or a cost function associated with a performance metric as well as optimization of compression. A performance metric may include a faster computational time, reduced I/O computation, faster scan time, etc.

Abstract: According to one embodiment of the present invention, a system performs a grouping operation for a database query. The system assigns data elements to groups and aggregates information for a group in response to assigning the group two or more data elements. The system passes the aggregated information for a group of two or more data elements for processing in accordance with the query, and passes information for a data element of a single-member group in a received form for processing in accordance with the query. Embodiments of the present invention further include a method and computer program product for grouping data elements in substantially the same manners described above.

Abstract: Data within a database object are accessed based on a query with a predicate including a plurality of conditional expressions. Elements of the database object are stored among a plurality of different storage regions along with range values for element values within each storage region. Each conditional expression of the query predicate is applied to the range values for each storage region to produce evaluation results of that conditional expression for each storage region. The evaluation result of each conditional expression for a corresponding storage region is combined to produce aggregated results for each of the storage regions, where the aggregated result for a corresponding storage region indicates results of a tri-state evaluation (e.g., true/false or unknown) of the conditional expressions for that storage region. One or more corresponding individual storage regions are scanned based on the aggregated results for those storage regions when the tri-state evaluation is unknown.

Abstract: According to one embodiment of the present invention, a system performs a grouping operation for a database query. The system assigns data elements to groups and aggregates information for a group in response to assigning the group two or more data elements. The system passes the aggregated information for a group of two or more data elements for processing in accordance with the query, and passes information for a data element of a single-member group in a received form for processing in accordance with the query. Embodiments of the present invention further include a method and computer program product for grouping data elements in substantially the same manners described above.