Abstract: With respect to an information processing method to be performed by a computer, the information processing method includes performing aggregation in a plurality of dimensions included in a virtual table for each value of a predetermined key, two tables in a natural number index format being combined by join using the predetermined key in the virtual table, and calculating a sum of results of the aggregation.

Abstract: With respect to a search method, for execution by a computer, for searching for multidimensional data that satisfies a search condition in a table representing a multidimensional data set including a plurality of search target parameters, the search method includes creating multidimensional indexes including a plurality of transposition blocks for identifying record numbers based on values of parameters of the plurality of search target parameters by using the multidimensional data set included in the table, and identifying a target record number of the multidimensional data that satisfies the search condition in the multidimensional data set included in the table by using the multidimensional indexes.

Abstract: With respect to a search method, for execution by a computer, for searching for multidimensional data that satisfies a search condition in a table representing a multidimensional data set including a plurality of search target parameters, the search method includes creating multidimensional indexes including a plurality of transposition blocks for identifying record numbers based on values of parameters of the plurality of search target parameters by using the multidimensional data set included in the table, and identifying a target record number of the multidimensional data that satisfies the search condition in the multidimensional data set included in the table by using the multidimensional indexes.

Abstract: In a system including nodes that store tables, respectively, each table storing one or more records, each node generates, from a table of the tables stored by an own node, a right structure used as a referred-side structure in an L-operation; generates, from the right structure, a left structure used as an operated-side structure in an L-operation; transmits the right structure generated by the own node to another node; receives a right structure generated by another node; performs an L-operation between the left structure and each of the right structure generated by the own node and the right structure received by the own node, and determines, for the one or more records stored by the table stored by the own node, corresponding positions in an order of all records stored by the tables that are stored by the nodes, respectively.

Abstract: To complete transfer of data of a node to all other nodes in a short time while suppressing the number of channels. A distributed processing system is formed by a plurality of rings. In addition, each ring is formed by sequentially connecting the same number of nodes in a ring shape by channels. In addition, the nodes of each ring are connected to a node having the same order on the ring of the other rings by a channel. Each node transmits data, which is received from the node immediately previous in the order on the ring, to a node next in the order on the ring and a node having the same order in the ring of other rings.

Abstract: Data of a plurality of tables are stored in compressed form so as to make integrated use of the tables easy. The ranks of entries of VL in which a value of the n-th record of the table (a1, b1) is registered are registered in the n-th entry of VL of an index of an index set (a2, b2). When integrating the index set (b2) of the table B into the integrated index (a3), a value not included in VL of the integrated index (a3) among values included in VL of the index is additionally registered (b3) in VL of the integrated index. In addition, a value indicating the ranks of entries of VL of the integrated index in which a value j registered in an entry VLE(k) of VL of the corresponding index ranked with a value k stored in the entry VNoE(i) of VNo of the index is registered is additionally registered in VNo of the integrated index.

Abstract: The object of the present disclosure is to compress array data with an improved compression efficiency so that an arbitrary portion in the array data may be promptly restored. Array data VL is divided into a plurality of blocks, and an approximate function is set in each of the blocks. For each entry included in each block k, a difference dV_i between a value V_i of the entry and a value F_k(i) obtained by substituting a rank i of the entry into an approximate function F_k set in a block k in which the entry is included is obtained. Then, a difference list dVL_k of the block k is created by arranging differences dV_i in the order of ranks of entries for which the differences dV_i are obtained. Then, a set of the approximate function F_k of each block k and the difference list dVL_k is set as block data BLD_k of the block k, and a set of the block data BLD_k obtained for each block is set as compressed data of the array data.

Abstract: Unit conversion of data in a database is performed, so that efficient use of data can be achieved. VL and VNo in an index associated with each field of a table, define correspondence between a record number and a field value. In the n-th entry of VNo, a rank of the entry in VL is registered where the field value associated with the record having n-th record number in the table is registered. When the system of units of the value registered in VL is not a predetermined system of unit, VLC is provided, so as to apply unit conversion to the value in each entry of VL and to register the converted value in the entry on the same rank in VLC. Then, instead of VL, VCL and VNo define the correspondence between the record number and the field value.

Abstract: Unit conversion of data in a database is performed, so that efficient use of data can be achieved. VL and VNo in an index associated with each field of a table, define correspondence between a record number and a field value. In the n-th entry of VNo, a rank of the entry in VL is registered where the field value associated with the record having n-th record number in the table is registered. When the system of units of the value registered in VL is not a predetermined system of unit, VLC is provided, so as to apply unit conversion to the value in each entry of VL and to register the converted value in the entry on the same rank in VLC. Then, instead of VL, VCL and VNo define the correspondence between the record number and the field value.

Abstract: Row jumping is executed continuously at high speed, for sequentially presenting rows of records each having the same value being registered. Record numbers of a table are registered respectively in entries of SOS in an index, sorted by the values registered in the record, and data indicating a range of the entries in SOS is registered in ETRS, the range including record numbers of the records where the same value is registered. Rows of the record numbers where the value selected by a user is registered are determined as rows of target record numbers, referring to ETRS and SOS. Every time of forward jump operation, a row of the record number of the record to be presented is moved forward one row, among the rows of target record numbers.

Abstract: A logical operation among plural sets in large-scale data (big data) is performed efficiently. The sets targeted for the logical operation is classified into predetermined common segments, each with a size allocatable to a memory, and the logical operation is performed with respect to each segment on the memory. The common segment is configured in such a manner that all the records of the sets are classified without duplications. Then, a direct sum of results of the logical operation on the respective segments is calculated, thereby obtaining a result of the logical operation. The size of the common segment is determined so that the records being classified are loadable on the memory.

Abstract: An information processing system includes a plurality of PMM and data transmission paths for connection between the PMM and transmitting a value of a PMM to another PMM. A memory of each PMM holds a list of values of first items arranged in the ascending order or descending order without overlap and/or a list of values of the second item to be shared. A memory module of each PMM transmits a value contained in the value list to another PMM, receives a value contained in the value list from the another PMM, references the value list of the first item and the value list of the second item of the another PMM, and generates a list of common values considering the values contained in the value lists of the first item and the second item of all the other PMM.

Abstract: Large-scale table data stored in a shared memory are sorted by a plurality of processors in parallel. According to the present invention, the records subjected to processing are first divided for allocation to the plurality of processors. Then, each processor counts the numbers of local occurrences of the field value sequence numbers associated with the records to be processed. The numbers of local occurrences of the field value sequence numbers counted by each processor is then converted into global cumulative numbers, i.e., the cumulative numbers used in common by the plurality of processors. Finally, each processor utilizes the global cumulative numbers as pointers to rearrange the order of the allocated records.

Abstract: An ascending ordered list without duplication is generated based on a value list divided and held by multiple memory modules. An information processing system has multiple PMMs (Processor Memory Modules), and the PMMs are interconnected via a data transmission path. The memory in the PMM has a list of values, which are ordered in ascending or descending order without duplication. The PMM determines, for a storage value in the value list (LOCAL_LIST) held by the PMM, whether or not the memory module is a representative module representing one or more memory modules holding the storage value based on rankings determined for the individual PMMs and the value lists received from the other PMMs, and if the memory module is determined to be the representative module (RV-0 . . . RV-7), associates to the storage value and stores information indicating that the memory module is the representative module.

Abstract: A relationship among data in a tree data structure is effectively traced by assigning nodes respective unique node identifiers, a parent-child relationship is represented by a C->P array containing node identifiers for parent nodes associated with node identifiers for non-root nodes that are nodes other than a root node, a list of vertex nodes is provided by storing node identifiers for respective vertex nodes in order to represent one or more node groups, each node group including a particular node, which is the vertex node, and descendant nodes of the particular node, and the node identifier for the vertex node belonging to other vertex nodes are deleted from the list of vertex nodes by referring to the C->P array such that neither vertex nodes nor respective descendant nodes of the vertex nodes duplicate each other across vertex nodes identified by the node identifiers included in the list of vertex nodes.

Abstract: A searching method for tree data structure topology employs an array generated as a search key array representing a tree serving as search key to represent a parent-child relationship between nodes. The array has the node identifier assigned to a parent node associated with a corresponding non-root node. Non-root nodes are nodes other than a root node, and the node identifier assigned to the parent node corresponds to the node identifier assigned to associated non-root nodes. An offset is applied to node identifiers in the search key array, the node identifiers to which offset is applied are compared with corresponding node identifiers contained in a portion in a C-P array, the portion determined according to the offset, and a vertex node list indicating a search result is stored, wherein the search result contains node identifiers included in a portion of the C-P array whose all nodes matched in comparison.

Abstract: Large-scale table format data on a common memory is sorted in parallel by a plurality of processors. A record to be processed is divided and assigned at first to the processors. Next, each processor counts the number of local appearances of item value numbers related to the record to be processed. Next, the number of local appearances of the item value numbers counted at the processors is converted into the global accumulation of item value numbers, i.e., the accumulation to be commonly used between the processors. Finally, each processor utilizes the global accumulation as a pointer to change the order of the assigned records.

Abstract: Table-formatted data is divided into information blocks, each including a value list where item values are arranged in order of item value number corresponding to the item value of each item, and a pointer array where pointer values, each indicate an item value number, are arranged in order of unique record number. A part of records is selected as a subset, and in response to the selection, an ordered set array including the record numbers of the subset is created. Each record number in the ordered set array indicates the position of one of the pointer values in the pointer array, which are arranged in the item value number array correspondingly to positions where the record numbers are arrayed. With reference to values in the item value number array, a second pointer array wherein position elements are arranged, and a second value list wherein value elements are arranged, are generated.

Abstract: Large-scale table data stored in a shared memory are sorted by a plurality of processors in parallel. According to the present invention, the records subjected to processing are first divided for allocation to the plurality of processors. Then, each processor counts the numbers of local occurrences of the field value sequence numbers associated with the records to be processed. The numbers of local occurrences of the field value sequence numbers counted by each processor is then converted into global cumulative numbers, i.e., the cumulative numbers used in common by the plurality of processors. Finally, each processor utilizes the global cumulative numbers as pointers to rearrange the order of the allocated records.

Abstract: In parallel computers, sorting and calculation of large-scale data are realized while large-scale data is held in the respective processors without sharing the large-scale data between the processors so as to reduce communication between the processors. An information processing method gives global dimension value numbers common to all the processing modules to the dimension values for calculation, calculates measures for each of the dimension value numbers within the processing module, and lastly calculates measures commonly between all processing modules. The value list and pointer arrangement to the value list are locally held in each processing module and the order of the dimension values as a reference is globally held between processing modules. As a result, it is possible to eliminate mutual access by processing modules for acquiring data required for calculation and only data required for deciding the order of the dimension values is communicated between the processing modules.