Abstract: A data layout model generation system generates, with reinforcement learning, a node configuration and a data layout key in a distributed parallel database. This system includes a sample acquisition processor that acquires, on the basis of a predetermined acquisition method, sample data from data stored in the distributed parallel database, a data layout estimator having, as states in the reinforcement learning, the node configuration and the data layout key including information regarding an order of sorting columns that constitute the data and information regarding a method for distribution between nodes, the data layout estimator estimating layout of the data on the basis of the state and the sample data, a reward calculator that calculates a reward in the reinforcement learning on the basis of a result obtained by estimating the layout of the data, the node configuration, and a processing cost of a query executed on the distributed parallel database.

Abstract: The processing load for joining a plurality of tables by hash join is reduced for a computer system in which the CPU of a node creates a partial bloom filter that manages a first table hash value of a joining key of a row corresponding to a query in an assigned row of a build table. An integrated bloom filter is created from a plurality of partial bloom filters, and a second table hash value of the joining key of the row corresponding to the condition of the query among the rows of a probe table is calculated. The row of the probe table is transmitted to the node containing a row of the build table of the join hash value for that row when the integrated bloom filter includes an identical first table hash value, and an integrated joined table is created and returned to the query request source.

Abstract: A database management system identifies a required column which is required for executing the query, reads out data of the identified required column from a storage device, and executes the query based on the data of the required column. When reading out the data of the required column, the database management system preferentially reads out the data of the required column from a high-speed storage device storing the data of the required column among a memory, a second storage, and a first storage, stores, in the memory, data of the second data size unit including the data of the required column used for executing the query, and, when the data of the required column is read out from the first storage, stores the data of the second data size unit in the memory and stores the read-out data of the first data size unit in the second storage.

Abstract: A database system includes a plurality of DBMSs included in a plurality of nodes. Each DBMS is a first or a second DBMS. The first DBMS transfers a search query and does not execute data retrieval, and the second DBMS executes data retrieval. The plurality of nodes configure one or more node groups. Each node group includes a first node and one or more second nodes. In each node group, the first node is a logical computer that provides a first storage area and executes a first DBMS and the second node is a logical computer that provides a second storage area and executes a second DBMS, each node in the node group stores the same database therein, and data retrieval from the database in the node group is executed by one or more second DBMSs in the node group.

Abstract: The data management device includes a determination unit that determines whether the secondary data generated from the source data to be processed complies with the data handling rules that use statistical information and a data processing unit that performs the processing a determination result by the determination unit. The determination unit estimates the statistical information from the source data to be processed, and determines whether the data handling rule is complied with, prior to the generation of the secondary data, based on whether the secondary data generated based on the estimated statistical information satisfies the statistical values of the statistical information. The data processing unit executes processing when it is determined that the data handling rules are complied with to generate secondary data and does not perform the processing process when it is determined that the data handling rules are not complied with.

Abstract: A data layout model generation system generates, with reinforcement learning, a node configuration and a data layout key in a distributed parallel database. This system includes a sample acquisition processor that acquires, on the basis of a predetermined acquisition method, sample data from data stored in the distributed parallel database, a data layout estimator having, as states in the reinforcement learning, the node configuration and the data layout key including information regarding an order of sorting columns that constitute the data and information regarding a method for distribution between nodes, the data layout estimator estimating layout of the data on the basis of the state and the sample data, a reward calculator that calculates a reward in the reinforcement learning on the basis of a result obtained by estimating the layout of the data, the node configuration, and a processing cost of a query executed on the distributed parallel database.

Abstract: Provided is a data processing assistant system, a data processing assistant method, and a data processing assistant program. The data processing assistant system includes: a processing record accumulation unit that accumulates processing records in which one or more pieces of data, data processing performed using the data, and a processing result of the data processing are associated with each other; a correspondence relation data creation unit that creates, based on the processing records, correspondence relation data indicative of a correspondence relation among a data type indicating a type of the data, a question to be solved by the data processing, and the processing result; and a processing information presentation unit that presents, upon receiving designation of the data type and the question, information related to appropriate data processing based on the correspondence relation data.

Abstract: The data management device includes a determination unit that determines whether the secondary data generated from the source data to be processed complies with the data handling rules that use statistical information and a data processing unit that performs the processing a determination result by the determination unit. The determination unit estimates the statistical information from the source data to be processed, and determines whether the data handling rule is complied with, prior to the generation of the secondary data, based on whether the secondary data generated based on the estimated statistical information satisfies the statistical values of the statistical information. The data processing unit executes processing when it is determined that the data handling rules are complied with to generate secondary data and does not perform the processing process when it is determined that the data handling rules are not complied with.

Abstract: A computer system according to the present invention has a plurality of processor cores that execute a plurality of threads in a parallel manner. When one of the threads updates a database (DB) region that is among a plurality of database regions associated with a database (DB), and that cannot be updated by more than one thread, the computer system selects one of one or more dedicated log buffers as a log buffer to which a log relating to the update of the database region is to be written. In contrast, when one of the threads updates a database region that is among the plurality of database regions, and that can be updated by more than one thread, the computer system selects one of one or more shared log buffers as a log buffer to which a log relating to the update of the database region is to be written. Each dedicated log buffer is a log buffer that can store one or more logs associated with only one thread and that cannot store two or more logs associate with two or more threads.

Abstract: A database system includes a plurality of DBMSs included in a plurality of nodes. Each DBMS is a first or a second DBMS. The first DBMS transfers a search query and does not execute data retrieval, and the second DBMS executes data retrieval. The plurality of nodes configure one or more node groups. Each node group includes a first node and one or more second nodes. In each node group, the first node is a logical computer that provides a first storage area and executes a first DBMS and the second node is a logical computer that provides a second storage area and executes a second DBMS, each node in the node group stores the same database therein, and data retrieval from the database in the node group is executed by one or more second DBMSs in the node group.

Abstract: To support an efficient data search. A data processing device comprises a processor, and additionally comprises, as processing units which run on the processor, a generation unit which generates a generated search condition, which is a new search condition, based on a designated search condition, which is a given search condition, an estimation unit which estimates, for each search condition, a number of results of a search conducted based on the designated search condition and the generated search condition by using statistical information of a database to be searched, an evaluation unit which evaluates the generated search condition, and an output unit which outputs a number of estimated results of the designated search condition, and additionally outputs the generated search condition and a number of estimated results and an evaluation result of the generated search condition.

Abstract: A monitoring apparatus is coupled to a sensor configured to observe a behavior of a monitoring target, and is accessible a storage device being configured to store: a database stored a phenomenon data group; stability information; and operation history information. The monitoring apparatus is configured to: calculate a stability of input phenomenon data; determine whether the stability of the input phenomenon data is a stability indicating a specific behavior; retrieve from the database, when the stability of the input phenomenon data is a stability, similar phenomenon data that is similar to the input phenomenon data; generate, by acquiring from the stability information a stability of subsequent phenomenon data continuous with the similar phenomenon data, similar case data combining the similar phenomenon data and the subsequent phenomenon data; identify, from the operation history information, operation content; and output the similar case data and the operation content.

Abstract: The database management system (DBMS) receives a first instruction specifying anonymization rule information corresponding to a column of the relation table, among anonymization rule information that is present for each column included in the relation table and shows a plurality of generalization rules. The DBMS reads the column from the relation table in response to the first instruction, and generates a temporary result obtained by generalizing each attribute value of the column based on any of a plurality of generalization rules. The DBMS generates an aggregate result obtained by aggregating the temporary result. The DBMS generates an anonymization method including generalization information indicating a correspondence relationship of each attribute value of the column and any of the plurality of generalization rules when the aggregate result satisfies a disclosure rule. The DBMS generates anonymization information as a result of processing the relation table based on the first anonymization method.

Abstract: As an I/O method of issuing an I/O request, there are a synchronous I/O method, in which a task is in a waiting state until an I/O response to the I/O request is returned and an asynchronous I/O method, in which another task can be executed before an I/O response to the I/O request is returned. When issuing an I/O request in execution of a task, a DBMS selects any one of the synchronous I/O method and the asynchronous I/O method, based on an I/O response speed of an I/O destination storage device and issues an I/O request according to the selected I/O method.

Abstract: A shared resource update apparatus includes: a processor unit including at least one processor having a plurality of processor cores that respectively execute a plurality of threads; and a storage unit storing a program that executes conflict avoidance control by being executed by the processor unit. A shared resource for the plurality of threads comprises a plurality of shared resource parts which are logically or physically partitioned. Each first thread among the plurality of threads is an update thread which updates an allocated shared resource part in response to an update request. Each second thread among the plurality of threads is a reference thread which issues an update request and references a shared resource part. Conflict avoidance control includes allocation of different shared resource parts to different update threads at a ratio of 1:n or 1:1, where n is an integer equal to or larger than 2.

Abstract: Example implementations described herein are directed to detection of historical anomalous events that are similar to currently occurring events in a transmission power system based on phasor management unit (PMU) data to provide information to grid operators with online decision support. From the high-resolution time synchronized PMU data, the historical events can be quickly retrieved and compared to the currently occurring event so that operators can be provided with remedy actions that were attempted in response to the historical events. Utilization of PMU information for such decision support may compliment operation practices relying on supervisory control and data acquisition (SCADA) measurements by allowing a much fast response to the currently occurring event. Accurate identification of similar, historical events can advise grid operators of the cause of disturbances and provide ideas for response.

Abstract: There is a storage apparatus which provides a storage area, comprises a cache memory, reads data into the cache memory from the storage area according to a read request and sends the data from the cache memory, and a computer is coupled to the storage apparatus. The computer receives a data processing request, determines an access usage based on the data processing request (or, the information relating to an access usage of the data processing request), selects a logical device corresponding to the determined access usage from a plurality of logical devices which are allocated to the storage area and issues a read request to the selected logical device.

Abstract: Example implementations described herein are directed to detection of historical anomalous events that are similar to currently occurring events in a transmission power system based on phasor management unit (PMU) data to provide information to grid operators with online decision support. From the high-resolution time synchronized PMU data, the historical events can be quickly retrieved and compared to the currently occurring event so that operators can be provided with remedy actions that were attempted in response to the historical events. Utilization of PMU information for such decision support may compliment operation practices relying on supervisory control and data acquisition (SCADA) measurements by allowing a much fast response to the currently occurring event. Accurate identification of similar, historical events can advise grid operators of the cause of disturbances and provide ideas for response.

Abstract: Example implementations described herein are directed to detecting similarity between anomalous events that are currently occurring or have previously occurred transmission power system based on phasor management unit (PMU) data to provide information to grid operators with online decision support. From the high-resolution time synchronized PMU data, the events can be quickly retrieved and compared so that operators can be provided with remedy actions that were attempted in response to the previous events. Utilization of PMU information for such decision support may compliment operation practices relying on supervisory control and data acquisition (SCADA) measurements by allowing a much fast response to the currently occurring event. Accurate identification of similar, historical events can advise grid operators of the cause of disturbances and provide ideas for response. Implementations of the proposed technology may improve the resilience and reliability of the transmission power systems.

Abstract: A database management system generates an execution plan by performing the following (A) and (B): (A) processing of dividing a provisional execution plan that is an access path into one or more query processing blocks that are each a simultaneously executable processing range, the access path being specified on the basis of a received query and indicating an execution order of database operation; and (B) processing of determining, for each of the one or more query processing blocks, whether an execution cost decreases by changing an inner configuration of the query processing block on the basis of at least one of a processing time, performance, and the number of storage devices for one or more processing in the query processing block, and changing the inner configuration of the query processing block when a determination result is true.