Abstract: A database management apparatus receives the specification of an origin column, calculates a confidentiality level of a column in a different database from the database related to the origin column based on a confidentiality level of the origin column and a degree of similarity between contents of data in the origin column and contents of data in the column in the different database. A confidentiality level of the different database is calculated based on the calculated confidentiality level and a value indicating identifiability of the data in the column in the different database, and a confidentiality level of a column selected in the different database is calculated based on the confidentiality level of the different database and a value indicating identifiability of data in the selected column. The selected column is set as the new origin column, and the calculated confidentiality level is set as its confidentiality level.

Abstract: The storage system control method is implemented by a controller of a storage system. The method includes a step of storing data on a storage in a shared memory as cache data, a step of changing the cache data based on a writing request from outside, and a writeback step of writing back dirty cache data as the cache data which have been changed based on the writing request to the storage. The method further includes a step of storing the dirty cache data in a writeback processing memory prior to the writeback step. The writeback processing memory requires time for executing the writeback data process shorter than time required by the shared memory.

Abstract: The processor receives a query definition and converts the query definition to a query graph; generates query control information that determines an execution sequence of operators comprising the query graph; generates a calculation thread including buffers, and stored number information; and configures, a temporary storage area; wherein the processor executes a calculation thread; each time the processing for an operator is completed, the increase or decrease in tuples, which is inputted or outputted between the temporary storage area and the buffers, is stored in the stored number information for each tuple; after the processing of the last operator comprising the query graph in the calculation thread has been completed, the sum of the stored number information is computed for each tuple; tuples that have become unnecessary are identified on the basis of the sum and a threshold value; and the area of the identified tuples are recovered.

Abstract: An input tuple including a data time stamp is assigned by a data source; a pending tuple in which a system time stamp at the time the input tuple was received is assigned to the input tuple; and the pending tuple is stored in a queue, one queue for each data source. The queues are sorted in the order of the data time stamps of the pending tuples at the head of each queue; and if, in the queue at the head of which is stored the pending tuple having the smallest data time stamp value, the value of the current system time stamp is greater than the value of a processing pending period added to the system time stamp of the pending tuple at the head of the queue, then the input tuple is acquired from the pending tuple at the head of the queue for an input stream.

Abstract: A data processing apparatus generates by a stream processing control program, for a time-series first stream data group of stream data out of a time-series stream data sequence, first vector data including elements acquired by collecting respective pieces of stream data of the time-series first stream data group; generates, by the stream processing control program, for a time-series second stream data group including, as a head, a piece of intermediate stream data of the time-series first stream data group and having the same number of pieces of data as the time-series first stream data group, second vector data including elements acquired by collecting respective pieces of stream data of the time-series second stream data group; and inputs, by the stream processing control program, the first and second vector data generated respectively to a batch program to control the batch program to carry out a batch processing.

Abstract: A computer scale-out method by adding a second computer to a first computer receiving stream data from a data source and executing a query to make the second computer execute the query, the computer scale-out method including: receiving, by a management computer, a request to scale out; a second step of generating, by the management computer, rewritten queries that are copies of the query; sending, by the management computer, instructions to scale out including the rewritten queries to the first computer and the second computer; receiving, by the first computer and the second computer, the instructions to scale out, extracting the rewritten queries, and switching to the extracted rewritten queries; notifying, by the first computer or the second computer, the management computer of readiness of the rewritten queries; and sending, by the management computer, an instruction to add the second computer as a destination to the data source.

Abstract: A query parser that converts query definition into a query graph and decides the execution order of operators is installed, a set of consecutive operators in the execution order is called a stage, the total of calculation costs of operators configuring each stage is called a calculation cost of the stage, the query graph is divided into multiple stages such that the calculation cost of each stage becomes a value less than a value dividing the total cost of all operators by the number of calculation cores, and each calculation core extracts tuples one by one from an input stream, and, when taking charge of and executing processing of the tuples from the entrance to exit of the query graph, before the execution of each stage, confirms whether processing of the stage is completed for a tuple previous to a charge tuple.

Abstract: An input tuple including a data time stamp is assigned by a data source; a pending tuple in which a system time stamp at the time the input tuple was received is assigned to the input tuple; and the pending tuple is stored in a queue, one queue for each data source. The queues are sorted in the order of the data time stamps of the pending tuples at the head of each queue; and if, in the queue at the head of which is stored the pending tuple having the smallest data time stamp value, the value of the current system time stamp is greater than the value of a processing pending period added to the system time stamp of the pending tuple at the head of the queue, then the input tuple is acquired from the pending tuple at the head of the queue for an input stream.

Abstract: A network interface receives stream data and a processor processes the stream data. The processor: constructs an operator graph comprising information regarding a plurality of operators for processing the stream data based on a query; assigns an operator execution order to the plurality of operators based on an inter-operator input and output relation, with respect to all of the operators on the operator graph; extracts a set of the operators that maintains the stream data assigned with a time stamp, a time of which is earlier than or equal to a reference time, in an input queue; and executes processing of the stream data assigned with the time stamp, having the earliest time, in the operator assigned a minimum operator graph execution order among the operators and maintaining the stream data assigned with the time stamp having the earliest time, among the extracted set of the operators.

Abstract: A stream data processing server for processing stream data comprising a stream data processing module for cutting the plurality of pieces of data that are included within a processing range as a target out of the stream data by using a sliding window, and executing analyzing processing for the cut out plurality of pieces of data, the stream data processing module having an approximate expression; the approximate expression calculating module being configured to: determine one of the time stamps of the cut out plurality of pieces of data as a time origin; modify the time stamps of the cut out plurality of pieces of data to relative time values in relation to the determined time origin; and use the modified time stamps and the values of the plurality of pieces of data to calculate the approximate expression.

Abstract: Provided is a query generating method for generating a query which processes an inputted data stream with a computer provided with a processor and memory, said method comprising: a first step of the computer separating the inputted data stream into a required column and an optional column, and loading a template which defines a process with respect to the required column; and a second step of the computer separating the inputted data stream into a required column and an optional column, processing the required columns with the template, and generating a query which outputs the result of the processing of the template and the optional column as one instance of data.

Abstract: A data processing apparatus generates by a stream processing control program, for a time-series first stream data group of stream data out of a time-series stream data sequence, first vector data including elements acquired by collecting respective pieces of stream data of the time-series first stream data group; generates, by the stream processing control program, for a time-series second stream data group including, as a head, a piece of intermediate stream data of the time-series first stream data group and having the same number of pieces of data as the time-series first stream data group, second vector data including elements acquired by collecting respective pieces of stream data of the time-series second stream data group; and inputs, by the stream processing control program, the first and second vector data generated respectively to a batch program to control the batch program to carry out a batch processing.

Abstract: A query parser that converts query definition into a query graph and decides the execution order of operators is installed, a set of consecutive operators in the execution order is called a stage, the total of calculation costs of operators configuring each stage is called a calculation cost of the stage, the query graph is divided into multiple stages such that the calculation cost of each stage becomes a value less than a value dividing the total cost of all operators by the number of calculation cores, and each calculation core extracts tuples one by one from an input stream, and, when taking charge of and executing processing of the tuples from the entrance to exit of the query graph, before the execution of each stage, confirms whether processing of the stage is completed for a tuple previous to a charge tuple.

Abstract: When reproducing the running state after a failure has occurred in stream data processing, all window operations are used while minimizing the storage amount necessary for obtaining backup data. While an operator is performing stream data processing in response to a query, a query analysis unit analyzes the operator, which holds the running state of the window, etc., and the recovery points of said operator. When obtaining backup data, a backup data management unit manages the capacity necessary to obtain snapshots of the analyzed recovery points, calculates the storage area capacity needed for backing up input data up to each recovery point and the storage area capacity needed to obtain a snapshot for a window that cannot be reproduced in that way, and records the execution state by selecting a recovery point which minimizes the total value of necessary storage capacity.

Abstract: In a duplex configuration of stream data processing, all window operations can be used without stopping the process when adding a standby system. The time when the standby system server is added is stored as the reproduction time, and data copied from the data generated at or after the reproduction time is transmitted to the standby system. While the data processing in the in-use system is continued, changes in the execution state which occur in operators holding execution state at or after the reproduction time are recorded. The execution states are copied to the standby system for each operator in parallel with the data processing. At this time, the execution states of the operators at the reproduction time are reproduced from the execution states of the operators when the copy is performed and the record of the changes of the execution states, and the reproduced execution states are copied.

Abstract: A network interface receives stream data and a processor processes the stream data. The processor: constructs an operator graph comprising information regarding a plurality of operators for processing the stream data based on a query; assigns an operator execution order to the plurality of operators based on an inter-operator input and output relation, with respect to all of the operators on the operator graph; extracts a set of the operators that maintains the stream data assigned with a time stamp, a time of which is earlier than or equal to a reference time, in an input queue; and executes processing of the stream data assigned with the time stamp, having the earliest time, in the operator assigned a minimum operator graph execution order among the operators and maintaining the stream data assigned with the time stamp having the earliest time, among the extracted set of the operators.

Abstract: A network interface receives stream data and a processor processes the stream data. The processor: constructs an operator graph comprising information regarding a plurality of operators for processing the stream data based on a query; assigns an operator execution order to the plurality of operators based on an inter-operator input and output relation, with respect to all of the operators on the operator graph; extracts a set of the operators that maintains the stream data assigned with a time stamp, a time of which is earlier than or equal to a reference time, in an input queue; and executes processing of the stream data assigned with the time stamp, having the earliest time, in the operator assigned a minimum operator graph execution order among the operators and maintaining the stream data assigned with the time stamp having the earliest time, among the extracted set of the operators.

Abstract: A stream data processing server for processing stream data comprising a stream data processing module for cutting the plurality of pieces of data that are included within a processing range as a target out of the stream data by using a sliding window, and executing analyzing processing for the cut out plurality of pieces of data, the stream data processing module having an approximate expression; the approximate expression calculating module being configured to: determine one of the time stamps of the cut out plurality of pieces of data as a time origin; modify the time stamps of the cut out plurality of pieces of data to relative time values in relation to the determined time origin; and use the modified time stamps and the values of the plurality of pieces of data to calculate the approximate expression.

Abstract: Provided is a stream data processing device for processing stream data composed of input data that includes time, the device having: a data input module for receiving the input data; a first key for designating, as data sets, the items of the input data for processing the input data in chronological order; a query recorder for receiving a stream data definition and a query definition, and generating an operator to process the input data; and a data executing module for determining the operator for processing the input data and outputting results; the input module sorting the received input data for each of the data sets according to the item designated by the first key, sorting the input data in chronological order for each of the data sets, and generating an input stream; and the data executing module processing the input stream with the operator for each of the data sets.

Abstract: Provided is a stream data processing method cooperable with external data in real time. By providing a stream predict cache corresponding to a hierarchical cache of relation data predicted as being a data matching target with stream data, the number of accesses to a database is reduced to improve performance. Data to be stored in the stream predict cache is determined based on a characteristic of the stream data input by a user or monitoring information obtained by monitoring the stream data.