Hitachi, Ltd.

The University of Tokyo

Kazuhiko Mogi

Norifumi Nishikawa

Masaru Kitsuregawa

Hideomi Idei

Nobuo Kawamura

Kazuo Goda

Takashi Oeda

Yoshiaki Eguchi

Shinji Fujiwara

Akira Shimizu

Kouji Arai

Yuto Hayamizu

Yasutomo Yamamoto

Hiroshi Arakawa

Seisuke Tokuda

Naokazu Nemoto

Michiko Yoshida

Toyohiro Nomoto

Yuya Isoda

Mayuko Ozawa

Yoshiki Kurokawa

Kouji Kimura

Satoru Watanabe

Tomohiro Hanai

Yasunori Kaneda

Manabu Kitamura

Yoshiki Kano

Hiroyuki Yamada

Takao Satoh

Katsunori Nakamura

Kyosuke Achiwa

Toshihiko Kashiyama

Michiko Tanaka

Takayuki Tsuchida

Makoto Ootahara

Norifuml Nishikawa

Kaokazu Nemoto

Masashi Toyoda

A data processing apparatus has a memory and a first storage apparatus and reads a data area from a second storage apparatus (a storage apparatus which is slower than the first storage apparatus and stores a plurality of data areas as data constituent elements). Regarding each processing block, the data processing apparatus determines whether an open/closed area for processing of a first processing block which is the processing block should be an entire area or a partial area of the data area, based on whether or not the data area which is input and/or output by the processing of the first processing block can also be accessed by processing of a second processing block which is a processing block other than the first processing block, and whether or not the second processing block is being executed.

Data processing apparatus and data processing method

An update method in which a computer updates data stored in a first storage device by copying a plurality of files stored in the first storage device to a second storage device and writing the files updated in the second storage device back to the first storage device, the plurality of files constituting a part of a database. The update method includes a query determination for determining whether a query for requesting writing to one of the files stored in the second storage device is based on a cluster key of the database, low-frequency file identification for identifying a file having a low writing frequency among the files stored in the second storage device, and write-back for writing the file having the low writing frequency identified in the low-frequency file identification to the first storage device.

Update method and database update apparatus

The scanning range of an inner table can be limited in the join processing irrespective of the existence of search conditions or a partition key, and the performance of the join processing can be improved. There is a column range index representing a range of values stored in a table. When a join result of a current stage is an outer table related to a join of a next stage in a join of each stage of the join processing, a database management apparatus identifies whether there is a possibility that an inner table related to a join of a next stage includes a hit record in an inner table related to a join of a current stage based on a column range index corresponding to a join column of a current stage and a column range index corresponding to a join column of a next stage.

Database management apparatus and method

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.

Storage system and data cache method

A database is stored in a plurality of pages that are a plurality of logical storage areas constituting a logical storage space. Data writing to a database in the logical storage space is performed in a page unit. A storage control apparatus coupled to an external storage and including a cache device writes data to the cache device in a page unit. The storage control apparatus determines whether an execution condition on external writing that is writing to the external storage is satisfied. When a result of the determination is true, the storage control apparatus writes data stored in the cache device to the external storage in a bulk unit that is larger than a page unit and is a writing unit in which consistency is maintained.

Storage control apparatus and method for a database storing data in pages

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.

Computer system and query processing method

A storage control apparatus generates an evaluated compression dictionary from a compression dictionary. The compression dictionary includes, for each of different values included in original data of compressed data, a value and a compression code. The evaluated compression dictionary includes, for each value in the compression dictionary, a value and a compression code. The compressed data includes a compression code for each value in the original data. The storage control apparatus performs, in generation or update of the evaluated compression dictionary, condition evaluation of the value. A compression code of a value determined to correspond to the search condition in the condition evaluation is a condition satisfied code. The storage control apparatus is configured to, in the search, for a compression code in the search range of the compressed data: output, when there is an evaluation dictionary record including a condition satisfied code matching the compression code, a value in the evaluation dictionary record; and output, when there is no evaluation dictionary record including a condition satisfied code matching the compression code, a value that means inconsistency.

Storage control apparatus and method

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.

Database system and query execution method

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.

Database management system and database processing method

A database management system (DBMS) generates a query execution plan including information representing one or more database (DB) operations necessary for executing a query and executes the query based on the query execution plan. In the execution of the query, the DBMS dynamically generates a task for executing a DB operation and executes the dynamically generated task. The DBMS executes a task in a plurality of threads executed by a processor core.

Database management system, computer, and database management method

When a DBMS receives a suspend instruction in which a suspend completion time of query processing is a future time and between receipt of the suspend instruction and the suspend completion time, if there is a target object (at least a processing object whose execution is in progress upon receipt of the suspend instruction) whose predicted completion time is at or precedes the suspend completion time, the DBMS changes the state of the target object to a state signifying a snapshot suspend. If there is a processing object whose state signifies a snapshot suspend, the DBMS executes the processing object at or before the suspend completion time.

Database management system and database management method

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. Each shared log buffer is a log buffer that can store two or more logs associated with two or more threads.

Computer system and database management method

There is provided a database management system (DBMS) in order to make anonymization processing of the database efficient. When receiving a query including a conversion rule, the database management system is configured to process a relationship table in the database based on the conversion rule. At that time, the DBMS is configured to acquire data from a processing result table (result of processing the relationship table) stored in the past for tuples the number of which for each value appearing in a predetermined attribute satisfies a condition required for the anonymization processing. On the other hand, for tuples the number of which for each value appearing in a predetermined attribute does not satisfy the condition required for the anonymization processing, the DBMS is configured to acquire data from the database or from a result of processing the relationship table, the result being stored in rather than the processing result table.

Database management system and anonymization processing method

If a query indicates joining of N (N is an integer of no less than 3) relation tables, a database management system calculates a query cost that is based on a power consumption amount for query execution, for each of a first query plan candidate in which a temporary table is generated and the temporary table is stored in a storage device unit with a first access cost, a second query plan candidate in which a temporary table is generated and the temporary table is stored in a storage device unit with a second access cost that is higher than the first access cost and a third query plan candidate in which the N relation tables are joined in a pipelined manner without generation of a temporary table, selects a relatively low-query cost query plan candidate and executes the query based on the query plan candidate.

Database management system and method

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.

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Yokohama, Japan

Kazuhiko Mogi