WO2015189970A1 - Information processing device and data processing method therefor - Google Patents

Information processing device and data processing method therefor Download PDF

Info

Publication number
WO2015189970A1
WO2015189970A1 PCT/JP2014/065671 JP2014065671W WO2015189970A1 WO 2015189970 A1 WO2015189970 A1 WO 2015189970A1 JP 2014065671 W JP2014065671 W JP 2014065671W WO 2015189970 A1 WO2015189970 A1 WO 2015189970A1
Authority
WO
WIPO (PCT)
Prior art keywords
data
update
database
hierarchy
unit
Prior art date
Application number
PCT/JP2014/065671
Other languages
French (fr)
Japanese (ja)
Inventor
義文 藤川
本村 哲朗
忠幸 松村
Original Assignee
株式会社日立製作所
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 株式会社日立製作所 filed Critical 株式会社日立製作所
Priority to PCT/JP2014/065671 priority Critical patent/WO2015189970A1/en
Publication of WO2015189970A1 publication Critical patent/WO2015189970A1/en

Links

Images

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F12/00Accessing, addressing or allocating within memory systems or architectures
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q40/00Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • G06Q40/04Exchange, e.g. stocks, commodities, derivatives or currency exchange

Abstract

Conventionally, since consideration has only been given to speeding up heap structures, there has been a problem that in continuous session processing, for example, there has not been a sufficient mechanism for parallel operation of execution assessment processing and heap processing. By providing a maximum priority data decision signal from a database update unit to a database update assessment unit, outputting the fact that a decision has been made at the moment when the maximum priority data is decided during database update processing, and carrying out database update assessment processing using the maximum priority data, the present invention makes it possible to operate the database update unit and database update assessment unit in parallel and improve processing speed.

Description

Information processing apparatus and data processing method thereof

The present invention relates to an information processing device that performs processing of a storage device that stores binary tree structure information, and in particular, operation contents of information in the storage device based on top priority information and input information in the stored information. The present invention relates to an information processing apparatus for determining

In stock trading, while the market is open, contract processing is performed by a method called Zaraba processing. In this process, an order that has not been filled in a past order is called a board. The boards are prioritized. In the sell order, an order with a lower price is given priority, and with the same price, the order with the first order is given priority. In the buy order, an order with a higher price is given priority, and with the same price, the order that has been placed first is given priority. When there is a new sell order, the price is compared with the price of the highest priority board in the buy order board, and the contract is executed when the sell order price is low, and the highest priority board is deleted. If not, the sell order is stored as a board. Similarly, if there is a new buy order, the price is compared with the price of the top priority board in the sell order board, and if the buy order price is high, it is executed, and the top priority board is deleted. The If not, the buy order is stored as a board.

As described above, in the mule processing, the plates are always sorted in the priority order, and the highest priority plate is deleted or a new plate is added while referring to the highest priority information.

In recent years, automatic trading orders using machines called algorithm trades are sometimes made, and the number of orders processed per unit time has increased dramatically. Therefore, it is necessary to increase the speed of the zaraba process. In order to speed up the execution of the contract determination, it is necessary to speed up the plate sorting process.

As a method for speeding up the sorting process, there is a method of using one heap structure of a binary tree structure shown in Non-Patent Document 1. Based on this method, there are apparatuses described in Patent Document 1 and Patent Document 2 as apparatuses that execute addition / deletion of data at high speed.

As shown in FIG. 7, the heap structure has one top priority data node in the first layer. Each node is associated with at most two nodes in the next lower hierarchy. The second hierarchy has up to two nodes, and the third hierarchy has up to four nodes. Each node is assigned an address in order from 1. As shown in FIG. 8, when the address of the upper node 81 is A, the addresses of the lower nodes 82 and 83 are (2A) and (2A + 1). The upper node always has higher priority than the lower two nodes. There is no ordering between the two lower nodes.

In Non-Patent Document 1 and Patent Document 2, valid nodes always occupy consecutive address nodes starting from 1. On the other hand, Patent Document 1 does not always use nodes having consecutive addresses. Since the effective number of nodes below the lower hierarchy is different on the left and right, the difference between the effective numbers is stored and managed in each node.

In Patent Document 2, in order to perform the processing of each layer that was sequentially processed in Non-Patent Document 1, at each node, whichever has the higher priority is stored in each of the two nodes below. To increase the speed.

Japanese Patent No. 3905221 Japanese Patent No. 4391464

J. W. J. Williams, "ALGORITHM 232 HEAPSORT", Communications of the ACM, Volume 7, Number 6, pp347--348, June, 1964.

Patent Document 1 and Patent Document 2 describe only the speedup of the heap structure, and node addition and deletion are treated as independent events. On the other hand, in the Zaraba process, a contract determination is made based on the conditions of the past highest priority data and new input data, and then an operation to delete or add a heap is determined. Due to this difference, there is a problem that the mechanism for the parallel operation of the contract determination process and the heap process is not sufficient.

In order to solve the above problems, the present invention provides:
In an information processing apparatus including a database that manages data in order of priority,
A database update unit for performing update of data addition or deletion in the database;
A database update determination unit that instructs the database update unit to update the data to the database;
From the database update unit to the database update determination unit, a notification of finalization of the highest priority data and the highest priority data are output,
A database update instruction and update data are output from the database update determination unit to the database update unit,
The database update determination unit
When receiving the confirmation notification of the highest priority data and the highest priority data, an update determination process is executed,
The database update unit
Updating the database based on the database update instruction and the update data;
When the highest priority data is confirmed, the confirmation notification of the highest priority data is output,
Data updating other than the highest priority data is sequentially executed.

Since the database update unit and the database update determination unit can operate in parallel, the processing speed of the entire system is improved several to ten times as compared with the case where the database update unit and the database update determination unit do not operate in parallel.

1 is a diagram illustrating a stream data processing apparatus according to a first embodiment. FIG. 10 is a diagram illustrating an example of a system according to a third embodiment. The figure which shows the Zaraba processing apparatus which can process the multiple brands of Example 3. FIG. 10 is a diagram illustrating a zaraba processing apparatus that processes one brand according to the third embodiment. The figure which shows the database update part and database of Example 1. FIG. The figure which shows the database update part and database of Example 2. FIG. The figure which shows a heap structure. The figure which shows the relationship between the nodes of a heap structure. The figure which shows the process of the pipeline stage which performs the addition process to a heap structure. The figure which shows the address of a series of nodes referred when performing an additional process. The figure which shows the address of a series of nodes referred when adding the 13th node. The figure which shows the start operation | movement of a deletion process when the addition process is not performed in the pipeline. The figure which shows the process of the pipeline stage which performs a deletion process. The figure which shows the start operation | movement of a deletion process in case the addition process is performed in the pipeline.

FIG. 1 shows a stream data processing apparatus using the present invention. The database 15 is a device that stores data managed in order of priority. The database update unit 14 is a device that updates the database 15 according to an instruction from the output calculation and database update determination unit 12. The data receiving unit 11 is a device that receives data. The output calculation and database update determination unit 12 is a unit that determines the operation of the database using the data received from the data reception unit 11 and the highest priority data received from the database update unit 14. The result output unit 13 is a device that outputs the result calculated by the output calculation and database update determination unit 12. The highest priority data determination signal 16 and the highest priority data signal 17 are connected from the database update unit 14 to the output calculation and database update determination unit 12. A data update instruction signal 18 and an additional update data signal 19 are connected from the output calculation and database update determination unit 12 to the database update unit 14.

The database operations include deleting the highest priority data, adding new data, and changing the highest priority data. Here, the change of the highest priority data does not change the priority but updates the attached information, and does not change the entire database. In the following, the change of the highest priority data is merely a change of one node, and the method is obvious and will be omitted.

If the database 15 has a configuration in which the highest priority data is first and the second priority data follows, there is no need to stick to the heap structure. In addition, when updating, the database updating unit 14 first determines the highest priority data first, and then updates the second priority data and thereafter. There is a heap structure as the lightest operation. In addition, it is possible to consider a structure that is linearly arranged in order of priority. Below, it demonstrates using a heap structure.

When the highest priority data has been confirmed, that is, when the operation in the first layer update unit 1401 (FIG. 5) is completed, the database update unit 14 outputs the highest priority data confirmation signal 16 and at the same time, The priority data is output using the highest priority data signal 17. When receiving the highest priority data confirmation signal 16, the output calculation and database update determination unit 12 uses the data of the highest priority data signal 17 and the data from the data reception unit 11 to calculate the data to be output and to operate the database. The data update instruction signal 18 and the additional update data signal 19 are output.

Upon receiving the data update instruction signal 18 and the additional update data signal 19, the database update unit 14 first determines the highest priority data. Then, the highest priority data determination signal 16 and the highest priority data signal 17 are output. Thereafter, the data after the highest priority data is sequentially updated. When this update processing is pipeline processing, there are cases where the update by the previous update instruction signal and the update by the new update instruction signal are performed simultaneously.

Next, a specific embodiment of the data update unit will be described with reference to FIG. The database 15 is divided into each storage element from the first layer storage element 1501 to the nth layer storage element 1505 for each layer of the heap structure. Corresponding to this, the database update unit 14 is also divided into a change unit of each layer of the first layer update unit 1401 to the nth layer update unit 1405, and together with this, the all layer control unit 1400 controls all layers. It is made up. Thus, a pipeline for each layer is configured in order from the first layer. The update unit of each layer includes an operation mode register 14011, an additional data register 14012, an operation target address register 14013, and a final storage address register 14014. The all-layer control unit 1400 includes an all valid node number register 14001 and a stored node number register 14002. The total valid node number register 14001 manages the total number of node data already stored in the database and node data that has not yet been stored and exists in the first layer update unit 1401 to the nth layer update unit 1405. The stored node number register 14002 manages the node having the largest address among the nodes stored in the database 15.

At the time of the addition operation, the total valid node number register 14001 is incremented by 1, the operation mode register 14011 of the first layer update unit 1401 is set to the addition mode, the data to be added is stored in the additional data register 1402, and the operation target address register 14013 Is set to 1, the value of the total valid node number register 14001 is stored in the final storage address register 14014, and the pipeline is started.

The operation in each layer at the time of addition will be described with reference to FIG. If the value of the operation target address register 913 is the same as the value of the final storage address register 914, the data of the additional data register 912 is stored in the target node 920 indicated by the operation target address register 913, and the stored node number register 14002. Is incremented by 1, and the pipeline operation is terminated. If the value of the operation target address register 913 is smaller than the value of the final storage address register 914, the data of the target node 920 indicated by the operation target address register 913 and the data of the additional data register 912 are compared, and the priority is high. One of the data is stored in the target node 920, and the one with the lower priority is stored in the additional data register 912. Then, the operation target address register 913 is updated as shown below, the registers 911 to 914 are stored in the registers of the next stage, and the pipeline is advanced. As shown in FIG. 10, the operation target address register 913 sequentially updates in accordance with each layer. Here, “[X]” is a Gaussian symbol indicating the maximum integer not exceeding X. FIG. 11 shows values in each layer of the operation target address register 913, taking the case where the value of the final storage address register 914 is 13, for example.

The operation at the start of the delete operation is divided into two cases depending on the state of the entire pipeline at the start of the delete pipeline. If there is no additional layer in the pipeline, as in Non-Patent Document 1, the data of the first layer is deleted (invalidated), and the value of the node with the highest address among the stored valid nodes Is used as the data of the first layer. That is, as shown in FIG. 12, the data 1506 indicated by the stored node number register 14002 is read and set in the additional data register 14012 in the first layer. The operation mode register 14011 is set to the delete mode, and the operation target address register 14013 is set to 1. Then, the values of the stored node number register 14002 and the total valid node number register 14001 are decreased by one. Then, the operations of the following pipeline layers are performed.

The operation in each layer at the time of deletion will be described with reference to FIG. The values of the two child nodes 930 and 931 derived from the value of the operation target register 913 are compared. Next, the data with the higher priority compared with the value of the additional data register 912 is compared. As a result, the data with the higher priority is stored in the target node 920 indicated by the operation target register 913. At this time, when the value of the additional data register 912 is stored in the target node 920, the deletion operation pipeline is terminated.

If the value stored in the target node 920 is either the child node 930 or the child node 931, the value of the operation target address register 913 is updated to the address value of the stored child node 930 or child node 931. To move to the next layer.

At the start of the delete operation, if there is a layer performing an add operation in the pipeline, it will be described with reference to FIG. Of the additional operation layers, the additional data 14062 at the shallowest layer is set in the additional data register 14012 of the first layer instead of the final data, and the pipeline operation of the layer that was performing the additional operation is stopped. The operation mode register 14011 is set to the delete mode, and the operation target address register 14013 is set to 1. Then, the value of the total valid node number register 14001 is decreased by one. The stored node number register 14002 is not changed. And the operation | movement in each layer at the time of deletion shown above is performed.
In this embodiment, when the node of the first hierarchy is determined, the highest priority data determination signal and the highest priority data signal are output from the database update unit 14 to the output calculation and database update determination unit 12, and the output calculation unit and A data update instruction signal and an additional update data signal are output from the database update determination unit 12 to the database update unit 14. Therefore, since the database update unit 14 and the output calculation and database update determination unit 12 can operate the processes in parallel, the processing speed of the entire system can be increased.
In addition, the above-described pipeline operation allows heap structure update operations that allow each operation to overlap without sacrificing speed. As a result, it is possible to update the heap structure database with a high processing speed.

Further, Patent Document 1 and Patent Document 2 require an additional storage element at each node for speeding up. There are cases where the number of plates for the zaraba processing is tens of thousands to several millions, and there is a problem that the cost of the additional storage element is increased. On the other hand, in the present embodiment, since the storage element is provided for each heap hierarchy, the number of storage elements can be reduced as compared with the conventional technique provided for each node.
In the present embodiment, in order to improve the processing of the heap structure without requiring an additional storage element, a pipeline is formed for each layer of the heap structure. When there is no additional processing on the pipeline when deleting the highest priority data, the data of the node with the highest address is extracted from the valid nodes as in Non-Patent Document 1 and Patent Document 2, and the data Then, the nodes are compared and exchanged in order with the nodes in the second layer and below. When deleting the highest-priority data, if there is an additional process on the pipeline, the process is interrupted, and the data to be added is used in place of the data of the node with the highest address. It is possible to compare and exchange with nodes below the layer in order.

FIG. 6 shows a memory element in the lower layer in FIG. 5 as a cache 621 and a double-data-rate SDRAM (hereinafter referred to as DDR S).
DRAM) 623). In this case, although the update of the lower layer is slightly delayed, it is effective when dealing with an enormous number of nodes in which all the nodes cannot be mounted in a Field Programmable Gate Array (hereinafter referred to as FPGA). Depending on the timing of the add operation and the delete operation, the add operation may be stopped halfway, thereby reducing access to the DDR SDRAM 623. Thereby, processing can be performed without sacrificing the processing speed.

FIG. 2 is a diagram showing the entire zalaba processing system using the present invention. The present invention is implemented in the FPGA 26 of FIG. Input of order data and execution results are input / output through the NIC 25. Some specific brands with a large number of orders are processed using the FPGA 26 and the DDR SDRAM 27, and other brands are processed using the CPU 21, the DDR SDRAM 22, the I / F 23 and the Storage 24.

Fig. 3 shows a functional block diagram of this mule processing unit. An order input through the NIC 25 is received by the new order receiving unit 30, and uses a brand-specific process sorting unit 31 and a specific brand register 32 to sort the processing destination for each brand. The specific brands are processed by the specific brand contract processing system indicated by 100, 101, and 102, and the other brands are processed by the other brand contract processing system 103. The processing results are collected in the contract result output unit 33 and output through the NIC 25.

3 is processed using 20, 21, 22, 23 and 24 of FIG. 100, 101, and 102 in FIG. 3 are implemented in the FPGA 26 in FIG.

FIG. 4 shows the internal structure of the specific brand 1 contract processing system 100. The specific brand order receiving unit 110 in FIG. 4 corresponds to the data receiving unit 11 in FIG. 4 is equivalent to the output calculation and database update determination unit 12 in FIG. The specific brand execution result output unit 130 in FIG. 4 corresponds to the result output unit 13 in FIG. The selling plate information update unit 140 and the selling plate information database 150 in FIG. 4 correspond to the database update unit 14 and the database 15 in FIG. Similarly, the buying plate information updating unit 141 and the buying plate information database 151 in FIG. 4 correspond to the database updating unit 14 and the database 15 in FIG.

That is, the specific brand 1 contract processing system 100 has two databases. When a new order is received, the specific brand execution determination and board information update determination unit 120 selectively uses the two databases depending on whether the new order is a sell order or a buy order.

If the new order is a sell order, the contract is judged using the highest priority data of the buying board information. If the contract is made, the highest priority board is deleted from the buying board information database 151. If not, the new order is added to the sales board information database 150 as a board.

Conversely, if the new order is a buy order, the contract is judged using the highest priority data in the sales board information. If the contract is made, the top priority board is deleted from the sales board information database 150. If not, the new order is added as a board to the buying board information database 151.

The signal line between the specific brand execution determination and board information update determination unit 120, the selling board information update unit 140, and the buying board information update unit 141 in FIG. 4 is the output calculation and database update determination unit 12 and database update unit in FIG. 14, there are two sets of the highest priority data determination signal 16, the highest priority data signal 17, the data update instruction signal 18, and the additional update data signal 19, and these signals operate the contract determination and the database update in parallel. This makes it possible to execute the contract determination process at high speed.

DESCRIPTION OF SYMBOLS 10 ... Stream data processor 11 ... Data reception part 12 ... Output calculation and database update determination part 13 ... Result output part 14 ... Database update part 15 ... Database 16 ... Top priority data decision signal 17 ... Top priority data signal 18 ... Data update Instruction signal 19 ... Additional update data signal 110 ... Specific brand order receiving unit 120 ... Specific brand execution determination and board information update determination unit 130 ... Specific brand execution result output unit 140 ... Selling board information update unit 141 ... Buying board information update unit 150 ... Selling board information database 151 ... Buying board information database

Claims (12)

  1. In an information processing apparatus including a database that manages data in order of priority,
    A database update unit for performing update of data addition or deletion in the database;
    A database update determination unit that instructs the database update unit to update the data to the database;
    From the database update unit to the database update determination unit, a notification of finalization of the highest priority data and the highest priority data are output,
    A database update instruction and update data are output from the database update determination unit to the database update unit,
    The database update determination unit
    When receiving the confirmation notification of the highest priority data and the highest priority data, an update determination process is executed,
    The database update unit
    Updating the database based on the database update instruction and the update data;
    When the highest priority data is confirmed, the confirmation notification of the highest priority data is output,
    An information processing apparatus that sequentially executes data updates other than the highest priority data.
  2. The information processing apparatus according to claim 1,
    The database has a hierarchical structure of heap structure,
    The database update unit includes a plurality of hierarchy update units corresponding to the hierarchy,
    A storage element is provided corresponding to the hierarchy of the database,
    An information processing apparatus that updates data from an upper hierarchy to a lower hierarchy by a pipeline operation based on the update instruction and update data.
  3. The information processing apparatus according to claim 2,
    In the case of additional updates, the hierarchy update unit
    The update data is set as additional data, the data of the target node in the highest hierarchy is compared with the additional data, and when the priority of the additional data is high, the additional data is stored as the data of the target node, and the target An information processing apparatus characterized in that, when the priority of data of a node is high, the additional data is used as an update of data of a node in a lower hierarchy.
  4. The information processing apparatus according to claim 2,
    The hierarchy update unit is a deletion update, and when no addition operation is executed in any hierarchy,
    An information processing apparatus that deletes data of the highest hierarchy and uses data of a node having the highest address stored in the database as data of the highest hierarchy.
  5. The information processing apparatus according to claim 2,
    The hierarchy update unit is a deletion update, and when performing an additional update in any hierarchy,
    Information processing apparatus characterized in that additional data in the highest priority layer among the layers to be added is set as additional data in the highest layer, and the pipeline operation of the layer to be added is stopped .
  6. The information processing apparatus according to claim 2,
    2. The information processing apparatus according to claim 1, wherein the storage element corresponding to the upper hierarchy is configured by an FPGA, and the storage element corresponding to the lower hierarchy is configured by a cache and DDR SDRAM.
  7. The information processing apparatus according to claim 1,
    The database update unit consists of a selling plate information update unit and a buying plate information update unit, the database consists of a selling plate information database and a buying plate information database,
    A plurality of sets of notifications for determining the highest priority data, the highest priority data, and database update instructions and update data are provided, and the data is input / output between the database update determination unit and the database update unit. A characteristic information processing apparatus.
  8. In a data processing method of an information processing apparatus including a database that manages data in order of priority,
    The information processing apparatus includes:
    A database update unit for performing update of data addition or deletion in the database;
    A database update determination unit that instructs the database update unit to update the data to the database;
    From the database update unit to the database update determination unit, a notification of finalization of the highest priority data and the highest priority data are output,
    A database update instruction and update data are output from the database update determination unit to the database update unit,
    The database update determination unit
    When receiving the confirmation notification of the highest priority data and the highest priority data, an update determination process is executed,
    The database update unit
    Updating the database based on the database update instruction and the update data;
    When the highest priority data is confirmed, the confirmation notification of the highest priority data is output,
    A data processing method characterized by sequentially executing data updates other than the highest priority data.
  9. The data processing method according to claim 8, wherein
    The database has a hierarchical structure of heap structure,
    The database update unit includes a plurality of hierarchy update units corresponding to the hierarchy,
    A storage element is provided corresponding to the hierarchy of the database,
    A data processing method characterized by executing data update from a higher hierarchy to a lower hierarchy by a pipeline operation based on the update instruction and update data.
  10. The data processing method according to claim 9, wherein
    In the case of additional updates, the hierarchy update unit
    The update data is set as additional data, the data of the target node in the highest hierarchy is compared with the additional data, and when the priority of the additional data is high, the additional data is stored as the data of the target node, and the target A data processing method characterized in that when the priority of data of a node is high, the additional data is used as an update of data of a node in a lower hierarchy.
  11. The data processing method according to claim 9, wherein
    The hierarchy update unit is a deletion update, and when no addition operation is executed in any hierarchy,
    A data processing method comprising deleting data of the highest hierarchy and using data of a node having the highest address stored in the database as data of the highest hierarchy.
  12. The data processing method according to claim 9, wherein
    The hierarchy update unit is a deletion update, and when performing an additional update in any hierarchy,
    A data processing method characterized in that the additional data in the highest priority layer among the layers in which the addition is performed is set as the additional data in the highest layer, and the pipeline operation of the layer in which the addition is performed is stopped .
PCT/JP2014/065671 2014-06-13 2014-06-13 Information processing device and data processing method therefor WO2015189970A1 (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
PCT/JP2014/065671 WO2015189970A1 (en) 2014-06-13 2014-06-13 Information processing device and data processing method therefor

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
PCT/JP2014/065671 WO2015189970A1 (en) 2014-06-13 2014-06-13 Information processing device and data processing method therefor
PCT/JP2014/077235 WO2015190007A1 (en) 2014-06-13 2014-10-10 Information processing device, computer system, and data processing method therefor

Publications (1)

Publication Number Publication Date
WO2015189970A1 true WO2015189970A1 (en) 2015-12-17

Family

ID=54833098

Family Applications (2)

Application Number Title Priority Date Filing Date
PCT/JP2014/065671 WO2015189970A1 (en) 2014-06-13 2014-06-13 Information processing device and data processing method therefor
PCT/JP2014/077235 WO2015190007A1 (en) 2014-06-13 2014-10-10 Information processing device, computer system, and data processing method therefor

Family Applications After (1)

Application Number Title Priority Date Filing Date
PCT/JP2014/077235 WO2015190007A1 (en) 2014-06-13 2014-10-10 Information processing device, computer system, and data processing method therefor

Country Status (1)

Country Link
WO (2) WO2015189970A1 (en)

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2017212525A1 (en) * 2016-06-06 2017-12-14 株式会社日立製作所 Computer and database processing method

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH08235217A (en) * 1995-02-24 1996-09-13 Pioneer Electron Corp Data retrieval and output device and karaoke device
JP2002007707A (en) * 2000-06-22 2002-01-11 Keio Gijuku Transaction system
JP2006221346A (en) * 2005-02-09 2006-08-24 Toyo Securities Co Ltd Transaction support system, transaction support method, transaction support program and recording medium

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US9626421B2 (en) * 2007-09-21 2017-04-18 Hasso-Plattner-Institut Fur Softwaresystemtechnik Gmbh ETL-less zero-redundancy system and method for reporting OLTP data
US8510261B1 (en) * 2012-05-29 2013-08-13 Sap Ag System and method of generating in-memory models from data warehouse models

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH08235217A (en) * 1995-02-24 1996-09-13 Pioneer Electron Corp Data retrieval and output device and karaoke device
JP2002007707A (en) * 2000-06-22 2002-01-11 Keio Gijuku Transaction system
JP2006221346A (en) * 2005-02-09 2006-08-24 Toyo Securities Co Ltd Transaction support system, transaction support method, transaction support program and recording medium

Also Published As

Publication number Publication date
WO2015190007A1 (en) 2015-12-17

Similar Documents

Publication Publication Date Title
Baumgartner Parsimony and causality
US9542176B2 (en) Predicting software build errors
TWI553496B (en) Increasing signal to noise ratio for creation of generalized and robust prediction models
TWI623838B (en) Method, non-transitory computer-readable storage medium, and system for big data analytics
JP6692561B2 (en) Blockchain consensus method and device
Roy et al. High precision discrete Gaussian sampling on FPGAs
US9836701B2 (en) Distributed stage-wise parallel machine learning
US8347292B2 (en) Transaction aggregation to increase transaction processing throughout
WO2016061283A1 (en) Configurable machine learning method selection and parameter optimization system and method
JP2016072963A (en) Techniques for routing service chain flow packets between virtual machines
CN107360206A (en) A kind of block chain common recognition method, equipment and system
US8990149B2 (en) Generating a predictive model from multiple data sources
US20180032375A1 (en) Data Processing Method and Apparatus
Befani Between complexity and generalization: Addressing evaluation challenges with QCA
US10438132B2 (en) Machine for development and deployment of analytical models
US9116720B2 (en) Decision tree ensemble compilation
Dai et al. An improved task assignment scheme for Hadoop running in the clouds
CN106294533A (en) Use the distributed work flow that data base replicates
WO2013173550A1 (en) Fusing conditional write instructions having opposite conditions in instruction processing circuits, and related processor systems, methods, and computer-readable media
US20160071023A1 (en) Computing Instance Launch Time
US9576072B2 (en) Database calculation using parallel-computation in a directed acyclic graph
US20160110409A1 (en) Large-Scale, Dynamic Graph Storage and Processing System
KR20120037413A (en) Productive distribution for result optimization within a hierarchical architecture
US9110946B2 (en) Database query optimization
WO2012006468A1 (en) Methods and systems for replaceable synaptic weight storage in neuro-processors

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 14894346

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase in:

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 14894346

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase in:

Ref country code: JP