KR20210053830A - A computer program for asynchronous data processing in a database management system - Google Patents

Abstract

In an embodiment of the present disclosure for solving problems, provided is a computer program stored in a computer-readable storage medium executable by one or more processors, the computer program causes the one or more processors to perform operations for asynchronous data processing in a base management system. The operations comprise: dividing an operation corresponding to a query into one or more operations when receiving the query issued from a client; allocating a sub-task for each of the one or more tasks to each of one or more worker threads; determining whether to balance the processing of the one or more tasks; and reallocating sub-tasks of the tasks related to imbalance to the worker threads when it is determined that the processing of the one or more tasks is imbalanced.

Description

A computer program for asynchronous data processing in a database management system {A COMPUTER PROGRAM FOR ASYNCHRONOUS DATA PROCESSING IN A DATABASE MANAGEMENT SYSTEM}

The present disclosure relates to a database management system (DBMS), and more particularly, to a computer program for asynchronous data processing in a database management system.

Database refers to a set of standard data that is integrated and managed for the purpose of being shared and used by multiple people. In general, it collects data related to a specific area of an organization, which can be used to provide information to support decision-making at different levels.

As the amount of data becomes larger today, the use of a database management system (hereinafter, DBMS) that efficiently supports it to search for necessary data from a database or to change (insert, modify, delete, and update) data is increasing.

DBMS can store all data in a database in the form of a table. A table is a basic structure for storing data in a database, and a table consists of one or more records. When a specific query is input from the outside, such a DBMS performs functions such as selecting, inserting, deleting, and updating data in the database according to the input query. Here, a query means a description of what kind of request for data stored in a database table, that is, what kind of manipulation you want to perform on the data, and can be expressed through a language such as SQL (Structured Query Language).

The DBMS stores records on disk in the form of tables and updates them in response to queries from outside (clients or other applications). At this time, if one CPU processes one task corresponding to an external query, the load may be high and the speed may be slow. Therefore, the data processing speed can be improved through a synchronous processing method by connecting several CPUs in parallel. have.

The synchronous processing method may mean serially performing a task. Specifically, the synchronous processing method is to execute tasks sequentially. When a thread performs a specific task, it allocates and waits for the next task, and when the thread finishes processing a specific task, it processes the next task that was waiting. to be.

However, when a task is sequentially performed through a synchronous processing method, a specific thread may remain in a standby state due to unbalanced tasks processed in each thread according to a difference in data processing speed between a plurality of threads performing the task. This is inefficient in the use of thread resources, and there is a concern that the work processing speed may be deteriorated.

Accordingly, there may be a demand in the industry for a computer program to increase efficiency in resource utilization by asynchronously allocating tasks to a plurality of threads according to data flow in the DBMS so that each thread performs tasks in a balanced manner.

Japanese Patent No. 4611830

The present disclosure is conceived in response to the above-described background technology, and is to provide a computer program for asynchronous data processing in a database management system.

In one embodiment of the present disclosure for solving the above-described problem, a computer program stored in a computer-readable medium executable by one or more processors is disclosed. When the computer program is executed by one or more processors, it causes the one or more processors to perform operations for asynchronous data processing in a database management system, and the operations are: When receiving a query issued from a client , An operation of dividing an operation corresponding to the query into one or more tasks, an operation of allocating a sub-task for each of the one or more tasks to each of one or more worker threads, an operation of determining whether or not the processing of the one or more tasks is balanced And when it is determined that the processing of the one or more tasks is unbalanced, reassigning a subtask of the task related to the imbalance to a worker thread.

Alternatively, the method of claim 1, wherein each of the one or more tasks is a group in which operations corresponding to the query are classified on a predetermined basis, and one of a parallel processing relationship for parallel processing of data, or a dependency relationship for linking data. At least one relationship can be formed.

Alternatively, when the one or more tasks form a dependency relationship, the tasks that form the dependency relationship are a master task that transmits data generated according to the processing result of the sub task to a slave task and from the master task. It may include the slave operation that performs an operation based on the received data.

Alternatively, the operation of allocating sub-tasks for each of the one or more tasks to each of one or more worker threads may include allocating a sub-task of the master task to a worker thread in order to perform a master task among the one or more tasks, When the work progress for the master task is more than a predetermined threshold, an operation of identifying at least one additional allocation worker thread for performing a slave task corresponding to the master task, and the additional allocation worker thread for the slave task It may include an operation of allocating sub-tasks.

Alternatively, the additional assignment worker thread may be at least one of a worker thread that performs a task corresponding to the master task, a worker thread that is not assigned a sub task, or a worker thread that performs an action corresponding to another query. have.

Alternatively, the determining whether the processing of the one or more jobs is balanced may include determining whether the balance is based on the amount of memory allocated to each of the one or more jobs, or a sub for each of the one or more jobs. It may include at least one of the operations of determining whether the balance is based on the work-related message received from the one or more worker threads that process the work.

Alternatively, the operation of determining whether the balance is based on the memory usage allocated to each of the one or more tasks is, when the memory usage allocated to each of the one or more tasks exceeds a predetermined first threshold usage, the one An operation of determining that the processing of the one or more tasks is unbalanced, and an operation of determining that the processing of the one or more tasks is unbalanced when the memory usage for each dependency relationship formed by each of the one or more tasks exceeds a predetermined second threshold amount of use. Including, the memory usage for each dependency relationship may be identified as the sum of the memory usage of each of the tasks included in each of the master task and the slave task.

Alternatively, the operation of determining whether the balance is based on a job-related message received from the one or more worker threads processing sub-tasks for each of the one or more jobs, processing sub-tasks for each of the one or more jobs Identifying a data processing result of each of the one or more jobs based on a job-related message received from the one or more worker threads and when the difference between the data processing result between the one or more jobs exceeds a predetermined threshold, the one It may include an operation of determining that the processing of the above operation is unbalanced.

Alternatively, when it is determined that the processing of the one or more tasks is unbalanced, the operation of reallocating the subtask of the task related to the imbalance to a worker thread is additional to perform the subtask of the task related to the imbalance of the task. An operation of identifying an assignment worker thread and an operation of allocating a subtask related to the imbalance to the additional assignment worker thread, and the additional assignment worker thread is a worker thread that performs a subtask on the work related to the imbalance , It may be at least one of a worker thread that is not assigned a task, or a worker thread that performs an operation corresponding to another query.

In another embodiment of the present disclosure, a method for asynchronous data processing in a database management system is disclosed. The method comprises, when receiving a query issued from a client, dividing an operation corresponding to the query into one or more tasks, allocating subtasks for each of the one or more tasks to each of one or more worker threads, the Determining whether or not the processing of one or more jobs is balanced, and when it is determined that the processing of the one or more jobs is unbalanced, reassigning a sub-task of the job related to the imbalance to a worker thread.

According to another embodiment of the present disclosure, a server for asynchronous data processing in a database management system is disclosed. The server includes a processor including one or more cores, a memory storing program codes executable by the processor, and a network unit for transmitting and receiving data to and from the client, and the processor, when receiving a query issued from the client, The operation corresponding to the query is divided into one or more tasks, subtasks for each of the one or more tasks are allocated to each of one or more worker threads, and the balance of the processing of the one or more tasks is determined, and the one When it is determined that the processing of the above task is unbalanced, the subtask of the task related to the imbalance can be reallocated to the worker thread.

The present disclosure can provide a computer program that performs asynchronous data processing in a database management system.

Various aspects are now described with reference to the drawings, wherein like reference numbers are used collectively to refer to like elements. In the examples that follow, for illustrative purposes, a number of specific details are presented to provide a comprehensive understanding of one or more aspects. However, it will be apparent that such aspect(s) may be practiced without these specific details.
1 is a block diagram of a server according to an embodiment of the present disclosure.
2 is a diagram schematically illustrating one or more tasks and subtasks corresponding to one query related to an embodiment of the present disclosure.
3 is an exemplary diagram illustrating a divided operation in response to one query related to an embodiment of the present disclosure.
4 is an exemplary diagram schematically illustrating a process of performing a divided operation in response to one query related to an embodiment of the present disclosure.
5 is an exemplary diagram illustrating a partitioned operation in response to one query related to another embodiment of the present disclosure.
6 is an exemplary diagram illustrating a partitioned operation in response to one query related to another embodiment of the present disclosure.
7 is a flowchart for providing asynchronous data processing in a database management system according to an embodiment of the present disclosure.
8 illustrates a module for performing asynchronous data processing in a database management system according to an embodiment of the present disclosure.
9 shows a simplified and general schematic diagram of an exemplary computing environment in which embodiments of the present disclosure may be implemented.

Various embodiments are now described with reference to the drawings. In this specification, various descriptions are presented to provide an understanding of the present disclosure. However, it is clear that these embodiments may be implemented without this specific description.

As used herein, the terms "component", "module", "system" and the like refer to a computer-related entity, hardware, firmware, software, a combination of software and hardware, or execution of software. For example, a component may be, but is not limited to, a process executed on a processor, a processor, an object, a thread of execution, a program, and/or a computer. For example, both an application running on a computing device and a computing device may be components. One or more components may reside within a processor and/or thread of execution. A component can be localized within a single computer. A component can be distributed between two or more computers. In addition, these components can execute from a variety of computer readable media having various data structures stored therein. Components can be, for example, through a signal with one or more data packets (e.g., data from one component interacting with another component in a local system, a distributed system, and/or a signal through another system and a network such as the Internet. Depending on the data being transmitted), it may communicate via local and/or remote processes.

In addition, the term “or” is intended to mean an inclusive “or” rather than an exclusive “or”. That is, unless specified otherwise or is not clear from the context, "X employs A or B" is intended to mean one of the natural inclusive substitutions. That is, X uses A; X uses B; Or when X uses both A and B, "X uses A or B" can be applied to either of these cases. In addition, the term “and/or” as used herein should be understood to refer to and include all possible combinations of one or more of the listed related items.

In addition, the terms "comprises" and/or "comprising" should be understood to mean that the corresponding features and/or components are present. However, it is to be understood that the terms "comprising" and/or "comprising" do not exclude the presence or addition of one or more other features, elements, and/or groups thereof. In addition, unless otherwise specified or when the context is not clear to indicate a singular form, the singular in the specification and claims should be interpreted as meaning "one or more" in general.

Those of skill in the art would further describe the various illustrative logical blocks, configurations, modules, circuits, means, logics, and algorithm steps described in connection with the embodiments disclosed herein, including electronic hardware, computer software, or a combination of both. It should be recognized that it can be implemented as To clearly illustrate the interchangeability of hardware and software, various illustrative components, blocks, configurations, means, logics, modules, circuits, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented in hardware or as software depends on the specific application and design restrictions imposed on the overall system. Skilled technicians can implement the described functionality in various ways for each particular application. However, such implementation decisions should not be interpreted as causing a departure from the scope of the present disclosure.

In the database management system related to the present disclosure, asynchronous data processing may be implemented through the server 100.

The client may mean any type of node(s) having a mechanism for communication with the server 100. For example, such clients may include PCs, laptop computers, workstations, terminals, and/or any electronic device with network connectivity. In addition, the client may include any server implemented by at least one of an agent, an application programming interface (API), and a plug-in.

According to an embodiment of the present disclosure, operations to be described later of the server 100 may be performed according to a query issued from a client.

Server 100 may include any type of computer system or computer device, such as, for example, a microprocessor, mainframe computer, digital single processor, portable device and device controller, and the like. The server 100 may include a database management system (DBMS). In addition, the server 100 may be used interchangeably with a device for executing a query.

The DBMS is a program for allowing the server 100 to perform operations such as parsing a query and searching for, inserting, modifying, and/or deleting necessary data. In the storage unit 120 of the server 100, the processor ( 130).

The server 100 may include a device including a processor 130 and a storage unit 120 for executing and storing instructions as a database of any type, but is not limited thereto. That is, the server 100 may include software, firmware, hardware, or a combination thereof. The software may include application(s) for creating, deleting and modifying database tables, schemas, indexes and/or data. The server 100 may receive transactions from a client or other computing device, and exemplary transactions include searching, inserting, modifying, deleting, and/or managing records of data, tables and/or indexes, etc. in the server 100 May include doing.

* FIG. 1 shows a block diagram of a server according to an embodiment of the present disclosure.

As shown in FIG. 1, the server 100 may include a network unit 110, a storage unit 120, and a processor 130. The above-described components are exemplary, and the scope of the present disclosure is not limited to the above-described components. That is, additional components may be included or some of the above-described components may be omitted according to implementation aspects of the embodiments of the present disclosure.

According to an embodiment of the present disclosure, the server 100 may include a network unit 110 that transmits and receives data to and from a client. In addition, the network unit 110 may provide a communication function between the server 100 and a client. The network unit 110 may receive an input from a client. For example, the network unit 110 may receive a request related to storage, change, and inquiry of data and change and inquiry of an index build from a client. When the network unit 110 is located outside the server 100, the network unit 110 may receive an output table generated by performing an operation based on the received SQL for a specific table from the server 100. Additionally, the network unit 110 may allow information transfer between the server 100 and the client by calling a procedure to the server 100. As a further embodiment, the network unit 110 in the present specification may include a database link (dblink), and accordingly, the server 100 may receive data from another database server by communicating through such a database link. .

According to an embodiment of the present disclosure, the storage unit 120 may include a persistent storage medium and a memory.

Persistent storage media include, for example, any data, such as magnetic disks, optical disks and magneto-optical storage devices, as well as storage devices based on flash memory and/or battery-backup memory. It may refer to a non-volatile storage medium capable of continuously performing. Such a permanent storage medium may communicate with the processor 130 and the memory of the server 100 through various communication means. In an additional embodiment, such a permanent storage medium may be located outside the server 100 to communicate with the server 100.

Memory is the primary storage device directly accessed by the processor, such as, for example, random access memory (RAM) such as dynamic random access memory (DRAM) and static random access memory (SRAM). It may refer to a volatile storage device in which stored information is instantaneously erased, but is not limited thereto. Such a memory may be operated by the processor 130. The memory may temporarily store a data table including data values. The data table may include data values, and in an embodiment of the present disclosure, the data values of the data table may be recorded from a memory to a permanent storage medium. In a further aspect, the memory includes a buffer cache, where data may be stored in a data block of the buffer cache. Data stored in the buffer cache may be written to a persistent storage medium by a background process.

According to an embodiment of the present disclosure, the processor 130 may control the overall operation of the server 100 in general. The processor 130 may perform operations for improving database management performance by processing signals, data, information, etc. through the above-described components or by driving an application program stored in the storage unit 120.

According to an embodiment of the present disclosure, the processor 130 may divide an operation corresponding to a query into one or more tasks. Specifically, the processor 130 may receive a query issued from a client to identify an operation corresponding to the query, and may divide the operation corresponding to the query into one or more operations.

A task is a group in which operations corresponding to a query are classified on a predetermined basis, and each of the tasks may form at least one of a parallel processing relationship for processing data in parallel with each other, or a dependency relationship for linking data with each other. In addition, the task may include one or more subtasks, which are the smallest units of data processing processed in the worker thread. One or more sub-tasks may be a minimum unit that a worker thread can process in each task. For example, in the case of a job of scanning records of a first table including 2000 rows, a first sub-job of scanning records of 1 to 1000 rows of the first table and 1001 of the first table A second sub-task of scanning records of ~2000 rows may be included. The description of specific numerical values for the scan range of each of the above-described sub-tasks is merely an example, and the present disclosure is not limited thereto.

In the parallel processing relationship, a data processing relationship formed between tasks may be a relationship in which data processing can be performed in parallel. For example, an operation corresponding to a query is performed by the processor 130 in a first operation for a first table scan, a second operation for a second table scan, and a specific column of the first table and the second table. When divided into a third operation that performs sorting for each table, the operation of scanning each table may be performed in parallel. That is, the first task and the second task may be in a parallel processing relationship. Detailed description of each of the above-described tasks is merely an example, and the present disclosure is not limited thereto.

The dependent processing relationship may be a relationship formed between jobs that process data in association, and may include a master job and a slave job. The master job may be a job of transferring a processing result of a sub job for each of one or more jobs to a slave job. In addition, the slave operation may be an operation that performs an operation based on data on a processing result of the master operation. For example, the operation corresponding to the query is a first operation for a first table scan by the processor 130 and a second operation for merging records of the first column and the second column of the first table. In the case of division, after processing for the first job, processing for the second job may be performed. That is, a first operation of scanning the first table and a second operation of merging records scanned through the first operation may have a dependency processing relationship with each other. In this case, the first task may be a master task that transfers data processed as the second task, and the second task may be a slave task that performs an operation by inputting data according to the processing result of the first task. Detailed description of each of the above-described tasks is merely an example, and the present disclosure is not limited thereto.

For a more specific example, if the first query 200 issued from the client is a query for sorting tables T1 and T2 based on records of column C3, the processor 130 performs one or more operations corresponding to the query. Can be divided into tasks. In detail, the processor 130 performs an operation for the first query 200 as shown in FIG. 2, a first operation 210 for scanning a record in the T1 table, and a first operation 210 for scanning a record in the T2 table. The second task 220 and the records scanned through the first task 210 and the second task 220 may be divided into a third task 230 that sorts the records of column C3 based on the records. This partitioning can be performed based on a plan for the query.

In this case, the first task 210 and the second task 220 are tasks for scanning each table and may have a parallel processing relationship with each other. In other words, the first operation 210 and the second operation 220 of scanning records of each of the T1 table and the T2 table may be performed in parallel. In addition, after a scan operation is performed on a record of each table in the first operation 210 and the second operation 220, the third operation 230 may be processed. The first operation 210 of scanning the T1 table and the third operation 230 of merging the records scanned through the first operation may have a dependency processing relationship with each other. In addition, the second operation 220 of scanning the T2 table and the third operation 230 of merging the records scanned through the second operation may have a dependency processing relationship with each other. That is, the first task 210 and the second task 220 may be master tasks for transferring processed data (ie, scanned records) to the third task 230, and the third task 230 It may be a slave operation that performs an operation for alignment based on data according to processing results of the first operation 210 and the second operation 220.

In addition, each of the first task 210, the second task 220, and the third task 230 divided by the processor 130 may include one or more subtasks. As shown in FIG. 2, the first operation 210 includes a first sub-operation 211 for scanning records of 1 to 1000 rows in the T1 table and a first sub-operation 211 for scanning records of 1001 to 2000 rows in the T1 table. A second sub-task 212 may be included. Further, the second operation 220 includes a first sub-operation 221 for scanning records of 1 to 1000 rows in the T2 table and a second sub-operation 222 for scanning records of 1001 to 2000 rows in the T2 table. ) Can be included. In addition, the third operation 230 is a first sub-task for performing sorting by dividing the size of the records in column C3 by section for the records scanned through the first operation 210 and the second operation 220 ( 231) and a second sub-task 232. Specifically, the first sub-task 231 of the third task 230 may be a sub-task that performs sorting based on the records of column C3 from 0 to 100, and the second sub-task of the third task 230 The task 232 may be a sub-task that performs sorting based on the records in the C3 column of 101 to 200. Detailed descriptions of queries, tasks, and subtasks described with reference to FIG. 2 are only examples to aid understanding of the present disclosure, and the present disclosure is not limited thereto.

According to an embodiment of the present disclosure, the processor 130 may allocate a sub-task for each of one or more tasks to each of one or more worker threads. Specifically, the processor 130 may divide an operation corresponding to a query into one or more tasks, and each of the divided one or more tasks forms a parallel processing relationship or a dependent processing relationship, so that they are processed in parallel or are dependent on Can be treated as In addition, each of the one or more tasks may include one or more sub-tasks capable of parallel processing. In other words, the processor 130 may allocate sub-tasks for each of one or more tasks to one or more worker threads so that sub-tasks of each task are performed in parallel.

For example, when a first job is a job of scanning a first table and a second job is a job of scanning a second table, the first job and the second job may be processed in parallel. In addition, the first operation may include a first sub-task of scanning rows 1 to 100 of the first table and a second sub-task of scanning rows 101 to 200, and the second operation is a second operation. A first sub-task of scanning rows 1 to 50 of the table and a second sub-task of scanning rows 51 to 100 may be included. In this case, sub-tasks included in each of the first task and the second task may be performed in parallel. That is, while the first task and the second task are processed in parallel, subtasks corresponding to each task may also be processed in parallel. Specific descriptions of the above-described tasks and sub-tasks are only examples, and the present disclosure is not limited thereto.

That is, the processor 130 divides the operation corresponding to the query into one or more tasks, and assigns subtasks capable of parallel processing to each of the one or more tasks to one or more worker threads to be processed in parallel, so that the operation corresponding to the query Can improve the processing speed.

According to an embodiment of the present disclosure, after the sub-task for the master task is performed, the processor 130 may allow the sub-task for the slave task to be performed. Specifically, if more than one task forms a dependency relationship, the slave task performs an operation through the data transmitted according to the execution result of the master task. Therefore, it should be performed at the point in time after the sub task for the master task is performed. I can. Accordingly, the processor 130 may allocate the sub-task for the master task to one or more worker threads to process data, and then allocate the sub-task for the slave task corresponding to the master task to one or more worker threads.

In detail, the processor 130 may allocate a subtask of the master task to a worker thread in order to perform the master task among one or more tasks. Also, the processor 130 may identify at least one additional allocated worker thread for performing the slave task corresponding to the master task when the progress of the task for the master task is equal to or greater than a predetermined threshold. The additional allocation worker thread may be at least one of a worker thread that performs a task corresponding to the master task, a worker thread that is not assigned a sub task, or a worker thread that performs an operation corresponding to another query. In addition, the processor 130 may allocate a subtask for a slave task to an additional assignment worker thread.

That is, the processor 130 provides the subtask for the slave task to the additional assignment worker thread in response to the time when the subtask for the master task is processed by a predetermined threshold (that is, when the subtask for the slave task can be processed). You can assign it to be processed. In addition, at least one of a worker thread that performs sub-tasks on the master task, a worker thread that has not been assigned a sub-task, or a worker thread that performs an operation corresponding to another query is identified as an additionally assigned worker thread to work asynchronously. Can be allocated, minimizing idle worker threads.

Therefore, it is possible to allocate worker threads to sub-tasks of each task at an optimal time in which each task can be processed, thereby smoothing the flow of data processing. In addition, by identifying idle worker threads to asynchronously process sub-tasks for tasks, it is possible to increase the efficiency in utilizing worker thread resources.

A more detailed process in which the processor 130 allocates sub-tasks for each of one or more tasks to each of one or more worker threads will be described later with reference to FIGS. 3 and 4.

As shown in FIG. 3, when the second query 300 issued from the client is a query for performing sorting (ie, order by) on table T, the processor 130 performs a sorting operation on table T. Can be divided into more than one task. In detail, the processor 130 may identify that the operation corresponding to the second query 300 is an operation of sorting the records of each row based on the record located in the column C2 of table T. The processor 130 performs an operation corresponding to the second query 300 as a first operation 400 for scanning records in the T table and a first operation for sorting the records identified through the first operation based on the records in column C2. Can be divided into two tasks 500. In this case, since the execution result of the first task 400 is a dependency relationship corresponding to the input of the second task 500, the first task 400 may be a master task, and the second task 500 is a master task. It may be a slave operation corresponding to.

As shown in FIG. 4, the first operation 400 is a first sub-task 411 for scanning records of rows 1 to 4 of table T and a second sub-task 411 for scanning records of rows 5 to 8 of table T. It may include a sub-task 421. The processor 130 allocates the first sub-task 411 to the first worker thread 410, and allocates the second sub-task 421 to the second worker thread 420 to perform each sub-task in parallel. You can do it. The processor 130 may transmit the processing result of the first operation (ie, the master operation, 400) (ie, the record scan of the table T) to the second operation.

The second operation (that is, the slave operation 500) receiving data on the processing result of the first operation 400 is a first sub-operation 511 that performs sorting based on records from 0 to 40 in the C2 column. And a second sub-task 521 of performing sorting based on 41 or more records in column C2.

In addition, the processor 130 may allocate the first sub-task 511 of the second task 500 to the third worker thread 510, as shown in FIG. 4, and the second task 500 The second sub-task 521 of may be assigned to the fourth worker thread 520. In this case, the third worker thread 510 and the fourth worker thread 520 may be additionally allocated worker threads identified by the processor 130. That is, the third worker thread 510 and the fourth worker thread 520 are worker threads that perform the master task (ie, the first worker thread 410 or the second worker thread 420), or the subtask is It may be an unallocated worker thread (ie, an idle worker thread), or at least one of a worker thread that performs an operation corresponding to another query.

The processor 130 is shown in FIG. 4 based on data processed by each of the third worker thread 510 and the fourth worker thread 520 performing the first sub-task 511 and the second sub-task 521. The result table 600 as described above may be generated. Description of the above-described tasks and sub-tasks specific values with reference to FIGS. 3 and 4 is only an example, and the present disclosure may include three or more tasks and sub-tasks to those of ordinary skill in the art. It will be self-evident.

That is, the processor 130 may process sub-tasks for each of one or more tasks (ie, a master task and a slave task) in parallel. Accordingly, it is possible to increase the speed of data processing through parallel execution of the sub-tasks of each task, and to share the load that is added to the execution of the sub-tasks.

According to an embodiment of the present disclosure, the processor 130 may determine whether to balance processing of one or more tasks. The processor 130 may determine whether an inefficient state such as a bottleneck occurs in parallel processing of one or more tasks. The processor 130 may determine whether the progress of each task is performed evenly or whether a bottleneck occurs. The processor 130 may determine whether to balance processing among one or more tasks based on a resource usage related to a task, a task progress state, and the like. Specifically, the processor 130 is performed in each task based on at least one of a memory usage allocated to each of one or more tasks and a task-related message received from one or more worker threads that process subtasks for each of the one or more tasks. It is possible to determine whether data processing is balanced or not.

In detail, the processor 130 may divide an operation corresponding to a query into one or more tasks. In this case, a memory capable of temporarily storing data may be allocated to each of the one or more jobs, and a data processing result of a sub-job included in the job may be temporarily stored (ie, buffered) in each memory.

The processor 130 may identify the amount of memory allocated to each of one or more tasks. Also, the processor 130 may determine whether to balance data processing performed in each of the one or more tasks based on a comparison between the memory usage of each of the one or more tasks and a predetermined threshold usage.

Specifically, when the memory usage allocated to each of the one or more tasks exceeds a predetermined first threshold usage, the processor 130 may determine that the processing of one or more tasks is unbalanced. The first threshold usage may be a criterion for determining whether data processing performed in each task is appropriate.

For example, an operation corresponding to a query is divided into a first operation for a first table scan and a second operation for a second table scan by the processor 130, and the memory usage of the first operation is 20%, When the memory usage of the second job is 70%, and the predetermined threshold usage is 65%, the processor 130 identifies that the memory usage for the second job exceeds the first predetermined threshold usage, It can be judged that the treatment is unbalanced.

For another example, an operation corresponding to a query is performed by the processor 130 to perform a first operation for a table scan, a second operation for performing a hash join on the records of the scanned table, and a filter for the result of the second operation. It is divided into a third task to be applied, and when the memory usage of each task is 18%, 75%, and 12%, and the first predetermined threshold usage is 70%, the processor 130 uses the memory usage for the second task. It can be determined that the processing of the job is unbalanced by identifying that it exceeds this predetermined first threshold usage amount. The description of specific values of the memory usage and the predetermined first threshold usage for each operation described above are only examples, and the present disclosure is not limited thereto.

In addition, the processor 130 may determine that the processing of one or more tasks is unbalanced when the memory usage for each dependency relationship formed by each of the one or more tasks exceeds a predetermined second threshold usage amount. The memory usage for each dependency relationship may be the sum of the memory usage of tasks included in each of the master task and the slave task. The second threshold usage may be a criterion for determining whether data processing between the master task and the slave task, that is, tasks forming a dependency relationship, is appropriate.

For a specific example, the operation corresponding to the query is a first operation of scanning a first table, a second operation of scanning a second table, and records scanned through the first operation and the second operation by the processor 130 When divided into a third task that performs sorting on the fields, the memory usage of each task is 40%, 55%, and 45%, and the first predetermined threshold usage and the second predetermined threshold usage are 70% and 90, respectively. It can be %. The first task and the second task may be a master task that transfers processed data to the third task, and the third task may be a slave task that performs an operation based on data processed by the master task. In this case, the memory usage by dependency relationship can be identified as 95% through the sum of the memory usage of the first task, which is the master task, and the memory usage of the second task, and 45 through the memory usage of the third task, which is a slave task. Can be identified by %. That is, the memory usage of each task does not exceed the first predetermined threshold usage (i.e., 75%), but the memory usage of the master task (95%) among the memory usage for each dependency relationship is the second threshold usage (90%). %), the processor 130 may determine that data processing performed in one or more tasks is unbalanced. The description of specific values of the memory usage, the first predetermined threshold usage, and the second predetermined threshold usage for each task described above are only examples, and the present disclosure is not limited thereto.

That is, when the memory usage for a specific task exceeds a predetermined first threshold usage, the processor 130 determines that data processing for a specific task is inefficient, and the data processing performed in each of the one or more tasks is unbalanced. can do. In addition, the processor 130 determines that a bottleneck occurs in which data cannot be processed and a delay occurs when the memory usage for each dependency relationship between the master job and the slave job exceeds a predetermined second threshold usage. It may be determined that data processing performed in each of one or more tasks is unbalanced. For example, it may be determined that the processing of the slave operation is impossible because the master operation is not performed.

Also, the processor 130 may determine whether to balance data processing performed in each of the one or more tasks based on a task-related message received from one or more worker threads that process sub-tasks for each of the one or more tasks. The task-related message received from the worker thread may be a message relating to completion of processing for a sub-task.

Specifically, the processor 130 may identify a data processing result of each of one or more tasks based on a task-related message received from one or more worker threads. The data processing result of each task can indicate the degree to which the sub task is completed. In addition, when the difference between the data processing results of each of the one or more jobs is equal to or less than a predetermined threshold, the data processing performed in each of the one or more jobs may be determined as a balance. In addition, when the difference between the data processing results of each of the one or more tasks of the processor 130 exceeds a predetermined threshold, the data processing performed in each of the one or more tasks may be determined as unbalanced.

For example, the operation corresponding to the query may be divided into a first operation for a first table scan by the processor 130 and a second operation for sorting records scanned through the first operation. In addition, the predetermined threshold may be 700, and a task-related message indicating that a scan of up to 1000 rows has been completed in the first table is received from worker threads performing subtasks for the first task, and A task-related message indicating that the alignment of up to 200 rows has been completed may be received from worker threads that perform subtasks for the task. In this case, the processor 130 may determine that the difference in the data processing result of the first job and the second job exceeds 700, which is a predetermined threshold of 800, and determines the processing of one or more jobs as unbalanced. That is, the processor 130 identifies that the table scan operation has been completed up to 1000 rows, but the sorting operation for the scanned records has been completed up to 200 rows, so that a bottleneck occurs in the record sorting operation (i.e., the second operation). It can be judged as.

For another example, an operation corresponding to a query is performed by the processor 130 to perform a first operation for a table scan, a second operation for performing a hash join on the records of the scanned table, and a filter for the result of the second operation. It can be divided into a third task to apply.

In addition, a predetermined threshold may be 500, and a task-related message indicating that a scan of up to 1000 rows in the table has been completed is received from worker threads performing sub-tasks for the first task, and a sub-task for the second task. A task-related message indicating that the join has been completed up to 700 rows is received from the worker threads performing the tasks, and a task-related message indicating that filter processing of up to 20 rows has been completed from the worker threads performing subtasks for the third task. Can be received. In this case, the processor 130 may determine that the difference in the data processing result of the second task and the third task exceeds 500, which is a predetermined threshold of 680, and determines the processing of one or more tasks as unbalanced. That is, the processor 130 identifies that the join operation has been completed up to 700 rows, but the filter operation for the joined records has completed up to 20 rows, and is a bottleneck in the filter operation (that is, the third operation) for the joined records. It can be determined that this has occurred. The description of specific values of the data processing for each of the above-described tasks and the specific values of the predetermined threshold are only examples, and the present disclosure is not limited thereto.

That is, the processor 130 can identify the data processing degree of each job through the job-related messages received from the worker threads performing sub-tasks of each job, and the processing level of each job exceeds a predetermined threshold. The point in time may be determined as unbalanced processing of one or more tasks.

According to an embodiment of the present disclosure, when it is determined that the processing of one or more tasks is unbalanced, the processor 130 may reallocate a subtask of a task related to the imbalance to a worker thread. Specifically, the processor 130 may identify an additional allocated worker thread for performing a sub-task of a task related to a task imbalance. The additionally allocated worker thread may be at least one of a worker thread that performs a sub-task for a task related to the imbalance, a worker thread that is not assigned a task, or a worker thread that performs an operation corresponding to another query.

For example, an operation corresponding to a query is performed by the processor 130 in a first operation of scanning a first table, a second operation of scanning a second table, and records scanned through the first operation and the second operation. When divided into the third task for performing sorting, the memory usage of each task may be 80%, 55%, and 45%, and the first predetermined threshold usage may be 75%. The processor 130 may identify that the operation of scanning the first table exceeds a first predetermined threshold usage amount. That is, the processor 130 determines that the data generated as a result of the processing of the first task (ie, the master task) is not consumed in the third task (ie, the slave task), and performs the subtask of the third task. Additional allocation worker threads can be identified. In this case, the additional assignment worker thread may be a worker thread that performs a sub-task of the first task or a worker thread that performs a sub-task of the second task.

The processor 130 identifies a worker thread that performs at least one of the subtasks of the first task and the second task corresponding to the master task as an additionally allocated worker thread, and is a third task (ie, a slave task) that is a task related to the imbalance. You can assign sub-tasks.

Accordingly, the number of worker threads of the master job that performs the work on the table scan may be reduced, and the number of worker threads of the slave work that performs the record sorting work may increase. Accordingly, the processing speed for the sub-task of the third task increases, and data processed in the first task can be consumed, so that the memory usage of the first task can be reduced (that is, the processing result of the first task is buffered. Data can be consumed through a third operation). When the memory usage of the first task is reduced and becomes less than or equal to the predetermined first threshold usage, the processor 130 determines that the processing of each task is balanced, and returns the first task to the worker thread that has allocated the sub task of the third task. The master task, which is a scan for the table, can be performed by assigning a task and a sub task of the second task. The detailed description of the memory usage and the predetermined memory usage of each operation described above is only an example, and the present disclosure is not limited thereto.

Referring to FIG. 5 in more detail, when receiving the third query 700, the processor 130 sorts the tables T1 711 and T2 721 based on the records in the column C1. It can be divided into the above tasks. Specifically, the processor 130 includes a first operation 710 for scanning the records of the T1 table 711, a second operation 720 for scanning the records of the T2 table 721, and the first operation 710. ) And the records scanned through the second operation 720 may be divided into a third operation 730 that sorts the records based on the records in the C1 column. In this case, since the execution result of the first task 710 and the second task 720 is a dependency relationship corresponding to the input of the third task 730, the first task 710 and the second task 720 are master It may be an operation, and the third operation may be a slave operation corresponding to the master operation.

The first operation 710 includes a first sub-task for scanning records of rows 1 to 10 of the T1 table 711 and a second sub-task for scanning records of rows 11 to 20 of the T1 table 711. In addition, the second operation 720 includes a first sub-operation for scanning records of rows 1 to 10 of the T2 table 721 and a first sub-operation for scanning records of rows 11 to 20 of the T2 table 721. It may include a second sub-task. In addition, the third operation 730 is a first sub-task that performs sorting based on records from 0 to 10 in column C1 and a second sub-task that sorts based on records from column C1 to 21 to 40. It may include.

For example, when the memory usage of the second task 720 exceeds a predetermined first threshold usage amount (80%) as 85%, the processor 130 may perform the first subtask and the second subtask of the second task 720. By identifying that the data processed through the sub-task is not consumed in the third task 730, it may be determined that the data processing of each task is unbalanced. Accordingly, the processor 130 provides at least one of the worker threads performing the first sub-task and the second sub-task of the second task 710 to scan the T2 table 721 to a sub-task of the third task. Tasks can be assigned.

That is, the processor 130 is at least one of a worker thread that has completed the execution of the first sub-task of the second task 720 or a worker thread that has completed the execution of the second sub-task of the second task 720. A third sub-task (sorting based on 41 or more records in column C1) of the third task 730 may be assigned to the thread. As the processor 130 reallocates the subtask of the third task 730 related to the imbalance to the worker thread performing the subtask of the second task 720, the worker thread performing the third task 730 The number may increase, and the number of worker threads performing sub-tasks of the second operation 720 may decrease. In other words, it is possible to prioritize data processing by identifying a task with high throughput, identifying an additionally allocated worker thread asynchronously to the task and assigning it to a subtask of the task.

For another example, referring to FIG. 6, an operation corresponding to a query is performed by the processor 130 for a first operation 810 for a table scan, and a second operation for performing a hash join on a record of the scanned table ( 820) and a third task 830 that applies a filter on the result of the second task 820, the memory usage of each task is 18%, 75%, and 12%, and a predetermined first threshold usage In the case of 70%, the processor 130 may identify that the memory usage for the second job exceeds the first predetermined threshold usage, and determine that the processing of the job is unbalanced. That is, the processor 130 determines that the data generated as a result of the processing of the second operation 820 is not consumed in the third operation 830, and in order to improve the processing speed of the third operation 830, Additional allocation worker threads for performing sub-tasks of task 830 may be identified. In this case, the additional assignment worker thread may be a worker thread that performs sub-tasks of the first task 810 and the second task 820.

That is, the processor 130 is a sub-task of the third task 830 to a worker thread that performs a sub-task for the second task 820 related to the imbalance or a worker thread that performs a sub-task of the first task 810. By assigning tasks asynchronously. By improving the processing speed of the third operation 830, data buffered in the memory of the second operation 820 may be quickly consumed.

Accordingly, the processing speed of the sub-task of the third task 830 increases, and data processed in the second task 820 may be consumed, and thus the memory usage of the second task 820 may be reduced. That is, the data buffered as a result of the processing of the second job 820 may be consumed due to an increase in the processing speed of the third job, so that a bottleneck may be eliminated.

In addition, when the memory usage of the second task 820 decreases due to the increase in the processing speed of the third task 830 and falls below the predetermined first threshold usage, the processor 130 determines that the processing of each task is balanced. After determining, assigning the subtasks of the first task 810 and the second task 820 back to the worker thread that has assigned the subtask of the third task 830 to perform a table scan or a hash join operation. can do.

Therefore, the processor 130 does not match specific worker threads to each of one or more tasks to perform a corresponding task, but when a bottleneck occurs in a specific task according to the flow of data, a worker thread of another task or, By asynchronously allocating idle worker threads, it is possible to efficiently process data between tasks. That is, it is possible to process data in a flexible manner according to the processing status of a job, so that the speed of data processing corresponding to a query can be improved, and a bottleneck occurring in a specific job can be quickly resolved.

7 is a flowchart illustrating a method for asynchronous data processing in a database management system according to an embodiment of the present disclosure.

According to an embodiment of the present disclosure, when receiving a query issued from a client, the server 100 may divide an operation corresponding to the query into one or more tasks (910).

According to an embodiment of the present disclosure, the server 100 may allocate sub-tasks for each of one or more tasks to each of one or more worker threads (920).

According to an embodiment of the present disclosure, the server 100 may determine whether to balance processing of one or more tasks (930 ).

According to an embodiment of the present disclosure, when it is determined that the processing of one or more tasks is unbalanced, the server 100 may reallocate a subtask of a task related to the imbalance to a worker thread (940).

The order of the steps illustrated in FIG. 7 may be changed as needed, and at least one or more steps may be omitted or added. That is, the above-described steps are only one embodiment of the present disclosure, and the scope of the present disclosure is not limited thereto.

8 illustrates a module for performing asynchronous data processing in a database management system according to an embodiment of the present disclosure.

According to an embodiment of the present disclosure, the server may be implemented by the following modules.

According to an embodiment of the present disclosure, when receiving a query issued from a client, the server 100 provides a module 1010 for dividing an operation corresponding to the query into one or more tasks, and for each of the one or more tasks. A module 1020 for allocating sub-tasks to each of one or more worker threads, a module 1030 for determining whether the processing of the one or more tasks is balanced, and when the processing of the one or more tasks is determined to be unbalanced, the A module 1040 for reallocating a sub-task of a task related to imbalance to a worker thread may be included.

Alternatively, the method of claim 1, wherein each of the one or more tasks is a group in which modules corresponding to the query are classified on a predetermined basis, a parallel processing relationship for parallel processing of data, or a dependency relationship for linking data. At least one of the relationships can be formed.

Alternatively, when the one or more tasks form a dependency relationship, the tasks that form the dependency relationship are a master task that transmits data generated according to the processing result of the sub task to a slave task and from the master task. It may include the slave operation that performs an operation based on the received data.

Alternatively, a module for allocating a sub-task for each of the one or more tasks to each of one or more worker threads is configured to allocate a sub-task of the master task to a worker thread in order to perform a master task among the one or more tasks. Module, a module for identifying at least one additional allocation worker thread for performing a slave job corresponding to the master job, and the slave to the additional allocation worker thread when the progress of the work on the master job is greater than or equal to a predetermined threshold It may include a module for allocating sub-tasks for the task.

Alternatively, the additional assignment worker thread is at least one of a worker thread that performs a task corresponding to the master task, a worker thread that is not assigned a sub task, or a worker thread that performs a module for responding to other queries. I can.

Alternatively, the module for determining whether to balance the processing of the one or more jobs is a module for determining whether the balance is based on the memory usage allocated to each of the one or more jobs, or for each of the one or more jobs It may include at least one operation of a module for determining whether the balance is based on a job-related message received from the one or more worker threads that process sub-tasks for the job.

Alternatively, the module for determining whether the balance is based on the memory usage allocated to each of the one or more tasks, when the memory usage allocated to each of the one or more tasks exceeds a predetermined first threshold usage amount, the If the module for determining that the processing of one or more tasks is unbalanced and the memory usage for each dependency relationship formed by each of the one or more tasks exceeds the second predetermined threshold usage, it is determined that the processing of the one or more tasks is unbalanced. It includes a module to perform, and the memory usage for each dependency relationship may be identified as the sum of the memory usage of each of the tasks included in each of the master task and the slave task.

Alternatively, the module for determining whether the balance is based on a job-related message received from the one or more worker threads processing sub-tasks for each of the one or more jobs, the sub-task for each of the one or more jobs A module for identifying a data processing result of each of the one or more jobs and a difference in a data processing result between the one or more jobs based on a job-related message received from the one or more worker threads to process exceeds a predetermined threshold, It may include a module for determining that the processing of the one or more tasks is unbalanced.

Alternatively, when it is determined that the processing of the one or more tasks is unbalanced, the module for reallocating the subtasks of the tasks related to the imbalance to a worker thread is for performing the subtasks of the tasks related to the imbalance of the tasks. A module for identifying an additional allocation worker thread and a module for allocating a sub-task related to the imbalance to the additional allocation worker thread, and the additional allocation worker thread performs a sub-task for the task related to the imbalance It may be at least one of a worker thread that performs a task, a worker thread that is not assigned a task, or a worker thread that executes a module for responding to other queries.

According to an embodiment of the present disclosure, a module for performing asynchronous data processing in a database system may be implemented by means, circuits, or logic for implementing a server.

Those of skill in the art would further describe the various illustrative logical blocks, configurations, modules, circuits, means, logics and algorithm steps described in connection with the embodiments disclosed herein, in electronic hardware, computer software, or combinations of both. It should be recognized that it can be implemented as To clearly illustrate the interchangeability of hardware and software, various illustrative components, blocks, configurations, means, logics, modules, circuits, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented in hardware or as software depends on the specific application and design restrictions imposed on the overall system. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present disclosure.

9 shows a simplified and general schematic diagram of an exemplary computing environment in which embodiments of the present disclosure may be implemented.

While the present disclosure has generally been described above with respect to computer-executable instructions that can be executed on one or more computers, those skilled in the art will appreciate that the present disclosure may be implemented in combination with other program modules and/or as a combination of hardware and software. will be.

Generally, program modules include routines, procedures, programs, components, data structures, etc. that perform particular tasks or implement particular abstract data types. Further, to those skilled in the art, the method of the present disclosure is not limited to single-processor or multiprocessor computer systems, minicomputers, mainframe computers, as well as personal computers, handheld computing devices, microprocessor-based or programmable household appliances, etc. (each of which is It will be appreciated that other computer system configurations may be implemented, including one that may operate in connection with one or more associated devices.

The described embodiments of the present disclosure may also be practiced in a distributed computing environment where certain tasks are performed by remote processing devices that are connected through a communication network. In a distributed computing environment, program modules may be located in both local and remote memory storage devices.

Computers typically include a variety of computer-readable media. Any medium accessible by the computer may be a computer-readable medium, and the computer-readable medium may include a computer-readable storage medium and a computer-readable transmission medium. Such computer-readable storage media include volatile and nonvolatile media, removable and non-removable media. Computer-readable storage media includes volatile and nonvolatile media, removable and non-removable media implemented in any method or technology for storing information such as computer readable instructions, data structures, program modules or other data. Computer-readable storage media include RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital video disk (DVD) or other optical disk storage, magnetic cassette, magnetic tape, magnetic disk storage, or other magnetic storage. Devices, or any other medium that can be accessed by a computer and used to store desired information.

Computer-readable transmission media typically implement computer-readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism. Includes information delivery media. The term modulated data signal refers to a signal in which one or more of the characteristics of the signal is set or changed so as to encode information in the signal. By way of example and not limitation, computer-readable transmission media include wired media such as a wired network or direct-wired connection, and wireless media such as acoustic, RF, infrared, and other wireless media. Combinations of any of the above-described media are also intended to be included within the scope of computer-readable transmission media.

An exemplary environment 1100 is shown that implements various aspects of the present disclosure, including a computer 1102, which includes a processing device 1104, a system memory 1106, and a system bus 1108. do. System bus 1108 couples system components, including but not limited to, system memory 1106 to processing device 1104. The processing unit 1104 may be any of a variety of commercially available processors. Dual processors and other multiprocessor architectures may also be used as processing unit 1104.

The system bus 1108 may be any of several types of bus structures that may be additionally interconnected to a memory bus, a peripheral bus, and a local bus using any of a variety of commercial bus architectures. System memory 1106 includes read-only memory (ROM) 1110 and random access memory (RAM) 1112. The basic input/output system (BIOS) is stored in non-volatile memory 1110 such as ROM, EPROM, EEPROM, etc. This BIOS is a basic input/output system that helps transfer information between components within the computer 1102, such as during startup. Includes routines. RAM 1112 may also include high speed RAM such as static RAM for caching data.

The computer 1102 also includes an internal hard disk drive (HDD) 1114 (e.g., EIDE, SATA)-this internal hard disk drive 1114 can also be configured for external use within a suitable chassis (not shown). Yes--, a magnetic floppy disk drive (FDD) 1116 (for example, to read from or write to a removable diskette 1118), and an optical disk drive 1120 (for example, a CD-ROM). For reading the disk 1122 or for reading from or writing to other high-capacity optical media such as DVD). The hard disk drive 1114, magnetic disk drive 1116, and optical disk drive 1120 are each connected to the system bus 1108 by a hard disk drive interface 1124, a magnetic disk drive interface 1126, and an optical drive interface 1128. ) Can be connected. The interface 1124 for implementing an external drive includes at least one or both of Universal Serial Bus (USB) and IEEE 1394 interface technologies.

These drives and their associated computer readable media provide non-volatile storage of data, data structures, computer executable instructions, and the like. In the case of computer 1102, drives and media correspond to storing any data in a suitable digital format. Although the description of the computer-readable medium above refers to a removable optical medium such as a HDD, a removable magnetic disk, and a CD or DVD, those skilled in the art may use a zip drive, a magnetic cassette, a flash memory card, a cartridge, etc. It will be appreciated that other types of computer-readable media, such as the ones, may also be used in the exemplary operating environment and that any such media may contain computer-executable instructions for performing the methods of the present disclosure.

A number of program modules, including the operating system 1130, one or more application programs 1132, other program modules 1134, and program data 1136, may be stored in the drive and RAM 1112. All or part of the operating system, applications, modules and/or data may also be cached in RAM 1112. It will be appreciated that the present disclosure may be implemented on several commercially available operating systems or combinations of operating systems.

A user may input commands and information to the computer 1102 through one or more wired/wireless input devices, for example, a pointing device such as a keyboard 1138 and a mouse 1140. Other input devices (not shown) may include a microphone, IR remote control, joystick, game pad, stylus pen, touch screen, and the like. These and other input devices are often connected to the processing unit 1104 through the input device interface 1142, which is connected to the system bus 1108, but the parallel port, IEEE 1394 serial port, game port, USB port, IR interface, It can be connected by other interfaces such as etc.

A monitor 1144 or other type of display device is also connected to the system bus 1108 through an interface such as a video adapter 1146. In addition to the monitor 1144, the computer generally includes other peripheral output devices (not shown) such as speakers, printers, and the like.

Computer 1102 may operate in a networked environment using logical connections to one or more remote computers, such as remote computer(s) 1148, via wired and/or wireless communication. The remote computer(s) 1148 may be a workstation, server computer, router, personal computer, portable computer, microprocessor-based entertainment device, peer device, or other common network node, and is generally referred to as computer 1102. Although including many or all of the described components, only memory storage device 1150 is shown for simplicity. The logical connections shown include wired/wireless connections to a local area network (LAN) 1152 and/or to a larger network, eg, a wide area network (WAN) 1154. Such LAN and WAN networking environments are common in offices and companies, and facilitate enterprise-wide computer networks such as intranets, all of which can be connected to worldwide computer networks, for example the Internet.

When used in a LAN networking environment, the computer 1102 is connected to the local network 1152 via a wired and/or wireless communication network interface or adapter 1156. Adapter 1156 may facilitate wired or wireless communication to LAN 1152, which also includes a wireless access point installed therein to communicate with wireless adapter 1156. When used in a WAN networking environment, the computer 1102 may include a modem 1158, connected to a communication server on the WAN 1154, or other Have means. The modem 1158, which may be an internal or external and a wired or wireless device, is connected to the system bus 1108 through a serial port interface 1142. In a networked environment, program modules described for the computer 1102 or portions thereof may be stored in the remote memory/storage device 1150. It will be appreciated that the network connections shown are exemplary and other means of establishing communication links between computers may be used.

Computer 1102 is associated with any wireless device or entity deployed and operated in wireless communication, e.g., a printer, scanner, desktop and/or portable computer, portable data assistant (PDA), communication satellite, wireless detectable tag. It operates to communicate with any device or place, and a phone. This includes at least Wi-Fi and Bluetooth wireless technologies. Accordingly, the communication may be a predefined structure as in a conventional network or may simply be ad hoc communication between at least two devices.

Wi-Fi (Wireless Fidelity) allows you to connect to the Internet, etc. without wires. Wi-Fi is a wireless technology such as a cell phone that allows such devices, for example computers, to transmit and receive data indoors and outdoors, that is, anywhere within the coverage area of a base station. Wi-Fi networks use a wireless technology called IEEE 802.11 (a, b, g, etc.) to provide a secure, reliable and high-speed wireless connection. Wi-Fi can be used to connect computers to each other, to the Internet, and to a wired network (using IEEE 802.3 or Ethernet). Wi-Fi networks can operate in unlicensed 2.4 and 5 GHz wireless bands, for example at 11 Mbps (802.11a) or 54 Mbps (802.11b) data rates, or in products that include both bands (dual band). have.

A person of ordinary skill in the art of the present disclosure includes various exemplary logical blocks, modules, processors, means, circuits and algorithm steps described in connection with the embodiments disclosed herein, electronic hardware, For the sake of clarity, it will be appreciated that it may be implemented by various forms of program or design code or a combination of both (referred to herein as "software"). To clearly illustrate this interchangeability of hardware and software, various illustrative components, blocks, modules, circuits, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware or software depends on the particular application and design constraints imposed on the overall system. A person of ordinary skill in the art of the present disclosure may implement the described functions in various ways for each specific application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present disclosure.

The various embodiments presented herein may be implemented as a method, apparatus, or article of manufacture using standard programming and/or engineering techniques. The term “article of manufacture” includes a computer program, carrier, or media accessible from any computer-readable device. For example, computer-readable media include magnetic storage devices (e.g., hard disks, floppy disks, magnetic strips, etc.), optical disks (e.g., CD, DVD, etc.), smart cards, and flash memory. Devices (eg, EEPROM, card, stick, key drive, etc.). In addition, the various storage media presented herein include one or more devices and/or other machine-readable media for storing information. The term “machine-readable medium” includes, but is not limited to, wireless channels and various other media capable of storing, holding, and/or transmitting instruction(s) and/or data.

It is to be understood that the specific order or hierarchy of steps in the presented processes is an example of exemplary approaches. Based on the design priorities, it is to be understood that within the scope of this disclosure a specific order or hierarchy of steps in processes may be rearranged. The appended method claims provide elements of the various steps in a sample order, but are not meant to be limited to the specific order or hierarchy presented.

A description of the presented embodiments is provided to enable any person skilled in the art to make or use the present disclosure. Various modifications to these embodiments will be apparent to those of ordinary skill in the art, and general principles defined herein may be applied to other embodiments without departing from the scope of the present disclosure. Thus, the present disclosure is not to be limited to the embodiments presented herein, but is to be construed in the widest scope consistent with the principles and novel features presented herein.

Claims (1)

A computer program stored on a computer readable storage medium.

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