CN113704076A - Task optimization method and device, electronic equipment and computer readable medium - Google Patents
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Abstract
The embodiment of the disclosure discloses a task optimization method, a task optimization device, an electronic device and a computer readable medium. One embodiment of the method comprises: determining a result table represented by the information of the result table to be optimized as a target result table, and determining a path on which the target result table depends to be generated to obtain a dependent path directed graph; splitting the dependence path directed graph to obtain a task link set; determining the execution time length of each task in the task link set; determining the execution time length of each task link in the task link set; selecting a task link with the execution duration being greater than or equal to a first preset threshold value from the task link set as a target task link to obtain a target task link set; and generating a key task information set according to the target task link set, and sending the key task information set to a display terminal. According to the embodiment, under the condition that the upstream task of the result table is kept unchanged, the output duration of the result table is shortened, and the output efficiency of the result table is improved.
Description
Technical Field
The embodiment of the disclosure relates to the technical field of computers, in particular to a task optimization method, a task optimization device, an electronic device and a computer-readable medium.
Background
Task optimization is a technique to speed up the outcome table throughput by shortening the execution duration of the task links. At present, when the output of the result table is accelerated, the following methods are generally adopted: and reducing the upstream tasks of the result table, namely reducing the tasks in the task link, thereby shortening the output time of the result table.
However, when the above method is adopted to accelerate the output of the result table, the following technical problems often exist:
firstly, the length of a task link is not necessarily connected with the output duration of a result table, so that the upstream tasks of the result table are reduced, and the output duration of the result table is not necessarily shortened;
secondly, reducing tasks in a task link may cause the result table not to be normally output, and in order to ensure the result table to be normally output, other tasks need to be introduced, which may further cause delay of output time of the result table, and reduce output efficiency of the result table.
Disclosure of Invention
This summary is provided to introduce a selection of concepts in a simplified form that are further described below in the detailed description. This summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used to limit the scope of the claimed subject matter.
Some embodiments of the present disclosure propose a task optimization method, apparatus, electronic device and computer readable medium to solve one or more of the technical problems mentioned in the background section above.
In a first aspect, some embodiments of the present disclosure provide a method for task optimization, the method comprising: in response to receiving information of a result table to be optimized, determining the result table represented by the information of the result table to be optimized as a target result table, determining a path on which the target result table depends to be generated, and obtaining a dependent path directed graph, wherein nodes in the dependent path directed graph are used for representing tasks for generating the result table; splitting the dependence path directed graph to obtain a task link set; determining the execution duration of each task in the task link set; determining the execution duration of each task link in the task link set according to the execution duration of each task in the task link set; selecting a task link with the execution duration being greater than or equal to a first preset threshold value from the task link set as a target task link to obtain a target task link set; and generating a key task information set according to the target task link set, and sending the key task information set to a display terminal.
In a second aspect, some embodiments of the present disclosure provide a task optimization device, the device comprising: the first generating unit is configured to respond to the received information of the result table to be optimized, determine the result table represented by the information of the result table to be optimized as a target result table, determine a path depended on by the target result table, and obtain a dependent path directed graph, wherein nodes in the dependent path directed graph are used for representing tasks for generating the result table; the splitting unit is configured to split the dependence path directed graph to obtain a task link set; a first determining unit configured to determine an execution time length of each task in the task link set; the second determining unit is configured to determine the execution time length of each task link in the task link set according to the execution time length of each task in the task link set; the selection unit is configured to select a task link with the execution duration being greater than or equal to a first preset threshold value from the task link set as a target task link to obtain a target task link set; and the second generating unit is configured to generate a key task information set according to the target task link set and send the key task information set to a display terminal.
In a third aspect, some embodiments of the present disclosure provide an electronic device, comprising: one or more processors; a storage device having one or more programs stored thereon, which when executed by one or more processors, cause the one or more processors to implement the method described in any of the implementations of the first aspect.
In a fourth aspect, some embodiments of the present disclosure provide a computer readable medium on which a computer program is stored, wherein the program, when executed by a processor, implements the method described in any of the implementations of the first aspect.
The above embodiments of the present disclosure have the following beneficial effects: through the task optimization method of some embodiments of the present disclosure, the output duration of the result table can be shortened under the condition that the upstream task of the result table is kept unchanged, and the output efficiency of the result table is improved. Specifically, the reason why the throughput duration of the result table after reducing the task upstream of the result table is not shortened is that: the execution time of each task is different, and the number of tasks cannot represent the execution time. Based on this, in the task optimization method of some embodiments of the present disclosure, first, in response to receiving information of a result table to be optimized, a result table represented by the information of the result table to be optimized is determined as a target result table, and a path on which the target result table is generated is determined, so as to obtain a dependent path directed graph, where a node in the dependent path directed graph is used to represent a task for generating the result table. Therefore, by determining the task of producing the result table to be optimized, the directed acyclic graph of all the production paths of the result table is determined. And then, splitting the dependence path directed graph to obtain a task link set. Thus, by splitting the dependent path directed graph, all paths that generate the target result table are determined. Then, the execution time length of each task in the task link set is determined. Therefore, the time efficiency of each task in the task link set is determined by determining the execution time length of each task in the task link set. And then, determining the execution time length of each task link in the task link set according to the execution time length of each task in the task link set. Thus, the time efficiency of each task link in the set of task links that generates the target result table may be determined. And then selecting a task link with the execution duration being greater than or equal to a first preset threshold value from the task link set as a target task link to obtain a target task link set. Therefore, by generating the target task link set, the task link with relatively low execution efficiency can be determined. And finally, generating a key task information set according to the target task link set, and sending the key task information set to a display terminal. Therefore, the task for prolonging the output of the result list can be determined as the key task, and the key task can be optimized by sending the key task to the target terminal, so that the execution time of the key task is shortened, and the output of the result list can be accelerated. And because the task optimization is to accelerate the output of the result table by shortening the execution time of the existing task, the purpose of shortening the output time of the result table can be achieved under the condition of keeping the task at the upstream of the result table unchanged.
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The above and other features, advantages and aspects of various embodiments of the present disclosure will become more apparent by referring to the following detailed description when taken in conjunction with the accompanying drawings. Throughout the drawings, the same or similar reference numbers refer to the same or similar elements. It should be understood that the drawings are schematic and that elements and elements are not necessarily drawn to scale.
FIG. 1 is a schematic diagram of one application scenario of a task optimization method of some embodiments of the present disclosure;
FIG. 2 is a flow diagram of some embodiments of a task optimization method according to the present disclosure;
FIG. 3 is a flow diagram of further embodiments of a task optimization method according to the present disclosure;
FIG. 4 is a schematic block diagram of some embodiments of a task optimization device according to the present disclosure;
FIG. 5 is a schematic structural diagram of an electronic device suitable for use in implementing some embodiments of the present disclosure.
Detailed Description
Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the present disclosure are shown in the drawings, it is to be understood that the disclosure may be embodied in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided for a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the disclosure are for illustration purposes only and are not intended to limit the scope of the disclosure.
It should be noted that, for convenience of description, only the portions related to the related invention are shown in the drawings. The embodiments and features of the embodiments in the present disclosure may be combined with each other without conflict.
It should be noted that the terms "first", "second", and the like in the present disclosure are only used for distinguishing different devices, modules or units, and are not used for limiting the order or interdependence relationship of the functions performed by the devices, modules or units.
It is noted that references to "a", "an", and "the" modifications in this disclosure are intended to be illustrative rather than limiting, and that those skilled in the art will recognize that "one or more" may be used unless the context clearly dictates otherwise.
The names of messages or information exchanged between devices in the embodiments of the present disclosure are for illustrative purposes only, and are not intended to limit the scope of the messages or information.
The present disclosure will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.
Fig. 1 is a schematic diagram of one application scenario of the task optimization method of some embodiments of the present disclosure.
In the application scenario of fig. 1, first, in response to receiving to-be-optimized result table information 102, a computing device 101 may determine a result table characterized by the to-be-optimized result table information 102 as a target result table 103, and determine a path on which the target result table 103 is generated, to obtain a dependent path directed graph 104, where nodes in the dependent path directed graph 104 are used to characterize a task of generating the result table. Then, the computing device 101 may split the dependency path directed graph 104 to obtain a task link set 105; then, the computing device 101 can determine the execution duration of each task in the task link set 105. Thereafter, the computing device 101 may determine the execution duration of each task link in the task link set 105 according to the execution duration of each task in the task link set 105. Then, the computing device 101 may select a task link with an execution duration greater than or equal to a first preset threshold from the task link set 105 as a target task link, so as to obtain a target task link set 106. Finally, the computing device 101 may generate a set of key task information 107 according to the set of target task links 106, and send the set of key task information 107 to the display terminal 108.
The computing device 101 may be hardware or software. When the computing device is hardware, it may be implemented as a distributed cluster composed of multiple servers or terminal devices, or may be implemented as a single server or a single terminal device. When the computing device is embodied as software, it may be installed in the hardware devices enumerated above. It may be implemented, for example, as multiple software or software modules to provide distributed services, or as a single software or software module. And is not particularly limited herein.
It should be understood that the number of computing devices in FIG. 1 is merely illustrative. There may be any number of computing devices, as implementation needs dictate.
With continued reference to FIG. 2, a flow 200 of some embodiments of a task optimization method according to the present disclosure is shown. The task optimization method comprises the following steps:
In some embodiments, an execution subject of the task optimization method (for example, the computing device 101 shown in fig. 1) may determine, in response to receiving information of the result table to be optimized, a result table characterized by the information of the result table to be optimized as a target result table, and determine, using a dynamic bayesian network model, a path on which the target result table is generated, to obtain a dependent path directed graph. And the nodes in the dependent path directed graph are used for characterizing the task of generating the result table. The dependency path directed graph may be a directed acyclic graph formed according to a dependency relationship between tasks.
Therefore, by determining the task of producing the result table to be optimized, the directed acyclic graph of all the production paths of the result table is determined.
In an optional manner of some embodiments, the determining, by the execution subject, a path on which the target result table depends to be generated to obtain a dependent path directed graph may include:
firstly, determining the task generating the target result table as a target task.
And secondly, generating a dependency path directed graph by taking the target task as a terminal point according to the dependency relationship among the tasks.
A directed graph model may be employed to generate a dependent path directed graph. The directed graph model may include, but is not limited to, at least one of a hidden markov model and a static bayesian network model.
Therefore, the dependent path directed graph can be generated for the path by taking the target task as the end point and taking the dependent relation between the tasks as the path.
In some embodiments, the execution subject may split the dependency path directed graph in a manner of a pre-order traversal using the target task as an end point to obtain a task link set.
Thus, by splitting the dependent path directed graph, all paths that generate the target result table are determined.
In some embodiments, the execution subject may determine an execution duration of each task in the task link set. The task may be a task for generating a result table. The execution main body may select an execution duration of each task when the target result table is generated at any time as an execution duration of each task in the task link set.
Therefore, the time efficiency of each task in the task link set is determined by determining the execution time length of each task in the task link set.
In an optional manner of some embodiments, the determining, by the execution main body, the execution duration of each task in the task link set may include:
the method comprises the steps of firstly, obtaining the execution duration of each task in the task link set in each execution within a preset time period, and obtaining a task execution duration group set.
And the task execution time groups in the task execution time group set correspond to the tasks in the task link set one by one. The preset time period may be a preset time period, and here, the setting of the preset time period is not limited.
And secondly, performing averaging processing on each task execution time group in the task execution time group set to generate a first target task execution time to obtain a first target task execution time group.
The arithmetic mean of each task execution duration group in the task execution duration group set may be determined as a first target task execution duration, so as to obtain a first target task execution duration set.
Therefore, the execution time length of each task in the task link set can be accurately determined by determining the average value of the execution time lengths of all tasks in the preset time period.
Optionally, the executing main body performs averaging processing on each task execution duration group in the task execution duration group set to generate a first target task execution duration, and may perform the following steps:
the method comprises the following steps of firstly, determining standard deviation and mean value of each task execution time length in the task execution time length group.
Wherein the average value is an arithmetic average value of the execution time lengths of the tasks in the task execution time length group.
And secondly, selecting the task execution time length meeting a first preset condition from the task execution time length group as a second target task execution time length to obtain a second target task execution time length group, wherein the first preset condition is that the task execution time length is greater than the difference value of two times of the mean value and the standard deviation and is less than the sum of two times of the mean value and the standard deviation.
Therefore, data deviated from the task execution time length can be deleted through the preset condition set in advance, and the influence of the deviated data on the determination of the task execution time length is reduced.
And thirdly, determining the average value of the execution time of each second target task in the second target task execution time group as the execution time of the first target task.
Therefore, the execution time of each task in the task link set can be determined more accurately by obtaining the average value of the execution time of each task meeting the preset condition.
And 204, determining the execution time of each task link in the task link set according to the execution time of each task in the task link set.
In some embodiments, the execution main body may determine, as the execution duration of the task link, the sum of the execution durations of the tasks included in each task link in the task link set, to obtain the execution duration of each task link in the task link set.
Thus, the time efficiency of each task link in the set of task links that generates the target result table may be determined.
In some embodiments, the execution main body may select a task link, of which the execution duration is greater than or equal to a first preset threshold, from the task link set as a target task link, so as to obtain a target task link set. Wherein the first preset threshold is a preset value. For example, the first preset threshold may be 6 hours.
Therefore, by generating the target task link set, the task link with relatively low execution efficiency can be determined.
And step 206, generating a key task information set according to the target task link set, and sending the key task information set to the display terminal.
In some embodiments, the execution main body may determine, according to the target task link set, each task included in the target task link set and the occurrence frequency of the task, then, by setting a preset threshold, take the task whose occurrence frequency is greater than or equal to the preset threshold as a key task, generate a key task information set, and send the key task information set to the computer terminal. The above-mentioned critical task information set may be an information set of a task whose execution time period needs to be shortened.
Therefore, the task for prolonging the output of the result list can be determined as the key task, and the key task can be optimized by sending the key task to the target terminal, so that the execution time of the key task is shortened, and the output of the result list can be accelerated.
The above embodiments of the present disclosure have the following beneficial effects: through the task optimization method of some embodiments of the present disclosure, the output time of the result table can be shortened under the condition that the upstream task of the result table is kept unchanged, and the output efficiency of the result table is improved. Specifically, the reason why the throughput time of the result table after reducing the task upstream of the result table has not been shortened is that: the execution time of each task is different, and the number of tasks cannot represent the execution time. Based on this, in the task optimization method of some embodiments of the present disclosure, first, in response to receiving information of a result table to be optimized, a result table represented by the information of the result table to be optimized is determined as a target result table, and a path on which the target result table is generated is determined, so as to obtain a dependent path directed graph, where a node in the dependent path directed graph is used to represent a task for generating the result table. Therefore, by determining the task of producing the result table to be optimized, the directed acyclic graph of all the production paths of the result table is determined. And then, splitting the dependence path directed graph to obtain a task link set. Thus, by splitting the dependent path directed graph, all paths that generate the target result table are determined. Then, the execution time length of each task in the task link set is determined. Therefore, the time efficiency of each task in the task link set is determined by determining the execution time length of each task in the task link set. And then, determining the execution time length of each task link in the task link set according to the execution time length of each task in the task link set. Thus, the time efficiency of each task link in the set of task links that generates the target result table may be determined. And then selecting a task link with the execution duration being greater than or equal to a first preset threshold value from the task link set as a target task link to obtain a target task link set. Therefore, by generating the target task link set, the task link with relatively low execution efficiency can be determined. And finally, generating a key task information set according to the target task link set, and sending the key task information set to a display terminal. Therefore, the task for prolonging the output of the result list can be determined as the key task, and the key task can be optimized by sending the key task to the target terminal, so that the execution time of the key task is shortened, and the output of the result list can be accelerated. And because the task optimization is to accelerate the output of the result table by shortening the execution time of the existing task, the purpose of shortening the output time of the result table can be achieved under the condition of keeping the task at the upstream of the result table unchanged.
With further reference to fig. 3, a flow 300 of further embodiments of an information method is illustrated. The process 300 of the task optimization method includes the following steps:
And step 302, splitting the dependence path directed graph to obtain a task link set.
And step 304, determining the execution time of each task link in the task link set according to the execution time of each task in the task link set.
And 305, selecting a task link with the execution duration being greater than or equal to a first preset threshold from the task link set as a target task link, and obtaining a target task link set.
In some embodiments, the specific implementation manner and technical effects of steps 301 and 305 may refer to steps 201 and 205 in those embodiments corresponding to fig. 2, which are not described herein again.
In some embodiments, the execution subject may determine the task included in the target task link set as a first task, resulting in a first task set. The first task described above may be a task for generating a result table.
Thus, by determining the individual tasks included in the target set of task links, all upstream tasks used to generate the results table may be determined.
In some embodiments, the performing, by the performing agent, a scoring process for each first task in the first task set may include:
the first step is that the times of the first task appearing in the target task link set are determined, and the target times are obtained.
And secondly, determining a product value of the target times and the first target task execution time length corresponding to the first task as a task score value corresponding to the first task.
From this, a task score value for each task in the set of task links may be determined.
In some embodiments, the executing entity may determine, in response to a task score value greater than or equal to a second preset threshold existing in the task score value set, a first task corresponding to the task score value greater than or equal to the second preset threshold as a second task, so as to obtain a second task set. The second preset threshold may be a preset value. For example, the second preset threshold may be 5 hours.
From this, tasks that reduce the yield efficiency of the results list can be identified.
And 309, selecting a second task with the first target task execution time length being greater than or equal to a third preset threshold value from the second task set as a key task, and obtaining a key task set.
In some embodiments, the execution subject may select, from the second task set, a second task whose first target task execution duration is greater than or equal to a third preset threshold as a critical task, so as to obtain a critical task set. The third preset threshold may be a preset value. For example, the third preset threshold may be 3 hours.
Thus, the tasks that need to be optimized among the tasks that reduce the yield efficiency of the result table can be determined.
And 310, determining each key task in the key task set, the target times corresponding to the key tasks and the first target task execution time corresponding to the key tasks as key task information to obtain a key task information set, and sending the key task information set to a display terminal.
In some embodiments, the execution main body may determine each key task in the key task set, the target number of times corresponding to the key task, and the first target task execution duration corresponding to the key task as key task information, obtain a key task information set, and send the key task information set to the display terminal.
Therefore, the determined tasks needing to be optimized are used as key tasks, the execution time of the tasks can be shortened by optimizing the key tasks on the premise of not introducing other tasks, the execution time of the task link is shortened, and the output efficiency of the result table is improved.
Step 306 and 310 and the related content serve as an invention point of the embodiment of the present disclosure, and solve the technical problem mentioned in the background art, i.e. reducing tasks in a task link may cause that a result table cannot be normally produced, and in order to ensure that the result table is normally produced, other tasks need to be introduced, which may further cause that the production time of the result table is delayed, and the production efficiency of the result table is reduced. The factors that lead to the delay in throughput time of the results table are as follows: it is necessary to introduce other tasks into the upstream tasks of the results table. If the factors are solved, the effect of shortening the output time of the result table can be achieved on the premise of not introducing other tasks. To achieve this, the present disclosure performs the scoring and selecting process described above such that the optimization task is performed in an existing upstream task. Therefore, the output time of the result table can be shortened on the premise of not introducing other tasks.
As can be seen from fig. 3, compared to the description of some embodiments corresponding to fig. 2, the flow 300 of the task optimization method in some embodiments corresponding to fig. 3 embodies steps of expanding the selection of the critical tasks. Therefore, the solutions described in the embodiments can select the tasks that need to be optimized, and by optimizing these key tasks, the output duration of the result table can be shortened and the output efficiency of the result table can be improved without reducing the tasks in the task link and introducing other tasks.
With further reference to fig. 4, as an implementation of the methods shown in the above figures, the present disclosure provides some embodiments of a task optimization device, which correspond to those of the method embodiments shown in fig. 2, and which may be applied in various electronic devices in particular.
As shown in FIG. 4, the task optimization device 400 of some embodiments includes: a first generation unit 401, a splitting unit 402, a first determination unit 403, a second determination unit 404, a selection unit 405, and a second generation unit 406. The first generating unit 401 is configured to, in response to receiving information of a result table to be optimized, determine a result table represented by the information of the result table to be optimized as a target result table, and determine a path on which the target result table depends to be generated, to obtain a dependent path directed graph, where nodes in the dependent path directed graph are used for representing tasks for generating the result table; the splitting unit 402 is configured to split the dependency path directed graph to obtain a task link set; the first determining unit 403 is configured to determine the execution time length of each task in the task link set; the second determining unit 404 is configured to determine an execution time of each task link in the task link set according to the execution time of each task in the task link set; a selecting unit 405 configured to select a task link with an execution duration greater than or equal to a first preset threshold from the task link set as a target task link, so as to obtain a target task link set; and the second generating unit 406 is configured to generate a set of mission critical information from the set of target mission links and to send the set of mission critical information to a display terminal.
It will be understood that the elements described in the apparatus 400 correspond to various steps in the method described with reference to fig. 2. Thus, the operations, features and resulting advantages described above with respect to the method are also applicable to the apparatus 400 and the units included therein, and will not be described herein again.
Referring now to FIG. 5, a block diagram of an electronic device (such as computing device 101 shown in FIG. 1) 500 suitable for use in implementing some embodiments of the present disclosure is shown. The electronic device shown in fig. 5 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present disclosure.
As shown in fig. 5, electronic device 500 may include a processing means (e.g., central processing unit, graphics processor, etc.) 501 that may perform various appropriate actions and processes in accordance with a program stored in a Read Only Memory (ROM) 502 or a program loaded from a storage means 508 into a Random Access Memory (RAM) 503. In the RAM 503, various programs and data necessary for the operation of the electronic apparatus 500 are also stored. The processing device 501, the ROM 502, and the RAM 503 are connected to each other through a bus 504. An input/output (I/O) interface 505 is also connected to bus 504.
Generally, the following devices may be connected to the I/O interface 505: input devices 506 including, for example, a touch screen, touch pad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, etc.; output devices 507 including, for example, a Liquid Crystal Display (LCD), speakers, vibrators, and the like; storage devices 508 including, for example, magnetic tape, hard disk, etc.; and a communication device 509. The communication means 509 may allow the electronic device 500 to communicate with other devices wirelessly or by wire to exchange data. While fig. 5 illustrates an electronic device 500 having various means, it is to be understood that not all illustrated means are required to be implemented or provided. More or fewer devices may alternatively be implemented or provided. Each block shown in fig. 5 may represent one device or may represent multiple devices as desired.
In particular, according to some embodiments of the present disclosure, the processes described above with reference to the flow diagrams may be implemented as computer software programs. For example, some embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In some such embodiments, the computer program may be downloaded and installed from a network via the communication means 509, or installed from the storage means 508, or installed from the ROM 502. The computer program, when executed by the processing device 501, performs the above-described functions defined in the methods of some embodiments of the present disclosure.
It should be noted that the computer readable medium described in some embodiments of the present disclosure may be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In some embodiments of the disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In some embodiments of the present disclosure, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, optical cables, RF (radio frequency), etc., or any suitable combination of the foregoing.
In some embodiments, the clients, servers may communicate using any currently known or future developed network Protocol, such as HTTP (HyperText Transfer Protocol), and may interconnect with any form or medium of digital data communication (e.g., a communications network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), the Internet (e.g., the Internet), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future developed network.
The computer readable medium may be embodied in the electronic device; or may exist separately without being assembled into the electronic device. The computer readable medium carries one or more programs which, when executed by the electronic device, cause the electronic device to: and in response to receiving the information of the result table to be optimized, determining the result table represented by the information of the result table to be optimized as a target result table, and determining the path on which the target result table depends to be generated to obtain a dependent path directed graph. And the nodes in the dependent path directed graph are used for characterizing the task of generating the result table. And splitting the dependent path directed graph to obtain a task link set. And determining the execution time length of each task in the task link set. And determining the execution time length of each task link in the task link set according to the execution time length of each task in the task link set. And selecting the task link with the execution duration being greater than or equal to a first preset threshold value from the task link set as a target task link to obtain a target task link set. And generating a key task information set according to the target task link set, and sending the key task information set to a display terminal.
Computer program code for carrying out operations for embodiments of the present disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + +, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units described in some embodiments of the present disclosure may be implemented by software, and may also be implemented by hardware. The described units may also be provided in a processor, and may be described as: a processor includes a first generation unit, a splitting unit, a first determination unit, a second determination unit, a selection unit, and a second generation unit. The names of these units do not form a limitation on the unit itself in some cases, and for example, the first determination unit may also be described as a "unit that determines the execution time length of each task in the task link set".
The functions described herein above may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), systems on a chip (SOCs), Complex Programmable Logic Devices (CPLDs), and the like.
The foregoing description is only exemplary of the preferred embodiments of the disclosure and is illustrative of the principles of the technology employed. It will be appreciated by those skilled in the art that the scope of the invention in the embodiments of the present disclosure is not limited to the specific combination of the above-mentioned features, but also encompasses other embodiments in which any combination of the above-mentioned features or their equivalents is made without departing from the inventive concept as defined above. For example, the above features and (but not limited to) technical features with similar functions disclosed in the embodiments of the present disclosure are mutually replaced to form the technical solution.
Claims (10)
1. A method of task optimization, comprising:
in response to receiving information of a result table to be optimized, determining the result table represented by the information of the result table to be optimized as a target result table, determining a path on which the target result table depends, and obtaining a dependent path directed graph, wherein nodes in the dependent path directed graph are used for representing tasks for generating the result table;
splitting the dependence path directed graph to obtain a task link set;
determining the execution duration of each task in the task link set;
determining the execution duration of each task link in the task link set according to the execution duration of each task in the task link set;
selecting a task link with the execution duration being greater than or equal to a first preset threshold value from the task link set as a target task link to obtain a target task link set;
and generating a key task information set according to the target task link set, and sending the key task information set to a display terminal.
2. The method of claim 1, wherein the determining the path on which the target result table depends results in a dependent path directed graph, comprising:
determining the task generating the target result table as a target task;
and generating a dependency path directed graph by taking the target task as a terminal point according to the dependency relationship among the tasks.
3. The method of claim 1, wherein the determining the execution duration of each task in the set of task links comprises:
acquiring the execution time of each task in the task link set within a preset time period to obtain a task execution time group set, wherein the task execution time groups in the task execution time group set correspond to the tasks in the task link set one by one;
and executing averaging processing on each task execution time group in the task execution time group set to generate a first target task execution time to obtain a first target task execution time set.
4. The method of claim 3, wherein the performing an averaging process on each of the set of task execution time durations to generate a first target task execution time duration comprises:
determining the standard deviation and the mean value of each task execution time length in the task execution time length group;
selecting task execution time meeting a first preset condition from the task execution time group as second target task execution time to obtain a second target task execution time group, wherein the first preset condition is that the task execution time is greater than the difference value of two times of the mean value and the standard deviation and less than the sum of two times of the mean value and the standard deviation;
and determining the average value of the execution time of each second target task in the second target task execution time group as the execution time of the first target task.
5. The method of claim 1, wherein the generating a set of mission critical information from the set of target task links and sending the set of mission critical information to a display terminal comprises:
determining the tasks included in the target task link set as first tasks to obtain a first task set;
performing scoring processing on each first task in the first task set to obtain a task score value set;
in response to the task score value larger than or equal to a second preset threshold value in the task score value set, determining a first task corresponding to the task score value larger than or equal to the second preset threshold value as a second task, and obtaining a second task set;
and selecting a second task with the first target task execution time length being greater than or equal to a third preset threshold value from the second task set as a key task to obtain a key task set.
6. The method of claim 5, wherein said performing a scoring process on each first task of the first set of tasks comprises:
determining the times of the first task appearing in the target task link set to obtain target times;
and determining the product value of the target times and the first target task execution time length corresponding to the first task as the task score value corresponding to the first task.
7. The method of claim 6, wherein the generating a set of mission critical information from the set of target task links and sending the set of mission critical information to a display terminal further comprises:
determining each key task in the key task set, the target times corresponding to the key task and the first target task execution time corresponding to the key task as key task information to obtain a key task information set, and sending the key task information set to a display terminal.
8. A task optimization device, comprising:
the first generation unit is configured to respond to the received information of the result table to be optimized, determine the result table represented by the information of the result table to be optimized as a target result table, determine a path on which the target result table depends, and obtain a dependent path directed graph, wherein nodes in the dependent path directed graph are used for representing tasks for generating the result table;
the splitting unit is configured to split the dependency path directed graph to obtain a task link set;
a first determining unit configured to determine an execution time length of each task in the task link set;
the second determining unit is configured to determine the execution time of each task link in the task link set according to the execution time of each task in the task link set;
the selection unit is configured to select a task link with the execution duration being greater than or equal to a first preset threshold value from the task link set as a target task link to obtain a target task link set;
and the second generation unit is configured to generate a key task information set according to the target task link set and send the key task information set to a display terminal.
9. An electronic device, comprising:
one or more processors;
a storage device having one or more programs stored thereon;
when executed by the one or more processors, cause the one or more processors to implement the method of any one of claims 1-7.
10. A computer-readable medium, on which a computer program is stored, wherein the program, when executed by a processor, implements the method of any one of claims 1 to 7.
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