CN115438083A - Target data segmentation method and device and storage medium - Google Patents

Abstract

The application discloses a method and a device for segmenting target data and a storage medium. The target data segmentation method comprises the following steps: acquiring target data to be divided from a source data table, wherein the data type of the target data is a non-integer type; determining the capacity of a plurality of subtasks according to the preset segmentation quantity, wherein the subtasks are used for indicating slice data obtained after the target data are segmented; and segmenting the target data according to the capacity to generate a plurality of subtasks.

Description

Target data segmentation method and device and storage medium

Technical Field

The present application relates to the field of information technology, and in particular, to a method and an apparatus for segmenting target data, and a storage medium.

Background

For the existing heterogeneous synchronization tool at the source end segmentation strategy, segmentation is mainly performed according to integer types, and the principle is that according to min (id) + the size of a data value of each slice, the starting position and the end position of a first slice can be determined. I.e., [ min (id), min (id) + the size of each slice data value ], and so on, the second slice is [ min (id) + the size of each slice data value, min (id) + the size of each slice data value x 2], until the data slice is completed. If the values of the integer type are not continuous, a problem of non-uniform slicing is caused. And the use of the above-described manner to segment data of non-integer type also causes such a problem. The prior art has therefore great limitations for the slicing of non-integer types of data.

In view of the above technical problem in the prior art that the non-integer type data cannot be split, which causes high limitation, no effective solution has been proposed at present.

Disclosure of Invention

Embodiments of the present application provide a method and an apparatus for segmenting target data, and a storage medium, so as to at least solve a technical problem in the prior art that a non-integer type of data cannot be segmented, which results in high limitation.

According to an aspect of an embodiment of the present application, there is provided a method for segmenting target data, including: acquiring target data to be divided from a source data table, wherein the data type of the target data is a non-integer type; determining the capacity of a plurality of subtasks according to the preset segmentation quantity, wherein the subtasks are used for indicating slice data obtained after the target data are segmented; and segmenting the target data according to the capacity to generate a plurality of subtasks.

According to another aspect of embodiments of the present application, there is also provided a storage medium including a stored program, wherein the method of any one of the above is performed by a processor when the program is run.

According to another aspect of the embodiments of the present application, there is also provided a target data segmentation apparatus, including: the data acquisition module is used for acquiring target data to be divided from a source data table, wherein the data type of the target data is a non-integer type; the capacity determining module is used for determining the capacity of a plurality of subtasks according to the preset segmentation quantity, wherein the subtasks are used for indicating the sliced data obtained by segmenting the target data; and the task generation module is used for segmenting the target data according to the capacity to generate a plurality of subtasks.

According to another aspect of the embodiments of the present application, there is also provided a target data segmentation apparatus, including: a processor; and a memory coupled to the processor for providing instructions to the processor for processing the following processing steps: acquiring target data to be divided from a source data table, wherein the data type of the target data is a non-integer type; determining the capacity of a plurality of subtasks according to the preset segmentation quantity, wherein the subtasks are used for indicating the sliced data obtained after the target data is segmented; and segmenting the target data according to the capacity to generate a plurality of subtasks.

In the embodiment of the application, the computing device determines the capacity of the plurality of subtasks according to the preset segmentation quantity, and segments the target data according to the position of the target data to be segmented to generate the plurality of subtasks. Compared with the prior art, the technical scheme can segment the data of the non-integer type without being limited to the data of the integer type, so that the limitation on the segmentation of the data of the non-integer type is reduced. And the technical problem that the non-integer type data cannot be split in the prior art, so that the limitation is high is solved.

Drawings

The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:

fig. 1 is a hardware block diagram of a computing device for implementing the method according to embodiment 1 of the present application;

FIG. 2 is a schematic flow chart of a target data segmentation method according to the first aspect of embodiment 1 of the present application;

FIG. 3 is a schematic diagram of a module for segmenting target data according to a first aspect of embodiment 1 of the present application;

FIG. 4 is a schematic diagram of a target data slicing apparatus according to embodiment 2 of the present application; and

fig. 5 is a schematic diagram of a target data slicing apparatus according to embodiment 3 of the present application.

Detailed Description

In order to make those skilled in the art better understand the technical solutions of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. It is to be understood that the embodiments described are merely exemplary of some, and not all, of the present application. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.

It should be noted that the terms "first," "second," and the like in the description and claims of this application and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It should be understood that the data so used may be interchanged under appropriate circumstances such that embodiments of the application described herein may be implemented in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.

Example 1

According to the present embodiment, there is provided a method embodiment of a method for segmenting target data, it should be noted that the steps shown in the flowchart of the figure may be performed in a computer system such as a set of computer executable instructions, and that while a logical order is shown in the flowchart, in some cases the steps shown or described may be performed in an order different than here.

The method embodiments provided by the present embodiment may be executed in a mobile terminal, a computer terminal, a server or a similar computing device. Fig. 1 shows a hardware block diagram of a computing device for implementing a method of segmenting target data. As shown in fig. 1, the computing device may include one or more processors (which may include, but are not limited to, a processing device such as a microprocessor MCU or a programmable logic device FPGA), a memory for storing data, and a transmission device for communication functions. Besides, the method can also comprise the following steps: a display, an input/output interface (I/O interface), a Universal Serial Bus (USB) port (which may be included as one of the ports of the I/O interface), a network interface, a power source, and/or a camera. It will be understood by those skilled in the art that the structure shown in fig. 1 is only an illustration and is not intended to limit the structure of the electronic device. For example, the computing device may also include more or fewer components than shown in FIG. 1, or have a different configuration than shown in FIG. 1.

It should be noted that the one or more processors and/or other data processing circuitry described above may be referred to generally herein as "data processing circuitry". The data processing circuitry may be embodied in whole or in part in software, hardware, firmware, or any combination thereof. Further, the data processing circuitry may be a single, stand-alone processing module, or incorporated in whole or in part into any of the other elements in the computing device. As referred to in the embodiments of the application, the data processing circuit acts as a processor control (e.g. selection of a variable resistance termination path connected to the interface).

The memory may be configured to store software programs and modules of application software, such as a program instruction/data storage device corresponding to the target data splitting method in the embodiment of the present application, and the processor executes various functional applications and data processing by operating the software programs and modules stored in the memory, that is, implements the above-mentioned target data splitting method of the application program. The memory may include high speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory may further include memory located remotely from the processor, which may be connected to the computing device over a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.

The transmission device is used for receiving or transmitting data via a network. Specific examples of such networks may include wireless networks provided by communication providers of the computing devices. In one example, the transmission device includes a Network adapter (NIC) that can be connected to other Network devices through a base station to communicate with the internet. In one example, the transmission device may be a Radio Frequency (RF) module, which is used to communicate with the internet in a wireless manner.

The display may be, for example, a touch screen type Liquid Crystal Display (LCD) that may enable a user to interact with a user interface of the computing device.

It should be noted here that in some alternative embodiments, the computing device shown in fig. 1 described above may include hardware elements (including circuitry), software elements (including computer code stored on a computer-readable medium), or a combination of both hardware and software elements. It should be noted that FIG. 1 is only one example of a particular specific example and is intended to illustrate the types of components that may be present in a computing device as described above.

In the above operating environment, according to the first aspect of the present embodiment, a method for segmenting target data is provided, and the method is implemented by the computing device shown in fig. 1. Fig. 2 shows a flow diagram of the method, which, with reference to fig. 2, comprises:

s202: acquiring target data to be divided from a source data table, wherein the data type of the target data is a non-integer type;

s204: determining the capacity of a plurality of subtasks according to the preset segmentation quantity, wherein the subtasks are used for indicating slice data obtained after the target data are segmented; and

s206: and segmenting the target data according to the capacity to generate a plurality of subtasks.

Specifically, when the computing device needs to segment the target data stored in the source data table, the target data to be segmented is obtained from the source data table. And wherein the data type of the target data is a non-integer type.

Further, the computing device presets the number of the segmentations of the segmentation target data, and takes the number of the segmentations as the number of the subtasks. And then, the computing equipment acquires the data volume of the target data, and the capacity of each subtask is calculated according to the data volume of the target data and the number of the subtasks through a preset computing model. The capacity of each subtask is the data volume of corresponding slice data obtained after target data are segmented.

Further, the computing device sorts the target data according to the capacity of the subtasks, and acquires the start position and the end position of each slice data from the target data. For example, the capacity of the subtask is 3, the target data that is not sorted is "abfdgcieh", and the computing device takes the capacity of the subtask as the number of target data participating in sorting at a time, that is, sorts the target data until the sorted first three-bit data is obtained, and thus the sorting ends. The top 3 bits of data resulting from sorting are "abc". Thus, the computing device sorts the target data according to the capacity of the subtask (i.e., 3), resulting in "abcfdgieh," and determines the start position and the end position of the first slice data according to the capacity of the subtask. Where the start position is "a" and the end position is "c", the first slice data corresponding to the start position and the end position is "abc", and the target data obtained after the first slicing is "fdgieh".

The computing device then ranks the target data "fdgieh" obtained after the first slicing until the top three ranked bits are obtained, and the ranking is complete. The data of the first 3 bits obtained after sorting is "def", and thus the target data after sorting is "defgih". The starting point position of the second slice data is "d", the end point position is "f", the second slice data corresponding to the starting point position and the end point position is "def", and the target data after the second slicing is "gih".

The computing device then sorts the target data "gih" obtained after the second slicing so that the first 3-bit data obtained after the sorting is "ghi" and so that the sorted target data is "gih". The starting point position of the third slice data is "g", the end point position is "i", so that the third slice data corresponding to the starting point position and the end point position is "gih", and the target data after the third slicing is "gih".

Thus, the computing device generates three subtasks according to the above-mentioned segmentation manner, namely, a subtask 1 corresponding to the slice data "abc", a subtask 2 corresponding to the slice data "def", and a subtask 3 corresponding to the slice data "ghj".

As described in the background art, for the existing heterogeneous synchronization tool, the source segmentation strategy is mainly to perform segmentation on integer types, and the principle is that according to min (id) + the data value size of each slice, the start position and the end position of the first slice can be determined. I.e., [ min (id), min (id) + the size of each slice data value ], and so on, the second slice is [ min (id) + the size of each slice data value, min (id) + the size of each slice data value x 2], until the data slice is completed. If the values of the integer type are not continuous, a problem of non-uniform slicing is caused. And the use of the above-described manner to segment data of non-integer type also causes such a problem. The prior art therefore has great limitations for the slicing of non-integer types of data.

For the technical problems, according to the technical scheme of the embodiment of the application, the computing equipment determines the capacity of the multiple subtasks according to the preset segmentation quantity, and segments the target data according to the position of the target data to be segmented to generate the multiple subtasks. Compared with the prior art, the technical scheme can segment the non-integer type data without being limited to the integer type data, so that the limitation on the segmentation of the non-integer type data is reduced. And the technical problem that the non-integer type data cannot be split in the prior art, so that the limitation is high is solved.

Optionally, the operation of determining the capacity of the plurality of subtasks according to the preset number of splits includes: determining the segmentation quantity according to the preset quantity of parallel task groups and the quantity of corresponding subtasks, wherein the parallel task groups comprise a plurality of subtasks; and determining the capacity of the plurality of subtasks according to the data volume and the segmentation quantity of the target data through a preset calculation model.

Specifically, referring to fig. 3, the computing device presets the number of parallel task groups and the number of corresponding subtasks. Each parallel task group comprises a plurality of subtasks, for example, the parallel task group 1 comprises subtasks 1 to 3, the parallel task group 2 comprises subtasks 4 to 6, and the parallel task group 3 comprises subtasks 7 to 9. The computing device then takes the number of subtasks in all parallel task groups as the number of splits. For example, if the number of subtasks is 9, the computing device takes the number of subtasks as the number of splits, i.e., the number of splits is also 9.

Further, the computing device obtains a data amount of the target data to calculate a volume of the sub-task according to a computing model, wherein a computing formula corresponding to the computing model is:

capacity of subtask = ROUNDUP [ amount of target data/(parallel task group): number of subtasks per group ]

Where the function ROUNDUP () is used to round up a number (i.e., the number incremented by 1 if the number to be truncated is less than 4).

In addition, in the case where the target data is not evenly divisible, the capacity of the last subtask is:

capacity of last subtask = data size of target data-capacity of other subtasks-parallel task group/number of subtasks per group

Therefore, the technical scheme accurately calculates the capacity of the subtasks through the preset calculation module, and improves the calculation speed.

Optionally, the method further comprises: the subtask writes the slice data into the buffer through a read thread; and the subtask reads the slice data from the buffer through the write thread.

Specifically, the computing device simultaneously starts corresponding subtasks in the parallel task group through a preset scheduler. For example, the subtask 1 in the parallel task group 1, the subtask 4 in the parallel task group 2, and the subtask 7 in the parallel task group 3 are simultaneously started. One of the subtasks corresponds to one of the task executors, and each task executor comprises a buffer, a reading thread and a writing thread.

After the computing device slices the target data, each parallel task group starts one subtask in series, that is, the subtask 1 in the parallel task group 1, the subtask 4 in the parallel task group 2, and the subtask 7 in the parallel task group 3 start at the same time, so that the subtask 1 in the parallel task group 1 reads corresponding slice data through the set read thread, and then writes the slice data into the buffer. When the cached data in the buffer reaches the upper limit, the subtask 1 in the parallel task group 1 reads the slice data from the buffer through the set write thread, and writes the slice data into the target end which needs to use the slice data. Similarly, the subtask 4 in the parallel task group 2 and the subtask 7 in the parallel task group 3 process the sliced data according to the method for processing the sliced data of the subtask 1.

Therefore, the technical scheme limits the data transmission speed through the buffer, thereby achieving the purpose of flow control. In the synchronization process, the technical scheme can control the execution of the subtasks to reach the optimal state in a flow control mode, and enables the source end and the target end to have a relatively proper pressure control in the synchronization task process.

Optionally, the method further comprises: and configuring configuration information of the subtasks, wherein the configuration information at least comprises the maximum byte number, the recording number, the writing speed and the recording speed of the buffer.

Further, the computing device configures configuration information of each subtask, such as a maximum number of bytes and a number of records to be accommodated by the buffer, and may also configure a default value of a writing speed byte speed, such as 1MB/s, the default value of the recording speed being 10000 pieces/s. The specific current limiting logic records the number of reading success bytes, the number of reading success records, the number of reading failure bytes, the number of reading failure records and the execution time of the execution operation every time a reading thread is executed. If the execution time is beyond the configured control interval, the flow monitoring is carried out, the principle is that the speed can be obtained by dividing the relevant data statistics by the time, and if the current flow is beyond the configured speed, the thread is read to carry out the dormant state. Therefore, the technical scheme configures the configuration information in advance, so that appropriate data for controlling the flow can be obtained, and the execution efficiency is improved.

Further, referring to fig. 1, according to a second aspect of the present embodiment, there is provided a storage medium. The storage medium comprises a stored program, wherein the method of any of the above is performed by a processor when the program is run.

Therefore, according to the embodiment, the computing device determines the capacity of the plurality of subtasks according to the preset segmentation quantity, and segments the target data according to the position of the target data to be segmented to generate the plurality of subtasks. Compared with the prior art, the technical scheme can segment the non-integer type data without being limited to the integer type data, so that the limitation on the segmentation of the non-integer type data is reduced. And the technical problem that the limitation is high due to the fact that non-integer type data cannot be split in the prior art is solved.

It should be noted that, for simplicity of description, the above-mentioned method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present invention is not limited by the order of acts, as some steps may occur in other orders or concurrently in accordance with the invention. Further, those skilled in the art should also appreciate that the embodiments described in the specification are preferred embodiments and that the acts and modules referred to are not necessarily required by the invention.

Through the description of the foregoing embodiments, it is clear to those skilled in the art that the method according to the foregoing embodiments may be implemented by software plus a necessary general hardware platform, and certainly may also be implemented by hardware, but the former is a better implementation mode in many cases. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which is stored in a storage medium (e.g., ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal device (e.g., a mobile phone, a computer, a server, or a network device) to execute the method according to the embodiments of the present invention.

Example 2

Fig. 4 shows a segmentation apparatus 400 of object data according to the present embodiment, which apparatus 400 corresponds to the method according to the first aspect of embodiment 1. Referring to fig. 4, the apparatus 400 includes: a data obtaining module 410, configured to obtain target data to be divided from a source data table, where a data type of the target data is a non-integer type; a capacity determining module 420, configured to determine capacities of multiple subtasks according to a preset number of segmentations, where a subtask is used to indicate slice data obtained by segmenting target data; and a task generating module 430, configured to segment the target data according to the capacity to generate a plurality of subtasks.

Optionally, the capacity determining module 420 includes: the first determining submodule is used for determining the segmentation quantity according to the preset quantity of parallel task groups and the quantity of corresponding subtasks, wherein the parallel task groups comprise a plurality of subtasks; and the second determining submodule is used for determining the capacity of a plurality of subtasks according to the data volume and the segmentation quantity of the target data through a preset calculation model.

Optionally, the apparatus 400 further comprises: the write-in module is used for writing the slice data into the buffer by the subtask through the read thread; and the reading module is used for reading the slice data from the buffer by the subtask through a write thread.

Optionally, the apparatus further comprises: and the configuration module is used for configuring the configuration information of the subtasks, wherein the configuration information at least comprises the maximum byte number, the recording number, the writing speed and the recording speed of the buffer.

Therefore, according to the embodiment, the computing device determines the capacity of the plurality of subtasks according to the preset segmentation quantity, and segments the target data according to the position of the target data to be segmented to generate the plurality of subtasks. Compared with the prior art, the technical scheme can segment the data of the non-integer type without being limited to the data of the integer type, so that the limitation on the segmentation of the data of the non-integer type is reduced. And the technical problem that the limitation is high due to the fact that non-integer type data cannot be split in the prior art is solved.

Example 3

Fig. 5 shows a device 500 for slicing target data according to the first aspect of the present embodiment, the device 500 corresponding to the method according to the first aspect of embodiment 1. Referring to fig. 5, the apparatus 500 includes: a processor 510; and a memory 520 coupled to processor 510 for providing processor 510 with instructions to process the following process steps: acquiring target data to be divided from a source data table, wherein the data type of the target data is a non-integer type; determining the capacity of a plurality of subtasks according to the preset segmentation quantity, wherein the subtasks are used for indicating slice data obtained after the target data are segmented; and segmenting the target data according to the capacity to generate a plurality of subtasks.

Optionally, the operation of determining the capacity of the plurality of subtasks according to the preset number of splits includes: determining the segmentation quantity according to the preset quantity of parallel task groups and the quantity of corresponding subtasks, wherein the parallel task groups comprise a plurality of subtasks; and determining the capacity of the plurality of subtasks according to the data volume and the segmentation quantity of the target data through a preset calculation model.

Optionally, the apparatus 500 further comprises: the subtask writes the slice data into the buffer through a read thread; and the subtask reads the slice data from the buffer through the write thread.

Optionally, the apparatus 500 further comprises: and configuring configuration information of the subtasks, wherein the configuration information at least comprises the maximum byte number, the recording number, the writing speed and the recording speed of the buffer.

Therefore, according to the embodiment, the computing device determines the capacity of the plurality of subtasks according to the preset segmentation quantity, and segments the target data according to the position of the target data to be segmented to generate the plurality of subtasks. Compared with the prior art, the technical scheme can segment the data of the non-integer type without being limited to the data of the integer type, so that the limitation on the segmentation of the data of the non-integer type is reduced. And the technical problem that the limitation is high due to the fact that non-integer type data cannot be split in the prior art is solved.

The above-mentioned serial numbers of the embodiments of the present invention are only for description, and do not represent the advantages and disadvantages of the embodiments.

In the above embodiments of the present invention, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.

In the embodiments provided in the present application, it should be understood that the disclosed technology can be implemented in other ways. The above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one type of logical functional division, and other divisions may be implemented in practice, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, units or modules, and may be in an electrical or other form.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.

The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.

The foregoing is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and decorations can be made without departing from the principle of the present invention, and these modifications and decorations should also be regarded as the protection scope of the present invention.

Claims (10)

1. A method for segmenting target data is characterized by comprising the following steps:

acquiring target data to be divided from a source data table, wherein the data type of the target data is a non-integer type;

determining the capacity of a plurality of subtasks according to the preset segmentation quantity, wherein the subtasks are used for indicating the sliced data obtained after the target data is segmented; and

and segmenting the target data according to the capacity to generate a plurality of subtasks.

2. The method of claim 1, wherein the act of determining the capacity of the plurality of subtasks based on the predetermined number of splits comprises:

determining the segmentation quantity according to the preset quantity of parallel task groups and the quantity of corresponding subtasks, wherein the parallel task groups comprise a plurality of subtasks; and

and determining the capacity of the plurality of subtasks according to the data volume of the target data and the segmentation quantity through a preset calculation model.

3. The method of claim 1, further comprising:

the subtask writes the slice data into a buffer through a read thread; and

and the subtask reads the slice data from the buffer through a write thread.

4. The method of claim 3, further comprising:

and configuring configuration information of the subtasks, wherein the configuration information at least comprises the maximum byte number, the recording number, the writing speed and the recording speed of the buffer.

5. A storage medium comprising a stored program, wherein the method of any one of claims 1 to 4 is performed by a processor when the program is run.

6. A target data segmentation apparatus, comprising:

the data acquisition module is used for acquiring target data to be divided from a source data table, wherein the data type of the target data is a non-integer type;

the capacity determining module is used for determining the capacity of a plurality of subtasks according to the preset segmentation quantity, wherein the subtasks are used for indicating the sliced data obtained by segmenting the target data; and

and the task generation module is used for segmenting the target data according to the capacity to generate a plurality of subtasks.

7. The apparatus of claim 6, wherein the operation of determining the capacity of the plurality of subtasks based on the predetermined number of splits comprises:

the first determining submodule is used for determining the segmentation quantity according to the preset quantity of parallel task groups and the quantity of corresponding subtasks, wherein the parallel task groups comprise a plurality of subtasks; and

and the second determining submodule is used for determining the capacity of the plurality of subtasks according to the data volume of the target data and the segmentation quantity through a preset calculation model.

8. The apparatus of claim 6, further comprising:

the writing module is used for writing the slice data into a buffer by the subtask through a reading thread; and

and the reading module is used for reading the slice data from the buffer by the subtask through a write thread.

9. The apparatus of claim 8, further comprising:

and the configuration module is used for configuring the configuration information of the subtasks, wherein the configuration information at least comprises the maximum byte number, the recording number, the writing speed and the recording speed of the buffer.

10. A target data segmentation apparatus, comprising:

a processor; and

a memory coupled to the processor for providing instructions to the processor for processing the following processing steps:

acquiring target data to be divided from a source data table, wherein the data type of the target data is a non-integer type;

determining the capacity of a plurality of subtasks according to the preset segmentation quantity, wherein the subtasks are used for indicating slice data obtained after the target data are segmented; and

and segmenting the target data according to the capacity to generate a plurality of subtasks.

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