CN110716813A - Data stream processing method and device, readable storage medium and processor - Google Patents
Data stream processing method and device, readable storage medium and processor Download PDFInfo
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- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/46—Multiprogramming arrangements
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Abstract
The embodiment of the invention provides a data stream processing method, a data stream processing device, a readable storage medium and a processor, and belongs to the technical field of data processing. The method comprises the following steps: dividing the data stream into a plurality of divided data; aiming at least one piece of divided data in the plurality of pieces of divided data, configuring a service main key of the data for each piece of divided data; dividing the same type of data in each divided data into the same memory queue according to the service main key to form a plurality of memory queues; and carrying out parallel processing on the plurality of memory queues. The data stream processing method, the data stream processing device, the readable storage medium and the processor can ensure the consistency of data services and simultaneously realize the rapid processing of the data streams.
Description
Technical Field
The present invention relates to the field of data processing technologies, and in particular, to a data stream processing method, an apparatus, a readable storage medium, and a processor.
Background
kafka or rockmq can be regarded as a message component, data can be divided into several parts by dividing (partition) the same topic (topic), but each part of divided data can be processed by only one consumer of one consumer group at the same time, and if the consumption efficiency is improved, the number of the consumers can be increased by adjusting the number of the divided parts in a conventional mode, but the number of the divided parts cannot be infinitely enlarged; in addition, in a general project, the same consumer processes distributed data through a single thread, which is certainly a waste, and meanwhile, even if a multi-thread mode is adopted in the same consumer, the same divided data is consumed relatively out of order, and under special conditions, the orderliness of services cannot be guaranteed.
Disclosure of Invention
Embodiments of the present invention provide a data stream processing method, an apparatus, a readable storage medium, and a processor, which can implement fast processing of a data stream while ensuring consistency in data services.
In order to achieve the above object, an embodiment of the present invention provides a data stream processing method, where the method includes: dividing the data stream into a plurality of divided data; aiming at least one piece of divided data in the plurality of pieces of divided data, configuring a service main key of the data for each piece of divided data; dividing the same type of data in each divided data into the same memory queue according to the service main key to form a plurality of memory queues; and carrying out parallel processing on the plurality of memory queues.
Preferably, the step of dividing the same type of data in each divided data into the same memory queue according to the service primary key to form a plurality of memory queues is performed by a hash algorithm.
Preferably, the hash algorithm is the murmurur hash2 algorithm or the murmurur hash3 algorithm.
Preferably, the parallel processing of the plurality of memory queues includes: respectively putting the plurality of memory queues into a plurality of threads, wherein one thread corresponds to one memory queue; the multiple threads are executed in parallel.
An embodiment of the present invention further provides a data stream processing apparatus, where the apparatus includes: the device comprises a dividing unit, a configuration unit, a slicing unit and a processing unit, wherein the dividing unit is used for dividing the data stream into a plurality of pieces of divided data; the configuration unit is used for configuring a service main key of data for each piece of divided data aiming at least one piece of divided data in the plurality of pieces of divided data; the fragmentation unit is used for dividing the same type of data in each part of divided data into the same memory queue according to the service main key so as to form a plurality of memory queues; the processing unit is used for carrying out parallel processing on the plurality of memory queues.
Preferably, the operations performed by the fragmentation unit are performed by a hashing algorithm.
Preferably, the hash algorithm is the murmurur hash2 algorithm or the murmurur hash3 algorithm.
Preferably, the parallel processing of the plurality of memory queues includes: respectively putting the plurality of memory queues into a plurality of threads, wherein one thread corresponds to one memory queue; the multiple threads are executed in parallel.
Embodiments of the present invention also provide a machine-readable storage medium, which stores instructions for causing a machine to execute the above-mentioned data stream processing method.
An embodiment of the present invention further provides a processor, configured to run a program, where the program is run to perform: a method of data stream processing as hereinbefore described.
By adopting the technical scheme, the data stream processing method, the device, the readable storage medium and the processor provided by the embodiment of the invention are adopted, and aiming at least one piece of divided data in a plurality of pieces of divided data, a service main key of the data is configured for each piece of divided data; dividing the same type of data in each divided data into the same memory queue according to the service main key to form a plurality of memory queues; and carrying out parallel processing on the plurality of memory queues. Because each type of data is positioned in one queue and the queues are processed in parallel, the consistency of data service can be ensured and the data flow can be processed quickly.
Additional features and advantages of embodiments of the invention will be set forth in the detailed description which follows.
Drawings
The accompanying drawings, which are included to provide a further understanding of the embodiments of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the embodiments of the invention without limiting the embodiments of the invention. In the drawings:
fig. 1 is a flowchart of a data stream processing method according to an embodiment of the present invention;
fig. 2 is a flowchart of a data stream processing method according to another embodiment of the present invention;
fig. 3 is a schematic flow chart illustrating an implementation of a data stream processing method according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of a data stream processing apparatus according to an embodiment of the present invention.
Description of the reference numerals
1 dividing unit 2 configuration unit
3 slicing unit 4 processing unit.
Detailed Description
The following detailed description of embodiments of the invention refers to the accompanying drawings. It should be understood that the detailed description and specific examples, while indicating embodiments of the invention, are given by way of illustration and explanation only, not limitation.
Fig. 1 is a flowchart of a data stream processing method according to an embodiment of the present invention. As shown in fig. 1, the method includes:
step S11, dividing the data stream into a plurality of divided data;
specifically, kafka or rockmq can be used as a message component, and kafka et al can divide data into multiple shares by performing a division (partition) process on a data stream of the same topic (topic) to form multiple divided data.
Step S12, for at least one of the plurality of divided data, configuring a service key of the data for each divided data;
specifically, according to the data characteristics, a service primary key is configured for each piece of divided data to be used as a basis for subsequent data slicing, for example, if the service primary key is a user ID, data of the same user may be a type of data, or if the service primary key is a house source ID, data of the same house source ID may be a type of data. If the service key is the house source ID, the data fragmentation is performed according to the house source ID.
Step S13, according to the service key, dividing the same type of data in each divided data into the same memory queue to form a plurality of memory queues;
specifically, a concurrency number n, i.e., the number of queues fragmented by the hash algorithm, is first allocated to the topic. Data fragmentation can then be performed by a hash (hash) algorithm, such as the murmurr hash2 algorithm or the murmurr hash3 algorithm. If the number of types of data is different from the number of the concurrency number n, for example, there are 4 types of data, and the concurrency number n is 2, then the 2 types of data may be placed in one queue, and the other 2 types of data may be placed in another queue, so as to ensure that the data of the same type is divided into one queue, but there is not necessarily only one type of data in one queue.
Step S14, parallel processing is performed on the plurality of memory queues.
Specifically, as shown in fig. 2, the parallel processing of the plurality of memory queues includes:
step S21, putting the plurality of memory queues into a plurality of threads, respectively, where one thread corresponds to one memory queue;
step S22, the plurality of threads are executed in parallel.
As described above, after one divided data is processed, the next divided data may be processed continuously, and the plurality of divided data may be processed in serial.
Fig. 3 is a schematic flow chart illustrating an execution of a data stream processing method according to an embodiment of the present invention. As shown in fig. 3, first, for each piece of divided data, batch acquisition is performed; then, the divided data may actually have a plurality of classes, for example, 1, 2, and 3 shown in the figure are respectively data of different classes; performing hash fragmentation, putting the data of the type represented by the 1 into a first queue, putting the data of the type represented by the 2 into a second queue, and putting the data of the type represented by the 3 into a third queue; finally, the three queues are processed in parallel.
Fig. 4 is a schematic structural diagram of a data stream processing apparatus according to an embodiment of the present invention. As shown in fig. 4, the apparatus includes: the device comprises a dividing unit 1, a configuration unit 2, a slicing unit 3 and a processing unit 4, wherein the dividing unit 1 is used for dividing the data stream into a plurality of pieces of divided data; the configuration unit 2 is configured to configure a service primary key of data for each piece of divided data, for at least one piece of divided data of the plurality of pieces of divided data; the fragmentation unit 3 is configured to divide the same type of data in each piece of divided data into the same memory queue according to the service primary key to form multiple memory queues; the processing unit 4 is configured to perform parallel processing on the plurality of memory queues.
Preferably, the operations performed by the fragmentation unit 3 are performed by a hash algorithm.
Preferably, the hash algorithm is the murmurur hash2 algorithm or the murmurur hash3 algorithm.
Preferably, the parallel processing of the plurality of memory queues includes: respectively putting the plurality of memory queues into a plurality of threads, wherein one thread corresponds to one memory queue; the multiple threads are executed in parallel.
The embodiments of the data stream processing apparatus are similar to the embodiments of the data stream processing method described above, and are not described herein again.
The data stream processing device comprises a processor and a memory, wherein the dividing unit, the configuration unit, the slicing unit, the processing unit and the like are stored in the memory as program units, and the processor executes the program units stored in the memory to realize corresponding functions.
The processor comprises a kernel, and the kernel calls the corresponding program unit from the memory. One or more than one kernel can be set, and the fast processing of the data stream is realized while the consistency of the data service is ensured by adjusting the kernel parameters.
The memory may include volatile memory in a computer readable medium, Random Access Memory (RAM) and/or nonvolatile memory such as Read Only Memory (ROM) or flash memory (flash RAM), and the memory includes at least one memory chip.
An embodiment of the present invention provides a storage medium on which a program is stored, the program implementing the data stream processing method when executed by a processor.
The embodiment of the invention provides a processor, which is used for running a program, wherein the data stream processing method is executed when the program runs.
The embodiment of the invention provides equipment, which comprises a processor, a memory and a program which is stored on the memory and can run on the processor, wherein the processor executes the program and realizes the following steps:
dividing the data stream into a plurality of divided data; aiming at least one piece of divided data in the plurality of pieces of divided data, configuring a service main key of the data for each piece of divided data; dividing the same type of data in each divided data into the same memory queue according to the service main key to form a plurality of memory queues; and carrying out parallel processing on the plurality of memory queues.
Preferably, the step of dividing the same type of data in each divided data into the same memory queue according to the service primary key to form a plurality of memory queues is performed by a hash algorithm.
Preferably, the hash algorithm is the murmurur hash2 algorithm or the murmurur hash3 algorithm.
Preferably, the parallel processing of the plurality of memory queues includes: respectively putting the plurality of memory queues into a plurality of threads, wherein one thread corresponds to one memory queue; the multiple threads are executed in parallel.
The device herein may be a server, a PC, a PAD, a mobile phone, etc.
The present application further provides a computer program product adapted to perform a program for initializing the following method steps when executed on a data processing device:
dividing the data stream into a plurality of divided data; aiming at least one piece of divided data in the plurality of pieces of divided data, configuring a service main key of the data for each piece of divided data; dividing the same type of data in each divided data into the same memory queue according to the service main key to form a plurality of memory queues; and carrying out parallel processing on the plurality of memory queues.
Preferably, the step of dividing the same type of data in each divided data into the same memory queue according to the service primary key to form a plurality of memory queues is performed by a hash algorithm.
Preferably, the hash algorithm is the murmurur hash2 algorithm or the murmurur hash3 algorithm.
Preferably, the parallel processing of the plurality of memory queues includes: respectively putting the plurality of memory queues into a plurality of threads, wherein one thread corresponds to one memory queue; the multiple threads are executed in parallel.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). The memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in the process, method, article, or apparatus that comprises the element.
The above are merely examples of the present application and are not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.
Claims (10)
1. A method for processing a data stream, the method comprising:
dividing the data stream into a plurality of divided data;
aiming at least one piece of divided data in the plurality of pieces of divided data, configuring a service main key of the data for each piece of divided data;
dividing the same type of data in each divided data into the same memory queue according to the service main key to form a plurality of memory queues;
and carrying out parallel processing on the plurality of memory queues.
2. The data stream processing method according to claim 1, wherein the step of dividing the same type of data in each of the divided data into the same memory queue according to the service key to form a plurality of memory queues is performed by a hash algorithm.
3. The data stream processing method of claim 2, wherein the hash algorithm is a murmurur hash2 algorithm or a murmurur hash3 algorithm.
4. The data stream processing method of claim 1, wherein the parallel processing of the plurality of memory queues comprises:
respectively putting the plurality of memory queues into a plurality of threads, wherein one thread corresponds to one memory queue;
the multiple threads are executed in parallel.
5. A data stream processing apparatus, characterized in that the apparatus comprises:
a dividing unit, a configuration unit, a slicing unit and a processing unit, wherein,
the dividing unit is used for dividing the data stream into a plurality of divided data;
the configuration unit is used for configuring a service main key of data for each piece of divided data aiming at least one piece of divided data in the plurality of pieces of divided data;
the fragmentation unit is used for dividing the same type of data in each part of divided data into the same memory queue according to the service main key so as to form a plurality of memory queues;
the processing unit is used for carrying out parallel processing on the plurality of memory queues.
6. The data stream processing apparatus according to claim 5, wherein the operations performed by the fragmentation unit are performed by a hashing algorithm.
7. The data stream processing apparatus of claim 6, wherein the hash algorithm is a murmurur hash2 algorithm or a murmurur hash3 algorithm.
8. The data stream processing apparatus of claim 5, wherein the parallel processing of the plurality of memory queues comprises:
respectively putting the plurality of memory queues into a plurality of threads, wherein one thread corresponds to one memory queue;
the multiple threads are executed in parallel.
9. A machine-readable storage medium having stored thereon instructions for causing a machine to perform the data stream processing method of any one of claims 1-4.
10. A processor configured to execute a program, wherein the program is configured to perform: a method of processing a data stream according to any of claims 1 to 4.
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