CN113342277A - Data processing method and device - Google Patents
Data processing method and device Download PDFInfo
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- CN113342277A CN113342277A CN202110688648.2A CN202110688648A CN113342277A CN 113342277 A CN113342277 A CN 113342277A CN 202110688648 A CN202110688648 A CN 202110688648A CN 113342277 A CN113342277 A CN 113342277A
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- G06F3/06—Digital input from, or digital output to, record carriers, e.g. RAID, emulated record carriers or networked record carriers
- G06F3/0601—Interfaces specially adapted for storage systems
- G06F3/0628—Interfaces specially adapted for storage systems making use of a particular technique
- G06F3/0655—Vertical data movement, i.e. input-output transfer; data movement between one or more hosts and one or more storage devices
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/06—Digital input from, or digital output to, record carriers, e.g. RAID, emulated record carriers or networked record carriers
- G06F3/0601—Interfaces specially adapted for storage systems
- G06F3/0628—Interfaces specially adapted for storage systems making use of a particular technique
- G06F3/0638—Organizing or formatting or addressing of data
- G06F3/0644—Management of space entities, e.g. partitions, extents, pools
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- G06F3/06—Digital input from, or digital output to, record carriers, e.g. RAID, emulated record carriers or networked record carriers
- G06F3/0601—Interfaces specially adapted for storage systems
- G06F3/0668—Interfaces specially adapted for storage systems adopting a particular infrastructure
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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
- G06F9/46—Multiprogramming arrangements
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- G06F9/5005—Allocation of resources, e.g. of the central processing unit [CPU] to service a request
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Abstract
The application provides a data processing method and a device, wherein the data processing method comprises the following steps: receiving a target service data acquisition request, wherein the target service data acquisition request comprises a target service identifier; determining and acquiring target service data in a target data source based on the target service identifier under the condition that the target service data corresponding to the target service identifier does not exist in the disk space of the service node; storing the target service data into a disk space of the service node, calculating the current disk space utilization rate of the service node and acquiring a preset disk space utilization rate, wherein the preset disk space utilization rate is determined according to a historical service data acquisition request; and under the condition that the current disk space utilization rate is greater than the preset disk space utilization rate, adjusting the disk space of the service node according to a preset disk space adjustment strategy.
Description
Technical Field
The present application relates to the field of data processing technologies, and in particular, to a data processing method. The application also relates to a data processing apparatus, a computing device, and a computer-readable storage medium.
Background
CDN services usually cache accessed data, a normal caching process is to fragment an entire file, the number of inodes increases and the memory usage increases (both Inode objects and associated objects need to occupy memory), and the disk capacity on a CDN machine is usually TB as a unit (55TB, i.e., 10 disks of 5.5T), and GB as a unit (128GB), and one fragment is usually 2Mb to 20Mb, which results in the number of files being approximately 288 ten thousand and 2883 ten thousand, and when the number of files increases and reaches the upper limit of memory usage, the service quality will be affected, so the space usage amount of the disk memory needs to be controlled within a reasonable range.
Disclosure of Invention
In view of this, the present application provides a data processing method. The application also relates to a data processing device, a computing device and a computer readable storage medium, which are used for solving the problem that the service quality is influenced due to the fact that the number of fragmented files in a cache is large and the occupied memory is large in the prior art. According to a first aspect of embodiments of the present application, there is provided a data processing method, including:
receiving a target service data acquisition request, wherein the target service data acquisition request comprises a target service identifier;
determining and acquiring target service data in a target data source based on the target service identifier under the condition that the target service data corresponding to the target service identifier does not exist in the disk space of the service node;
storing the target service data into a disk space of the service node, calculating the current disk space utilization rate of the service node and acquiring a preset disk space utilization rate, wherein the preset disk space utilization rate is determined according to a historical service data acquisition request;
and under the condition that the current disk space utilization rate is greater than the preset disk space utilization rate, adjusting the disk space of the service node according to a preset disk space adjustment strategy.
According to a second aspect of embodiments of the present application, there is provided a data processing apparatus including:
the system comprises a receiving module, a sending module and a receiving module, wherein the receiving module is configured to receive a target service data acquisition request, and the target service data acquisition request comprises a target service identifier;
the determining module is configured to determine and acquire target service data in a target data source based on the target service identifier under the condition that the target service data corresponding to the target service identifier does not exist in the disk space of the service node;
the computing module is configured to store the target service data into a disk space of the service node, compute a current disk space utilization rate of the service node and acquire a preset disk space utilization rate, wherein the preset disk space utilization rate is determined according to a historical service data acquisition request;
and the adjusting module is configured to adjust the disk space of the service node according to a preset disk space adjusting strategy under the condition that the current disk space utilization rate is greater than the preset disk space utilization rate.
According to a third aspect of embodiments herein, there is provided a computing device comprising a memory, a processor and computer instructions stored on the memory and executable on the processor, the processor implementing the steps of the data processing method when executing the instructions.
According to a fourth aspect of embodiments of the present application, there is provided a computer-readable storage medium storing computer instructions which, when executed by a processor, implement the steps of the data processing method.
The data processing method provided by the application comprises the steps of receiving a target service data acquisition request, wherein the target service data acquisition request comprises a target service identifier; determining and acquiring target service data in a target data source based on the target service identifier under the condition that the target service data corresponding to the target service identifier does not exist in the disk space of the service node; storing the target service data into a disk space of the service node, calculating the current disk space utilization rate of the service node and acquiring a preset disk space utilization rate, wherein the preset disk space utilization rate is determined according to a historical service data acquisition request; and under the condition that the current disk space utilization rate is greater than the preset disk space utilization rate, adjusting the disk space of the service node according to a preset disk space adjustment strategy.
According to the embodiment of the application, the upper limit value of the disk space utilization rate is determined according to the cache hit growth rate, and the files in the disk space are eliminated under the condition that the current disk space utilization rate is the maximum upper limit value, so that the disk space utilization rate is reduced, and the influence on the service quality caused by the fact that the memory reaches the use upper limit is avoided.
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Fig. 1 is a flowchart of a data processing method according to an embodiment of the present application;
FIG. 2 is a flowchart illustrating a method for calculating a current disk space utilization according to an embodiment of the present application;
fig. 3 is a flowchart of a method for obtaining a utilization rate of a predetermined disk space according to an embodiment of the present application;
fig. 4 is a processing flow chart of a data processing method applied to a service node a receiving a data acquisition request according to an embodiment of the present application;
FIG. 5 is a flowchart of a method for calculating a current disk space utilization according to an embodiment of the present application;
fig. 6 is a flowchart of a method for obtaining a utilization rate of a predetermined disk space according to an embodiment of the present application;
fig. 7 is a schematic structural diagram of a data processing apparatus according to an embodiment of the present application;
fig. 8 is a block diagram of a computing device according to an embodiment of the present application.
Detailed Description
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present application. This application is capable of implementation in many different ways than those herein set forth and of similar import by those skilled in the art without departing from the spirit of this application and is therefore not limited to the specific implementations disclosed below.
The terminology used in the one or more embodiments of the present application is for the purpose of describing particular embodiments only and is not intended to be limiting of the one or more embodiments of the present application. As used in one or more embodiments of the present application and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used in one or more embodiments of the present application refers to and encompasses any and all possible combinations of one or more of the associated listed items.
It will be understood that, although the terms first, second, etc. may be used herein in one or more embodiments of the present application to describe various information, these information should not be limited by these terms. These terms are only used to distinguish one type of information from another. For example, a first aspect may be termed a second aspect, and, similarly, a second aspect may be termed a first aspect, without departing from the scope of one or more embodiments of the present application. The word "if" as used herein may be interpreted as "at … …" or "when … …" or "in response to a determination", depending on the context.
First, the noun terms to which one or more embodiments of the present application relate are explained.
CDN: and edge servers are deployed in various places to provide content services for users.
Inode: each file in the Linux file system has 1 Inode for recording index information of the file.
SPDK: initiated by Intel, for use of NVMe SSD as an acceleration library for backend stored application software.
Through the SPDK technology, the CDN can bypass a file system of a system when caching, namely not using Inode, so that the memory is prevented from being excessively occupied; however, the SPDK has high specialization, extremely high development and maintenance costs, and is not easily widely used.
Based on this, in the present application, a data processing method is provided, and the present application simultaneously relates to a data processing apparatus, a computing device, and a computer-readable storage medium, which are individually detailed in the following embodiments.
Fig. 1 shows a flowchart of a data processing method according to an embodiment of the present application, which specifically includes the following steps 102 to 108:
step 102: receiving a target service data acquisition request, wherein the target service data acquisition request comprises a target service identifier.
The target service data acquisition request refers to a data acquisition request sent by a user or other service nodes and used for acquiring service data from the service nodes.
The target service data acquisition request carries a target service identifier, and target service data corresponding to the target service identifier can be determined in the service data of the service node according to the target service identifier.
The target service data refers to data related to a specific service, for example, in a video processing service, the target service data may be a video; in the audio processing service, the target service data may be audio; in the picture processing service, the target service data may be a picture or the like.
In a specific embodiment of the present application, taking receiving a video data acquisition request as an example, the video data acquisition request is received, where the video data acquisition request carries a video identifier "video a".
Step 104: and under the condition that the target service data corresponding to the target service identifier does not exist in the disk space of the service node, determining and acquiring the target service data in a target data source based on the target service identifier.
A service node refers to a node in a content distribution network. A Content Delivery Network (CDN) is a one-layer intelligent virtual Network based on the existing Internet, which is formed by placing node servers at various places in the Network, and can redirect a user's request to a service node closest to the user in real time according to Network traffic, connection of each node, load conditions, distance to the user, response time, and other comprehensive information, and the service Content is cached in the node servers, so that the user can obtain desired Content nearby, the problem of Internet Network congestion is solved, and the response speed of the user accessing a website is increased.
The target data source refers to a service node storing an original address of the service data, namely a data source of the service node corresponding to the target service data; the data stored by the service node is part of data distributed to the service node by the content distribution network, namely the service node stores part of data in the data source; when the service data required by the service acquisition request does not exist in the service node, the service data can be acquired from the data source.
The disk space of the service node refers to the disk space of the service node for storing data.
The target service data acquisition request carries a target service identifier, and is inquired at a service node according to the target service identifier, and if the target service data corresponding to the target service data acquisition request is stored at the service node, the target service data corresponding to the target service identifier is read from the service node; and if the service data corresponding to the request is not inquired in the service node, determining a target data source stored by the target service data according to the target service identifier, and acquiring the target service data corresponding to the target service identifier from the target data source.
In a specific embodiment of the present application, taking an example that target service data 1 is stored in a serving node B, and target service data 1, target service data 2, and target service data 3 are stored in a target data source C, it is determined that a target service identifier is "2" and corresponds to target service data 2. And under the condition that the target service data 2 corresponding to the target service identifier "2" is not read in the service node B, determining a target data source C based on the target service identifier "2" and acquiring the target service data 2 corresponding to the target service identifier "2" from the target data source C.
In another specific embodiment of the present application, after receiving the target service data acquisition request, the method further includes:
and under the condition that target service data corresponding to the target service identifier exists in the disk space of the service node, acquiring the target service data corresponding to the target service identifier in the disk space of the service node.
In practical application, if the target service data corresponding to the target service identifier is stored in the service node, the target service data can be directly read from the disk space of the service node, and subsequent operation processing is performed.
For example, the service node Q stores target service data 5 and target service data 6, and when the target service identifier is "5", the service node Q queries the target service data 5 corresponding to the target service identifier "5", that is, directly obtains the target service data 5 corresponding to the target service identifier "5" in the disk space of the service node Q.
Step 106: and storing the target service data into the disk space of the service node, calculating the current disk space utilization rate of the service node and acquiring a preset disk space utilization rate, wherein the preset disk space utilization rate is determined according to the historical service data acquisition request.
After the target service data is acquired from the target data source, the target service data needs to be stored in the disk space of the service node. The current disk space utilization rate refers to the utilization degree of the current data of the service node. The preset disk space utilization rate refers to a preset upper limit value of usable disk space. And under the condition that the utilization rate of the disk space is less than the preset utilization rate of the disk space, the service node can achieve the optimal service performance.
Specifically, storing the target service data in the disk space of the service node includes S1062 to S1066:
and S1062, acquiring a preset fragment value.
When the target service data is stored in the service node, the target service data needs to be fragmented, the preset fragmentation value refers to a fragmentation value used when the data is fragmented, and the target service data can be divided into at least two service sub-data consistent with the preset fragmentation value through the preset fragmentation value. For example, the preset fragmentation value may be 2Mb, and when the target traffic data is 7Mb, the target traffic data may be divided into 4 data fragments with a size of 2 Mb.
S1064, fragmenting the target service data according to the preset fragmentation value to obtain the target service sub-data.
The target service subdata refers to data obtained by fragmenting target service data according to a preset fragmentation value, and is used for storing the data to the service node to finish the process of storing the data into the service node.
The target service data is fragmented according to a preset fragmentation value to obtain at least two service sub-data, each service sub-data is used as the target service sub-data, and still taking the target service data P as 7Mb and the preset fragmentation value as 2Mb as examples, 4 service sub-data P1, P2, P3 and P4 can be obtained, and the service sub-data P1, P2, P3 and P4 are respectively stored to the service node.
S1066, storing the target service subdata into the disk space of the service node.
And storing the target service sub-data obtained by fragmenting the target service data according to the fragmentation value into the disk space of the service node receiving the request.
In a specific embodiment of the present application, for example, storing picture data in a disk space of a service node, obtaining a preset fragmentation value of 2Mb, fragmenting the picture data according to the preset fragmentation value of 2Mb, and obtaining picture sub-data a and picture sub-data b, where file sizes of the picture sub-data a and the picture sub-data b are both the preset fragmentation value of 2 Mb; and storing the picture sub-data a and the picture sub-data b into the disk space of the service node.
After the target service data is stored in the disk space of the service node, calculating a current disk space utilization rate of the service node, specifically, a method for calculating the current disk space utilization rate is shown in fig. 2, where fig. 2 is a flowchart of a method for calculating the current disk space utilization rate according to an embodiment of the present application, and includes steps 202 to 206:
step 202: and acquiring the current disk space utilization capacity and the total disk space capacity of the service node.
The current disk space usage capacity refers to the amount of space that has been used by the disk space. The total capacity of the disk space refers to the maximum capacity of the disk space capable of storing data. For example, the current disk usage capacity is 4.7TB, and the total disk space capacity is 5.5 TB.
Step 204: and calculating the ratio of the current disk space utilization capacity to the total disk space capacity.
And dividing the current disk space utilization capacity by the total disk space capacity to obtain the ratio of the current disk space utilization capacity to the total disk space capacity.
Step 206: and taking the ratio as the current disk space utilization rate of the service node.
In a specific embodiment of the application, taking calculation of the current disk space utilization rate of the service node G as an example, the current disk space usage capacity is obtained as 4.7TB, and the total disk space capacity is obtained as 5.5 TB; and the current disk space utilization rate of the service node G is obtained by dividing the current disk space usage capacity 4.7TB by the total disk space capacity 5.5 TB.
The preset disk space utilization rate is obtained while the current disk space utilization rate is calculated, and the subsequent steps are convenient to process the preset disk space utilization rate. The preset disk space utilization rate refers to a disk space utilization rate determined according to a historical service data acquisition request, where the historical service data acquisition request refers to information related to a service data acquisition request acquired within a preset time interval, such as the total number of requests of the service data acquisition request, whether each service data acquisition request inquires service data in the service node, and the like. For example, in the past 1 minute, 20 service data acquisition requests are acquired, wherein 15 service data requests inquire corresponding service data at the service node, and 5 service data requests do not acquire corresponding service data at the service node.
Specifically, fig. 3 is a flowchart of a method for obtaining a preset disk space utilization ratio according to an embodiment of the present application, where the method for obtaining a preset disk space utilization ratio includes steps 302 to 308:
step 302: and receiving a disk space utilization rate adjusting instruction in the current statistical period.
The statistical period refers to a fixed time period, and the disk space utilization rate adjustment is performed every time a statistical period passes, for example, the statistical period may be 10 seconds, 20 seconds, or 30 seconds; the disk space utilization adjustment command may be received once every statistical period, for example, when the statistical period is 10 seconds, that is, once every 10 seconds.
The disk space utilization rate adjusting instruction specifically refers to an instruction for adjusting the size of the disk space of the service node.
In an embodiment of the present application, taking the preset statistical period as 10 seconds as an example, the disk space utilization adjusting instruction is received every 10 seconds.
Step 304: and obtaining the current cache hit rate and the last cache hit rate.
The current cache hit rate refers to the cache probability of hit of the request in the current statistical period; the previous cache hit rate refers to a probability that a request in a previous statistical period hits a cache, and the request hit cache probability refers to a probability that a received service data acquisition request hits service data stored in the service node. For example, the total number of requests for receiving the service data obtaining requests is 385984092, wherein 332443070 service data obtaining requests cache corresponding service data in the service node, that is, the number of request hits in the cache is 332443070, and according to the number of request hits in the cache and the total number of requests, the request hit cache probability can be determined to be 86.12%.
The request hit cache specifically refers to that service data corresponding to the service data acquisition request is queried in the service node, and if the service data corresponding to the service data acquisition request is not queried in the service node, the request hit cache is called a request miss cache.
In practical application, obtaining a current cache hit rate and a previous cache hit rate specifically includes: and determining the current cache hit rate and the last cache hit rate according to the historical service data acquisition request.
Specifically, the historical service data obtaining request may be obtained from log information of the service node, and relevant information of the historical service data obtaining request, that is, the total number of times of cache hit and the total number of times of request in a preset time interval, is obtained from the log information.
The method for specifically calculating the current cache hit rate and the last cache hit rate includes S3042-S3044:
s3042, obtaining the number of cache hits and the total number of requests of the service data obtaining request in the previous statistical period, and obtaining the number of cache hits and the total number of requests of the service data obtaining request in the current statistical period.
S3044, calculating a first ratio between the number of cache hits of the service data obtaining request and the total number of requests in the last statistical period, and taking the first ratio as a last cache hit rate; and calculating a second ratio of the number of cache hits of the service data acquisition requests to the total number of requests in the current statistical period, and taking the second ratio as the current cache hit rate.
In a specific embodiment of the present application, taking the current cache hit rate and the previous cache hit rate of the service node G as an example, 332443070 of the number of cache hits of the service data acquisition request and 385984092 of the total number of requests of the service data acquisition request in the previous statistical period are obtained, and 86.12% of the previous cache hit rate is obtained by dividing the number of cache hits of the requests by the total number of requests; similarly, the current cache hit rate 86.13% is calculated according to the number of cache hits requested by the service data acquisition request and the total number of requests in the current statistical period.
Step 306: and determining the cache hit growth rate according to the current cache hit rate and the last cache hit rate.
The cache hit growth rate refers to a difference between a current cache hit rate in a current statistical period and a previous cache hit rate in a previous statistical period. And setting the current disk space utilization rate as an upper limit value by judging the amplitude of the cache hit growth rate.
In a specific embodiment of the present application, following the above example, the current cache hit rate 86.13% and the previous cache hit rate 86.12% are obtained, and the cache hit growth rate is obtained by subtracting the previous cache hit rate from the current cache hit rate, which is 0.01%.
Step 308: and determining the utilization rate of a preset disk space based on the cache hit growth rate and a preset cache hit growth rate interval.
The preset cache hit growth rate interval refers to a preset cache hit growth rate range for judging whether the disk space needs to be adjusted. When the cache hit rate tends to be stable, namely within a preset cache hit growth interval, calculating the current disk space utilization rate, and taking the current disk space utilization rate as an upper limit value of the disk space utilization rate of the service node; and when the cache hit rate is not in the preset cache hit growth rate interval, taking the initially set disk space utilization rate as the preset disk space utilization rate.
The method for obtaining the preset disk space utilization rate according to the cache hit growth rate and the preset cache hit growth rate interval comprises the following steps of S3082-S3088:
s3082, obtaining the initial disk space utilization rate.
The initial disk space utilization rate refers to a disk space utilization rate set when the service of the service node is started and initialized, and may be set according to the actual requirement of the service node, for example, the initial disk space utilization rate is set to 85%.
S3084, judging whether the cache hit growth rate is within the preset cache hit growth rate interval, if so, executing S3086, and if not, executing S3088.
S3086, calculating the current disk space utilization rate, and taking the current disk space utilization rate as a preset disk space utilization rate.
And S3088, taking the initial disk space utilization rate as a preset disk space utilization rate.
The preset cache hit growth rate interval is provided with a maximum cache hit growth rate and a minimum cache hit rate, for example, the cache hit growth rate interval is set to be 0% -3%, or 0% -10%, and the like.
Specifically, when the cache hit rate is within a preset cache hit growth interval, calculating the current disk space utilization rate and taking the current disk space utilization rate as the preset disk space utilization rate; and when the cache hit rate is not in the preset cache hit growth rate interval, taking the initial disk space utilization rate as the preset disk space utilization rate.
Step 108: and under the condition that the current disk space utilization rate is greater than the preset disk space utilization rate, adjusting the disk space of the service node according to a preset disk space adjustment strategy.
The preset disk space utilization rate is obtained through the step 106, the preset disk space utilization rate is used as an upper limit value of the disk space utilization, and data in the disk space needs to be eliminated after the upper limit value is exceeded, so that the disk space utilization rate is reduced, and the better service quality of the service node is maintained.
Specifically, adjusting the disk space of the service node according to a preset disk space adjustment policy includes: and eliminating the target service data file in the disk space of the service node according to the preset disk space adjusting strategy.
The preset disk space adjusting policy refers to an algorithm for eliminating data in the service node disk space, for example, an algorithm with an elimination cache effect, such as FIFO (first in first out), LRU (least recently used), LRU (least frequently used), and the like, and is not limited herein.
In another specific embodiment of the present application, after acquiring the target service data, the method further includes:
and feeding back the target service data.
After target service data is acquired at a service node according to a target service identifier, when a target service data acquisition request is sent by a user, the target service data is fed back to the user; and when the target service data acquisition request is sent by other service nodes, transmitting the target service data to the corresponding service node sending the target service data acquisition request.
The data processing method comprises the steps of receiving a target service data acquisition request, wherein the target service data acquisition request comprises a target service identifier; determining and acquiring target service data in a target data source based on the target service identifier under the condition that the target service data corresponding to the target service identifier does not exist in the disk space of the service node; storing the target service data into a disk space of the service node, calculating the current disk space utilization rate of the service node and acquiring a preset disk space utilization rate, wherein the preset disk space utilization rate is determined according to a historical service data acquisition request; and under the condition that the current disk space utilization rate is greater than the preset disk space utilization rate, adjusting the disk space of the service node according to a preset disk space adjustment strategy. According to the data processing method, the upper limit value of the disk space utilization rate is determined according to the cache hit growth rate, and the files in the disk space are eliminated under the condition that the current disk space utilization rate is the maximum upper limit value, so that the disk space utilization rate is reduced, and the influence on the service quality caused by the fact that the memory reaches the upper limit value is avoided.
The following describes the data processing method with reference to fig. 4 by taking an application of the method provided by the present application for receiving a target service data acquisition request at a service node a as an example. Fig. 4 shows a processing flow chart of a data processing method applied to a service node a receiving a data acquisition request according to an embodiment of the present application, which specifically includes the following steps:
step 402: receiving a target service data acquisition request, wherein the target service data acquisition request carries a target service data identifier.
In a specific embodiment provided by the present application, a service node a receives an acquisition request for acquiring video data X sent by a user U, where the acquisition request carries a video data identifier "X" of the video data X.
Step 404: and judging whether a cache corresponding to the target service identifier exists in the service node, if so, executing step 406, and if not, executing step 408.
In a specific embodiment provided by the present application, along with the above example, according to the video data identifier "X" of the video data X carried in the acquisition request, the service node a performs an inquiry. Since the service node a does not store the video data X, the service node a does not inquire the data corresponding to the video data X, and then step 408 is executed.
Step 406: and reading target service data from a disk of the service node.
Specifically, the service data corresponding to the target service data identifier in the service node is searched for according to the target service data identifier and read.
Step 408: and acquiring target service data from the data source.
And when the service node does not acquire the service data corresponding to the target service data identifier, determining a target data source according to the target service data identifier, and acquiring the target service data from the target data source.
In a specific embodiment provided by the present application, following the above example, a data source of the video data X is determined as a service node L according to the video data identifier "X", and the video data X is obtained from the service node L.
Step 410: and returning the target service data.
And returning the acquired target service data to a sender of the target service data acquisition request, wherein the sender can be a user or other service nodes.
In a specific embodiment provided by the present application, the video data X obtained from the service node L is returned to the user U along the above example.
Step 412: and fragmenting the target service data according to a preset fragmentation value to obtain the target service sub data.
And acquiring a preset fragmentation value of the service node, and fragmenting the target service data according to the preset fragmentation value to obtain at least two target service subdata.
In a specific embodiment provided by the present application, the preset fragmentation value is 3Mb, and the video data X is divided according to the preset fragmentation value 3Mb to obtain the video sub-data 1, the video sub-data 2, and the video sub-data 3.
Step 414: and writing the target service subdata into a disk of the service node.
And writing each target service subdata into a disk of the service node.
In a specific embodiment provided by the present application, the above example is continued, and the video sub-data 1, the video sub-data 2, and the video sub-data 3 obtained by fragmentation are written into the service node a.
Step 416: and calculating the current disk space utilization rate.
And acquiring the current disk space utilization capacity and the total disk space capacity of the service node, and calculating the ratio of the current disk space utilization capacity to the total disk space capacity to serve as the current disk space utilization rate.
Specifically, the method for calculating the current disk space utilization rate is shown in fig. 5, where fig. 5 is a flowchart of a method for calculating the current disk space utilization rate according to an embodiment of the present application, and the method includes steps 502 and 506:
step 502: and acquiring the current disk use capacity.
Step 504: and acquiring the total capacity of the disk.
Step 506: and dividing the current disk use capacity by the total disk capacity to obtain the current disk space utilization rate.
In a specific embodiment provided by the present application, along with the above example, the current disk space usage capacity 4.7TB and the total disk capacity 5.5TB of the service node a are obtained, and a ratio of the current disk space usage capacity of the service node a to the total disk capacity is calculated to be 85%, that is, the current disk space utilization rate is 85%.
Step 418: and judging whether the current disk space utilization rate is greater than the preset disk space utilization rate, if so, executing the step 420, and if not, ending the step.
The current space utilization ratio obtained in step 416 is compared with the preset space utilization ratio, and the current space utilization ratio and the preset space utilization ratio are determined.
Fig. 6 shows a method for obtaining a preset disk space utilization rate, where fig. 6 is a flowchart of a method for obtaining a preset disk space utilization rate according to an embodiment of the present application, and the method includes steps 602-612:
step 602: and receiving a disk space utilization rate adjusting instruction in the current statistical period.
Step 604: and setting the initial disk space utilization rate N, and calculating the cache hit growth rate.
Specifically, a current cache hit rate and a previous cache hit rate are obtained; and determining the cache hit growth rate according to the current cache hit rate and the last cache hit rate.
The current cache hit rate and the last cache hit rate are determined according to the historical service data acquisition request. And acquiring log information of the service node, and acquiring historical service data request information from the log information, wherein the historical service data request information comprises the number of times of request hit cache and the total number of times of requests of a target service data acquisition request in a statistical period.
In practical application, obtaining the request hit cache times and the total request times of the service data obtaining requests in the last statistical period from the log information, and obtaining the request hit cache times and the total request times of the service data obtaining requests in the current statistical period;
calculating a first ratio of the number of times of cache hit requests and the total number of times of requests of the service data acquisition requests in a first statistical period, and taking the first ratio as a last cache hit rate;
calculating a second ratio of the number of cache hits of the service data acquisition requests to the total number of requests in the current statistical period, and taking the second ratio as the current cache hit rate;
and determining the cache hit growth rate according to the current cache hit rate and the last cache hit rate.
In a specific embodiment of the present application, following the above example, the number of cache hits 332443070 and the total number of requests 385984092 of service data acquisition requests in the last statistical period are obtained from log information of the service node a, and the number of cache hits is divided by the total number of requests to obtain a last cache hit ratio 86.12%; similarly, the request hit cache times and the total request times of the service data acquisition requests in the current statistical period are obtained, and the current cache hit rate is 86.13% by dividing the request hit cache times by the total request times. The current cache hit rate 86.13% is subtracted by the last cache hit rate 86.12% to obtain the cache hit growth rate of the service node A of 0.01%.
Step 606: determining whether the cache hit growth rate is greater than 0, if so, executing step 608, otherwise, entering a next statistic cycle.
In an embodiment of the present application, following the above example, it is determined that the cache hit growth rate of the service node a is greater than 0.01%.
Step 608: and judging whether the cache hit growth rate is smaller than R, if so, executing a step 610, and if not, entering the next statistic cycle.
In an embodiment of the present application, following the above example, where the value of R is 3%, it is determined that the cache hit growth rate of the service node a is 0.01% smaller than R, then step 610 is executed.
Step 610: and calculating the current disk space utilization rate.
That is, the current disk space utilization rate in the statistical period of obtaining the preset disk space utilization rate, the specific calculation step may be referred to as step 302 and step 306, which are not described herein again.
Step 612: and assigning the current disk space utilization rate to the initial disk space utilization rate N to obtain the preset disk space utilization rate.
Specifically, the current disk space utilization obtained in step 610 replaces the initial disk space utilization as the preset disk space utilization.
Step 420: and releasing the memory of the service node based on a preset elimination strategy.
And deleting the files in the service node based on a memory elimination strategy, thereby increasing the disk space and reducing the utilization rate.
In a specific embodiment of the present application, the above example is continued, and according to a preset elimination strategy: LRU (least recently used), deletes data in the disk space of the service node a, reducing the disk space utilization of the service node a.
The data processing method comprises the steps of receiving a target service data acquisition request, wherein the target service data acquisition request comprises a target service identifier; determining and acquiring target service data in a target data source based on the target service identifier under the condition that the target service data corresponding to the target service identifier does not exist in the disk space of the service node; storing the target service data into a disk space of the service node, calculating the current disk space utilization rate of the service node and acquiring a preset disk space utilization rate, wherein the preset disk space utilization rate is determined according to a historical service data acquisition request; and under the condition that the current disk space utilization rate is greater than the preset disk space utilization rate, adjusting the disk space of the service node according to a preset disk space adjustment strategy. According to the data processing method, the upper limit value of the disk space utilization rate is determined according to the cache hit growth rate, and the files in the disk space are eliminated under the condition that the current disk space utilization rate is the maximum upper limit value, so that the disk space utilization rate is reduced, and the influence on the service quality caused by the fact that the memory reaches the upper limit value is avoided.
Corresponding to the above method embodiment, the present application further provides an embodiment of a data processing apparatus, and fig. 7 shows a schematic structural diagram of a data processing apparatus provided in an embodiment of the present application. As shown in fig. 7, the apparatus includes:
a receiving module 702, configured to receive a target service data acquisition request, where the target service data acquisition request includes a target service identifier;
a determining module 704, configured to determine and obtain target service data in a target data source based on the target service identifier when there is no target service data corresponding to the target service identifier in a disk space of the service node;
a calculating module 706, configured to store the target service data into a disk space of the service node, calculate a current disk space utilization rate of the service node, and obtain a preset disk space utilization rate, where the preset disk space utilization rate is determined according to a historical service data obtaining request;
an adjusting module 708, configured to adjust the disk space of the service node according to a preset disk space adjusting policy when the current disk space utilization rate is greater than the preset disk space utilization rate.
Optionally, the calculating module 706 is further configured to:
acquiring a preset slicing value;
fragmenting the target service data according to the preset fragmentation value to obtain target service sub-data;
and storing the target service subdata into a disk space of the service node.
Optionally, the calculating module 706 is further configured to:
acquiring the current disk space use capacity and the total disk space capacity of the service node;
calculating the ratio of the current disk space utilization capacity to the total disk space capacity;
and taking the ratio as the current disk space utilization rate of the service node.
Optionally, the calculating module 706 is further configured to:
receiving a disk space utilization rate adjusting instruction in the current statistical period;
obtaining a current cache hit rate and a last cache hit rate;
determining a cache hit growth rate according to the current cache hit rate and the last cache hit rate;
and determining the utilization rate of a preset disk space based on the cache hit growth rate and a preset cache hit growth rate interval.
Optionally, the calculating module 706 is further configured to:
and determining the current cache hit rate and the last cache hit rate according to the historical service data acquisition request.
Optionally, the calculating module 706 is further configured to:
obtaining the request hit cache times and the total request times of the service data obtaining requests in the last statistical period, and obtaining the request hit cache times and the total request times of the service data obtaining requests in the current statistical period;
calculating a first ratio of the number of times of cache hit requests and the total number of times of requests of the service data acquisition requests in a first statistical period, and taking the first ratio as a last cache hit rate;
and calculating a second ratio of the number of cache hits of the service data acquisition requests to the total number of requests in the current statistical period, and taking the second ratio as the current cache hit rate.
Optionally, the calculating module 706 is further configured to:
obtaining an initial disk space utilization rate;
judging whether the cache hit growth rate is within the preset cache hit growth rate interval or not;
if so, calculating the current disk space utilization rate, and taking the current disk space utilization rate as a preset disk space utilization rate;
and if not, taking the initial disk space utilization rate as a preset disk space utilization rate.
Optionally, the apparatus further comprises:
and the elimination module is configured to eliminate the target service data file in the disk space of the service node according to the preset disk space adjusting strategy.
Optionally, the apparatus further comprises:
and the obtaining module is configured to obtain the target service data corresponding to the target service identifier in the disk space of the service node under the condition that the target service data corresponding to the target service identifier exists in the disk space of the service node.
Optionally, the apparatus further comprises:
a feedback module configured to feed back the target service data.
The above is a schematic configuration of a data processing apparatus of the present embodiment. It should be noted that the technical solution of the data processing apparatus and the technical solution of the data processing method belong to the same concept, and details that are not described in detail in the technical solution of the data processing apparatus can be referred to the description of the technical solution of the data processing method.
Fig. 8 shows a block diagram of a computing device according to an embodiment of the present application. The components of the computing device 800 include, but are not limited to, memory 810 and a processor 820. The processor 820 is coupled to the memory 810 via a bus 830, and the database 850 is used to store data.
Computing device 800 also includes access device 840, access device 840 enabling computing device 800 to communicate via one or more networks 860. Examples of such networks include the Public Switched Telephone Network (PSTN), a Local Area Network (LAN), a Wide Area Network (WAN), a Personal Area Network (PAN), or a combination of communication networks such as the internet. Access device 840 may include one or more of any type of network interface (e.g., a Network Interface Card (NIC)) whether wired or wireless, such as an IEEE802.11 Wireless Local Area Network (WLAN) wireless interface, a worldwide interoperability for microwave access (Wi-MAX) interface, an ethernet interface, a Universal Serial Bus (USB) interface, a cellular network interface, a bluetooth interface, a Near Field Communication (NFC) interface, and so forth.
In one embodiment of the application, the above-described components of the computing device 800 and other components not shown in fig. 8 may also be connected to each other, for example, by a bus. It should be understood that the block diagram of the computing device architecture shown in FIG. 8 is for purposes of example only and is not limiting as to the scope of the present application. Those skilled in the art may add or replace other components as desired.
Computing device 800 may be any type of stationary or mobile computing device, including a mobile computer or mobile computing device (e.g., tablet, personal digital assistant, laptop, notebook, netbook, etc.), a mobile phone (e.g., smartphone), a wearable computing device (e.g., smartwatch, smartglasses, etc.), or other type of mobile device, or a stationary computing device such as a desktop computer or PC. Computing device 800 may also be a mobile or stationary server.
Wherein the processor 820 implements the steps of the data processing method when executing the instructions.
The above is an illustrative scheme of a computing device of the present embodiment. It should be noted that the technical solution of the computing device and the technical solution of the data processing method belong to the same concept, and details that are not described in detail in the technical solution of the computing device can be referred to the description of the technical solution of the data processing method.
An embodiment of the present application further provides a computer readable storage medium, which stores computer instructions, and the instructions, when executed by a processor, implement the steps of the data processing method as described above.
The above is an illustrative scheme of a computer-readable storage medium of the present embodiment. It should be noted that the technical solution of the storage medium belongs to the same concept as the technical solution of the data processing method, and details that are not described in detail in the technical solution of the storage medium can be referred to the description of the technical solution of the data processing method.
The foregoing description of specific embodiments of the present application has been presented. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.
The computer instructions comprise computer program code which may be in the form of source code, object code, an executable file or some intermediate form, or the like. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like. It should be noted that the computer readable medium may contain content that is subject to appropriate increase or decrease as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer readable media does not include electrical carrier signals and telecommunications signals as is required by legislation and patent practice.
It should be noted that, for the sake of simplicity, the above-mentioned method embodiments are described as a series of acts or combinations, but those skilled in the art should understand that the present application is not limited by the described order of acts, as some steps may be performed in other orders or simultaneously according to the present application. 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 in this application.
In the above embodiments, 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.
The preferred embodiments of the present application disclosed above are intended only to aid in the explanation of the application. Alternative embodiments are not exhaustive and do not limit the invention to the precise embodiments described. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the application and its practical applications, to thereby enable others skilled in the art to best understand and utilize the application. The application is limited only by the claims and their full scope and equivalents.
Claims (13)
1. A data processing method is applied to a service node and comprises the following steps:
receiving a target service data acquisition request, wherein the target service data acquisition request comprises a target service identifier;
determining and acquiring target service data in a target data source based on the target service identifier under the condition that the target service data corresponding to the target service identifier does not exist in the disk space of the service node;
storing the target service data into a disk space of the service node, calculating the current disk space utilization rate of the service node and acquiring a preset disk space utilization rate, wherein the preset disk space utilization rate is determined according to a historical service data acquisition request;
and under the condition that the current disk space utilization rate is greater than the preset disk space utilization rate, adjusting the disk space of the service node according to a preset disk space adjustment strategy.
2. The data processing method of claim 1, wherein storing the target service data in a disk space of the service node comprises:
acquiring a preset slicing value;
fragmenting the target service data according to the preset fragmentation value to obtain target service sub-data;
and storing the target service subdata into a disk space of the service node.
3. The data processing method of claim 1, wherein calculating the current disk space utilization for the service node comprises:
acquiring the current disk space use capacity and the total disk space capacity of the service node;
calculating the ratio of the current disk space utilization capacity to the total disk space capacity;
and taking the ratio as the current disk space utilization rate of the service node.
4. The data processing method of claim 1, wherein obtaining a predetermined disk space utilization comprises:
receiving a disk space utilization rate adjusting instruction in the current statistical period;
obtaining a current cache hit rate and a last cache hit rate;
determining a cache hit growth rate according to the current cache hit rate and the last cache hit rate;
and determining the utilization rate of a preset disk space based on the cache hit growth rate and a preset cache hit growth rate interval.
5. The data processing method of claim 4, wherein obtaining a current cache hit rate and a previous cache hit rate comprises:
and determining the current cache hit rate and the last cache hit rate according to the historical service data acquisition request.
6. The data processing method of claim 5, wherein determining the current cache hit rate and the previous cache hit rate according to the historical service data acquisition requests comprises:
obtaining the request hit cache times and the total request times of the service data obtaining requests in the last statistical period, and obtaining the request hit cache times and the total request times of the service data obtaining requests in the current statistical period;
calculating a first ratio of the number of times of cache hit requests and the total number of times of requests of the service data acquisition requests in a first statistical period, and taking the first ratio as a last cache hit rate;
and calculating a second ratio of the number of cache hits of the service data acquisition requests to the total number of requests in the current statistical period, and taking the second ratio as the current cache hit rate.
7. The data processing method of claim 4, wherein determining a preset disk space utilization based on the cache hit growth rate and a preset cache hit growth rate interval comprises:
obtaining an initial disk space utilization rate;
judging whether the cache hit growth rate is within the preset cache hit growth rate interval or not;
if so, calculating the current disk space utilization rate, and taking the current disk space utilization rate as a preset disk space utilization rate;
and if not, taking the initial disk space utilization rate as a preset disk space utilization rate.
8. The data processing method according to claim 1, wherein when the current disk space utilization rate is greater than the preset disk space utilization rate, adjusting the disk space of the service node according to a preset disk space adjustment policy includes:
and eliminating the target service data file in the disk space of the service node according to the preset disk space adjusting strategy.
9. The data processing method according to any of claims 1 to 8, wherein after receiving the target service data acquisition request, further comprising:
and under the condition that target service data corresponding to the target service identifier exists in the disk space of the service node, acquiring the target service data corresponding to the target service identifier in the disk space of the service node.
10. The data processing method according to any one of claims 1 to 8, wherein after acquiring the target service data, further comprising:
and feeding back the target service data.
11. A data processing apparatus, comprising:
the system comprises a receiving module, a sending module and a receiving module, wherein the receiving module is configured to receive a target service data acquisition request, and the target service data acquisition request comprises a target service identifier;
the determining module is configured to determine and acquire target service data in a target data source based on the target service identifier under the condition that the target service data corresponding to the target service identifier does not exist in the disk space of the service node;
the computing module is configured to store the target service data into a disk space of the service node, compute a current disk space utilization rate of the service node and acquire a preset disk space utilization rate, wherein the preset disk space utilization rate is determined according to a historical service data acquisition request;
and the adjusting module is configured to adjust the disk space of the service node according to a preset disk space adjusting strategy under the condition that the current disk space utilization rate is greater than the preset disk space utilization rate.
12. A computing device comprising a memory, a processor, and computer instructions stored on the memory and executable on the processor, wherein the processor implements the steps of the method of any one of claims 1-10 when executing the instructions.
13. A computer-readable storage medium storing computer instructions, which when executed by a processor, perform the steps of the method of any one of claims 1 to 10.
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