CN111831519A - Data acquisition method, device and equipment - Google Patents
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Abstract
The application provides a data acquisition method, a device and equipment, wherein the method comprises the following steps: determining a starting time point when the first thread is switched from the unprocessed IO task to the processed IO task and an ending time point when the first thread is switched from the processed IO task to the unprocessed IO task; determining a first busy time interval of the first thread in a specified statistical period by using the starting time point and the ending time point; determining a second busy time interval of the IO forwarding system in a specified counting period by using the first busy time interval of the plurality of threads in the specified counting period; and acquiring the system utilization rate of the specified statistical period according to the second busy time interval. According to the technical scheme, the accurate system utilization rate can be obtained, and the processing performance of the IO task is improved.
Description
Technical Field
The present application relates to the field of internet technologies, and in particular, to a data acquisition method, apparatus, and device.
Background
The cloud technology is to unify resources such as hardware, software, network and the like in a wide area network or a local area network to realize calculation, storage, processing and sharing of data. For example, a service provider may provide cloud computing resources, such as CPU (central processing Unit) resources, to a user for providing computing services to the user; cloud storage resources, such as disk resources, are used to provide storage services for users. In order to access the cloud storage resource, a user may send an IO (input output) request to the storage server, where the IO request often passes through multiple physical servers before reaching the storage server, and the physical servers are referred to as IO forwarding systems, that is, the IO forwarding systems are used to receive the IO request and forward the IO request to the storage server.
In order to enable the operation and maintenance personnel to know the operation condition of the IO forwarding system, the IO forwarding system needs to collect performance data, such as the number of IO requests executed per second, the execution duration of the IO requests, the system utilization rate, and the like. The system usage rate indicates the proportion of time per second that IO tasks are present. For example, in 1 second, 500 milliseconds have IO tasks (i.e. processing IO requests), 500 milliseconds have no IO tasks, and the system utilization rate is 50%.
However, in some application scenarios, if the IO forwarding system uses multiple threads to process IO tasks, an error may be caused in the statistical data of the system usage rate. For example, in 1 second, the thread a has an IO task in 500 milliseconds, and the thread B also has an IO task in 500 milliseconds, so the statistical result is that the IO forwarding system has IO tasks in 1 second, and the system utilization rate is 100%. However, if thread a had IO tasks in the first 500 milliseconds of 1 second and thread B had IO tasks in the first 500 milliseconds of 1 second, then the correct result for system usage is 50%, and obviously 100% of the above system usage is the wrong statistic.
Disclosure of Invention
The application provides a data acquisition method, which is applied to an input/output (IO) forwarding system comprising a plurality of threads, wherein the plurality of threads are all used for processing IO tasks, and the method comprises the following steps:
determining a starting time point when the first thread is switched from the unprocessed IO task to the processed IO task and an ending time point when the first thread is switched from the processed IO task to the unprocessed IO task; determining a first busy time interval of the first thread in a specified statistical period by using the starting time point and the ending time point;
determining a second busy time interval of the IO forwarding system in a specified counting period by using the first busy time interval of the plurality of threads in the specified counting period;
acquiring the system utilization rate of the specified statistical period according to the second busy time interval;
wherein the first thread is any one of the plurality of threads.
The application provides a data acquisition device is applied to the IO forwarding system of input/output including a plurality of threads, a plurality of threads all are used for handling the IO task, the device includes:
the first determining module is used for determining the starting time point of the first thread switched from the unprocessed IO task to the processed IO task and the ending time point of the first thread switched from the processed IO task to the unprocessed IO task;
the second determining module is used for determining a first busy time interval of the first thread in a specified statistical period by using the starting time point and the ending time point;
a third determining module, configured to determine, by using the first busy time interval of the multiple threads in a specified statistics period, a second busy time interval of the IO forwarding system in the specified statistics period;
the acquisition module is used for acquiring the system utilization rate of the specified statistical period according to the second busy time interval; wherein the first thread is any one of the plurality of threads.
The application provides a data acquisition device, data acquisition device includes a plurality of threads, a plurality of threads all are used for handling the IO task, data acquisition device includes:
a processor and a machine-readable storage medium having stored thereon a plurality of computer instructions, the processor when executing the computer instructions performs:
determining a starting time point when the first thread is switched from the unprocessed IO task to the processed IO task and an ending time point when the first thread is switched from the processed IO task to the unprocessed IO task; determining a first busy time interval of the first thread in a specified statistical period by using the starting time point and the ending time point;
determining a second busy time interval of the IO forwarding system in a specified counting period by using the first busy time interval of the plurality of threads in the specified counting period;
acquiring the system utilization rate of the specified statistical period according to the second busy time interval;
wherein the first thread is any one of the plurality of threads.
Based on the technical scheme, in the embodiment of the application, if the IO forwarding system uses a plurality of threads to process the IO task, a first busy time interval of each thread in a specified statistical period can be determined, a second busy time interval of the IO forwarding system in the specified statistical period is determined by using the first busy time interval corresponding to each thread, and the system utilization rate of the specified statistical period is obtained according to the second busy time interval, so that accurate system utilization rate can be obtained, and operation and maintenance personnel can know the operation condition of the IO forwarding system. Moreover, a plurality of threads can process a plurality of IO tasks in parallel, so that the processing performance of the IO tasks is improved.
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In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments of the present application or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments described in the present application, and other drawings can be obtained by those skilled in the art according to the drawings of the embodiments of the present application.
FIG. 1 is a schematic diagram of an application scenario in one embodiment of the present application;
FIG. 2 is a schematic flow chart diagram of a data acquisition method in one embodiment of the present application;
FIG. 3 is a schematic flow chart diagram of a data acquisition method in another embodiment of the present application;
FIG. 4 is a schematic flow chart diagram of a data acquisition method in another embodiment of the present application;
FIG. 5 is a schematic diagram of a data acquisition device according to an embodiment of the present application;
fig. 6 is a schematic structural diagram of an IO forwarding system in an embodiment of the present application.
Detailed Description
The terminology used in the embodiments of the present application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in this application and the 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 herein is meant to encompass any and all possible combinations of one or more of the associated listed items.
It should be understood that although the terms first, second, third, etc. may be used in the embodiments of the present application to describe various information, the information should not be limited to these terms. These terms are only used to distinguish one type of information from another. For example, first information may also be referred to as second information, and similarly, second information may also be referred to as first information, without departing from the scope of the present application. Depending on the context, moreover, the word "if" as used may be interpreted as "at … …" or "when … …" or "in response to a determination".
Before introducing the data acquisition method of the embodiment of the present application, the following concepts are introduced:
cloud server: the server is produced by a cloud host manufacturer based on a cloud computing technology, so that a user can operate and manage in a remote login mode. In the use mode, the cloud server is the same as a common remote physical server, and a user operates the cloud server in the use mode of the remote physical server.
Cloud disk: the disk instance established on the distributed storage system can take the cloud disk as a computer disk in the cloud server, and the cloud disk is read and written. Furthermore, the distributed storage system may be composed of a plurality of storage servers, which are used to provide cloud storage resources, such as disk resources.
IO request: when a user uses the cloud disk, the data of the cloud disk needs to be read, and the data is written into the cloud disk. In order to read the data of the cloud disk, a read operation request may be sent; to write data to the cloud disk, a write operation request may be sent. Based on this, the read operation request and the write operation request may be referred to as IO requests.
IO forwarding system: from a cloud server using a cloud disk to a storage server (i.e., a distributed storage system) which really stores data at a back end, multiple physical servers are often needed to be passed through therebetween, and the physical servers are transmitted backward at a first level, and the physical servers may be referred to as an IO forwarding system, which may be a functional module of the physical server, for example, the IO forwarding system is a functional module for processing an IO request, that is, the IO forwarding system is configured to receive the IO request and forward the IO request to the direction of the storage server.
IO task: after receiving the IO request, the IO forwarding system establishes an IO task for the IO request, and after receiving an IO response (i.e., an IO response returned by the distributed storage system) for the IO request, the IO forwarding system forwards the IO response to the cloud disk, so that the IO forwarding system completes the IO task.
When one or more IO tasks are being processed (i.e. the processing process for the IO request is not yet finished), it indicates that the current state of the IO forwarding system is to process the IO task. In addition, when no IO task is being processed, it indicates that the current state of the IO forwarding system is an unprocessed IO task.
Multithreading IO forwarding system: in order to improve the processing performance of the IO forwarding system, the IO forwarding system may use multiple threads to process IO tasks simultaneously, that is, each thread processes IO tasks separately, and the IO forwarding system that uses multiple threads to process IO tasks simultaneously may be referred to as a multi-threaded IO forwarding system.
Performance data: in order to make the operation and maintenance personnel know the operation status of the IO forwarding system, the IO forwarding system needs to collect performance data related to the IO requests, such as the number of IO requests executed per second, the execution duration of the IO requests, the system utilization rate, and the like. The technical scheme of the embodiment of the application is used for acquiring the system utilization rate in the performance data, so that only the acquisition process of the system utilization rate is introduced in the subsequent embodiments.
And (3) specifying a statistical period: according to different statistical granularities, different statistical periods can be set, such as a second-level statistical period, a minute-level statistical period, an hour-level statistical period, and the like, which is not limited herein. For convenience of description, a second-level statistical period is taken as an example, that is, the IO forwarding system obtains the system usage rate in seconds. The system utilization rate acquired in seconds can effectively reflect the performance change trend of the IO forwarding system, and is information concerned by operation and maintenance personnel.
For example, seconds 0-1 are a specified statistical period, seconds 1-2 are a specified statistical period, seconds 2-3 are a specified statistical period, and so on, each second may be a specified statistical period. For another example, 0.5-1.5 seconds is a specified statistical period, 1.5-2.5 seconds is a specified statistical period, 2.5-3.5 seconds is a specified statistical period, and so on, each second may be a specified statistical period.
Of course, the above is only an example of the specified statistical period, and the specified statistical period is not limited.
System usage (also known as system busy time, an index that measures system status): indicating the proportion of time that IO tasks are present within each specified statistical period (e.g., time per second). For example, in a specified statistical period of 1-2 seconds, 500 milliseconds have IO tasks, 500 milliseconds have no IO tasks, and the system utilization rate is 50%.
In a multi-threaded IO transfer system, although it is possible to process an IO task using a plurality of threads, there is a problem that statistical data of a system usage rate is erroneous. For example, in a specified statistical period of 1-2 seconds, a thread a has an IO task in 500 milliseconds, and a thread B also has an IO task in 500 milliseconds, so that the statistical result is that the IO forwarding system has an IO task in 1 second, that is, the system utilization rate is 100%. However, if thread A has IO tasks in 1 st to 1.5 th seconds and thread B also has IO tasks in 1 st to 1.5 th seconds, then the correct result of the system utilization is 50%, obviously, 100% of the system utilization is wrong statistical data.
In view of the above discovery, an embodiment of the present application provides a data obtaining method, where the method is used to obtain a system utilization rate. The method can be applied to an IO forwarding system comprising a plurality of threads, namely a multi-threaded IO forwarding system, and the plurality of threads are all used for processing IO tasks. Referring to fig. 1, which is a schematic view of an application scenario of the embodiment of the present application, taking an IO forwarding system including two threads (i.e., a thread 101 and a thread 102) as an example, in an actual application, the number of threads of the IO forwarding system may be greater, which is not limited to this.
In the application scenario, referring to fig. 2, a schematic flow diagram of a data acquisition method in the embodiment of the present application is shown, where the method may be applied to an IO forwarding system, and the method may include:
Wherein the first thread may be any one of the plurality of threads. For example, the first thread may be the thread 101, and the start time point when the thread 101 switches from the unprocessed IO task to the processed IO task and the end time point when the thread 101 switches from the processed IO task to the unprocessed IO task are determined. Alternatively, the first thread may be the thread 102, and the start time point when the thread 102 switches from the unprocessed IO task to the processed IO task and the end time point when the thread 102 switches from the processed IO task to the unprocessed IO task are determined. For convenience of description, the first thread is taken as the thread 101, and the processing procedure of the thread 102 is similar.
For example, thread 101 is not processing IO tasks in the time interval from time A1 to time A2. In the time interval from time A2 to time A3, an IO task (e.g., one or more IO tasks) is processed. In the time interval from time A3 to time A4, IO tasks are not processed. In the time interval from the time point a4 to the time point a5, the IO task is processed. In the time interval from time A5 to time A6, IO tasks are not processed, and so on.
Obviously, the time a2 is a starting time point for switching from the unprocessed IO task to the processed IO task, the time A3 is an ending time point for switching from the processed IO task to the unprocessed IO task, and the time a2 and the time A3 correspond to the task processing time interval 1. The time a4 is a start time point when switching from the unprocessed IO task to the processed IO task, the time a5 is an end time point when switching from the processed IO task to the unprocessed IO task, and the time a4 and the time a5 correspond to the task processing time interval 2. By analogy, other task processing time intervals may also include a start time point and an end time point, which are not repeated herein.
Based on the above processing, a plurality of task processing time intervals for the threads 101 may be obtained, and in each task processing time interval, a start time point and an end time point may be included, for example, the start time point in the task processing time interval 1 is time a2, the end time point is time A3, the start time point in the task processing time interval 2 is time a4, the end time point is time a5, and so on.
In one example, the determination of the first busy time interval may include, but is not limited to:
determining a task processing time interval by using the starting time point and the ending time point; then, a fine time interval at the specified statistical period may be selected from the task processing time intervals and determined as a first busy time interval of the first thread at the specified statistical period.
For example, the statistical period is specified to be 1 to 2 seconds, the task processing time interval 1 is [0.8, 1.1], that is, the start time point is 0.8 seconds, the end time point is 1.1 seconds, the task processing time interval 2 is [1.3, 1.5], the task processing time interval 3 is [1.7, 1.9], and the task processing time interval 4 is [2.1, 2.7 ].
The fine time interval [1, 1.1] in the specified statistical period [1, 2] is selected from the task processing time interval 1, the fine time interval [1.3, 1.5] in the specified statistical period [1, 2] is selected from the task processing time interval 2, and the fine time interval [1.7, 1.9] in the specified statistical period [1, 2] is selected from the task processing time interval 3. In summary, the fine time interval [1, 1.1], the fine time interval [1.3, 1.5], and the fine time interval [1.7, 1.9] are the first busy time intervals [1-1.1, 1.3-1.5, 1.7-1.9] specifying the statistical period.
Of course, the above-mentioned is an example of the specified statistical period (1 st to 2 nd seconds), the processing procedure for other specified statistical periods is similar, and the task processing time interval may be more, and will not be described repeatedly herein.
In one example, a fine array may be maintained for a given statistical period (1 st-2 nd seconds), and first busy time intervals [1-1.1, 1.3-1.5, 1.7-1.9] may be recorded via the fine array.
Determining a task processing time interval by using the starting time point and the ending time point; and dividing the appointed statistical period into a plurality of fuzzy time intervals, and if the task processing time interval and the fuzzy time intervals have intersection, determining the fuzzy time interval as a first busy time interval of the first thread in the appointed statistical period.
For example, the statistical period is specified to be 1 to 2 seconds, the task processing time interval 1 is [0.8, 1.1], that is, the start time point is 0.8 seconds, the end time point is 1.1 seconds, the task processing time interval 2 is [1.3, 1.5], the task processing time interval 3 is [1.7, 1.9], and the task processing time interval 4 is [2.1, 2.7 ].
Assume that the specified statistical period [1, 2] is divided into 10 fuzzy time intervals, which are respectively fuzzy time intervals [1, 1.1], fuzzy time intervals [1.1, 1.2], fuzzy time intervals [1.2, 1.3], fuzzy time intervals [1.3, 1.4], fuzzy time intervals [1.4, 1.5], fuzzy time intervals [1.5, 1.6], fuzzy time intervals [1.6, 1.7], fuzzy time intervals [1.7, 1.8], fuzzy time intervals [1.8, 1.9], and fuzzy time intervals [1.9, 2.0 ]. Of course, the above-mentioned dividing manner of the fuzzy time interval is only an example, and the dividing manner is not limited.
Since the task processing time interval 1 intersects the fuzzy time interval [1, 1.1], the fuzzy time interval [1, 1.1] is the first busy time interval. Since the task processing time interval 2 intersects the fuzzy time interval [1.3, 1.4] and the fuzzy time interval [1.4, 1.5], the fuzzy time interval [1.3, 1.4] and the fuzzy time interval [1.4, 1.5] are the first busy time interval. Since the task processing time interval 3 intersects the fuzzy time interval [1.7, 1.8] and the fuzzy time interval [1.8, 1.9], the fuzzy time interval [1.7, 1.8] and the fuzzy time interval [1.8, 1.9] are the first busy time interval. In summary, the first busy interval for a given statistical period may be [1-1.1, 1.3-1.4, 1.4-1.5, 1.7-1.8, 1.8-1.9 ].
Of course, the above-mentioned is an example of the specified statistical period (1 st to 2 nd seconds), the processing procedure for other specified statistical periods is similar, and the task processing time interval may be more, and will not be described repeatedly herein.
In one example, a fuzzy array may be maintained for a specified statistical period (1 st-2 nd seconds) and the first busy time interval [1-1.1, 1.3-1.4, 1.4-1.5, 1.7-1.8, 1.8-1.9] may be recorded by the fuzzy array.
Specifically, for each first thread in the multiple threads, the processing may be performed by using step 201 and step 202, so as to obtain a first busy time interval. Based on a first busy time interval of each first thread for a specified statistical period, a second busy time interval of the IO forwarding system for the specified statistical period may be determined.
In one example, the manner of determining the second busy interval may include, but is not limited to:
the method comprises the steps of obtaining a union of first busy time intervals corresponding to each first thread in a plurality of threads, and determining the first busy time intervals corresponding to the union as second busy time intervals, namely the union of all the first busy time intervals, which is the second busy time intervals of the IO forwarding system in a specified statistical period.
For example, if the specified statistical period is 1-2 seconds, the first busy time interval of the thread 101 in the specified statistical period is [1-1.1, 1.3-1.5, 1.7-1.9], and the first busy time interval of the thread 102 in the specified statistical period is [1.1-1.2, 1.3-1.5, 1.6-1.9], then the union of all the first busy time intervals is [1-1.2, 1.3-1.5, 1.6-1.9], that is, the second busy time interval is [1-1.2, 1.3-1.5, 1.6-1.9 ].
Dividing the appointed statistical period into a plurality of merging time intervals; if the first busy time interval corresponding to the first thread (i.e. any one of all threads) intersects with the merging time interval, determining the merging time interval as a second busy time interval of the IO forwarding system in the specified statistical period.
For example, the statistical period is specified as 1 st to 2 nd seconds, and is divided into 10 merging time intervals, and the number of the merging time intervals may be more, which is not limited. The 10 merging time intervals are a merging time interval [1, 1.1], a merging time interval [1.1, 1.2], a merging time interval [1.2, 1.3], a merging time interval [1.3, 1.4], a merging time interval [1.4, 1.5], a merging time interval [1.5, 1.6], a merging time interval [1.6, 1.7], a merging time interval [1.7, 1.8], a merging time interval [1.8, 1.9] and a merging time interval [1.9, 2.0 ].
The first busy time interval of the thread 101 in the specified statistical period is [1-1.1, 1.3-1.5, 1.7-1.9], and the first busy time interval of the thread 102 in the specified statistical period is [1.1-1.2, 1.3-1.5, 1.6-1.9 ].
On the basis, the combination time interval [1, 1.1], the combination time interval [1.1, 1.2], the combination time interval [1.3, 1.4], the combination time interval [1.4, 1.5], the combination time interval [1.6, 1.7], the combination time interval [1.7, 1.8] and the combination time interval [1.8, 1.9] are intersected with the first busy time interval, so that the combination time intervals are second busy time intervals, namely, the second busy time intervals can be [1-1.1, 1.1-1.2, 1.3-1.4, 1.4-1.5, 1.6-1.7, 1.7-1.8 and 1.8-1.9 ].
And step 204, acquiring the system utilization rate of the specified statistical period according to the second busy time interval.
Specifically, the IO forwarding system may obtain a proportional relationship between the second busy time interval and the specified statistical period, and obtain the system usage rate of the specified statistical period according to the proportional relationship, that is, the system usage rate of the IO forwarding system in the specified statistical period may be the proportional relationship.
For example, assume the second busy time interval is [1-1.2, 1.3-1.5, 1.6-1.9], the specified statistical period is [1, 2], and therefore the system usage rate of the IO forwarding system in the specified statistical period [1, 2] is 70%.
In an example, the execution sequence is only an example given for convenience of description, and in practical applications, the execution sequence between steps may also be changed, and the execution sequence is not limited. Moreover, in other embodiments, the steps of the respective methods do not have to be performed in the order shown and described herein, and the methods may include more or less steps than those described herein. Moreover, a single step described in this specification may be broken down into multiple steps for description in other embodiments; multiple steps described in this specification may be combined into a single step in other embodiments.
Based on the technical scheme, in the embodiment of the application, if the IO forwarding system uses a plurality of threads to process the IO task, a first busy time interval of each thread in a specified statistical period can be determined, a second busy time interval of the IO forwarding system in the specified statistical period is determined by using the first busy time interval corresponding to each thread, and the system utilization rate of the specified statistical period is obtained according to the second busy time interval, so that accurate system utilization rate can be obtained, and network management personnel can know the operation condition of the IO forwarding system. Moreover, a plurality of threads can process a plurality of IO tasks in parallel, so that the processing performance of the IO tasks is improved.
The following describes a data acquisition method according to an embodiment of the present application with reference to specific embodiments.
In the embodiment of the application, an array structure is added for each thread (such as the thread 101 and the thread 102), and the array structure is recorded as a busy time array, and the busy time array is used for recording a specific busy time period. Referring to table 1, the busy time array consists of N Tmix structures, each responsible for recording a specific busy time period for a thread in one second. At the beginning of each second, the Tmix structure corresponding to the second is constructed, and after the Tmix structure is constructed, no data exists in the initial state.
TABLE 1
| Second 1 [0, 1]] | Second 2 [1, 2]] | Second 3 [2, 3]] | Second 4 [3, 4]] | … | Second n |
| Tmix structure | Tmix structure | Tmix structure | Tmix structure | … | Tmix structure |
Each Tmix structure includes a fine array and a fuzzy array. The fine array is an array of time ranges that records the "start-end" time range for each busy thread. Each member of the fine array consists of two time points [ x, y ] to record the time period from time x to time y, this thread is busy.
For example, assume that the fine array includes the following members: [1.25, 1.45], [1.50, 1.55], [1.70, 1.93], this means that the thread is busy for 1.25 seconds to 1.45 seconds, the thread is busy for 1.50 seconds to 1.55 seconds, the thread is busy for 1.70 seconds to 1.93 seconds, and so on. Obviously, for each busy time, only two time points [ x, y ] need to be added to the fine array, and the efficiency is high.
The fuzzy array may include K members, and the value of K may be configured empirically, meaning that one second is divided into K shares, e.g., an average is divided into K shares, each share corresponding to a time interval. For example, one second is divided into 10 shares, the first share represents the time interval of 1-100 milliseconds, the second share represents the time interval of 101-200 milliseconds, the third share represents the time interval of 201-300 milliseconds, and so on.
In one example, the fuzzy array may record K values, each value is 0 or 1, 0 indicates that the thread is in an idle state in the corresponding time interval, and 1 indicates that the thread is in a busy state in the corresponding time interval. For example, the fuzzy array is 0000011111, the time interval of 1-100 ms, 101-.
In another example, the fuzzy array may record a plurality of time intervals, such as [501, 600], [601, 700], [701, 800], [801, 900], [901, 1000], indicating that the time intervals of 600 ms 501-.
Clearly, either way, the busy state time interval may be determined based on the fuzzy array.
In one example, the Tmix structure may include a fine array, and the "start-end" time range for each busy thread is recorded by the fine array. Alternatively, the Tmix structure may include a fuzzy array and record the busy state of the thread at the corresponding time interval through the fuzzy array. Alternatively, the Tmix structure may include a fine array and a fuzzy array, the case of which is described below.
If the busy time periods change frequently, for example, a large number of busy time periods occur in one second, and if all busy time periods are stored in the fine array, the occupied storage space is large, so in order to avoid the occupied space being too large, an upper limit of the number of members of the fine array may be specified, for example, the upper limit of the number of members is 10, that is, at most 10 members are recorded in the fine array (each member is a busy time period and consists of two time points [ x, y ]).
When the number of members recorded in the fine array exceeds 10, the following busy period is added to the fuzzy array, but the busy period already recorded in the fine array is not added to the fuzzy array.
Referring to fig. 3, for each thread (such as thread 101 and thread 102, which is described later by taking thread 101 as an example), the busy time interval of the specified counting period can be counted in the following manner.
And 305, judging whether the number of members in the fine array of the Tmix structure reaches the upper limit of the number of members.
If not, go to step 306; if so, step 307 is performed.
Specifically, a fine time interval located at a specified statistical period may be selected from the task processing time intervals [ t1, t2] and recorded into a fine array of the Tmix structure.
For example, the specified statistical period is 1-2 seconds, and the task processing time interval [ t1, t2] is [0.8, 1.1], and therefore, the fine time interval [1.0, 1.1] located at the specified statistical period may be selected from the task processing time interval [0.8, 1.1], and the fine time interval [1.0, 1.1] may be recorded into the fine array of the Tmix structure.
Specifically, fuzzy time intervals with intersections with the task processing time intervals [ t1, t2] may be determined, and then the fuzzy time intervals with intersections may be recorded into the fuzzy array of the Tmix structure.
For example, the statistical period is specified to be 1-2 seconds, the task processing time interval [ t1, t2] is specified to be [0.8, 1.1], the fuzzy array records K values, K is 10, the fuzzy time interval is [1.0, 1.1], [1.1, 1.2], and so on. Obviously, since the task processing time interval [0.8, 1.1] and the fuzzy time interval [1.0, 1.1] have an intersection, the fuzzy time interval [1.0, 1.1] is recorded into the fuzzy array of the Tmix structure.
When the fuzzy time interval [1.0, 1.1] is recorded in the fuzzy array of the Tmix structure, in one mode, the value corresponding to the fuzzy time interval [1.0, 1.1] in the fuzzy array is modified into 1, and the thread is in a busy state at [1.0, 1.1 ]. In another approach, the fuzzy time interval [1.0, 1.1] is recorded into the fuzzy array.
Further, the above steps 302 to 307 may be repeated.
Based on the busy time interval of each thread (such as thread 101 and thread 102) in a specified counting period, the system usage rate may be counted, and as shown in fig. 4, the counting process of the system usage rate may include:
in step 401, the Tmix structure (such as the fine array and the fuzzy array) of the thread 101 in the specified statistical period is obtained, and the Tmix structure (such as the fine array and the fuzzy array) of the thread 102 in the specified statistical period is obtained.
For example, thread 101 has busy time intervals of [1-1.1, 1.3-1.5, 1.7-1.9] for a specified statistical period, and thread 102 has busy time intervals of [1.1-1.2, 1.3-1.5, 1.6-1.9] for a specified statistical period.
Optionally, in an example, a union of busy time interval 1 and busy time interval 2 may be obtained, and the union of busy time interval 1 and busy time interval 2 may be determined as busy time interval 3.
For example, busy time interval 1 is [1-1.1, 1.3-1.5, 1.7-1.9], busy time interval 2 is [1.1-1.2, 1.3-1.5, 1.6-1.9], and the union of the two is [1-1.2, 1.3-1.5, 1.6-1.9], that is, busy time interval 3 of the IO forwarding system at a given statistical period may be [1-1.2, 1.3-1.5, 1.6-1.9 ].
Optionally, in another example, a merged array is constructed for a specified statistical period, the merged array may include M members, a value of M may be configured according to experience, and a value of M may be greater than a value of K, which means that one second is divided into M shares, for example, an average is divided into M shares, and each share corresponds to one time interval. For example, a second is sliced into 1000 shares, the first representing the 0-1 millisecond time interval, the second representing the 1-2 millisecond time interval, the third representing the 2-3 millisecond time interval, and so on.
In the first case, the merge array may record M values, each value is 0 or 1, 0 indicates that the thread is in an idle state in the corresponding time interval, and 1 indicates that the thread is in a busy state in the corresponding time interval. For example, the fuzzy array is 0000011 …, and the fuzzy array is idle for the time interval of 0-1 ms, 1-2 ms, 2-3 ms, 3-4 ms, and 4-5 ms, and busy for the time interval of 5-6 ms, and 6-7 ms.
Based on this, the merging time interval (i.e. the time intervals corresponding to the above M values) intersecting with the busy time interval 1 may be determined, and then the values of these merging time intervals are modified to 1 in the merging array. In addition, merge time intervals that intersect busy time interval 2 may be determined, and then the values of these merge time intervals are modified to 1 in the merge array. Further, a time interval with a value of 1 in the merged array is a busy time interval 3 of the IO forwarding system in the specified statistical period.
In the second case, the merge array may record multiple time intervals, indicating that the time intervals are busy. Based on this, the merging time intervals (i.e., the time intervals corresponding to the M values) intersecting the busy time interval 1 can be determined, and these merging time intervals are recorded in the merging array. Merge time intervals that intersect busy time interval 2 may be determined and recorded in the merge array (merge time intervals that already exist in the merge array are not recorded anymore). Further, the time interval in the merged array is the busy time interval 3 of the IO forwarding system in the specified statistical period.
Based on the technical scheme, in the embodiment of the application, the accurate system utilization rate can be obtained, so that network management personnel can know the operation state of the IO forwarding system. Moreover, a plurality of threads can process a plurality of IO tasks in parallel, so that the processing performance of the IO tasks is improved. In addition, a two-stage mode of a fine array and a fuzzy array is provided, the fine array can be adopted when the data volume is not large, so that efficient and fine recording can be realized, the fuzzy array can be adopted when the data volume is large, the storage space can be ensured not to be excessively occupied, and the storage space is saved.
Based on the same application concept as the method described above, an embodiment of the present application further provides a data acquisition apparatus, which is applied to an IO forwarding system including multiple threads, where the multiple threads are all used to process an IO task, as shown in fig. 5, the data acquisition apparatus is a structure diagram of the data acquisition apparatus, and the data acquisition apparatus includes:
a first determining module 51, configured to determine a starting time point when the first thread is switched from the unprocessed IO task to the processed IO task, and an ending time point when the first thread is switched from the processed IO task to the unprocessed IO task;
a second determining module 52, configured to determine a first busy time interval of the first thread in a specified statistical period by using the starting time point and the ending time point;
a third determining module 53, configured to determine, by using the first busy time interval of the multiple threads in a specified statistics period, a second busy time interval of the IO forwarding system in the specified statistics period;
an obtaining module 54, configured to obtain a system utilization rate of the specified statistical period according to the second busy time interval; wherein the first thread is any one of the plurality of threads.
The second determining module 52 determines, by using the starting time point and the ending time point, that the first thread is specifically configured to:
determining a task processing time interval by using the starting time point and the ending time point;
selecting a fine time interval positioned in a specified statistical period from the task processing time intervals;
determining the fine time interval as the first busy time interval.
The second determining module 52 determines, by using the starting time point and the ending time point, that the first thread is specifically configured to:
determining a task processing time interval by using the starting time point and the ending time point;
and dividing the appointed statistical period into a plurality of fuzzy time intervals, and if the task processing time interval and the fuzzy time interval have intersection, determining the fuzzy time interval as the first busy time interval.
The third determining module 53 determines, by using the first busy time interval of the plurality of threads in the specified statistical period, that the IO forwarding system is specifically configured to: acquiring a union of first busy time intervals corresponding to each first thread in the multiple threads, and determining the first busy time interval corresponding to the union as the second busy time interval.
The third determining module 53 determines, by using the first busy time interval of the plurality of threads in the specified statistical period, that the IO forwarding system is specifically configured to: dividing a specified statistical period into a plurality of merging time intervals;
and if the first busy time interval corresponding to the first thread and the merging time interval have intersection, determining the merging time interval as the second busy time interval.
The obtaining module 54 is specifically configured to, when obtaining the system usage rate of the specified statistical period according to the second busy time interval: acquiring the proportional relation between the second busy time interval and the specified statistical period; and acquiring the system utilization rate of the specified statistical period according to the proportional relation.
Based on the same application concept as the method, an embodiment of the present application further provides a data acquisition device, where the data acquisition device includes a plurality of threads, the plurality of threads are all used for processing an IO task, and the data acquisition device includes: a processor and a machine-readable storage medium having stored thereon a plurality of computer instructions, the processor when executing the computer instructions performs:
determining a starting time point when the first thread is switched from the unprocessed IO task to the processed IO task and an ending time point when the first thread is switched from the processed IO task to the unprocessed IO task; determining a first busy time interval of the first thread in a specified statistical period by using the starting time point and the ending time point;
determining a second busy time interval of the IO forwarding system in a specified counting period by using the first busy time interval of the plurality of threads in the specified counting period;
acquiring the system utilization rate of the specified statistical period according to the second busy time interval;
wherein the first thread is any one of the plurality of threads.
The embodiment of the application also provides a machine-readable storage medium, wherein a plurality of computer instructions are stored on the machine-readable storage medium; the computer instructions when executed perform the following:
determining a starting time point when the first thread is switched from the unprocessed IO task to the processed IO task and an ending time point when the first thread is switched from the processed IO task to the unprocessed IO task; determining a first busy time interval of the first thread in a specified statistical period by using the starting time point and the ending time point;
determining a second busy time interval of the IO forwarding system in a specified counting period by using the first busy time interval of the plurality of threads in the specified counting period;
acquiring the system utilization rate of the specified statistical period according to the second busy time interval;
wherein the first thread is any one of the plurality of threads.
Referring to fig. 6, which is a structural diagram of a data acquisition device proposed in an embodiment of the present application, the data acquisition device 60 may include: a processor 61, a network interface 62, a bus 63, and a memory 64. The memory 64 may be any electronic, magnetic, optical, or other physical storage device that can contain or store information such as executable instructions, data, and the like. For example, the memory 64 may be: RAM (random Access Memory), volatile Memory, non-volatile Memory, flash Memory, a storage drive (e.g., a hard drive), a solid state drive, any type of storage disk (e.g., a compact disk, a dvd, etc.).
The systems, devices, modules or units illustrated in the above embodiments may be implemented by a computer chip or an entity, or by a product with certain functions. A typical implementation device is a computer, which may take the form of a personal computer, laptop computer, cellular telephone, camera phone, smart phone, personal digital assistant, media player, navigation device, email messaging device, game console, tablet computer, wearable device, or a combination of any of these devices.
For convenience of description, the above devices are described as being divided into various units by function, and are described separately. Of course, the functionality of the units may be implemented in one or more software and/or hardware when implementing the present application.
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, embodiments of 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.
Furthermore, 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.
The above description is only an example of the present application and is 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 (13)
1. A data acquisition method is applied to an input/output (IO) forwarding system comprising a plurality of threads, wherein the plurality of threads are all used for processing IO tasks, and the method comprises the following steps:
determining a starting time point when the first thread is switched from the unprocessed IO task to the processed IO task and an ending time point when the first thread is switched from the processed IO task to the unprocessed IO task; determining a first busy time interval of the first thread in a specified statistical period by using the starting time point and the ending time point;
determining a second busy time interval of the IO forwarding system in a specified counting period by using the first busy time interval of the plurality of threads in the specified counting period;
acquiring the system utilization rate of the specified statistical period according to the second busy time interval;
wherein the first thread is any one of the plurality of threads.
2. The method of claim 1, wherein determining a first busy interval for the first thread for a specified statistical period using the start time point and the end time point comprises:
determining a task processing time interval by using the starting time point and the ending time point;
selecting a fine time interval positioned in a specified statistical period from the task processing time intervals;
determining the fine time interval as the first busy time interval.
3. The method of claim 1, wherein determining a first busy interval for the first thread for a specified statistical period using the start time point and the end time point comprises:
determining a task processing time interval by using the starting time point and the ending time point;
and dividing the appointed statistical period into a plurality of fuzzy time intervals, and if the task processing time interval and the fuzzy time interval have intersection, determining the fuzzy time interval as the first busy time interval.
4. The method of claim 1,
determining, by the plurality of threads in the first busy time interval of a specified statistical period, that the IO forwarding system is in the second busy time interval of the specified statistical period, including:
acquiring a union of first busy time intervals corresponding to each first thread in the multiple threads, and determining the first busy time interval corresponding to the union as the second busy time interval.
5. The method of claim 1,
determining, by the plurality of threads in the first busy time interval of a specified statistical period, that the IO forwarding system is in the second busy time interval of the specified statistical period, including:
dividing a specified statistical period into a plurality of merging time intervals;
and if the first busy time interval corresponding to the first thread and the merging time interval have intersection, determining the merging time interval as the second busy time interval.
6. The method of claim 1,
obtaining the system utilization rate of the specified statistical period according to the second busy time interval, including:
acquiring the proportional relation between the second busy time interval and the specified statistical period;
and acquiring the system utilization rate of the specified statistical period according to the proportional relation.
7. A data acquisition apparatus, applied to an input/output (IO) forwarding system including a plurality of threads, the plurality of threads each being configured to process an IO task, the apparatus comprising:
the first determining module is used for determining the starting time point of the first thread switched from the unprocessed IO task to the processed IO task and the ending time point of the first thread switched from the processed IO task to the unprocessed IO task;
the second determining module is used for determining a first busy time interval of the first thread in a specified statistical period by using the starting time point and the ending time point;
a third determining module, configured to determine, by using the first busy time interval of the multiple threads in a specified statistics period, a second busy time interval of the IO forwarding system in the specified statistics period;
the acquisition module is used for acquiring the system utilization rate of the specified statistical period according to the second busy time interval;
wherein the first thread is any one of the plurality of threads.
8. The apparatus of claim 7,
the second determining module determines, by using the starting time point and the ending time point, that the first thread is specifically used for:
determining a task processing time interval by using the starting time point and the ending time point;
selecting a fine time interval positioned in a specified statistical period from the task processing time intervals;
determining the fine time interval as the first busy time interval.
9. The apparatus of claim 7,
the second determining module determines, by using the starting time point and the ending time point, that the first thread is specifically used for:
determining a task processing time interval by using the starting time point and the ending time point;
and dividing the appointed statistical period into a plurality of fuzzy time intervals, and if the task processing time interval and the fuzzy time interval have intersection, determining the fuzzy time interval as the first busy time interval.
10. The apparatus of claim 7, wherein the third determining module determines, using the first busy time interval of the plurality of threads for a specified statistical period, that the IO forwarding system is specifically configured to, when the second busy time interval of the specified statistical period:
acquiring a union of first busy time intervals corresponding to each first thread in the multiple threads, and determining the first busy time interval corresponding to the union as the second busy time interval.
11. The apparatus of claim 7, wherein the third determining module determines, using the first busy time interval of the plurality of threads for a specified statistical period, that the IO forwarding system is specifically configured to, when the second busy time interval of the specified statistical period:
dividing a specified statistical period into a plurality of merging time intervals;
and if the first busy time interval corresponding to the first thread and the merging time interval have intersection, determining the merging time interval as the second busy time interval.
12. The apparatus of claim 7, wherein the obtaining module, when obtaining the system usage rate for the specified statistical period according to the second busy time interval, is specifically configured to:
acquiring the proportional relation between the second busy time interval and the specified statistical period;
and acquiring the system utilization rate of the specified statistical period according to the proportional relation.
13. A data acquisition device, characterized in that the data acquisition device includes a plurality of threads, the plurality of threads are all used for processing IO tasks, the data acquisition device includes:
a processor and a machine-readable storage medium having stored thereon a plurality of computer instructions, the processor when executing the computer instructions performs:
determining a starting time point when the first thread is switched from the unprocessed IO task to the processed IO task and an ending time point when the first thread is switched from the processed IO task to the unprocessed IO task; determining a first busy time interval of the first thread in a specified statistical period by using the starting time point and the ending time point;
determining a second busy time interval of the IO forwarding system in a specified counting period by using the first busy time interval of the plurality of threads in the specified counting period;
acquiring the system utilization rate of the specified statistical period according to the second busy time interval;
wherein the first thread is any one of the plurality of threads.
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