WO2017118341A1

WO2017118341A1 - Data monitoring method and apparatus

Info

Publication number: WO2017118341A1
Application number: PCT/CN2016/113454
Authority: WO
Inventors: 陈磊; 解敏; 范茸; 陈国俊
Original assignee: 阿里巴巴集团控股有限公司
Priority date: 2016-01-06
Filing date: 2016-12-30
Publication date: 2017-07-13
Also published as: CN106952106A

Abstract

A data monitoring method and apparatus. The method comprises: acquiring a data sampling configuration, wherein the data sampling configuration indicates the proportional position of sampled data (101); acquiring, from data to be monitored, at least two pieces of sampled data corresponding to the proportional position (102); acquiring a data fluctuation feature of the at least two pieces of sampled data (103); and according to the data fluctuation feature, obtaining a monitoring result of the data to be monitored (104). Since not all data in the data to be monitored need to be monitored, instead, at least two pieces of sampled data are sampled by means of a data sampling configuration, and the data is monitored by means of a data fluctuation feature of the at least two pieces of sampled data, data monitoring is realized, and at the same time, workloads can be reduced.

Description

Data monitoring method and device

The present application claims the priority of the Chinese Patent Application Serial No. No. No. No. No. No.

Technical field

The present application relates to the field of computer technology, and in particular, to a data monitoring method and apparatus.

Background technique

In the era of big data, data is being analyzed and used more and more widely. However, due to the increasing data volume of data, the collection process becomes more and more complicated, which leads to stability problems in data. Therefore, how to monitor the stability of data is particularly important.

At present, the commonly used data monitoring method is to use a manual monitoring method or a simple script file for data comparison, and judge whether the data has stability problem according to the comparison result.

However, whether it is a manual monitoring method or a simple script file for monitoring, the amount of data tends to be large, which will result in a large workload.

Summary of the invention

The technical problem to be solved by the present application is to provide a data monitoring method and device, which can reduce the workload while realizing data monitoring.

To this end, the technical solution to solve the technical problem of the present application is:

The application provides a data monitoring method, including:

Acquiring a data sampling configuration, the data sampling configuration indicating a proportional position of the sampled data;

Acquiring at least two sampling data corresponding to the proportional position from the data to be monitored;

Obtaining data fluctuation characteristics of the at least two sampled data;

Obtaining a monitoring result of the data to be monitored according to the data fluctuation feature.

Optionally, the data to be monitored includes sampling data of multiple cycles; the proportional position includes the same proportional position of at least two periods, at least two proportional positions of the same period, or at least two of the total number of periods Proportional position.

Optionally, the proportional position includes a first proportional position of the first period and the second period;

Acquiring at least two sampling data corresponding to the proportional position from the data to be monitored, including:

Obtaining sampling data corresponding to the first proportional position of the first period and sampling data corresponding to the first proportional position of the second period from the data to be monitored;

Obtaining data fluctuation characteristics of the at least two sampled data, including:

Comparing the sampling data corresponding to the first proportional position of the second period with the sampling data corresponding to the first proportional position of the first period to obtain a comparison result;

The data fluctuation feature is obtained based on the comparison result.

Optionally, the method includes: the proportional position includes a first proportional position of the first period and the second period, and a second proportional position of the first period and the second period;

Obtain at least two sample data from the data to be monitored, including:

Obtaining, from the data to be monitored, sampling data corresponding to a first proportional position of the first period, sampling data corresponding to a first proportional position of the second period, sampling data corresponding to a second proportional position of the first period, and a second period The sampling data corresponding to the second proportional position;

Comparing the sampling data corresponding to the first proportional position of the second period with the sampling data corresponding to the first proportional position of the first period to obtain a first comparison result;

Comparing the sampling data corresponding to the second proportional position of the second period with the sampling data corresponding to the second proportional position of the first period to obtain a second comparison result;

The data fluctuation feature is obtained according to the first comparison result and the second comparison result.

Optionally, the proportional position includes at least three proportional positions of the current period;

Obtaining sampling data corresponding to at least three proportional positions of the current period from the data to be monitored;

Obtaining a change trend of sampling data corresponding to the adjacent proportional position according to sampling data corresponding to at least three proportional positions of the current period;

The data fluctuation feature is acquired according to the change trend.

Optionally, the proportional position includes at least three proportional positions of the total number of cycles;

Obtaining, from the data to be monitored, sampling data of a period corresponding to the at least three proportional positions in all periods;

And obtaining the data fluctuation feature according to the sampling data of the period corresponding to the at least three proportional positions respectively.

Optionally, the data fluctuation feature includes at least one of the following data features:

The fluctuation amount, the fluctuation ratio, the fluctuation amount or the fluctuation ratio attribute, the fluctuation tendency, and the standard deviation of the at least two sampled data.

The application provides a data monitoring device, including:

a configuration acquiring unit, configured to acquire a data sampling configuration, where the data sampling configuration indicates a proportional position of the sampled data;

a data acquiring unit, configured to acquire at least two sampling data corresponding to the proportional position from data to be monitored;

a feature acquiring unit, configured to acquire data fluctuation characteristics of the at least two sampled data;

And a result obtaining unit, configured to obtain, according to the data fluctuation feature, a monitoring result of the data to be monitored.

The data acquiring unit is configured to: obtain, from the data to be monitored, sampling data corresponding to a first proportional position of a first period and sampling data corresponding to a first proportional position of a second period;

The feature acquiring unit is configured to compare sampling data corresponding to the first proportional position of the second period with sampling data corresponding to the first proportional position of the first period, to obtain a comparison result, and according to the comparison result The data fluctuation characteristics are obtained.

Optionally, the proportional position includes a first proportional position of the first period and the second period, and a second proportional position of the first period and the second period;

The data acquiring unit is configured to: obtain, from the data to be monitored, sampling data corresponding to a first proportional position of a first period, sampling data corresponding to a first proportional position of a second period, and a second ratio of the first period Sampling data corresponding to the location and sampling data corresponding to the second proportional position of the second period;

The feature acquiring unit is configured to compare sampling data corresponding to the first proportional position of the second period with sampling data corresponding to the first proportional position of the first period, to obtain a first comparison result, where the first Comparing the sampling data corresponding to the second proportional position of the two periods with the sampling data corresponding to the second proportional position of the first period, obtaining a second comparison result, and obtaining the basis according to the first comparison result and the second comparison result The characteristics of data fluctuations.

The data acquiring unit is configured to: obtain, from the data to be monitored, sampling data corresponding to at least three proportional positions of a current period;

The feature acquiring unit is configured to acquire a trend of the sampling data corresponding to the adjacent proportional position according to the sampling data corresponding to the at least three proportional positions of the current period, and acquire the data fluctuation feature according to the changing trend.

The data acquiring unit is configured to: acquire, from the data to be monitored, sampling data of a period corresponding to the at least three proportional positions in all periods;

The feature acquiring unit is configured to obtain the data fluctuation feature according to the sampling data of the period corresponding to the at least three proportional positions.

According to the foregoing technical solution, in the embodiment of the present application, the data sampling configuration is obtained, where the data sampling configuration indicates the proportional position of the sampled data, and thus at least two sampling data corresponding to the proportional position are obtained from the data to be monitored, That is, the data to be monitored is sampled, and the monitoring result of the data to be monitored is obtained according to the data fluctuation characteristics of the at least two sampled data. It can be seen that, in the embodiment of the present application, all data of the monitoring data is no longer monitored, but at least two sampling data are sampled by using the data sampling configuration, and data fluctuation characteristics of at least two sampling data are used for data monitoring, thereby implementing Data monitoring can reduce the workload at the same time.

DRAWINGS

In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings used in the description of the embodiments will be briefly described below. It is obvious that the drawings in the following description are only some embodiments of the present application. Other figures may also be obtained from those of ordinary skill in the art in view of these figures.

1 is a schematic flow chart of an embodiment of a method provided by the present application;

2 is a schematic flow chart of another method embodiment provided by the present application;

FIG. 3 is a schematic structural diagram of an apparatus embodiment provided by the present application.

detailed description

As the data volume of data increases, the collection process becomes more and more complicated, and it is inevitable that stability will occur due to data errors or large fluctuations in the data itself. Therefore, how to monitor the stability of the data, when the data is a problem, find and repair in time, it is particularly important.

Continuous data mainly refers to data representing business characteristics generated every fixed period in the database. For example, in big data, it usually produces one piece of data per day, one piece of data per week, or one piece of data per month, which can be stored in different partitions in the database.

The fluctuation of continuous data usually meets certain rules, and the rule is used to monitor the volatility of continuous data to ensure the continuous stability of data is called stability monitoring. For example, a certain health bureau's data is monthly drug consumption. If this data suddenly increases, the fluctuation is more serious, which means that the number of patients in the area is increasing, and the health department needs to make an advance plan for a certain Drugs are macro-dispatched to ensure the health of members of society.

At present, the commonly used data monitoring method is to use a manual monitoring method or a simple script file for data comparison, and judge whether the data has stability problem according to the comparison result. However, whether it is a manual monitoring method or a simple script file for monitoring, the amount of data tends to be large, which will result in a large workload.

The embodiment of the present application provides a data monitoring method and device, which can reduce the workload while realizing data monitoring.

The technical solutions in the embodiments of the present application are clearly and completely described in the following, in which the technical solutions in the embodiments of the present application are clearly and completely described. The embodiments are only a part of the embodiments of the present application, and not all of them. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments of the present application without departing from the inventive scope should fall within the scope of the present invention.

Referring to FIG. 1, the present application provides an embodiment of a method for monitoring data. The method of this embodiment includes:

101: Acquire a data sampling configuration, where the data sampling configuration indicates a proportional position of the sampled data.

In the embodiment of the present application, the data sampling configuration may be pre-configured by the user to determine the proportional position of the sampled data, that is, the position at which the sampled data is located according to the ratio of (number or time, etc.). For example, the proportional position of the sampled data is m%, indicating that the sampled data is located at a position corresponding to the number or time ratio of m%, and may also be referred to as an M-score, M=m/10.

Step 102: Obtain at least two sampling data corresponding to the proportional position from data to be monitored.

In this embodiment, the data to be monitored may be read from a database such as an Open Data Processing Service (ODPS) or a data warehouse Hive.

The data to be monitored may include sampling data of a plurality of cycles; the proportional position may include at least two identical positions of at least two cycles, at least two proportional positions of the same cycle, or at least two of a total number of cycles Proportional position. The details are as follows. Can be read from an offline database.

In the first case, the proportional position includes the same proportional position of at least two cycles. For example, the proportional position includes the first proportional position of the first period and the second period, and then the sampling data corresponding to the first proportional position of the first period and the sampling data corresponding to the first proportional position of the second period are acquired in 102. For example, the first period is the current day, the second period is the previous day, and the first proportional position is 30%, and the sampling data corresponding to the first proportional position of the first period refers to all data of the current day, 30% of the corresponding sampling data, assuming that 100 samples of data are generated in chronological order on the same day, specifically may refer to the 30th (100×30%) sampling data; the sampling data corresponding to the second proportional position of the second period Refers to the sampling data corresponding to the 30th position of all the data of the previous day.

In the second case, the proportional position includes at least two proportional positions of the same period. For example, the proportional position includes the first proportional position and the second proportional position of the current period, and then the sampling data corresponding to the first proportional position of the current period and the sampling data corresponding to the second proportional position of the current period are acquired. For example, the first proportional position is 30%, and the second proportional position is 60%. The sampling data corresponding to the first proportional position of the current period refers to the sampling data corresponding to the 30%th position of all the data of the current day. The sampling data corresponding to the second proportional position of the period refers to the sampling data corresponding to the 60%th position of all the data of the day.

In the third case, the proportional position includes at least two proportional positions of the total number of cycles. For example, the proportional position includes a first proportional position and a second proportional position of the total number of cycles, and in the total number of acquisition cycles in 102, the sampling data of the period corresponding to the first proportional position, and the second The sampling data of the period corresponding to the proportional position. For example, the first proportional position is 20%, the second proportional position is 40%, and the total number of periods is 100. The sampling data of the period corresponding to the first proportional position refers to the sampling data of the 20th period. The sampling data of the period corresponding to the second proportional position refers to the sampling data of the 40th period.

103: Acquire data fluctuation characteristics of the at least two sampled data.

In the embodiment of the present application, the data fluctuation feature may include at least one of the following data characteristics: an attribute of the fluctuation amount, the fluctuation ratio, the fluctuation amount, or the fluctuation ratio of the at least two sampling data (for example, a standard deviation or a variance) Etc), fluctuation trends, and standard deviations, etc. After acquiring the data fluctuation feature in this embodiment, the data fluctuation feature may be stored in a database.

Wherein, when the sampled data is accumulated data, that is to say, the sampled data is accumulated data, for example, the at least two sampled data includes the total amount of commodities corresponding to the 5th hour of the day, and the 8th hour of the day corresponds to The total amount of goods, the data fluctuation characteristics can be obtained according to the fluctuation amount, the fluctuation ratio, the fluctuation amount or the fluctuation ratio data, or the fluctuation trend.

When the sampled data is independent data, that is, the sampled data are independent of each other, for example, the at least two sampled data include the number of commodities respectively produced on the current day and the previous day, and the data fluctuation characteristics can be acquired according to the standard deviation.

104: Obtain a monitoring result of the data to be monitored according to the data fluctuation feature.

Due to the data fluctuation characteristic, the fluctuation characteristics of at least two sampled data can be reflected, thereby being capable of indirectly reflecting the fluctuation characteristics of the data to be monitored. Therefore, according to the data fluctuation feature, it can be determined whether the fluctuation of the data to be monitored exceeds a normal range, and if so, an alarm or prompt information can be generated for prompting the user. For example, if the data fluctuation characteristic is greater than a preset fluctuation threshold, an alarm or prompt information may be generated.

According to the foregoing technical solution, in the embodiment of the present application, the data sampling configuration is obtained, where the data sampling configuration indicates the proportional position of the sampled data, and thus at least two sampling data corresponding to the proportional position are obtained from the data to be monitored, That is, the sampling of the data to be monitored is performed, and the monitoring result of the data to be monitored is obtained according to the data fluctuation characteristics of the sampled at least two sampling data. It can be seen that, in the embodiment of the present application, all data in the monitoring data is no longer monitored, but at least two sampling data are sampled by using the data sampling configuration, and data fluctuation characteristics of at least two sampling data are used for data monitoring, so While realizing data monitoring, it can reduce the workload.

In the embodiment of the present application, the stability check rule may be preset, and the data fluctuation feature is calculated according to the stability check rule, thereby obtaining the band characteristic of the sampled data. Four alternative implementations of the stability check rule will be provided in the following embodiments of the present application.

(1) In the first stability check rule, data fluctuation characteristics are acquired according to sampling data corresponding to the same proportional position of at least two periods.

Specifically, the proportional position includes a first proportional position of the first period and the second period. The first period, the second period, and the first proportional position may be set by the user in the data sampling configuration. For example, the first period may be the current day, and the second period may be the first N days, where N may be Take values from the set (1, 3, 7). The first proportional position may be a position corresponding to m%, and m may be a value in the set (20, 30, 40, 50, 60, 70, 80, 90).

The method 102 includes: acquiring sampling data corresponding to a first proportional position of the first period from the data to be monitored, and The sampling data corresponding to the first proportional position of the second period.

For example, from the data to be monitored, the sampling data corresponding to the m% position of all the data of the day, and the sampling data corresponding to the m% position of all the data of the first N days, if the m% The position corresponds to a decimal and can be rounded off. The sampled data may be accumulated data. For example, each sampled data corresponds to the total amount of commodities at a certain moment, and the data of the mth digit may be the total amount of commodities corresponding to the m%th position.

The method 103 includes: comparing sampling data corresponding to the first proportional position of the second period with sampling data corresponding to the first proportional position of the first period to obtain a comparison result; and obtaining the data fluctuation characteristic according to the comparison result.

For example, in all the data of the day, the sampling data corresponding to the m% position is X, and the data corresponding to the m% position of all the data of the first N days is Y, and the comparison result may be the fluctuation amount: XY or Fluctuation ratio: (XY) / X. The comparison result may be compared with a preset fluctuation threshold. If the comparison result is greater than the preset fluctuation threshold, the fluctuation is relatively large, and the prompt or alarm information may be generated at this time.

(2) In the second stability check rule, data fluctuation characteristics are acquired according to sampling data corresponding to a plurality of identical proportional positions of at least two periods.

Specifically, the proportional position includes a first proportional position of the first period and the second period, and a second proportional position of the first period and the second period. The first period, the second period, the first proportional position, and the second proportional position may all be set by the user in the data sampling configuration. For example, the first period may be the current day, and the second period may be the first N days. , where N can take values in the set (1, 3, 7). The first proportional position may be a position corresponding to m1%, the first proportional position may be a position corresponding to m2%, and m1 and m2 are respectively taken in a set (20, 30, 40, 50, 60, 70, 80, 90) , m1 < m2.

The method includes: acquiring, from the data to be monitored, sampling data corresponding to a first proportional position of a first period, sampling data corresponding to a first proportional position of a second period, sampling data corresponding to a second proportional position of the first period, and The sample data corresponding to the second proportional position of the second period.

For example, from the data to be monitored, the sampling data corresponding to the m1% position and the sampling data corresponding to the m2% position of all the data of the day, and all the data of the first N days are at the m1%. The sampling data corresponding to the position and the sampling data corresponding to the position of the m2%. The sampled data may be accumulated data. For example, each sampled data corresponds to the total quantity of products at a certain moment, and the data of the m1%th bit may be the total quantity of commodities corresponding to the position of the m1%, and the data of the m2%th bit. It can be the total amount of goods corresponding to the m2% position.

103: comparing sampling data corresponding to the first proportional position of the second period with sampling data corresponding to the first proportional position of the first period to obtain a first comparison result; and second ratio of the second period Location pair The sampled data is compared with the sampled data corresponding to the second proportional position of the first cycle to obtain a second comparison result; and the data fluctuation feature is obtained according to the first comparison result and the second comparison result.

For example, the sampling data corresponding to the m1% position of all the data of the day is X1, and the sampling data corresponding to the m1% position of all the data of the first N days is Y1, and the first comparison result may be the fluctuation amount X1. -Y1 or fluctuation ratio (X1-Y1)/X1. The sampling data corresponding to the m2% position of all the data of the day is X2, and the sampling data corresponding to the m2% position of all the data of the first N days is Y2, and the second comparison result may be the fluctuation amount X2-Y2. Or the fluctuation ratio (X2-Y2)/X2.

The attributes of the first comparison result and the second comparison result, such as standard deviation, variance, or change trend, etc., may be used as the data fluctuation feature. The data fluctuation characteristic is compared with a preset fluctuation threshold. If the data fluctuation characteristic is greater than a preset fluctuation threshold, the fluctuation is relatively large, and the prompt or alarm information may be generated at this time.

(3) In the third stability check rule, data fluctuation characteristics are acquired according to sampling data corresponding to different proportional positions of the same period.

Specifically, the proportional position includes at least three proportional positions of the current period. Wherein, at least three proportional positions may be set by the user in the data sampling configuration, for example, the at least three proportional positions may include 1 minute, 2 minutes, 3 minutes, ..., 9 points, 9 in total position.

The method includes: acquiring sampling data corresponding to at least three proportional positions of the current period from the data to be monitored. For example, from the data to be monitored, among all the data of the day, the sampling data corresponding to the 10th, 20th, 30th, ..., 90thth positions respectively.

The method includes: acquiring, according to the sampling data corresponding to the at least three proportional positions of the current period, a variation trend of the sampling data corresponding to the adjacent proportional position; and acquiring the data fluctuation feature according to the changing trend.

In this rule, the data fluctuation characteristics are mainly determined according to the trend of the sampled data. For example, in some cases, the sampled data is continuously increased, for example, when the sampled data is specifically the age of the user, and if the change trend is judged at this time In order to increase, it indicates that the data fluctuation characteristics are better; on the contrary, if the change trend is increased or decreased, the data fluctuation characteristics are poor, and prompt or alarm information can be generated at this time. In other cases, the sampled data is continuously reduced. For example, the sampled data is specifically the remaining number of commodities, and at this time, the data fluctuation characteristics can be judged according to whether the change trend is always reduced.

(4) In the fourth stability check rule, the data fluctuation characteristics are acquired according to the sampling data corresponding to the proportional position of the time.

Specifically, the proportional position includes at least three proportional positions of the total number of cycles. Wherein, at least three proportional positions may be set by the user in a data sampling configuration, for example, the at least three proportional positions may include 2 The position corresponding to the quantile, 4th, 6th, and 8th positions.

The method includes: acquiring, from the data to be monitored, sampling data of a period corresponding to the at least three proportional positions in all periods. For example, a total of 30 cycles (for example, 1 cycle per cycle) are obtained, and sampling data of the 20th, 40th, 60th, and 80thth positions respectively corresponding to the positions of the 30th cycle, that is, the first The sample data corresponding to the 6th, 12th, 18th, and 24th cycles, respectively. The sampled data may be independent data. For example, the sampled data of each cycle may be the total number of data generated in this cycle.

The method 103 includes: obtaining the data fluctuation feature according to sampling data of a period corresponding to the at least three proportional positions respectively.

The standard deviation of the sampling data of the period corresponding to the at least three proportional positions may be used as the data fluctuation characteristic. For example, the standard deviation is calculated based on the total number of pieces of data generated at the sixth, twelfth, eighteenth, and twenty-fourth cycles. The calculated standard deviation can be compared with a preset fluctuation threshold. If the calculated standard deviation is greater than the preset fluctuation threshold, the fluctuation is relatively large, and a prompt or alarm information can be generated at this time. Alternatively, the fluctuation value or the fluctuation ratio between the periods of the adjacent proportional positions may be separately calculated, and the data fluctuation characteristics may be determined according to the fluctuation value or the variation trend of the fluctuation ratio. For example, the sampled data is the drug consumption value, and the fluctuation ratio of the adjacent two data is calculated according to the drug consumption value generated in the sixth, twelfth, 18th, and 24th cycles, and if the fluctuation ratio is continuously high, the health is indicated. The degree is decreasing, and a prompt or alarm message can be generated at this time.

The present application is described below by way of a specific embodiment.

Referring to FIG. 2, the present application provides an embodiment of a method for monitoring data. The method of this embodiment includes:

201: Call a data production task to generate continuous data.

202: Simultaneously generating continuous data, triggering a stability monitoring module, and the stability monitoring module acquires a data sampling configuration set by a user. The data sampling configuration indicates a proportional position of the sampled data.

203: Acquire at least two sampling data corresponding to the proportional position from the generated continuous data.

204: Acquire multiple stability check rules, and classify each stability check rule according to a predefined degree of importance classification.

205: Acquire data fluctuation characteristics of the at least two sampled data according to the result of the classification, and using each stability check rule.

206: Obtain a monitoring result of the data to be monitored according to the data fluctuation feature.

Corresponding to the foregoing method embodiments, the embodiment of the present application further provides a corresponding device embodiment, which is specifically described below.

Referring to FIG. 3, the present application provides an apparatus embodiment of a data monitoring apparatus. The device of the embodiment The configuration includes: a configuration acquisition unit 301, a data acquisition unit 302, a feature acquisition unit 303, and a result acquisition unit 304.

The configuration obtaining unit 301 is configured to acquire a data sampling configuration, where the data sampling configuration indicates a proportional position of the sampled data.

In the embodiment of the present application, the data sampling configuration may be pre-configured by the user to determine the proportional position of the sampled data, that is, the position at which the sampled data is located according to the ratio of (number or time, etc.). For example, the proportional position of the sampled data is m%, indicating that the sampled data is located at a position corresponding to the number or time ratio of m%.

The data obtaining unit 302 is configured to acquire at least two sampling data corresponding to the proportional position from the data to be monitored.

The data to be monitored may include sampling data of a plurality of periods; the proportional position may include the same proportional position of at least two periods, at least two proportional positions of the same period, or at least two of the total number of periods Proportional position. The details are as follows.

In the first case, the proportional position includes the same proportional position of at least two cycles. For example, the proportional position includes a first proportional position of the first period and the second period, and the data acquiring unit 302 acquires sampling data corresponding to the first proportional position of the first period and sampling corresponding to the first proportional position of the second period. data.

In the second case, the proportional position includes at least two proportional positions of the same period. For example, the proportional position includes the first proportional position and the second proportional position of the current period, and the data acquiring unit 302 acquires the sampling data corresponding to the first proportional position of the current period and the sampling data corresponding to the second proportional position of the current period.

In the third case, the proportional position includes at least two proportional positions of the total number of cycles. For example, the proportional position includes a first proportional position and a second proportional position of the total number of cycles, and the data acquiring unit 302 acquires sampling data of a period corresponding to the first proportional position, and the The sampling data of the period corresponding to the second proportional position.

The feature acquiring unit 303 is configured to acquire data fluctuation characteristics of the at least two pieces of sample data.

In the embodiment of the present application, the data fluctuation feature may include at least one of the following data characteristics: an attribute of the fluctuation amount, the fluctuation ratio, the fluctuation amount, or the fluctuation ratio of the at least two sampling data (for example, a standard deviation or a variance) Etc), fluctuation trends, and standard deviations, etc.

Wherein, when the sampled data is accumulated data, for example, the at least two sampled data includes the total amount of commodities corresponding to the 5th hour of the day, and the total amount of commodities corresponding to the 8th hour of the day, the data fluctuation characteristic may be according to Data on fluctuations, volatility, volatility or volatility, or volatility acquisition.

When the sampled data is independent data, for example, the at least two sampled data includes the number of commodities respectively produced on the current day and the previous day, the data fluctuation characteristics may be acquired according to the standard deviation.

The result obtaining unit 304 is configured to obtain a monitoring result of the data to be monitored according to the data fluctuation feature.

Due to the data fluctuation characteristic, the fluctuation characteristics of at least two sampled data can be reflected, thereby being capable of indirectly reflecting the fluctuation characteristics of the data to be monitored. Therefore, the device may further include a generating unit, configured to determine, according to the data fluctuation feature, whether the fluctuation of the data to be monitored exceeds a normal range, and if yes, generate an alarm or prompt information for prompting the user . For example, if the data fluctuation characteristic is greater than a preset fluctuation threshold, an alarm or prompt information may be generated.

It can be seen that, in the embodiment of the present application, all data in the monitoring data is no longer monitored, but at least two sampling data are sampled by using the data sampling configuration, and data fluctuation characteristics of at least two sampling data are used for data monitoring, so While realizing data monitoring, it can reduce the workload.

In the first stability check rule, data fluctuation characteristics are acquired according to sampling data corresponding to the same proportional position of at least two periods.

Specifically, the proportional position includes a first proportional position of the first period and the second period. The data obtaining unit 302 is configured to acquire, from the data to be monitored, sampling data corresponding to a first proportional position of a first period and sampling data corresponding to a first proportional position of a second period. The feature acquiring unit 303 is configured to compare sampling data corresponding to the first proportional position of the second period with sampling data corresponding to the first proportional position of the first period, obtain a comparison result, and obtain the comparison result according to the comparison result. The data fluctuation feature.

Wherein, the comparison result may be a fluctuation amount or a fluctuation ratio. The comparison result may be compared with a preset fluctuation threshold. If the comparison result is greater than the preset fluctuation threshold, the fluctuation is relatively large, and the prompt or alarm information may be generated at this time.

In the second stability check rule, data fluctuation characteristics are acquired according to sampling data corresponding to a plurality of identical proportional positions of at least two periods.

Specifically, the proportional position includes a first proportional position of the first period and the second period, and a second proportional position of the first period and the second period. The data obtaining unit 302 is configured to: obtain, from the data to be monitored, sampling data corresponding to a first proportional position of a first period, sampling data corresponding to a first proportional position of a second period, and a second proportional position of the first period. Corresponding sample data and sample data corresponding to the second proportional position of the second period. The feature acquiring unit 303 is specifically configured to: sample data corresponding to the first proportional position of the second period and the first period Comparing the sampling data corresponding to the first proportional position, obtaining a first comparison result, comparing the sampling data corresponding to the second proportional position of the second period with the sampling data corresponding to the second proportional position of the first period, to obtain the first And comparing the results, and obtaining the data fluctuation characteristic according to the first comparison result and the second comparison result.

The first comparison result may be a fluctuation amount or a fluctuation ratio, and the second comparison result may be a fluctuation amount or a fluctuation ratio. The attributes of the first comparison result and the second comparison result, such as standard deviation, variance, or change trend, etc., may be used as the data fluctuation feature. The data fluctuation characteristic is compared with a preset fluctuation threshold. If the data fluctuation characteristic is greater than a preset fluctuation threshold, the fluctuation is relatively large, and the prompt or alarm information may be generated at this time.

In the third stability check rule, data fluctuation characteristics are acquired according to sampling data corresponding to different proportional positions of the same period.

Specifically, the proportional position includes at least three proportional positions of the current period. The data obtaining unit 302 is configured to: obtain, from the data to be monitored, sampling data corresponding to at least three proportional positions of the current period respectively; the feature acquiring unit 303 is specifically configured to: respectively, according to at least three proportional positions of the current period Sampling data, obtaining a trend of the sampling data corresponding to the adjacent proportional position; and acquiring the data fluctuation characteristic according to the changing trend.

In the fourth stability check rule, the data fluctuation characteristics are acquired according to the sampling data corresponding to the proportional position of the time.

Specifically, the proportional position includes at least three proportional positions of the total number of cycles; the data obtaining unit 302 is specifically configured to: acquire, from the data to be monitored, a period corresponding to the at least three proportional positions in all the periods And the feature acquiring unit 303 is configured to obtain the data fluctuation feature according to the sampling data of the period corresponding to the at least three proportional positions.

The standard deviation of the sampling data of the period corresponding to the at least three proportional positions may be used as the data fluctuation feature. Alternatively, the fluctuation value or the fluctuation ratio between the periods of the adjacent proportional positions may be separately calculated, and the data fluctuation characteristics may be determined according to the fluctuation value or the variation trend of the fluctuation ratio.

A person skilled in the art can clearly understand that for the convenience and brevity of the description, the specific working process of the system, the device and the unit described above can refer to the corresponding process in the foregoing method embodiment, and details are not described herein again.

In the several embodiments provided by the present application, it should be understood that the disclosed system, apparatus, and method may be implemented in other manners. For example, the device embodiments described above are merely illustrative. For example, the division of the unit is only a logical function division. In actual implementation, there may be another division manner, for example, multiple units or components may be combined or Can be integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interface, device or unit, and may be in an electrical, mechanical or other form.

The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, may be located in one place, or may be distributed to multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above integrated unit can be implemented in the form of hardware or in the form of a software functional unit.

The integrated unit, if implemented in the form of a software functional unit and sold or used as a standalone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application, in essence or the contribution to the prior art, or all or part of the technical solution may be embodied in the form of a software product stored in a storage medium. A number of instructions are included to cause a computer device (which may be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present application. The foregoing storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, and the like. .

The above embodiments are only used to explain the technical solutions of the present application, and are not limited thereto; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that they can still The technical solutions described in the embodiments are modified, or the equivalents of the technical features are replaced by the equivalents. The modifications and substitutions of the embodiments do not depart from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

A method for monitoring data, characterized in that it comprises:

Acquiring a data sampling configuration, the data sampling configuration indicating a proportional position of the sampled data;

Acquiring at least two sampling data corresponding to the proportional position from the data to be monitored;

Obtaining data fluctuation characteristics of the at least two sampled data;

Obtaining a monitoring result of the data to be monitored according to the data fluctuation feature.
The method according to claim 1, wherein the data to be monitored includes sampling data of a plurality of cycles; the proportional position includes the same proportional position of at least two periods, at least two proportional positions of the same period, Or at least two proportional positions of the total number of cycles.
The method according to claim 1 or 2, wherein the proportional position comprises a first proportional position of the first period and the second period;

Acquiring at least two sampling data corresponding to the proportional position from the data to be monitored, including:

Obtaining sampling data corresponding to the first proportional position of the first period and sampling data corresponding to the first proportional position of the second period from the data to be monitored;

Obtaining data fluctuation characteristics of the at least two sampled data, including:

Comparing the sampling data corresponding to the first proportional position of the second period with the sampling data corresponding to the first proportional position of the first period to obtain a comparison result;

The data fluctuation feature is obtained based on the comparison result.
The method according to claim 1 or 2, comprising: said proportional position comprising a first proportional position of the first period and the second period, and a second proportional position of the first period and the second period;

Obtain at least two sample data from the data to be monitored, including:

Obtaining, from the data to be monitored, sampling data corresponding to a first proportional position of the first period, sampling data corresponding to a first proportional position of the second period, sampling data corresponding to a second proportional position of the first period, and a second period The sampling data corresponding to the second proportional position;

Obtaining data fluctuation characteristics of the at least two sampled data, including:

Comparing the sampling data corresponding to the first proportional position of the second period with the sampling data corresponding to the first proportional position of the first period to obtain a first comparison result;

Comparing the sampling data corresponding to the second proportional position of the second period with the sampling data corresponding to the second proportional position of the first period to obtain a second comparison result;

The data fluctuation feature is obtained according to the first comparison result and the second comparison result.
The method according to claim 1 or 2, wherein said proportional position comprises at least three proportional positions of a current period;

Acquiring at least two sampling data corresponding to the proportional position from the data to be monitored, including:

Obtaining sampling data corresponding to at least three proportional positions of the current period from the data to be monitored;

Obtaining data fluctuation characteristics of the at least two sampled data, including:

Obtaining a change trend of sampling data corresponding to the adjacent proportional position according to sampling data corresponding to at least three proportional positions of the current period;

The data fluctuation feature is acquired according to the change trend.
The method according to claim 1 or 2, wherein the proportional position comprises at least three proportional positions of the total number of cycles;

Acquiring at least two sampling data corresponding to the proportional position from the data to be monitored, including:

Obtaining, from the data to be monitored, sampling data of a period corresponding to the at least three proportional positions in all periods;

Obtaining data fluctuation characteristics of the at least two sampled data, including:

And obtaining the data fluctuation feature according to the sampling data of the period corresponding to the at least three proportional positions respectively.
The method of claim 1 or 2 wherein said data fluctuation characteristic comprises at least one of the following data characteristics:

The fluctuation amount, the fluctuation ratio, the fluctuation amount or the fluctuation ratio attribute, the fluctuation tendency, and the standard deviation of the at least two sampled data.
A data monitoring device, comprising:

a configuration acquiring unit, configured to acquire a data sampling configuration, where the data sampling configuration indicates a proportional position of the sampled data;

a data acquiring unit, configured to acquire at least two sampling data corresponding to the proportional position from data to be monitored;

a feature acquiring unit, configured to acquire data fluctuation characteristics of the at least two sampled data;

And a result obtaining unit, configured to obtain, according to the data fluctuation feature, a monitoring result of the data to be monitored.
The apparatus according to claim 8, wherein the data to be monitored includes sampling data of a plurality of cycles; the proportional position includes the same proportional position of at least two periods, at least two proportional positions of the same period, Or at least two proportional positions of the total number of cycles.
The apparatus according to claim 8 or 9, wherein said proportional position comprises a first proportional position of the first period and the second period;

The data acquiring unit is configured to: obtain, from the data to be monitored, sampling data corresponding to a first proportional position of a first period and sampling data corresponding to a first proportional position of a second period;

The feature acquiring unit is configured to compare sampling data corresponding to the first proportional position of the second period with sampling data corresponding to the first proportional position of the first period, to obtain a comparison result, and according to the comparison result The data fluctuation characteristics are obtained.
The apparatus according to claim 8 or 9, wherein said proportional position comprises a first proportional position of the first period and the second period, and a second proportional position of the first period and the second period;

The data acquiring unit is configured to: obtain, from the data to be monitored, sampling data corresponding to a first proportional position of a first period, sampling data corresponding to a first proportional position of a second period, and a second ratio of the first period Sampling data corresponding to the location and sampling data corresponding to the second proportional position of the second period;

The feature acquiring unit is configured to compare sampling data corresponding to the first proportional position of the second period with sampling data corresponding to the first proportional position of the first period, to obtain a first comparison result, where the first Comparing the sampling data corresponding to the second proportional position of the two periods with the sampling data corresponding to the second proportional position of the first period, obtaining a second comparison result, and obtaining the basis according to the first comparison result and the second comparison result The characteristics of data fluctuations.
The apparatus according to claim 8 or 9, wherein said proportional position comprises at least three proportional positions of a current period;

The data acquiring unit is configured to: obtain, from the data to be monitored, sampling data corresponding to at least three proportional positions of a current period;

The feature acquiring unit is configured to acquire a trend of the sampling data corresponding to the adjacent proportional position according to the sampling data corresponding to the at least three proportional positions of the current period, and acquire the data fluctuation feature according to the changing trend.
The apparatus according to claim 8 or 9, wherein said proportional position comprises at least three proportional positions of a total number of cycles;

The data acquiring unit is configured to: acquire, from the data to be monitored, sampling data of a period corresponding to the at least three proportional positions in all periods;

The feature acquiring unit is configured to obtain the data fluctuation feature according to the sampling data of the period corresponding to the at least three proportional positions.
The apparatus of claim 8 or 9, wherein the data fluctuation characteristic comprises at least one of the following data characteristics:

The fluctuation amount, the fluctuation ratio, the fluctuation amount or the fluctuation ratio attribute, the fluctuation tendency, and the standard deviation of the at least two sampled data.