WO2017118341A1 - Procédé et appareil de surveillance de données - Google Patents

Procédé et appareil de surveillance de données Download PDF

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Publication number
WO2017118341A1
WO2017118341A1 PCT/CN2016/113454 CN2016113454W WO2017118341A1 WO 2017118341 A1 WO2017118341 A1 WO 2017118341A1 CN 2016113454 W CN2016113454 W CN 2016113454W WO 2017118341 A1 WO2017118341 A1 WO 2017118341A1
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data
period
proportional
sampling
proportional position
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PCT/CN2016/113454
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English (en)
Chinese (zh)
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陈磊
解敏
范茸
陈国俊
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阿里巴巴集团控股有限公司
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • G06Q30/0201—Market modelling; Market analysis; Collecting market data
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/06—Buying, selling or leasing transactions
    • G06Q30/0601—Electronic shopping [e-shopping]
    • G06Q30/0623—Item investigation
    • G06Q30/0625—Directed, with specific intent or strategy

Definitions

  • the present application relates to the field of computer technology, and in particular, to a data monitoring method and apparatus.
  • 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.
  • 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.
  • the application provides a data monitoring method, including:
  • the data sampling configuration indicating a proportional position of the sampled data
  • 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.
  • the proportional position includes a first proportional position of the first period and the second period;
  • Obtaining data fluctuation characteristics of the at least two sampled data including:
  • the data fluctuation feature is obtained based on the comparison result.
  • 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;
  • 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:
  • the data fluctuation feature is obtained according to the first comparison result and the second comparison result.
  • the proportional position includes at least three proportional positions of the current period
  • Obtaining data fluctuation characteristics of the at least two sampled data including:
  • the data fluctuation feature is acquired according to the change trend.
  • the proportional position includes at least three proportional positions of the total number of cycles
  • Obtaining data fluctuation characteristics of the at least two sampled data including:
  • 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 are 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
  • a result obtaining unit configured to obtain, according to the data fluctuation feature, a monitoring result of the data to be monitored.
  • 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.
  • 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 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 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 proportional position includes at least three proportional positions of the 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 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 are 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.
  • FIG. 1 is a schematic flow chart of an embodiment of a method provided by the present application.
  • FIG. 3 is a schematic structural diagram of an apparatus embodiment provided by the present application.
  • 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.
  • 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.
  • 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.
  • 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 present application provides an embodiment of a method for monitoring data.
  • the method of this embodiment includes:
  • 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.).
  • Step 102 Obtain at least two sampling data corresponding to the proportional position from data to be monitored.
  • the data to be monitored may be read from a database such as an Open Data Processing Service (ODPS) or a data warehouse Hive.
  • ODPS Open Data Processing Service
  • Hive a database
  • 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.
  • the proportional position includes the same proportional position of at least two cycles.
  • 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.
  • the first period is the current day
  • the second period is the previous day
  • the first proportional position is 30%
  • 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.
  • the proportional position includes at least two proportional positions of the same period.
  • 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.
  • the first proportional position is 30%
  • 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.
  • the proportional position includes at least two proportional positions of the total number of cycles.
  • 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.
  • the first proportional position is 20%
  • the second proportional position is 40%
  • 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.
  • 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.
  • the data fluctuation feature may be stored in a database.
  • the sampled data is accumulated data
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • the first period may be the current day
  • 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.
  • the sampled data may be accumulated data.
  • 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.
  • 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.
  • 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.
  • the first period may be the current day
  • 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%
  • 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.
  • 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 sampled data may be accumulated data.
  • 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.
  • 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.
  • the attributes of the first comparison result and the second comparison result 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.
  • the proportional position includes at least three proportional positions of the current period.
  • 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.
  • the data fluctuation characteristics are mainly determined according to the trend of the sampled data.
  • 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.
  • the sampled data is continuously reduced.
  • 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.
  • the data fluctuation characteristics are acquired according to the sampling data corresponding to the proportional position of the time.
  • the proportional position includes at least three proportional positions of the total number of cycles.
  • 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.
  • 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.
  • 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.
  • 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.
  • the sampled data is the drug consumption value
  • 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 provides an embodiment of a method for monitoring data.
  • the method of this embodiment includes:
  • the data sampling configuration indicates a proportional position of the sampled data.
  • the embodiment of the present application further provides a corresponding device embodiment, which is specifically described below.
  • 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.
  • 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 proportional position includes the same proportional position of at least two cycles.
  • 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.
  • the proportional position includes at least two proportional positions of the same period.
  • 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.
  • the proportional position includes at least two proportional positions of the total number of cycles.
  • 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.
  • 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.
  • the data fluctuation characteristic may be according to Data on fluctuations, volatility, volatility or volatility, or volatility acquisition.
  • the sampled data is independent data
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • data fluctuation characteristics are acquired according to sampling data corresponding to the same proportional position of at least two periods.
  • 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 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 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.
  • data fluctuation characteristics are acquired according to sampling data corresponding to a plurality of identical proportional positions of at least two periods.
  • 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
  • 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.
  • 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.
  • the data fluctuation characteristics are mainly determined according to the trend of the sampled data.
  • 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.
  • the sampled data is continuously reduced.
  • 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.
  • the data fluctuation characteristics are acquired according to the sampling data corresponding to the proportional position of the time.
  • 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 disclosed system, apparatus, and method may be implemented in other manners.
  • the device embodiments described above are merely illustrative.
  • the division of the unit is only a logical function division.
  • 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.
  • 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.
  • 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.
  • a computer readable 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. .

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  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Game Theory and Decision Science (AREA)
  • Data Mining & Analysis (AREA)
  • Testing And Monitoring For Control Systems (AREA)

Abstract

L'invention concerne un procédé et un appareil de surveillance de données. Le procédé comprend les étapes suivantes : acquérir une configuration d'échantillonnage de données, où la configuration d'échantillonnage de données indique la position proportionnelle de données échantillonnées (101) ; acquérir, à partir de données à surveiller, au moins deux données échantillonnées correspondant à la position proportionnelle (102) ; acquérir une caractéristique de fluctuation de données desdites deux données échantillonnées (103) ; et selon la caractéristique fluctuation de données, obtenir un résultat de surveillance des données à surveiller (104). Comme il n'est pas nécessaire de surveiller toutes les données à surveiller, à la place, au moins deux données échantillonnées sont échantillonnées grâce à une configuration d'échantillonnage de données, et les données sont surveillées grâce à une caractéristique de fluctuation de données desdites deux données échantillonnées, la surveillance de données est effectuée, et simultanément, les charges de travail peuvent être réduites.
PCT/CN2016/113454 2016-01-06 2016-12-30 Procédé et appareil de surveillance de données WO2017118341A1 (fr)

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CN110764975B (zh) * 2018-07-27 2021-10-22 华为技术有限公司 设备性能的预警方法、装置及监控设备

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CN101770419A (zh) * 2008-12-31 2010-07-07 中国银联股份有限公司 系统健壮性分析器和分析方法
US20150095719A1 (en) * 2013-10-01 2015-04-02 Samsung Sds Co., Ltd. Data preprocessing device and method thereof
CN104698937A (zh) * 2015-03-06 2015-06-10 南京欧泰物联网科技有限公司 三维冲击记录仪及其记录方法

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CN101399883B (zh) * 2008-10-10 2013-02-27 中兴通讯股份有限公司 异常监测管理方法及装置
CN102608286B (zh) * 2012-03-01 2015-07-08 煤炭科学技术研究院有限公司 一种实时监测煤矿瓦斯监测值异常的方法

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US20150095719A1 (en) * 2013-10-01 2015-04-02 Samsung Sds Co., Ltd. Data preprocessing device and method thereof
CN104698937A (zh) * 2015-03-06 2015-06-10 南京欧泰物联网科技有限公司 三维冲击记录仪及其记录方法

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