analysis index calculation platform based on KKS coding rule and big data structure
A technology for analyzing indicators and computing platforms, applied in computing, data processing applications, instruments, etc., can solve problems such as weak correlation ability, scattered features, and difficulty in providing intuitive information, and achieve the effect of meeting user needs
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Embodiment 1
[0060] Such as figure 1 As shown, the present embodiment 1 provides an analysis indicator calculation platform based on KKS coding rules and big data architecture (hereinafter referred to as "KKM platform"), and the platform obtains digital data through KKS coding rules from the real-time data platform. After the processed data is analyzed and calculated, the results are displayed on the application display platform, which includes the following parts:
[0061] A receiver module 1, configured to acquire data from different external data sources, and unify the format of the data;
[0062] A streaming preprocessing module 2, configured to receive data from the receiver module 1 and perform filtering processing to obtain available valid data;
[0063] There are two types of data collection: active and passive. In the active mode, the platform pulls data through the receiver, for example, from the end of the file at regular intervals, or from the message queue. In the passive m...
Embodiment 2
[0074] Such as figure 2 As shown, this embodiment 2 provides an analysis index calculation platform based on KKS coding rules and big data architecture on the basis of embodiment 1, and this embodiment 2 further defines that the stream preprocessing module 2 includes the following parts :
[0075] A data cleaning unit 21, configured to filter the monitoring data to obtain the valid data;
[0076] The data alignment unit 22 is configured to cache the valid data and perform synchronous alignment to ensure that the data entering the computing link is consistent at a time point.
[0077] Due to the influence of the environment, the monitored real-time data is always mixed with invalid data such as noise and glitches that affect the normal use of the data. Therefore, before entering the actual analysis, it must be filtered to eliminate the impact of invalid data.
[0078] The data distribution module 3 includes the following parts:
[0079] A data grouping unit 31, configured t...
Embodiment 3
[0104] Such as image 3 As shown, on the basis of Embodiment 1, this Embodiment 3 provides an analysis index calculation platform based on KKS coding rules and a big data architecture. This Embodiment 3 further defines that the data cleaning unit 21 includes the following parts:
[0105] Threshold filtering subunit 211, configured to set upper and lower thresholds for the data, determine the valid range, and discard or replace values beyond the valid range;
[0106] Condition filtering subunit 212, configured to set logical conditions for the data and make a judgment, and discard or replace values that do not meet the logical conditions;
[0107] The filtering subunit 213 is configured to perform smoothing processing on the values retained after being processed by the threshold filtering subunit 121 and the conditional filtering subunit 212 .
[0108] When performing data cleaning, first, the threshold filtering subunit 211 is used to directly exclude some data that doe...
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