CN114201238A - Intelligent enterprise software component management system based on big data - Google Patents
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Abstract
The invention relates to an intelligent enterprise software component management system based on big data, which comprises a storage module, a sorting module, a proofreading module and an extraction module. The storage module is arranged to store various data of an enterprise, when the data are extracted, the arrangement module is arranged to sequence the data to be extracted according to the use frequency, when the data with the same use frequency appear, the arrangement module sequences the data in each preset use frequency interval according to the byte length of the data and the use frequency, the important data with high use frequency can be extracted in advance, the important data are prevented from being damaged in the extraction process, the arrangement module is arranged to correct the data sequence according to the storage duration, meanwhile, two extraction units are arranged in the extraction module to extract the data simultaneously, and the data are transferred and extracted according to the byte amount, so that the important data are extracted at first rate, and the data extraction efficiency is improved.
Description
Technical Field
The invention relates to the technical field of enterprise software management, in particular to an intelligent enterprise software component management system based on big data.
Background
The intelligent enterprise is a novel management mode and organization form after the enterprise is digitally transformed and intelligently applied, is a deep fusion of an advanced information technology, an industrial technology and a management technology, can promote the transformation and upgrade of the internal production relation of the enterprise through the construction of the intelligent enterprise, completes the harmonious connection with the social productivity of the Internet plus, can further release the innovation and efficacy-creating activity of enterprise employees, and provides sustainable development source power for the enterprise.
Due to the limitation of maintenance personnel, data loss and slow data extraction are easy to occur when information of each component in the software is extracted, and important data of an enterprise can be damaged, so that the productivity is reduced.
Disclosure of Invention
Therefore, the invention provides an intelligent enterprise software component management system based on big data, which is used for overcoming the problems of slow data extraction and missing of important data in the prior art.
In order to achieve the above object, the present invention provides an intelligent enterprise software component management system based on big data, comprising,
the storage module is internally provided with a workload component, an attendance component and a conference component, and workload data are stored in the workload component; attendance data are stored in the attendance component; conference data are stored in the conference component; the storage module can select each data to be extracted;
the sorting module is connected with the storage module and can sort the data to be extracted according to the use frequency of the data to be extracted, the sorting module can judge the byte length of the data to be extracted with the same use frequency according to the standard sorting byte length, the sorting module can sort the data to be extracted with the same use frequency and the byte length not exceeding the standard sorting byte length according to the byte length, and the sorting module can sort the data to be extracted with the same use frequency and the byte length exceeding the standard sorting byte length according to a first preset use frequency and a second preset use frequency which are internally arranged and form a sorting data sequence;
the checking module is connected with the sorting module and can determine a part needing to be checked of the sorted data sequence according to limited use frequency arranged in the checking module; the proofreading module can compare the storage duration of each data to be extracted in the part to be proofread with the standard storage duration and the standard storage duration difference set in the proofreading module, and judge each data to be proofread according to the comparison result; the checking module sorts the data to be checked according to the byte length of the data to be checked and extracted, and combines the data to be checked and extracted without checking to form a checking data sequence;
the extraction module is connected with the calibration module, and a first extraction unit and a second extraction unit are arranged in the extraction module; the extraction module can label each data to be extracted in the proofreading data sequence, and selects an extraction channel from the first extraction unit and the second extraction unit according to the label of each data to be extracted; the extraction module is internally provided with a standard byte quantity difference, the extraction module can calculate the byte quantity difference between the sum of the byte quantities of the data to be extracted, which are required to be extracted by the first extraction unit, and the sum of the byte quantities of the data to be extracted, which are required to be extracted by the second extraction unit, and the extraction module carries out exchange adjustment on the extracted data of each band, which are extracted by the first extraction unit and the second extraction unit, according to the comparison result of the byte quantity difference and the standard byte quantity difference; the first extraction unit and the second extraction unit can perform data extraction simultaneously.
Further, when the management system extracts data, the data to be extracted are selected from the storage module, the sorting module identifies the data to be extracted and obtains the use frequency of the data to be extracted, and the sorting module sorts the data to be extracted according to the sequence of the use frequencies of the data to be extracted from large to small to form an initial data sequence;
when the sorting module identifies that the data to be extracted with the same use frequency exist, the sorting module acquires the byte length of the data to be extracted with the same use frequency so as to sort the data to be extracted with the same use frequency.
Furthermore, a standard sorting byte length Lb is arranged in the sorting module, when the sorting module identifies that the data to be extracted with the same use frequency exists, the sorting module acquires the byte length Lh of the data to be extracted with the same use frequency, the sorting module compares the byte length Lh with the standard sorting byte length Lb,
when Lh is less than or equal to Lb, the sorting module judges that the byte length of the data to be extracted does not exceed the standard sorting byte length, and sorts the data to be extracted which do not exceed the standard sorting byte length according to the sequence of the byte lengths from large to small to form a data sequence with the same use frequency;
when Lh is greater than Lb, the sorting module judges that the byte length of the data to be extracted exceeds the standard sorting byte length, and the sorting module acquires the use frequency of each data to be extracted, which exceeds the standard sorting byte length and has the use frequency, so as to sort the data.
Further, a first preset use frequency F1 and a second preset use frequency F2 are arranged in the sorting module, wherein F1 is less than F2, when the sorting module judges that data exceeding the standard sorting byte length exist in the data to be extracted with the same use frequency, the sorting module obtains the use frequency Fs of the data exceeding the standard sorting byte length, the sorting module compares the use frequency Fs with the first preset use frequency F1 and the second preset use frequency F2 respectively,
when Fs is less than F1, the sorting module judges that the use frequency is lower than a first preset use frequency, the sorting module arranges the data to be extracted with the length exceeding the standard sorting byte length at the tail end of the initial data sequence according to the sequence of the character length from large to small, and finishes sorting of the extracted data to form a sorted data sequence;
when Fs is not less than F1 and not more than F2, the sorting module judges that the use frequency is between a first preset use frequency and a second preset use frequency, the sorting module arranges data to be extracted with the length exceeding the standard sorting byte length at the front end of a data sequence with the same use frequency from large to small, and finishes sorting of the extracted data to form a sorted data sequence;
and when Fs is larger than F2, the sorting module judges that the use frequency is higher than a second preset use frequency, arranges the data to be extracted with the length exceeding the standard sorting byte length at the front end of the initial data sequence according to the sequence of the character length from large to small, and finishes sorting the extracted data to form a sorted data sequence.
Furthermore, a limited use frequency Fx is arranged in the proofreading module, the proofreading module determines a proofreading node in the collated data sequence according to the limited use frequency Fx, and the proofreading module judges a part of the collated data sequence exceeding the limited use frequency Fx as a data sequence which does not need to be proofread, so as to form an initial proofreading data sequence; and the proofreading module judges the part which does not exceed the limited use frequency Fx in the sorted data sequence as the data sequence to be proofread to form a data sequence to be proofread, and proofreads the data sequence to be proofread according to the storage time of each data to be extracted.
Furthermore, a standard storage time length Tb and a standard storage time length difference Delta Tb are arranged in the proofreading module, the proofreading module obtains the storage time length Tc of each data to be extracted in the data sequence to be proofread, the proofreading module calculates the storage time length difference Delta Tc of each data to be extracted according to the storage time length Tc of each data to be extracted and the standard storage time length Tb, the Delta Tc = | Tb-Tc |, the proofreading module compares the storage time length difference Delta Tc of each data to be extracted with the standard storage time length difference Delta Tb,
when the delta Tc is less than or equal to the delta Tb, the proofreading module judges that the storage time of the data to be extracted is within a standard range, and does not proofread the data to be extracted;
when the delta Tc is larger than the delta Tb, the proofreading module judges that the storage time length of the data to be extracted is not in the standard range, the proofreading module marks the data to be extracted, and the proofreading module proofreads the sequence of the data to be extracted in the data sequence to be proofread according to the storage time length Tc and the standard storage time length Tb of the data to be extracted.
Further, the checking module compares the storage time length Tc of each marked data to be extracted with the standard storage time length Tb,
when Tc is larger than Tb, the proofreading module judges that the storage time length of each marked data to be extracted is longer than the standard storage time length, and the proofreading module discharges each marked data to be extracted to the tail end of the data sequence to be proofread according to the sequence from small to large of the byte length of each marked data to be extracted;
when Tc is less than Tb, the proofreading module judges that the storage time of each marked data to be extracted is shorter than the standard storage time, and the proofreading module discharges each marked data to be extracted to the front end of the data sequence to be proofread according to the sequence of the byte lengths of each marked data to be extracted from large to small;
and the proofreading module discharges the proofread data sequence to be proofread to the rear end of the initial proofread data sequence to finish proofreading the data sequence and form a proofread data sequence.
Furthermore, the extraction module labels each data to be extracted in the collated data sequence, the extraction module labels each data to be extracted as B1, B2, and B3.. Bn according to the sorting result of the collated data sequence, the extraction module extracts each data to be extracted with a single label in the first extraction unit according to the sequence of labels from small to large, and the extraction module extracts each data to be extracted with a double label in the second extraction unit according to the sequence of labels from small to large.
Furthermore, a standard byte quantity difference Mb is provided in the extracting module, the extracting module calculates a sum M1 of the data byte quantities to be extracted that the first extracting unit needs to extract as a first byte quantity, the extracting module calculates a sum M2 of the data byte quantities to be extracted that the second extracting unit needs to extract as a second byte quantity, the extracting module calculates a byte quantity difference Mc, Mc = | M1-M2| according to the first byte quantity M1 and the second byte quantity M2, the extracting module compares the byte quantity difference Mc with the standard byte quantity difference Mb,
when Mc is less than or equal to Mb, the extraction module judges that the byte quantity difference is within a standard range, and the first extraction unit and the second extraction unit simultaneously extract data extracted by each band;
when Mc is larger than Mb, the extracting module judges that the byte quantity difference is not in the standard range, and the extracting module compares the first byte quantity M1 with the second byte quantity M2 to extract each data to be extracted.
Further, when the extracting module determines that the byte quantity difference is not within the standard range, the extracting module compares the first byte quantity M1 with the second byte quantity M2,
when M1 is greater than M2, the extraction module judges that the first byte amount is greater than the second byte amount, the extraction module adjusts the data to be extracted at the tail end of the sequence in the data to be extracted which needs to be extracted by the first extraction unit, the extraction module adjusts the data to be extracted to the tail end of the sequence in the data to be extracted which needs to be extracted by the second extraction unit, and the extraction module repeats the judgment and adjustment operation according to the byte amount until the adjusted byte amount difference Mc' is less than or equal to Mb, and the first extraction unit and the second extraction unit simultaneously extract the data to be extracted;
when M1 is less than M2, the extraction module judges that the second byte amount is greater than the first byte amount, the extraction module adjusts the data to be extracted at the tail end of the sequence in the data to be extracted which needs to be extracted by the second extraction unit, the extraction module adjusts the data to be extracted to the tail end of the sequence of the data to be extracted which needs to be extracted by the first extraction unit, and the extraction module repeats the judgment and adjustment operation according to the byte amount until the adjusted byte amount difference Mc' is less than or equal to Mb, and the first extraction unit and the second extraction unit extract the data simultaneously.
Compared with the prior art, the invention has the advantages that various data of enterprises are stored by arranging the storage module, when the data are extracted, the data to be extracted are sorted according to the use frequency by arranging the sorting module, when the data with the same use frequency appear, the sorting module sorts the data in the interval of each preset use frequency by sorting the byte length of the data and the use frequency, the important data with higher use frequency can be extracted in advance, the important data are prevented from being damaged in the extraction process, the data sorting is collated by arranging the collating module, the collating module sorts the data with lower use frequency according to the storage duration of the data, the important data with lower use frequency are extracted preferentially, meanwhile, two extraction units are arranged in the extraction module, and according to the respective byte quantity to be extracted of the two extraction units, the data to be extracted by the two extraction units are transferred and adjusted, so that the priority extraction of important data is guaranteed, the data loss is prevented, and the data extraction efficiency is improved.
Particularly, the sorting module is used for obtaining the use frequency of each data to be extracted and sequencing the data to be extracted according to the sequence of the use frequency of each data to be extracted from large to small, so that the priority extraction of important data with high use frequency is guaranteed, and the problem that the important data is lost due to data damage in the data extraction process is solved.
Furthermore, when the data are sequenced according to the use frequency of each data to be extracted, the use frequency of a plurality of data is the same, the byte length with the same use frequency is obtained and sequenced according to the length of the bytes, meanwhile, the standard sequencing byte length is arranged in the sorting module, and when the byte length of the data item exceeds the standard sequencing byte length, the use frequency is judged, so that the priority extraction of important data is further ensured, and the loss of the important data is prevented.
Furthermore, a first preset use frequency and a second preset use frequency are arranged in the sorting module, when the sorting module is in sorting, the use frequencies are the same, and the byte length of the data is high, the sorting module acquires the use frequencies, compares the use frequencies with the first preset use frequency and the second preset use frequency, when the use frequencies are lower than the first preset use frequency, the sorting module judges that the use frequencies are small, arranges the data with high byte length and low use frequency at the tail end of the data sequence, reduces the extraction time of front important data, and when the use frequencies are higher than the second preset use frequency, indicates that the use frequencies of the data are high and the byte length is high, arranges the data at the front end of the data sequence, performs preferential extraction, prevents loss of the important data, and improves the safety of data extraction.
Particularly, after the sorting module sorts the data, the data sequence is checked through the checking module, the limited use frequency is set, and the data sequence lower than the limited use frequency is checked, so that the important data is preferentially extracted when the data with the lower use frequency is extracted, and the important data is prevented from being lost.
Furthermore, a standard storage time range is set in the calibration module, the storage time of the data to be calibrated is extracted and judged, when the storage time is within the standard range, the data of the part is not specially checked, and when the storage time is not within the standard range, the data of the part is not specially checked, the data of the part is specially checked, so that the special processing of the special data is guaranteed, and the normal operation of the management system is guaranteed.
Further, the checking module judges the storage time of the data with particularity, when the storage time is long, the data is low in use frequency and long in storage time, the data is judged not to be important data, the data is sequenced at the tail end of the data sequence, when the storage time is short, the data is judged to be low in use frequency possibly caused by short recording time, the data is sequenced at the front end of the data sequence to be preferentially extracted, the important data is further determined to be preferentially extracted, and data missing is prevented.
Particularly, two extraction channels are arranged in the extraction module, bidirectional extraction can be carried out simultaneously, when data extraction is carried out, the sorted data are labeled, the extraction channels are selected according to the parity of the labels, the data extracted by the song extraction channels are guaranteed to be sorted important data which are extracted preferentially, the loss probability of the important data is reduced, and the data extraction efficiency is further improved.
Furthermore, when the data extraction is performed by the two extraction units, the extraction module compares the total extracted byte quantity of each extraction unit, and judges the byte quantity difference between the two extraction units by combining the standard byte quantity difference set inside the extraction module, when the byte quantity difference between the two extraction units is low, the data to be extracted of the two extraction units does not need to be adjusted, and when the byte quantity difference between the two extraction units is high, the data to be extracted of the two extraction units are adjusted according to the byte quantity difference, so that the difference between the respective extracted byte quantities of the two extraction units is small, and the data extraction efficiency is further improved.
Further, when the total byte amount of the data extracted by the two extraction units is judged, if the byte amount of the first extraction unit is high, the data to be extracted at the tail end of the data sequence extracted by the first extraction unit is transferred to the tail end of the data sequence extracted by the second extraction unit, repeated judgment and adjustment are carried out, and adjustment is stopped until the difference value of the total byte amounts of the data extracted by the two extraction units is within a standard range, so that the data extraction efficiency is improved, and the normal operation of the management system is guaranteed.
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FIG. 1 is a schematic diagram of a big data-based intelligent enterprise software component management system according to the present invention.
Detailed Description
In order that the objects and advantages of the invention will be more clearly understood, the invention is further described below with reference to examples; it should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only for explaining the technical principle of the present invention, and do not limit the scope of the present invention.
It should be noted that in the description of the present invention, the terms of direction or positional relationship indicated by the terms "upper", "lower", "left", "right", "inner", "outer", etc. are based on the directions or positional relationships shown in the drawings, which are only for convenience of description, and do not indicate or imply that the device or element must have a specific orientation, be constructed in a specific orientation, and be operated, and thus, should not be construed as limiting the present invention.
Furthermore, it should be noted that, in the description of the present invention, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, and may be, for example, fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.
Referring to fig. 1, which is a schematic structural diagram of an intelligent enterprise software component management system based on big data according to the present invention, the present invention provides an intelligent enterprise software component management system based on big data, including,
the storage module is internally provided with a workload component, an attendance component and a conference component, and workload data are stored in the workload component; attendance data are stored in the attendance component; conference data are stored in the conference component; the storage module can select each data to be extracted;
the sorting module is connected with the storage module and can sort the data to be extracted according to the use frequency of the data to be extracted, the sorting module can judge the byte length of the data to be extracted with the same use frequency according to the standard sorting byte length, the sorting module can sort the data to be extracted with the same use frequency and the byte length not exceeding the standard sorting byte length according to the byte length, and the sorting module can sort the data to be extracted with the same use frequency and the byte length exceeding the standard sorting byte length according to a first preset use frequency and a second preset use frequency which are internally arranged and form a sorting data sequence;
the checking module is connected with the sorting module and can determine a part needing to be checked of the sorted data sequence according to limited use frequency arranged in the checking module; the proofreading module can compare the storage duration of each data to be extracted in the part to be proofread with the standard storage duration and the standard storage duration difference set in the proofreading module, and judge each data to be proofread according to the comparison result; the checking module sorts the data to be checked according to the byte length of the data to be checked and extracted, and combines the data to be checked and extracted without checking to form a checking data sequence;
the extraction module is connected with the calibration module, and a first extraction unit and a second extraction unit are arranged in the extraction module; the extraction module can label each data to be extracted in the proofreading data sequence, and selects an extraction channel from the first extraction unit and the second extraction unit according to the label of each data to be extracted; the extraction module is internally provided with a standard byte quantity difference, the extraction module can calculate the byte quantity difference between the sum of the byte quantities of the data to be extracted, which are required to be extracted by the first extraction unit, and the sum of the byte quantities of the data to be extracted, which are required to be extracted by the second extraction unit, and the extraction module carries out exchange adjustment on the extracted data of each band, which are extracted by the first extraction unit and the second extraction unit, according to the comparison result of the byte quantity difference and the standard byte quantity difference; the first extraction unit and the second extraction unit can perform data extraction simultaneously.
The storage module is arranged to store various enterprise data, when the data are extracted, the arrangement module is arranged to sort the data to be extracted according to the use frequency, when the data with the same use frequency appear, the arrangement module is arranged to sort the data in each preset use frequency interval according to the byte length of the data and the use frequency, important data with higher use frequency can be extracted in advance, the important data are prevented from being damaged in the extraction process, the data sorting is checked by the arrangement of the check module, the check module is arranged to sort the data with lower use frequency according to the storage duration of the data, the important data with lower use frequency are extracted preferentially, meanwhile, the two extraction units are arranged in the extraction module, and the data to be extracted by the two extraction units are transferred and adjusted according to the respective byte quantities to be extracted of the two extraction units, the method and the device not only ensure the preferential extraction of important data and prevent the data loss, but also improve the efficiency of data extraction.
Specifically, when the management system extracts data, the data to be extracted are selected from the storage module, the sorting module identifies the data to be extracted and obtains the use frequency of the data to be extracted, and the sorting module sorts the data to be extracted according to the sequence of the use frequencies of the data to be extracted from large to small to form an initial data sequence;
when the sorting module identifies that the data to be extracted with the same use frequency exist, the sorting module acquires the byte length of the data to be extracted with the same use frequency so as to sort the data to be extracted with the same use frequency.
The sorting module is used for obtaining the use frequency of each data to be extracted and sequencing the data to be extracted according to the sequence of the use frequency of each data to be extracted from large to small, so that the priority extraction of important data with high use frequency is guaranteed, and the problem that the important data is lost due to data damage in the data extraction process is solved.
Specifically, a standard sorting byte length Lb is arranged in the sorting module, when the sorting module identifies that data to be extracted with the same use frequency exist, the sorting module acquires the byte length Lh of the data to be extracted with the same use frequency, the sorting module compares the byte length Lh with the standard sorting byte length Lb,
when Lh is less than or equal to Lb, the sorting module judges that the byte length of the data to be extracted does not exceed the standard sorting byte length, and sorts the data to be extracted which do not exceed the standard sorting byte length according to the sequence of the byte lengths from large to small to form a data sequence with the same use frequency;
when Lh is greater than Lb, the sorting module judges that the byte length of the data to be extracted exceeds the standard sorting byte length, and the sorting module acquires the use frequency of each data to be extracted, which exceeds the standard sorting byte length and has the use frequency, so as to sort the data.
When the data are sequenced according to the use frequency of each data to be extracted, the use frequency of a plurality of data is the same, the byte length with the same use frequency is obtained, the data are sequenced according to the length of the byte, meanwhile, the standard sequencing byte length is arranged in the arrangement module, when the byte length of the data item exceeds the standard sequencing byte length, the use frequency is judged, the priority extraction of important data is further guaranteed, and the loss of the important data is prevented.
Specifically, a first preset use frequency F1 and a second preset use frequency F2 are arranged in the sorting module, wherein F1 is less than F2, when the sorting module determines that data exceeding the standard sorting byte length exists in the data to be extracted with the same use frequency, the sorting module obtains the use frequency Fs of the data exceeding the standard sorting byte length, the sorting module compares the use frequency Fs with the first preset use frequency F1 and the second preset use frequency F2 respectively,
when Fs is less than F1, the sorting module judges that the use frequency is lower than a first preset use frequency, the sorting module arranges the data to be extracted with the length exceeding the standard sorting byte length at the tail end of the initial data sequence according to the sequence of the character length from large to small, and finishes sorting of the extracted data to form a sorted data sequence;
when Fs is not less than F1 and not more than F2, the sorting module judges that the use frequency is between a first preset use frequency and a second preset use frequency, the sorting module arranges data to be extracted with the length exceeding the standard sorting byte length at the front end of a data sequence with the same use frequency from large to small, and finishes sorting of the extracted data to form a sorted data sequence;
and when Fs is larger than F2, the sorting module judges that the use frequency is higher than a second preset use frequency, arranges the data to be extracted with the length exceeding the standard sorting byte length at the front end of the initial data sequence according to the sequence of the character length from large to small, and finishes sorting the extracted data to form a sorted data sequence.
The method comprises the steps that a first preset use frequency and a second preset use frequency are arranged in a sorting module, when the sorting module is used for sorting, the use frequencies are the same, and the byte length of data is high, the sorting module obtains the use frequencies, compares the use frequencies with the first preset use frequency and the second preset use frequency, when the use frequencies are lower than the first preset use frequency, judges that the use frequencies are small, arranges data with high byte length and low use frequency at the tail end of a data sequence, reduces extraction time of front important data, and when the use frequencies are higher than the second preset use frequency, indicates that the use frequencies of the data are high and the byte length is high, arranges the data at the front end of the data sequence, performs priority extraction, prevents important data from being lost, and improves data extraction safety.
Specifically, a limited use frequency Fx is arranged in the proofreading module, the proofreading module determines a proofreading node in the collated data sequence according to the limited use frequency Fx, and the proofreading module judges a part of the collated data sequence exceeding the limited use frequency Fx as a data sequence which does not need to be proofread, so as to form an initial proofreading data sequence; and the proofreading module judges the part which does not exceed the limited use frequency Fx in the sorted data sequence as the data sequence to be proofread to form a data sequence to be proofread, and proofreads the data sequence to be proofread according to the storage time of each data to be extracted.
After the arrangement module sequences the data, the data sequence is corrected through the correction module, the limited use frequency is set, the data sequence lower than the limited use frequency is corrected, the important data are preferentially extracted when the data with the lower use frequency are extracted, and the important data are prevented from being lost.
Specifically, a standard storage time length Tb and a standard storage time length difference Δ Tb are arranged in the calibration module, the calibration module obtains a storage time length Tc of each data to be extracted in the data sequence to be calibrated, the calibration module calculates a storage time length difference Δ Tc, Δ Tc = | Tb-Tc | of each data to be extracted according to the storage time length Tc of each data to be extracted and the standard storage time length Tb, the calibration module compares the storage time length difference Δ Tc of each data to be extracted with the standard storage time length difference Δ Tb,
when the delta Tc is less than or equal to the delta Tb, the proofreading module judges that the storage time of the data to be extracted is within a standard range, and does not proofread the data to be extracted;
when the delta Tc is larger than the delta Tb, the proofreading module judges that the storage time length of the data to be extracted is not in the standard range, the proofreading module marks the data to be extracted, and the proofreading module proofreads the sequence of the data to be extracted in the data sequence to be proofread according to the storage time length Tc and the standard storage time length Tb of the data to be extracted.
And setting a standard storage time range in the proofreading module, extracting and judging the storage time of the data to be proofread, indicating that the part of data has no particularity when the storage time is in the standard range, not proofreading the part of data, indicating that the part of data has the particularity when the storage time is not in the standard range, proofreading the part of data, guaranteeing the special processing of the special data and simultaneously ensuring the normal operation of the management system.
Specifically, the checking module compares the storage time length Tc of each marked data to be extracted with the standard storage time length Tb,
when Tc is larger than Tb, the proofreading module judges that the storage time length of each marked data to be extracted is longer than the standard storage time length, and the proofreading module discharges each marked data to be extracted to the tail end of the data sequence to be proofread according to the sequence from small to large of the byte length of each marked data to be extracted;
when Tc is less than Tb, the proofreading module judges that the storage time of each marked data to be extracted is shorter than the standard storage time, and the proofreading module discharges each marked data to be extracted to the front end of the data sequence to be proofread according to the sequence of the byte lengths of each marked data to be extracted from large to small;
and the proofreading module discharges the proofread data sequence to be proofread to the rear end of the initial proofread data sequence to finish proofreading the data sequence and form a proofread data sequence.
The checking module judges the storage time of the data with particularity, when the storage time is long, the data is low in use frequency and long in storage time, the data is judged not to be important data and is sequenced at the tail end of the data sequence, when the storage time is short, the data is judged to be low in use frequency possibly caused by short recording time and is sequenced at the front end of the data sequence to be preferentially extracted, the important data is further determined to be preferentially extracted, and data missing is prevented.
Specifically, the extraction module labels each to-be-extracted data in the collated data sequence, the extraction module labels each to-be-extracted data as B1, B2, and B3.. Bn according to a sorting result of the collated data sequence, the extraction module extracts each to-be-extracted data with a singular label in the first extraction unit according to a descending order of labels, and the extraction module extracts each to-be-extracted data with a double label in the second extraction unit according to a descending order of labels.
The two extraction channels are arranged in the extraction module, bidirectional extraction can be carried out simultaneously, when data extraction is carried out, the data in the sequence are labeled, the extraction channels are selected according to the parity of the labels, the condition that the data extracted by the song extraction channels are the important data which are extracted preferentially in the sequence is guaranteed, the loss probability of the important data is reduced, and the efficiency of the data extraction is further improved.
Specifically, a standard byte quantity difference Mb is provided in the extracting module, the extracting module calculates a total M1 of the data byte quantities to be extracted that the first extracting unit needs to extract as a first byte quantity, the extracting module calculates a total M2 of the data byte quantities to be extracted that the second extracting unit needs to extract as a second byte quantity, the extracting module calculates a byte quantity difference Mc, Mc = | M1-M2| according to the first byte quantity M1 and the second byte quantity M2, the extracting module compares the byte quantity difference Mc with the standard byte quantity difference Mb,
when Mc is less than or equal to Mb, the extraction module judges that the byte quantity difference is within a standard range, and the first extraction unit and the second extraction unit simultaneously extract data extracted by each band;
when Mc is larger than Mb, the extracting module judges that the byte quantity difference is not in the standard range, and the extracting module compares the first byte quantity M1 with the second byte quantity M2 to extract each data to be extracted.
When the data extraction is carried out by the two extraction units, the total extracted byte quantity of each extraction unit is compared, the byte quantity difference between the two extraction units is judged by combining the standard byte quantity difference arranged in the extraction module, when the byte quantity difference between the two extraction units is low, the data to be extracted of the two extraction units does not need to be adjusted, when the byte quantity difference between the two extraction units is high, the data to be extracted of the two extraction units are adjusted according to the byte quantity difference, so that the byte quantity difference extracted by the two extraction units is small, and the data extraction efficiency is further improved.
Specifically, when the extraction module determines that the difference is not within the standard range, the extraction module compares the first byte amount M1 with the second byte amount M2,
when M1 is greater than M2, the extraction module judges that the first byte amount is greater than the second byte amount, the extraction module adjusts the data to be extracted at the tail end of the sequence in the data to be extracted which needs to be extracted by the first extraction unit, the extraction module adjusts the data to be extracted to the tail end of the sequence in the data to be extracted which needs to be extracted by the second extraction unit, and the extraction module repeats the judgment and adjustment operation according to the byte amount until the adjusted byte amount difference Mc' is less than or equal to Mb, and the first extraction unit and the second extraction unit simultaneously extract the data to be extracted;
when M1 is less than M2, the extraction module judges that the second byte amount is greater than the first byte amount, the extraction module adjusts the data to be extracted at the tail end of the sequence in the data to be extracted which needs to be extracted by the second extraction unit, the extraction module adjusts the data to be extracted to the tail end of the sequence of the data to be extracted which needs to be extracted by the first extraction unit, and the extraction module repeats the judgment and adjustment operation according to the byte amount until the adjusted byte amount difference Mc' is less than or equal to Mb, and the first extraction unit and the second extraction unit extract the data simultaneously.
When the total byte quantity of the data extracted by the two extraction units is judged, if the byte quantity of the first extraction unit is higher, the data to be extracted at the tail end of the data sequence extracted by the first extraction unit is transferred to the tail end of the data sequence extracted by the second extraction unit, repeated judgment and adjustment are carried out, and the adjustment is stopped until the difference value of the total byte quantities of the data extracted by the two extraction units is within a standard range, so that the data extraction efficiency is improved, and the normal operation of the management system is guaranteed.
So far, the technical solutions of the present invention have been described in connection with the preferred embodiments shown in the drawings, but it is easily understood by those skilled in the art that the scope of the present invention is obviously not limited to these specific embodiments. Equivalent changes or substitutions of related technical features can be made by those skilled in the art without departing from the principle of the invention, and the technical scheme after the changes or substitutions can fall into the protection scope of the invention.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention; various modifications and alterations to this invention will become apparent to those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. An intelligent enterprise software component management system based on big data is characterized by comprising,
the storage module is internally provided with a workload component, an attendance component and a conference component, and workload data are stored in the workload component; attendance data are stored in the attendance component; conference data are stored in the conference component; the storage module can select each data to be extracted;
the sorting module is connected with the storage module and can sort the data to be extracted according to the use frequency of the data to be extracted, the sorting module can judge the byte length of the data to be extracted with the same use frequency according to the standard sorting byte length, the sorting module can sort the data to be extracted with the same use frequency and the byte length not exceeding the standard sorting byte length according to the byte length, and the sorting module can sort the data to be extracted with the same use frequency and the byte length exceeding the standard sorting byte length according to a first preset use frequency and a second preset use frequency which are internally arranged and form a sorting data sequence;
the checking module is connected with the sorting module and can determine a part needing to be checked of the sorted data sequence according to limited use frequency arranged in the checking module; the proofreading module can compare the storage duration of each data to be extracted in the part to be proofread with the standard storage duration and the standard storage duration difference set in the proofreading module, and judge each data to be proofread according to the comparison result; the checking module sorts the data to be checked according to the byte length of the data to be checked and extracted, and combines the data to be checked and extracted without checking to form a checking data sequence;
the extraction module is connected with the calibration module, and a first extraction unit and a second extraction unit are arranged in the extraction module; the extraction module can label each data to be extracted in the proofreading data sequence, and selects an extraction channel from the first extraction unit and the second extraction unit according to the label of each data to be extracted; the extraction module is internally provided with a standard byte quantity difference, the extraction module can calculate the byte quantity difference between the sum of the byte quantities of the data to be extracted, which are required to be extracted by the first extraction unit, and the sum of the byte quantities of the data to be extracted, which are required to be extracted by the second extraction unit, and the extraction module carries out exchange adjustment on the extracted data of each band, which are extracted by the first extraction unit and the second extraction unit, according to the comparison result of the byte quantity difference and the standard byte quantity difference; the first extraction unit and the second extraction unit can perform data extraction simultaneously.
2. The intelligent enterprise software component management system based on big data as claimed in claim 1, wherein when the management system performs data extraction, each data to be extracted is selected from the storage module, the sorting module identifies each data to be extracted and obtains the frequency of use of each data to be extracted, and the sorting module sorts each data to be extracted according to the sequence of the frequency of use of each data to be extracted from big to small to form an initial data sequence;
when the sorting module identifies that the data to be extracted with the same use frequency exist, the sorting module acquires the byte length of the data to be extracted with the same use frequency so as to sort the data to be extracted with the same use frequency.
3. The intelligent enterprise software component management system based on big data as claimed in claim 2, wherein the arrangement module has a standard byte length Lb, when the arrangement module identifies that there is data to be extracted with the same frequency of use, the arrangement module will obtain the byte length Lh of the data to be extracted with the same frequency of use, the arrangement module will compare the byte length Lh with the standard byte length Lb,
when Lh is less than or equal to Lb, the sorting module judges that the byte length of the data to be extracted does not exceed the standard sorting byte length, and sorts the data to be extracted which do not exceed the standard sorting byte length according to the sequence of the byte lengths from large to small to form a data sequence with the same use frequency;
when Lh is greater than Lb, the sorting module judges that the byte length of the data to be extracted exceeds the standard sorting byte length, and the sorting module acquires the use frequency of each generation of extracted data which exceeds the standard sorting byte length and has the use frequency so as to sort the data.
4. The intelligent enterprise software component management system based on big data as claimed in claim 3, wherein the arrangement module is configured with a first preset frequency F1 and a second preset frequency F2, wherein F1 < F2, when the arrangement module determines that there is data exceeding the standard byte length in the data to be extracted with the same frequency, the arrangement module obtains the frequency Fs of the data exceeding the standard byte length, the arrangement module compares the frequency Fs with the first preset frequency F1 and the second preset frequency F2,
when Fs is less than F1, the sorting module judges that the use frequency is lower than a first preset use frequency, the sorting module arranges the data to be extracted with the length exceeding the standard sorting byte length at the tail end of the initial data sequence according to the sequence of the character length from large to small, and finishes sorting of the extracted data to form a sorted data sequence;
when Fs is not less than F1 and not more than F2, the sorting module judges that the use frequency is between a first preset use frequency and a second preset use frequency, the sorting module arranges data to be extracted with the length exceeding the standard sorting byte length at the front end of a data sequence with the same use frequency from large to small, and finishes sorting of the extracted data to form a sorted data sequence;
and when Fs is larger than F2, the sorting module judges that the use frequency is higher than a second preset use frequency, arranges the data to be extracted with the length exceeding the standard sorting byte length at the front end of the initial data sequence according to the sequence of the character length from large to small, and finishes sorting the extracted data to form a sorted data sequence.
5. The intelligent enterprise software component management system based on big data as claimed in claim 4, wherein the proof reading module is provided with a limited use frequency Fx, the proof reading module determines a proof reading node in the sorted data sequence according to the limited use frequency Fx, and the proof reading module judges the part of the sorted data sequence exceeding the limited use frequency Fx as a data sequence without proof reading to form an initial proof reading data sequence; and the proofreading module judges the part which does not exceed the limited use frequency Fx in the sorted data sequence as the data sequence to be proofread to form a data sequence to be proofread, and proofreads the data sequence to be proofread according to the storage time of the extracted data of each generation.
6. The intelligent enterprise software component management system based on big data as claimed in claim 5, wherein the calibration module is provided with a standard storage time length Tb and a standard storage time length difference Δ Tb, the calibration module obtains a storage time length Tc of each data to be extracted in the data sequence to be calibrated, the calibration module calculates the storage time length difference Δ Tc and Δ Tc = | Tb-Tc | of each data to be extracted according to the storage time length Tc and the standard storage time length Tb of each data to be extracted, the calibration module compares the storage time length difference Δ Tc of each data to be extracted with the standard storage time length difference Δ Tb,
when the delta Tc is less than or equal to the delta Tb, the proofreading module judges that the storage time of the data to be extracted is within a standard range, and does not proofread the data to be extracted;
when the delta Tc is larger than the delta Tb, the proofreading module judges that the storage time length of the data to be extracted is not in the standard range, the proofreading module marks the data to be extracted, and the proofreading module proofreads the sequence of the data to be extracted in the data sequence to be proofread according to the storage time length Tc and the standard storage time length Tb of the data to be extracted.
7. The intelligent enterprise software component management system based on big data as claimed in claim 6, wherein the collation module compares the storage time period Tc of each marked data to be extracted with the standard storage time period Tb,
when Tc is larger than Tb, the proofreading module judges that the storage time length of each marked data to be extracted is longer than the standard storage time length, and the proofreading module discharges each marked data to be extracted to the tail end of the data sequence to be proofread according to the sequence from small to large of the byte length of each marked data to be extracted;
when Tc is less than Tb, the proofreading module judges that the storage time of each marked data to be extracted is shorter than the standard storage time, and the proofreading module discharges each marked data to be extracted to the front end of the data sequence to be proofread according to the sequence of the byte lengths of each marked data to be extracted from large to small;
and the proofreading module discharges the proofread data sequence to be proofread to the rear end of the initial proofread data sequence to finish proofreading the data sequence and form a proofread data sequence.
8. The intelligent enterprise software component management system based on big data as claimed in claim 7, wherein the extraction module labels each data to be extracted in the collated data sequence, the extraction module labels each data to be extracted as B1, B2, and B3.
9. The intelligent enterprise software component management system based on big data as claimed in claim 8, wherein the extracting module has a standard byte quantity difference Mb, the extracting module calculates the total M1 of the data bytes to be extracted by the first extracting unit as a first byte quantity, the extracting module calculates the total M2 of the data bytes to be extracted by the second extracting unit as a second byte quantity, the extracting module calculates the byte quantity difference Mc, Mc = | M1-M2| according to the first byte quantity M1 and the second byte quantity M2, the extracting module compares the byte quantity difference Mc with the standard byte quantity difference Mb,
when Mc is less than or equal to Mb, the extraction module judges that the byte quantity difference is within a standard range, and the first extraction unit and the second extraction unit simultaneously extract data extracted by each band;
when Mc is larger than Mb, the extracting module judges that the byte quantity difference is not in the standard range, and the extracting module compares the first byte quantity M1 with the second byte quantity M2 to extract each data to be extracted.
10. The intelligent enterprise software component management system based on big data as claimed in claim 9, wherein when the extracting module determines that the difference of the byte amounts is not within the standard range, the extracting module compares the first byte amount M1 with the second byte amount M2,
when M1 is greater than M2, the extraction module judges that the first byte amount is greater than the second byte amount, the extraction module adjusts the data to be extracted at the tail end of the sequence in the data to be extracted which needs to be extracted by the first extraction unit, the extraction module adjusts the data to be extracted to the tail end of the sequence in the data to be extracted which needs to be extracted by the second extraction unit, and the extraction module repeats the judgment and adjustment operation according to the byte amount until the adjusted byte amount difference Mc' is less than or equal to Mb, and the first extraction unit and the second extraction unit simultaneously extract the data to be extracted;
when M1 is less than M2, the extraction module judges that the second byte amount is greater than the first byte amount, the extraction module adjusts the data to be extracted at the tail end of the sequence in the data to be extracted which needs to be extracted by the second extraction unit, the extraction module adjusts the data to be extracted to the tail end of the sequence of the data to be extracted which needs to be extracted by the first extraction unit, and the extraction module repeats the judgment and adjustment operation according to the byte amount until the adjusted byte amount difference Mc' is less than or equal to Mb, and the first extraction unit and the second extraction unit extract the data simultaneously.
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