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WO2016206377A1 - 数据整合处理方法及装置 - Google Patents

数据整合处理方法及装置 Download PDF

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Publication number
WO2016206377A1
WO2016206377A1 PCT/CN2016/071780 CN2016071780W WO2016206377A1 WO 2016206377 A1 WO2016206377 A1 WO 2016206377A1 CN 2016071780 W CN2016071780 W CN 2016071780W WO 2016206377 A1 WO2016206377 A1 WO 2016206377A1
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WIPO (PCT)
Prior art keywords
performance
data
asset
asset data
field
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PCT/CN2016/071780
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English (en)
French (fr)
Inventor
胡常举
刘万慧
范书田
丁柏
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中兴通讯股份有限公司
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Publication of WO2016206377A1 publication Critical patent/WO2016206377A1/zh

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/24—Querying
    • G06F16/245—Query processing
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/22—Indexing; Data structures therefor; Storage structures
    • G06F16/2228—Indexing structures

Definitions

  • the present invention relates to the field of communications, and in particular to a data integration processing method and apparatus.
  • the original performance processing method mainly uses the Structured Query Language (SQL) statement of the in-memory database for processing, which occupies high memory, complicated to write SQL statements, and is troublesome to maintain, and it takes time to process a time point. Longer to meet the growing demand for large numbers of performance processing.
  • SQL Structured Query Language
  • the present invention provides a data integration processing method and apparatus, so as to at least solve the problem that the asset data and performance data processing process of the networking in the related art is complicated and takes a long time.
  • a data integration processing method including:
  • the asset file and the performance file are read into the memory to generate a corresponding asset table and performance table;
  • the performance data in the performance array of the asset data is integrated according to a calculation formula of the configured performance field, and the integrated performance field value of the asset data is obtained to assign the asset performance table.
  • the method further includes:
  • the calculation formula according to the configured performance field integrates the performance of the asset data Performance data within the group, obtaining the integrated performance field value of the asset data.
  • the asset performance table includes:
  • the asset performance table is assigned to the performance data of the asset data. If the asset data has multiple performance data, according to the configured field type and formula The performance data is calculated, and the performance data of the asset data after the calculation is assigned to the asset performance table.
  • calculating the performance data according to the configured field type and formula includes:
  • the performance data is calculated by an iterative calculation method according to the configured field type and formula.
  • querying the performance table according to the key segment value of the asset data to obtain an performance data array of the asset data includes:
  • the performance data of the location identifier is obtained and added to the performance data array.
  • a data integration processing apparatus including:
  • the generating module is configured to read the asset file and the performance file into the memory according to the memory field information of the configured asset data and the memory field information of the performance data to generate a corresponding asset table and a performance table;
  • a sorting module configured to set a key segment value of the asset data and the performance data, and sort the asset table and the performance table according to the key segment value
  • a module is configured to loop the sorted asset table as a main object, and query the performance table according to the key segment value of the asset data to obtain an performance data array of the asset data;
  • the integration module is configured to integrate the performance data in the performance array of the asset data according to a calculation formula of the configured performance field, and obtain the integrated performance field value of the asset data to assign the asset performance table.
  • the device further includes:
  • a filtering module configured to set a filtering condition of the asset data, and if the asset data does not meet the filtering condition, query the performance table according to the keyword segment value of the asset data to obtain the asset Performance data for the data.
  • the integration module comprises:
  • a first integration unit configured to assign only one piece of the performance data to the asset data, and assign the asset performance table to performance data of the asset data;
  • a second integration unit configured to calculate the performance data according to the configured field type and formula, and assign the performance data of the asset data to the asset after the calculation, if the asset data has multiple pieces of performance data. Performance table.
  • the integration module comprises:
  • the iteration unit is configured to calculate the performance data by an iterative calculation according to the configured field type and formula.
  • the creating module includes:
  • An identifier unit configured to acquire a location identifier of the performance table, compare the key field value of the asset data with a key field value of the location identifier of the performance table, in the asset data If the key field value is equal to the key field value of the location identifier of the performance table, the performance data of the location identifier is obtained and added to the performance data array.
  • the asset file and the performance file are read into the memory to generate a corresponding asset table and performance table, and the key of the asset data and the performance data is set.
  • FIG. 1 is a flow chart of a data integration processing method according to an embodiment of the present invention.
  • FIG. 2 is a structural block diagram of a data integration processing apparatus according to an embodiment of the present invention.
  • FIG. 3 is a schematic diagram of a main flow of asset performance processing according to a preferred embodiment of the present invention.
  • FIG. 4 is a schematic diagram of an asset circulation process in accordance with a preferred embodiment of the present invention.
  • FIG. 5 is a schematic diagram of a performance query process according to a preferred embodiment of the present invention.
  • FIG. 6 is a schematic diagram of a performance processing flow in accordance with a preferred embodiment of the present invention.
  • FIG. 1 is a flowchart of a data integration processing method according to an embodiment of the present invention. As shown in FIG. 1, the process includes the following steps:
  • Step S102 according to the memory field information of the configured asset data and the memory field information of the performance data, the asset file and the performance file are read into the memory to generate a corresponding asset table and a performance table;
  • Step S104 setting the asset data and the key field value of the performance data, and sorting the asset table and the performance table according to the key segment value;
  • Step S106 the sorted asset table is looped as a main object, and the performance data table is obtained according to the keyword segment value of the asset data to obtain an performance data array of the asset data;
  • Step S108 Integrate the performance data in the performance array of the asset data according to the calculation formula of the configured performance field, and obtain the integrated performance field value of the asset data to assign the asset performance table.
  • the asset file and the performance file are read into the memory to generate a corresponding asset table, a performance table, and the key of the asset data and the performance data is set.
  • the asset data and the key field value of the performance data are set, and after the asset table and the performance table are sorted according to the key segment value, the filtering condition of the asset data is set, and the asset data is set in the asset data. If the filter condition is not met, querying the performance table according to the key field value of the asset data to obtain performance data of the asset data.
  • the asset data has only one piece of the performance data, and the performance data of the asset data is assigned to the asset performance table. If the asset data has multiple performance data, according to the configured field type and formula pair The performance data is calculated, and the performance data of the asset data is calculated and assigned to the asset performance table.
  • the performance data can be calculated by an iterative calculation method according to the configured field type and formula.
  • the location identifier of the performance table may be obtained, and the key segment value of the asset data and the key segment value of the location identifier of the performance table are compared, and the key segment value of the asset data is equal to
  • the performance data of the location identifier is obtained and added to the performance data array.
  • a data integration processing device is provided, which is used to implement the above-mentioned embodiments and preferred embodiments, and has not been described again.
  • the term “module” may implement a combination of software and/or hardware of a predetermined function.
  • the apparatus described in the following embodiments is preferably implemented in software, hardware, or a combination of software and hardware, is also possible and contemplated.
  • FIG. 2 is a structural block diagram of a data integration processing apparatus according to an embodiment of the present invention. As shown in FIG. 2, the apparatus includes
  • the generating module 22 is configured to: according to the memory field information of the configured asset data and the memory field information of the performance data, The asset file and the performance file are read into the memory to generate a corresponding asset table and performance table;
  • the sorting module 24 is configured to set the key data value of the asset data and the performance data, and sort the asset table and the performance table according to the key segment value;
  • the creating module 26 is configured to cycle the sorted asset table as a main object, and query the performance table according to the keyword segment value of the asset data to obtain an performance data array of the asset data;
  • the integration module 28 is configured to integrate the performance data in the performance array of the asset data according to the calculation formula of the configured performance field, and obtain the integrated performance field value of the asset data to assign the asset performance table.
  • the asset file and the performance file are read into the memory to generate a corresponding asset table, a performance table, and the key of the asset data and the performance data is set.
  • the device further includes:
  • the filtering module is configured to set a filtering condition of the asset data, and if the asset data does not satisfy the filtering condition, querying the performance table according to the key field value of the asset data to obtain performance data of the asset data.
  • the integration module 28 includes:
  • the first integration unit is configured to assign only one performance data in the asset data, and assign the asset performance table to the performance data of the asset data;
  • the second integration unit is configured to calculate the performance data according to the configured field type and formula when the asset data has multiple pieces of performance data, and assign the performance data of the asset data to the asset performance table after the calculation.
  • the integration module 28 includes:
  • the iteration unit is set to calculate the performance data by an iterative calculation according to the configured field type and formula.
  • the creating module 26 includes:
  • An identifier unit configured to obtain a location identifier of the performance table, compare the key field value of the asset data with a key field value of the location identifier of the performance table, where the key field value of the asset data is equal to the performance
  • the performance data of the location identifier is obtained and added to the performance data array.
  • the preferred embodiment provides a universal and efficient data integration processing method, which can efficiently process the same kind of resources Multiple performance files produced, which implement formulas and special cases, can be applied to multiple scenarios and specialties. At the same time, this method is very scalable and easy for developers to maintain.
  • the preferred embodiment is applied to an existing system collector to provide a universal and efficient performance integration processing method, which mainly includes:
  • Asset performance file integration extract key information into the configuration file, read the asset and performance files into the memory table and sort according to the key fields, loop the asset table as the main table, and query related performance according to the keyword key segment.
  • the corresponding formulas of the configuration are configured to perform performance summarization to obtain performance data of the required assets.
  • Performance data query Encapsulate the sorted performance table, set the performance table array subscript, compare the asset key segment value with the performance corresponding keyword segment value, and obtain the performance of the corresponding asset.
  • Asset Performance Filtering Configure filtering criteria for assets and performance, and filter data that does not meet the criteria when querying for asset loops and performance.
  • Formula application When integrating multiple performance data, use the iterative method to perform efficient performance calculation according to the configured formula.
  • the preferred embodiment provides a universal and efficient data integration processing method, which can efficiently process multiple performance files of the same asset, implement formulas and special cases, and can be applied to multiple scenarios and professions. At the same time, this method is very scalable and easy for developers to maintain.
  • Table 1 is the table of assets to be processed
  • Table 2 and Table 3 are the associated performance tables
  • Table 1 Table 2 and Table 3 hold the required field names and field values read from the asset and performance files, sorted after encapsulation
  • the key field value in the asset table corresponds to the key field value in the associated performance table.
  • Some properties of some assets may not exist; the assets in the performance table may not all belong to the asset table; the correspondence between assets and performance is one-to-one or one-to-many.
  • FIG. 3 is a schematic diagram of a main process of asset performance processing according to a preferred embodiment of the present invention. As shown in FIG. 3, the detailed main process of asset performance processing is shown in FIG. 3 and the flow step description.
  • Attribute 1 Attribute 2 Attribute 3 Attribute 4 Attribute 5 Performance 1 Performance 2 Performance 3 Num1 Asset attribute Asset attribute Asset attribute Asset attribute Asset attribute M1 N1 R1 Num2 Asset attribute Asset attribute Asset attribute Asset attribute M2 N2 R2 Num3 Asset attribute Asset attribute Asset attribute Asset attribute Asset attribute M3 N3 R3 Num4 Asset attribute Asset attribute Asset attribute Asset attribute M4 N4 R4
  • the for loop is performed with the asset table as the main object.
  • the specific loop process refer to Figure 4 and the process step description; obtain the key segment value of the single asset, to the association Obtain the asset-related performance data array in the performance table.
  • the specific query process see Figure 5 and the query flow description.
  • After obtaining the performance data array calculate the performance of each field according to the configured performance field information.
  • the specific calculation process see Figure 6. And calculating the process steps; assigning the values of the obtained performance fields to the asset performance table.
  • Table 4 is an asset performance table processed by the method of the present invention, and the performance of all required assets is integrated into the asset performance table and finally output to the required file. If the relationship between the asset and the performance is one-to-one, the corresponding performance is obtained from the performance table according to the performance field name of the asset, and the assignment is performed; if the correspondence between the asset and the performance is one-to-many, all the calculations are calculated according to the configured field calculation formula. The field value of the associated performance, the final result is assigned to the performance corresponding to the asset; if the asset does not query the corresponding performance data, the value is all empty.
  • FIG. 3 is a schematic diagram of a main process of asset performance processing according to a preferred embodiment of the present invention. As shown in FIG. 3, the main processing steps are as follows:
  • Step S301 Read all configuration files related to assets and performance, mainly including: a valid column configuration file for performance calculation, the file includes a performance field name, a type, a merged field name, an asset corresponding field name, a calculation formula, etc.
  • the configuration file contains all the information about the fields in the performance integration; the configuration file contains the asset type and its associated filter conditions; the asset and performance memory table configuration file, which contains all the field information of the asset and performance memory table.
  • Step S302 According to the configured asset and performance memory field information, the required asset and performance files are read into the memory and saved in the form of an in-memory table.
  • Step S303 Encapsulating the asset table and the corresponding performance table into an object.
  • the object is created, setting a keyword associated with the asset and the performance, and sorting the asset table and the performance table according to the key segment value; and setting the asset filtering in the object Condition, the corresponding filter condition is acquired from step S301.
  • Step S304 Perform a for loop with the asset table as the main object, and the specific process is shown in FIG. 4 .
  • Step S305 Acquiring the asset data. If the asset data does not meet the filtering condition, that is, the asset is not filtered, the corresponding performance data is queried according to the key segment value of the asset data to the related performance table, and saved in an array.
  • Step S306 Perform performance data aggregation according to the performance array obtained in step S305 and the asset and performance effective column data obtained in step S301. If there is only one performance data, it is directly assigned; if there are multiple performance data, you need to calculate the performance of each field according to the field type and formula configured by the valid column, and then assign the value.
  • Step S307 Steps S305 and S306 are repeated until the performance processing of all assets is completed.
  • FIG. 4 is a schematic diagram of an asset circulation process according to a preferred embodiment of the present invention. As shown in FIG. 4, the main processing steps are as follows:
  • Step S401 Acquire a sorted asset table and perform a for loop.
  • Step S402 Acquire asset data, and obtain a key segment value in the asset data according to the key segment name set in the asset table object.
  • Step S403 Verify the asset according to the filtering condition, verify whether the asset data satisfies the condition, if not, filter the piece of data, repeat step S402 and step S403; if the condition is met, continue the process.
  • Step S404 Obtain performance data from the corresponding performance table according to the key segment value of the asset data. See Figure 5 for the specific process.
  • Step S405 Processing the acquired performance data, performing assignment according to actual conditions, and acquiring performance data of the asset.
  • Step S406 If the asset performance is not processed, steps S402, S403, S404, and S405 are repeated; if all the assets are processed, the process is completed.
  • FIG. 5 is a schematic diagram of a performance query process according to a preferred embodiment of the present invention. As shown in FIG. 5, the main processing steps are as follows:
  • Step S501 Acquire a key field value of the asset data.
  • Step S502 Acquire a related performance table object of the asset according to the asset type.
  • An asset may have multiple associated performance tables.
  • the processing flow for each performance table is the same. This process only shows the performance acquisition process of one of the performance tables.
  • Step S503 Create an array for saving performance data corresponding to the asset.
  • Step S504 Obtain the location identifier of the performance table, and the default is 0, that is, the search starts from the first performance. Obtain current performance data based on the location identifier for asset data matching.
  • Step S505 comparing the key value of the asset with the key segment value of the performance of the performance table location identifier, and converting the value into the long data by using a common conversion tool to determine the size of the two.
  • Step S506 If the asset key segment value is greater than the performance key segment value, it indicates that the performance does not belong to the asset, and there may be performance belonging to the asset later, so the location identifier is +1.
  • Step S507 If the asset key segment value is equal to the performance key segment value, it indicates that the performance belongs to the asset, and the performance is added to the performance array created in step S503. If the asset-performance correspondence is one-to-many, there may be performances belonging to this asset later, so the location identifier is +1; if the asset-performance correspondence is many-to-one, there is no longer the performance of the asset. The logo does not move.
  • Step S508 Steps S504, S505, S506, and S507 are repeated until the asset key segment value is greater than the performance key segment value, indicating that the location identifier and the subsequent performance do not belong to the asset, and the performance data query of the asset data is completed. An array of performance data for this asset.
  • Step 509 Processing an array of performance data of the asset. See Figure 6 for the specific process.
  • FIG. 6 is a schematic diagram of a performance processing flow according to a preferred embodiment of the present invention. As shown in FIG. 6, the main processing steps are as follows:
  • Step S601 Obtain an array of performance data corresponding to the asset, and the specific process is shown in Figure 5.
  • Step S602 If the asset performance array has no performance data, the value used is assigned an invalid value; if there is performance data, the valid column array required for performance is obtained, and the array contains detailed information of all the performance fields that need to be processed.
  • Step S603 Perform a for loop mainly with an effective column array, and process data of each performance field according to the information of the configured field.
  • Step S604 Acquire detailed information of the to-be-processed field, including the field name, the merged field name (the performance field name corresponding to the asset), the field name of the merged data, the field calculation formula, the field calculation complex formula, the data internal field calculation formula, and the like. .
  • Step S605 The formula for calculating the field according to the actual situation may be divided into multiple cases: multiple data are subjected to single addition, subtraction, multiplication and division calculation; multiple data are subjected to complex hybrid calculation, such as max(a,sum(b,c) ), etc.; multiple fields in a single performance for data calculation, etc.
  • Step S606 Integrate the performance data array by using the calculation formula obtained in step S605, and obtain the corresponding field value of each performance data. If a single formula calculation is performed, the calculation is directly performed; if complex hybrid calculation is performed, the iteration function is used. .
  • Step S607 Assign the calculated field performance value to the corresponding field of the asset.
  • Step S608 Steps S604, S605, S606, and S607 are repeated until all the performance data fields are processed.
  • the method according to the above embodiment can be implemented by means of software plus a necessary general hardware platform, and of course, by hardware, but in many cases, the former is A better implementation.
  • the technical solution of the present invention which is essential or contributes to the prior art, may be embodied in the form of a software product stored in a storage medium (such as ROM/RAM, disk,
  • the optical disc includes a number of instructions for causing a terminal device (which may be a mobile phone, a computer, a server, or a network device, etc.) to perform the method of various embodiments of the present invention.
  • each of the above modules may be implemented by software or hardware.
  • the foregoing may be implemented by, but not limited to, the foregoing modules are all located in the same processor; or, the modules are located in multiple In the processor.
  • Embodiments of the present invention also provide a storage medium.
  • the above storage medium may be arranged to store program code for performing the method steps of the following embodiments:
  • the foregoing storage medium may include, but not limited to, a USB flash drive, a Read-Only Memory (ROM), a Random Access Memory (RAM), a mobile hard disk, and a magnetic memory.
  • the processor performs the method steps of the foregoing embodiments according to the stored program code in the storage medium.
  • modules or steps of the present invention described above can be implemented by a general-purpose computing device that can be centralized on a single computing device or distributed across a network of multiple computing devices. Alternatively, they may be implemented by program code executable by the computing device such that they may be stored in the storage device by the computing device and, in some cases, may be different from the order herein.
  • the steps shown or described are performed, or they are separately fabricated into individual integrated circuit modules, or a plurality of modules or steps thereof are fabricated as a single integrated circuit module.
  • the invention is not limited to any specific combination of hardware and software.
  • the asset file and the performance file are read into the memory to generate a corresponding asset table and performance table, and the asset is set.
  • the data field and the key field value of the performance data, sorting the asset table and the performance table according to the key field value, and circulating the sorted asset table as a main object, according to the key field of the asset data The value query is performed on the performance table to obtain an performance data array of the asset data, and the performance data in the performance data array of the asset data is integrated according to the calculation formula of the configured performance field, and the integrated performance field value of the asset data is obtained and the asset performance table is assigned.

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Abstract

一种数据整合处理方法及装置，其中，该方法根据配置资产数据的内存字段信息和性能数据的内存字段信息，将资产文件、性能文件读取到内存中生成对应的资产表、性能表（S102），设置该资产数据和该性能数据的关键字段值，根据该关键字段值对该资产表和该性能表进行排序（S104），将已排序的该资产表为主对象进行循环，根据该资产数据的该关键字段值查询该性能表得到该资产数据的性能数据数组（S106），根据配置的性能字段的计算公式整合该资产数据的性能数组内的性能数据，获取该资产数据的整合后的性能字段值赋值该资产性能表（S108），解决了组网的资产数据和性能数据处理过程复杂，耗时时间长的问题，实现了高效处理同种资产数据的多个性能数据文件。

Description

数据整合处理方法及装置 技术领域
本发明涉及通信领域，具体而言，涉及一种数据整合处理方法及装置。
背景技术
随着分组传送网(Packet Transport Network，简称为PTN)网络应用规模越来越大，组网的资产和性能也越来越多；需求亦在不停的变更，需要增加或者删除文件、字段等。原有的性能处理方法，主要使用内存数据库的结构类查询语言(Structured Query Language，简称为SQL)语句进行处理，占用内存高，SQL语句编写复杂困难，以及维护比较麻烦，处理一个时间点耗时较长，无法满足日益增长的大数量性能处理需求。
针对相关技术中，组网的资产数据和性能数据处理过程复杂，耗时时间长的问题，目前还没有有效的解决技术方案。
发明内容
本发明提供了一种数据整合处理方法及装置，以至少解决相关技术中组网的资产数据和性能数据处理过程复杂，耗时时间长的问题。
根据本发明的一个实施例，提供了一种数据整合处理方法，包括：
根据配置资产数据的内存字段信息和性能数据的内存字段信息，将资产文件、性能文件读取到内存中生成对应的资产表、性能表；
设置所述资产数据和所述性能数据的关键字段值，根据所述关键字段值对所述资产表和所述性能表进行排序；
将已排序的所述资产表为主对象进行循环，根据所述资产数据的所述关键字段值查询所述性能表得到所述资产数据的性能数据数组；
根据配置的性能字段的计算公式整合所述资产数据的性能数组内的性能数据，获取所述资产数据的整合后的性能字段值赋值所述资产性能表。
在本发明的实施例中，设置所述资产数据和所述性能数据的关键字段值，根据所述关键字段值对所述资产表和所述性能表进行排序之后，还包括：
设置所述资产数据的过滤条件，在所述资产数据未满足所述过滤条件的情况下，根据所述资产数据的所述关键字段值查询所述性能表得到所述资产数据的性能数据。
在本发明的实施例中，所述根据配置的性能字段的计算公式整合所述资产数据的性能数 组内的性能数据，获取所述资产数据的整合后的性能字段值赋值所述资产性能表包括：
在所述资产数据只有一条所述性能数据，对所述资产数据的性能数据赋值所述资产性能表，在所述资产数据有多条性能数据的情况下，根据配置的字段类型、公式对所述性能数据进行计算，将计算后所述资产数据的性能数据赋值所述资产性能表。
在本发明的实施例中，根据配置的字段类型、公式对所述性能数据进行计算包括：
根据配置的字段类型、公式，通过迭代的计算方式对所述性能数据进行计算。
在本发明的实施例中，根据所述资产数据的所述关键字段值查询所述性能表得到所述资产数据的性能数据数组包括：
获取所述性能表的位置标识，比较所述资产数据的所述关键字段值与所述性能表的所述位置标识的关键字段值，在所述资产数据的所述关键字段值等于所述性能表的所述位置标识的关键字段值情况下，获取所述位置标识的性能数据，添加到所述性能数据数组。
根据本发明的另一个实施例，还提供了一种数据整合处理装置，包括：
生成模块，设置为根据配置资产数据的内存字段信息和性能数据的内存字段信息，将资产文件、性能文件读取到内存中生成对应的资产表、性能表；
排序模块，设置为设置所述资产数据和所述性能数据的关键字段值，根据所述关键字段值对所述资产表和所述性能表进行排序；
创建模块，设置为将已排序的所述资产表为主对象进行循环，根据所述资产数据的所述关键字段值查询所述性能表得到所述资产数据的性能数据数组；
整合模块，设置为根据配置的性能字段的计算公式整合所述资产数据的性能数组内的性能数据，获取所述资产数据的整合后的性能字段值赋值所述资产性能表。
在本发明的实施例中，所述装置还包括：
过滤模块，设置为设置所述资产数据的过滤条件，在所述资产数据未满足所述过滤条件的情况下，根据所述资产数据的所述关键字段值查询所述性能表得到所述资产数据的性能数据。
在本发明的实施例中，所述整合模块包括：
第一整合单元，设置为在所述资产数据只有一条所述性能数据，对所述资产数据的性能数据赋值所述资产性能表；
第二整合单元，设置为在所述资产数据有多条性能数据的情况下，根据配置的字段类型、公式对所述性能数据进行计算，将计算后所述资产数据的性能数据赋值所述资产性能表。
在本发明的实施例中，所述整合模块包括：
迭代单元，设置为根据配置的字段类型、公式，通过迭代的计算方式对所述性能数据进行计算。
在本发明的实施例中，所述创建模块包括：
标识单元，设置为获取所述性能表的位置标识，比较所述资产数据的所述关键字段值与所述性能表的所述位置标识的关键字段值，在所述资产数据的所述关键字段值等于所述性能表的所述位置标识的关键字段值情况下，获取所述位置标识的性能数据，添加到所述性能数据数组。
通过本发明，根据配置资产数据的内存字段信息和性能数据的内存字段信息，将资产文件、性能文件读取到内存中生成对应的资产表、性能表，设置该资产数据和该性能数据的关键字段值，根据该关键字段值对该资产表和该性能表进行排序，将已排序的该资产表为主对象进行循环，根据该资产数据的该关键字段值查询该性能表得到该资产数据的性能数据数组，根据配置的性能字段的计算公式整合该资产数据的性能数组内的性能数据，获取该资产数据的整合后的性能字段值赋值该资产性能表，解决了组网的资产数据和性能数据处理过程复杂，耗时时间长的问题，实现了高效处理同种资产数据的多个性能数据文件。
附图说明
此处所说明的附图用来提供对本发明的进一步理解，构成本申请的一部分，本发明的示意性实施例及其说明用于解释本发明，并不构成对本发明的不当限定。在附图中：
图1是根据本发明实施例的一种数据整合处理方法的流程图；
图2是根据本发明实施例的一种数据整合处理装置的结构框图；
图3是根据本发明优选实施例的资产性能处理主流程示意图；
图4是根据本发明优选实施例的资产循环流程示意图；
图5是根据本发明优选实施例的性能查询流程示意图；
图6是根据本发明优选实施例的性能处理流程示意图。
具体实施方式
下文中将参考附图并结合实施例来详细说明本发明。需要说明的是，在不冲突的情况下，本申请中的实施例及实施例中的特征可以相互组合。
需要说明的是，本发明的说明书和权利要求书及上述附图中的术语“第一”、“第二”等是用于区别类似的对象，而不必用于描述特定的顺序或先后次序。
在本实施例中提供了一种数据整合处理方法，图1是根据本发明实施例的一种数据整合处理方法的流程图，如图1所示，该流程包括如下步骤：
步骤S102，根据配置资产数据的内存字段信息和性能数据的内存字段信息，将资产文件、性能文件读取到内存中生成对应的资产表、性能表；
步骤S104，设置该资产数据和该性能数据的关键字段值，根据该关键字段值对该资产表和该性能表进行排序；
步骤S106，将已排序的该资产表为主对象进行循环，根据该资产数据的该关键字段值查询该性能表得到该资产数据的性能数据数组；
步骤S108，根据配置的性能字段的计算公式整合该资产数据的性能数组内的性能数据，获取该资产数据的整合后的性能字段值赋值该资产性能表。
通过上述步骤，根据配置资产数据的内存字段信息和性能数据的内存字段信息，将资产文件、性能文件读取到内存中生成对应的资产表、性能表，设置该资产数据和该性能数据的关键字段值，根据该关键字段值对该资产表和该性能表进行排序，将已排序的该资产表为主对象进行循环，根据该资产数据的该关键字段值查询该性能表得到该资产数据的性能数据数组，根据配置的性能字段的计算公式整合该资产数据的性能数组内的性能数据，获取该资产数据的整合后的性能字段值赋值该资产性能表，解决了组网的资产数据和性能数据处理过程复杂，耗时时间长的问题，实现了高效处理同种资产数据的多个性能数据文件。
在本实施例中，设置该资产数据和该性能数据的关键字段值，根据该关键字段值对该资产表和该性能表进行排序之后，设置该资产数据的过滤条件，在该资产数据未满足该过滤条件的情况下，根据该资产数据的该关键字段值查询该性能表得到该资产数据的性能数据。
在本实施例中，在该资产数据只有一条该性能数据，对该资产数据的性能数据赋值该资产性能表，在该资产数据有多条性能数据的情况下，根据配置的字段类型、公式对该性能数据进行计算，将计算后该资产数据的性能数据赋值该资产性能表。
在本实施例中，可以根据配置的字段类型、公式，通过迭代的计算方式对该性能数据进行计算。
在本实施例中，可以获取该性能表的位置标识，比较该资产数据的该关键字段值与该性能表的该位置标识的关键字段值，在该资产数据的该关键字段值等于该性能表的该位置标识的关键字段值情况下，获取该位置标识的性能数据，添加到该性能数据数组。
在本实施例中还提供了一种数据整合处理装置，该装置用于实现上述实施例及优选实施方式，已经进行过说明的不再赘述。如以下所使用的，术语“模块”可以实现预定功能的软件和/或硬件的组合。尽管以下实施例所描述的装置较佳地以软件来实现，但是硬件，或者软件和硬件的组合的实现也是可能并被构想的。
图2是根据本发明实施例的一种数据整合处理装置的结构框图，如图2所示，该装置包括
生成模块22，设置为根据配置资产数据的内存字段信息和性能数据的内存字段信息，将 资产文件、性能文件读取到内存中生成对应的资产表、性能表；
排序模块24，设置为设置该资产数据和该性能数据的关键字段值，根据该关键字段值对该资产表和该性能表进行排序；
创建模块26，设置为将已排序的该资产表为主对象进行循环，根据该资产数据的该关键字段值查询该性能表得到该资产数据的性能数据数组；
整合模块28，设置为根据配置的性能字段的计算公式整合该资产数据的性能数组内的性能数据，获取该资产数据的整合后的性能字段值赋值该资产性能表。
通过上述步骤，根据配置资产数据的内存字段信息和性能数据的内存字段信息，将资产文件、性能文件读取到内存中生成对应的资产表、性能表，设置该资产数据和该性能数据的关键字段值，根据该关键字段值对该资产表和该性能表进行排序，将已排序的该资产表为主对象进行循环，根据该资产数据的该关键字段值查询该性能表得到该资产数据的性能数据数组，根据配置的性能字段的计算公式整合该资产数据的性能数组内的性能数据，获取该资产数据的整合后的性能字段值赋值该资产性能表，解决了组网的资产数据和性能数据处理过程复杂，耗时时间长的问题，实现了高效处理同种资产数据的多个性能数据文件。
在本实施例中，该装置还包括：
过滤模块，设置为设置该资产数据的过滤条件，在该资产数据未满足该过滤条件的情况下，根据该资产数据的该关键字段值查询该性能表得到该资产数据的性能数据。
在本实施例中，该整合模块28包括：
第一整合单元，设置为在该资产数据只有一条该性能数据，对该资产数据的性能数据赋值该资产性能表；
第二整合单元，设置为在该资产数据有多条性能数据的情况下，根据配置的字段类型、公式对该性能数据进行计算，将计算后该资产数据的性能数据赋值该资产性能表。
在本实施例中，该整合模块28包括：
迭代单元，设置为根据配置的字段类型、公式，通过迭代的计算方式对该性能数据进行计算。
在本实施例中，该创建模块26包括：
标识单元，设置为获取该性能表的位置标识，比较该资产数据的该关键字段值与该性能表的该位置标识的关键字段值，在该资产数据的该关键字段值等于该性能表的该位置标识的关键字段值情况下，获取该位置标识的性能数据，添加到该性能数据数组。
下面结合优选实施例和实施方式对本发明进行详细说明。
本优选实施例提供了一种通用高效的数据整合处理方法，该方法能够高效的处理同种资 产的多个性能文件，实现公式及特殊情况的处理，可以应用于多个场景及专业。同时，此方法具有很好的扩展性，便于开发人员进行维护。
本优选实施例应用在现有系统采集器上，提供一种通用高效的性能整合处理方法，主要包括：
资产性能文件整合：提取关键信息到配置文件中，将资产和性能文件读取到内存表并根据关键字段进行排序，以资产表为主表进行循环，根据资产关键字段查询相关性能，利用配置的相应公式等规则进行性能汇总，获得所需的资产的性能数据。
性能数据查询：封装已排序的性能表，设定性能表数组下标，将资产关键字段值与性能相应的关键字段值进行比较，获取相应的资产的性能。
资产性能过滤：配置资产与性能的过滤条件，资产循环和性能查询时，过滤不满足条件的数据。
公式应用：多个性能数据进行整合时，根据配置的公式，使用迭代等方法进行高效的性能计算。
本优选实施例提供了一种通用高效的数据整合处理方法，该方法能够高效的处理同种资产的多个性能文件，实现公式及特殊情况的处理，可以应用于多个场景及专业。同时，此方法具有很好的扩展性，便于开发人员进行维护。为使本发明的目的、技术方案和优点更加清楚明白，下文中将结合附图对本发明的实施进行详细说明。
表1是待处理的资产表，表2和表3是关联性能表，表1、表2及表3保存了从资产和性能文件中读取的所需字段名称及字段值，封装后进行排序，资产表中的关键字段值与其关联性能表中的关键字段值对应。某些资产的某些性能可能不存在；性能表中的资产不一定全部属于资产表；资产与性能的对应关系是一对一或者一对多。资产表中存在一些自带的性能，处理时无需进行整合，直接赋值到资产性能表中即可。图3是根据本发明优选实施例的资产性能处理主流程示意图，如图3所示，资产性能处理的详细主流程参见图3和流程步骤说明。
表1
关键字段 属性1 属性2 属性3 属性4 属性5 性能1 性能2 性能3
Num1 资产属性 资产属性 资产属性 资产属性 资产属性 m1 n1 r1
Num2 资产属性 资产属性 资产属性 资产属性 资产属性 m2 n2 r2
Num3 资产属性 资产属性 资产属性 资产属性 资产属性 m3 n3 r3
num4 资产属性 资产属性 资产属性 资产属性 资产属性 m4 n4 r4
表2
关键字段 性能4 性能5 性能6 性能7
Num1 a1 b1 c1 d1
Num2 a2 b2 c2 d2
Num2 a3 b3 c3 d3
Num3 a4 b4 c4 d4
Num3 a5 b5 c5 d5
Num4 a6 b6 c6 d6
表3
关键字段 性能8 性能9 性能10 性能11 性能12
Num0 e1 f1 g1 h1 k1
Num1 e2 f2 g2 h2 k2
Num1 e3 f3 g3 h3 k3
Num2 e4 f4 g4 h4 k4
Num4 e5 f5 g5 h5 k5
Num4 e6 f6 g6 h6 k6
得到需要处理的封装好的资产表及其相关性能表对象后，以资产表为主对象进行for循环，具体的循环流程参见图4和流程步骤说明；获取单个资产的关键字段值，到关联性能表中获取资产相关的性能数据数组，具体的查询流程参见图5和查询流程说明；得到性能数据数组后，根据配置的各个性能字段信息，计算各个字段的性能，具体的计算流程参见图6和计算流程步骤；将获取得到的各个性能字段的值赋值到资产性能表中。
表4是使用本发明的方法处理后的资产性能表，将所有需要的资产的性能整合处理到资产性能表中，最后输出到所需的文件中。若资产与性能对应关系是一对一，则根据资产的性能字段名称从性能表中获取对应的性能，进行赋值；若资产和性能对应关系是一对多，则根据配置的字段计算公式计算所有关联性能的字段值，最终的结果赋值给资产对应的性能；若资产查询不到相应的性能数据，则值全部为空。
表4
关键字段 性能2 性能2 性能3 性能4 性能5 性能6 性能7 性能8 性能9 性能10 性能11 性能12
Num1 m1 n1 r1 a1 b1 c1 d1 sum(e2，e3) sum(f2，f3) sum(g2，g3) sum(h2，h3) sum(k2，k3)
Num2 m2 n2 r2 max(a2，a3 max(b2，b3) max(c2，d3) max(d，d3) e4 f4 g4 h4 4
Num3 m3 n3 r3 avg(a4，a5) avg(b4，b5) avg(c4，c5) avg(c4，d5)          
num4 m4 n4 r4 a6 b6 c6 d6 min(e5，e6) min(f5，f6) min(g5，g6) min(h5，h6) min(k5，k6)
图3是根据本发明优选实施例的资产性能处理主流程示意图，如图3所示，主要处理步骤如下：
步骤S301：读取资产和性能相关的所有配置文件，主要包括：用于性能计算的有效列配置文件，文件中包含性能字段名称、类型、合并字段名称、资产对应字段名称、计算公式等，此配置文件包含性能整合时字段的所有信息；过滤配置文件，文件中包含资产类型以及与其相关的过滤条件；资产和性能内存表配置文件，文件中包含资产和性能内存表的所有字段信息。
步骤S302：根据配置的资产和性能内存字段信息，将所需的资产和性能文件读取到内存中，以内存表的形式保存。
步骤S303：将资产表和对应的性能表封装成对象，创建对象时，设置资产和性能相关联的关键字，并根据关键字段值对资产表和性能表进行排序；对象中设置资产的过滤条件，对应的过滤条件从步骤S301中获取。
步骤S304：以资产表为主对象，进行for循环，具体的流程参见图4。
步骤S305：获取资产数据，若资产数据未满足过滤条件，即资产未被过滤，则根据资产数据的关键字段值，到相关的性能表中查询对应的性能数据，并保存到数组中。
步骤S306：根据步骤S305获得的性能数组以及步骤S301获得的资产和性能有效列数据，进行性能数据汇总。如果只有一条性能数据，则直接赋值；如果存在多条性能数据，则需要根据有效列配置的字段类型、公式进行各个字段的性能计算，然后赋值。
步骤S307：重复步骤S305和步骤S306，直到所有资产的性能处理完成。
图4是根据本发明优选实施例的资产循环流程示意图，如图4所示，主要处理步骤如下：
步骤S401：获取已排序的资产表，进行for循环。
步骤S402：获取资产数据，根据资产表对象中设置的关键字段名称获得此资产数据中的关键字段值。获取资产表对象中设置的过滤条件，过滤字段及其过滤条件，均可在配置文件中进行设置，过滤字段可以为一个或者多个，满足不同情况的需求；过滤条件包含“＝＝”，“in”,“not in”等。
步骤S403：根据过滤条件对资产进行校验，验证资产数据是否满足条件，如果不满足，则过滤此条数据，重复步骤S402和步骤S403；如果满足条件，则继续流程。
步骤S404：根据资产数据的关键字段值，到相应的性能表中获取性能数据。具体的流程参见图5。
步骤S405：对获取的性能数据进行处理，根据实际情况进行赋值，获取资产的性能数据。
步骤S406：若资产性能未处理完成，则重复步骤S402、S403、S404和S405；若资产全部处理完成，则完成此流程。
图5是根据本发明优选实施例的性能查询流程示意图，如图5所示，主要处理步骤如下：
步骤S501：获取资产数据的关键字段值。
步骤S502：根据资产类型，获取此资产的相关性能表对象。资产可能会有多个关联性能表，每个性能表的处理流程一样，本流程只展示其中一个性能表的性能获取流程。
步骤S503：创建数组，用于保存和资产对应的性能数据。
步骤S504：获取性能表的位置标识，默认为0，即从第一条性能开始进行查找。根据位置标识获取当前性能数据，用于资产数据进行匹配。
步骤S505：将资产关键值与性能表位置标识所在的性能的关键字段值进行比较，使用公用转换工具将值转换为long型数据，判断二者的大小。
步骤S506：若资产关键字段值大于性能关键字段值，则表示性能不属于此资产，后面可能存在属于此资产的性能，因此位置标识+1。
步骤S507：若资产关键字段值等于性能关键字段值，则表示性能属于此资产，将此性能添加到步骤S503创建的性能数组中。若资产和性能对应关系是一对多，则后面可能存在属于此资产的性能，因此位置标识+1；若资产和性能对应关系是多对一，则后面不再存在属于此资产的性能，位置标识不动。
步骤S508：重复步骤S504，S505，S506，S507，直到资产关键字段值大于性能关键字段值，则表示位置标识及后面的性能不属于此资产，此条资产数据的性能数据查询完成，得到 此条资产的性能数据数组。
步骤509：处理资产的性能数据数组，具体流程参见图6。
图6是根据本发明优选实施例的性能处理流程示意图，如图6所示，主要处理步骤如下：
步骤S601：获取资产相应的性能数据数组，具体流程参见图5.
步骤S602：若资产性能数组没有性能数据，则将对用的值赋值为无效值；若存在性能数据，则获取性能所需的有效列数组，数组中包含所有需要处理的性能字段的详细信息。
步骤S603：以有效列数组为主进行for循环，根据配置的字段的信息处理每个性能字段的数据。
步骤S604：获取待处理字段的详细信息，包含字段名称、合并后的字段名称(资产对应的性能字段名称)、合并数据的字段名称、字段计算公式、字段计算复杂公式、数据内部字段计算公式等。
步骤S605：根据实际情况获取字段计算的公式，可分为多种情况：多个数据进行单一的加减乘除计算；多个数据进行复杂的混合计算，比如max(a，sum(b，c))等；单条性能中个多个字段进行数据计算等。
步骤S606：利用步骤S605获取的计算公式，对性能数据数组进行整合，获取每条性能数据的对应字段数值，若进行单一的公式计算，直接进行计算；若进行复杂的混合计算，则使用迭代功能。
步骤S607：将计算整合后的字段性能值赋值给资产相应的字段。
步骤S608：重复步骤S604，S605，S606，S607，直到所有的性能数据字段处理完成。
通过以上的实施方式的描述，本领域的技术人员可以清楚地了解到根据上述实施例的方法可借助软件加必需的通用硬件平台的方式来实现，当然也可以通过硬件，但很多情况下前者是更佳的实施方式。基于这样的理解，本发明的技术方案本质上或者说对现有技术做出贡献的部分可以以软件产品的形式体现出来，该计算机软件产品存储在一个存储介质(如ROM/RAM、磁碟、光盘)中，包括若干指令用以使得一台终端设备(可以是手机，计算机，服务器，或者网络设备等)执行本发明各个实施例该的方法。
需要说明的是，上述各个模块是可以通过软件或硬件来实现的，对于后者，可以通过以下方式实现，但不限于此：上述模块均位于同一处理器中；或者，上述模块分别位于多个处理器中。
本发明的实施例还提供了一种存储介质。可选地，在本实施例中，上述存储介质可以被设置为存储用于执行以下上述实施例的方法步骤的程序代码：
可选地，在本实施例中，上述存储介质可以包括但不限于：U盘、只读存储器(ROM，Read-Only Memory)、随机存取存储器(RAM，Random Access Memory)、移动硬盘、磁碟或 者光盘等各种可以存储程序代码的介质。
可选地，在本实施例中，处理器根据存储介质中已存储的程序代码执行上述实施例的方法步骤。
显然，本领域的技术人员应该明白，上述的本发明的各模块或各步骤可以用通用的计算装置来实现，它们可以集中在单个的计算装置上，或者分布在多个计算装置所组成的网络上，可选地，它们可以用计算装置可执行的程序代码来实现，从而，可以将它们存储在存储装置中由计算装置来执行，并且在某些情况下，可以以不同于此处的顺序执行所示出或描述的步骤，或者将它们分别制作成各个集成电路模块，或者将它们中的多个模块或步骤制作成单个集成电路模块来实现。这样，本发明不限制于任何特定的硬件和软件结合。
以上所述仅为本发明的优选实施例而已，并不用于限制本发明，对于本领域的技术人员来说，本发明可以有各种更改和变化。凡在本发明的精神和原则之内，所作的任何修改、等同替换、改进等，均应包含在本发明的保护范围之内。
工业实用性
基于本发明实施例提供的上述技术方案，根据配置资产数据的内存字段信息和性能数据的内存字段信息，将资产文件、性能文件读取到内存中生成对应的资产表、性能表，设置该资产数据和该性能数据的关键字段值，根据该关键字段值对该资产表和该性能表进行排序，将已排序的该资产表为主对象进行循环，根据该资产数据的该关键字段值查询该性能表得到该资产数据的性能数据数组，根据配置的性能字段的计算公式整合该资产数据的性能数组内的性能数据，获取该资产数据的整合后的性能字段值赋值该资产性能表，解决了组网的资产数据和性能数据处理过程复杂，耗时时间长的问题，实现了高效处理同种资产数据的多个性能数据文件。

Claims (10)

  1. 一种数据整合处理方法，包括：
    根据配置资产数据的内存字段信息和性能数据的内存字段信息，将资产文件、性能文件读取到内存中生成对应的资产表、性能表；
    设置所述资产数据和所述性能数据的关键字段值，根据所述关键字段值对所述资产表和所述性能表进行排序；
    将已排序的所述资产表为主对象进行循环，根据所述资产数据的所述关键字段值查询所述性能表得到所述资产数据的性能数据数组；
    根据配置的性能字段的计算公式整合所述资产数据的性能数组内的性能数据，获取所述资产数据的整合后的性能字段值赋值所述资产性能表。
  2. 根据权利要求1所述的方法，其中，设置所述资产数据和所述性能数据的关键字段值，根据所述关键字段值对所述资产表和所述性能表进行排序之后，还包括：
    设置所述资产数据的过滤条件，在所述资产数据未满足所述过滤条件的情况下，根据所述资产数据的所述关键字段值查询所述性能表得到所述资产数据的性能数据。
  3. 根据权利要求1所述的方法，其中，所述根据配置的性能字段的计算公式整合所述资产数据的性能数组内的性能数据，获取所述资产数据的整合后的性能字段值赋值所述资产性能表包括：
    在所述资产数据只有一条所述性能数据，对所述资产数据的性能数据赋值所述资产性能表，在所述资产数据有多条性能数据的情况下，根据配置的字段类型、公式对所述性能数据进行计算，将计算后所述资产数据的性能数据赋值所述资产性能表。
  4. 根据权利要求3所述的方法，其中，根据配置的字段类型、公式对所述性能数据进行计算包括：
    根据配置的字段类型、公式，通过迭代的计算方式对所述性能数据进行计算。
  5. 根据权利要求1所述的方法，其中，根据所述资产数据的所述关键字段值查询所述性能表得到所述资产数据的性能数据数组包括：
    获取所述性能表的位置标识，比较所述资产数据的所述关键字段值与所述性能表的所述位置标识的关键字段值，在所述资产数据的所述关键字段值等于所述性能表的所述位置标识的关键字段值情况下，获取所述位置标识的性能数据，添加到所述性能数据数组。
  6. 一种数据整合处理装置，包括：
    生成模块，设置为根据配置资产数据的内存字段信息和性能数据的内存字段信息，将资产文件、性能文件读取到内存中生成对应的资产表、性能表；
    排序模块，设置为设置所述资产数据和所述性能数据的关键字段值，根据所述关键字段值对所述资产表和所述性能表进行排序；
    创建模块，设置为将已排序的所述资产表为主对象进行循环，根据所述资产数据的所述关键字段值查询所述性能表得到所述资产数据的性能数据数组；
    整合模块，设置为根据配置的性能字段的计算公式整合所述资产数据的性能数组内的性能数据，获取所述资产数据的整合后的性能字段值赋值所述资产性能表。
  7. 根据权利要求6所述的装置，其中，所述装置还包括：
    过滤模块，设置为设置所述资产数据的过滤条件，在所述资产数据未满足所述过滤条件的情况下，根据所述资产数据的所述关键字段值查询所述性能表得到所述资产数据的性能数据。
  8. 根据权利要求6所述的装置，其中，所述整合模块包括：
    第一整合单元，设置为在所述资产数据只有一条所述性能数据，对所述资产数据的性能数据赋值所述资产性能表；
    第二整合单元，设置为在所述资产数据有多条性能数据的情况下，根据配置的字段类型、公式对所述性能数据进行计算，将计算后所述资产数据的性能数据赋值所述资产性能表。
  9. 根据权利要求8所述的装置，其中，所述整合模块包括：
    迭代单元，设置为根据配置的字段类型、公式，通过迭代的计算方式对所述性能数据进行计算。
  10. 根据权利要求6所述的装置，其中，所述创建模块包括：
    标识单元，设置为获取所述性能表的位置标识，比较所述资产数据的所述关键字段值与所述性能表的所述位置标识的关键字段值，在所述资产数据的所述关键字段值等于所述性能表的所述位置标识的关键字段值情况下，获取所述位置标识的性能数据，添加到所述性能数据数组。
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