A cloud database construction and management method and system for a group company

Abstract

The present invention discloses a construction and management method and system of a cloud database of a group company, relates to the field of data storage, and solves the problem of excessive database performance and low resource utilization due to imperfect construction and management methods of current cloud databases. The present invention comprises step S1: obtaining performance requirement classification data, step S2: creating a group cloud database according to the performance requirement classification data, step S3: establishing a composite index in the group cloud database, and step S4: optimizing the performance of the group cloud database. The present invention determines the performance requirements of the cloud database of the group company, obtains the performance requirement classification data, selects the cloud data instance template according to the requirements, thereby improving the utilization efficiency of database resources and reducing the company's operating costs.

Description

Technical Field

[0001] The present invention belongs to the field of data storage and relates to cloud computing technology, and specifically to a method and system for constructing and managing a cloud database of a group company. Background Art

[0002] Cloud database is a database service provided based on cloud computing platform. It combines traditional database functions with the flexibility and scalability of cloud computing. Users do not need to purchase, install and maintain hardware equipment by themselves. They can use database services through the Internet. Cloud databases usually have the characteristics of high availability, elastic expansion, disaster recovery and security, and can meet the needs of enterprises and individual users of different sizes and needs.

[0003] In the prior art, when building and managing cloud databases, there are the following defects:

[0004] 1. When building a cloud database, there is no effective judgment on database requirements, resulting in excessive database performance and low resource utilization;

[0005] 2. When managing cloud data, database retrieval is performed through a single index, resulting in low data query efficiency;

[0006] To this end, we propose a method and system for building and managing a cloud database for a group company. Summary of the invention

[0007] In view of the deficiencies in the prior art, the purpose of the present invention is to provide a method and system for constructing and managing a cloud database of a group company. The present invention is based on obtaining performance requirement grading data, creating a group cloud database according to the performance requirement grading data, using a high-performance parameter template to create cloud data for a group company that is in a first database performance requirement, and using a common performance template to create cloud data for a group company that is in a second database performance requirement, to obtain a group cloud database, obtain files to be stored, file type data to be stored and timestamps of files to be stored, establish a composite index for the files to be stored according to the file type data to be stored and the timestamps of files to be stored, respectively, obtain the average CPU utilization, average memory utilization and average network traffic of the group cloud database, calculate the database operation monitoring coefficient, obtain database operation status grading data by thresholding the database operation monitoring coefficient, and optimize the performance of the group cloud database according to the database operation status grading data.

[0008] The purpose of the present invention can be achieved through the following technical solutions. A method for building and managing a cloud database of a group company specifically includes the following steps:

[0009] Step S1: Divide the group companies into a first performance demand judgment interval and a second performance demand judgment interval, and perform performance demand judgment on the group companies corresponding to the first performance demand judgment interval and the second performance demand judgment interval, respectively, to obtain performance demand classification data;

[0010] Step S2: Create a group cloud database according to the performance requirement classification data, use a high-performance parameter template to create cloud data for group companies that meet the first database performance requirement, and use a common performance template to create cloud data for group companies that meet the second database performance requirement, to obtain a group cloud database;

[0011] Step S3: obtaining the file to be stored, the type data of the file to be stored and the timestamp of the file to be stored, and establishing a composite index for the file to be stored according to the type data of the file to be stored and the timestamp of the file to be stored respectively;

[0012] Step S4: respectively obtain the average CPU utilization, average memory utilization and average network traffic of the group cloud database, calculate the database operation monitoring coefficient, divide the database operation monitoring coefficient into thresholds, obtain the database operation status classification data, and optimize the performance of the group cloud database according to the database operation status classification data.

[0013] Furthermore, the step S1: judging the performance requirements of the cloud database to obtain performance requirement classification data, specifically includes the following steps:

[0014] Step S11: Group companies that build cloud databases are divided into a first performance requirement judgment interval and a second performance requirement judgment interval, wherein group companies corresponding to the first performance requirement judgment interval have self-built databases, and group companies corresponding to the second performance requirement judgment interval do not have self-built databases;

[0015] Step S111: performing performance requirement judgment on the group company corresponding to the first performance requirement judgment interval;

[0016] Step S112: performing performance requirement judgment on the group company corresponding to the second performance requirement judgment interval;

[0017] Step S12: defining the group companies corresponding to the first database performance requirement interval and the second database performance requirement interval respectively as performance requirement classification data.

[0018] Furthermore, the step S111: performing performance requirement judgment on the first performance requirement judgment interval, specifically comprises the following steps:

[0019] Step S1111: obtaining the storage capacity value of the self-built database, obtaining the concurrent access volume corresponding to the self-built database per second, obtaining the number of operations per second of the self-built database and the amount of data corresponding to each operation;

[0020] Step S1112: Calculate the storage capacity value, concurrent access volume, number of operations per second, and the amount of data corresponding to each operation to obtain a first performance requirement reference coefficient;

[0021] Step S1113: obtaining a first performance requirement reference coefficient threshold, performing numerical comparison between the first performance requirement reference coefficient and the first performance requirement reference coefficient threshold, and obtaining first performance requirement classification data;

[0022] Step S11131: when the first performance requirement reference coefficient is greater than or equal to the first performance requirement reference coefficient threshold, it is determined to be a first database performance requirement interval;

[0023] Step S11132: When the first performance requirement reference coefficient is less than the first performance requirement reference coefficient threshold, it is determined to be the second database performance requirement interval.

[0024] Furthermore, the step S111: performing performance requirement judgment on the second performance requirement judgment interval, specifically comprises the following steps:

[0025] Step S1121: Obtain the company's monthly business volume, the number of company employees, and the amount of single business data;

[0026] Step S1122: Calculate the company's monthly business volume, the number of company employees, and the amount of single business data to obtain a second performance requirement reference coefficient;

[0027] Step S1123: obtaining a second performance requirement reference coefficient threshold, performing numerical comparison between the second performance requirement reference coefficient and the second performance requirement reference coefficient threshold, and obtaining second performance requirement classification data;

[0028] Step S11231: when the second performance requirement reference coefficient is greater than or equal to the second performance requirement reference coefficient threshold, it is determined to be the first database performance requirement interval;

[0029] Step S11232: When the second performance requirement reference coefficient is less than the second performance requirement reference coefficient threshold, it is determined to be the second database performance requirement interval.

[0030] Furthermore, the step S2: creating a group cloud database according to the performance requirement classification data, the specific steps are as follows:

[0031] Step S21: Select the cloud database RDS service through the cloud service provider's console, select to create an instance through the cloud database RDS management console, and select an instance parameter template;

[0032] Step S211: for the first database performance requirement interval, the instance parameter template selected is a high-performance parameter template;

[0033] Step S212: for the second database performance requirement interval, the instance parameter template selected is a common performance template;

[0034] Step S22: configuring the cloud database instance according to the cloud database installation wizard, where the configuration content includes basic information of the instance, performance specifications, network security, and backup strategy;

[0035] Step S23: Use the data transfer service DTS to migrate and import data, and update the database connection information in the application configuration file to the cloud database information;

[0036] Step S24: define the created cloud database as a group cloud database.

[0037] Furthermore, the step S3: establishing a composite index in the group cloud database, the specific steps are as follows:

[0038] Step S31: Obtaining data to be stored from a database;

[0039] Step S32: using a file manager to classify the data to be stored into file types, and obtaining data of the file types to be stored;

[0040] Step S33: Obtain the timestamp corresponding to the stored file type data through the file extension name to obtain the timestamp of the file to be stored;

[0041] Step S34: creating a table in the group cloud database to store the file type data and the timestamp of the file to be stored;

[0042] Step S35: Create a composite index in the group cloud database based on the file type data to be stored and the file timestamp to be stored.

[0043] Furthermore, the step S4: monitoring the operation of the group cloud database, specifically includes the following steps:

[0044] Step S41: select m time points when the group cloud data is running as characteristic time points, and obtain the CPU utilization, memory utilization and network traffic at the characteristic time points through the cloud database monitoring tool;

[0045] Step S42: Calculate the average values ​​of the CPU utilization, memory utilization and network traffic at the characteristic time points respectively to obtain the average CPU utilization, average memory utilization and average network traffic;

[0046] Step S43: Calculate the average CPU utilization, the average memory utilization and the average network traffic to obtain a database operation monitoring coefficient;

[0047] Step S44: obtaining a first database operation monitoring coefficient threshold and a second database operation monitoring coefficient threshold, comparing the database operation monitoring coefficient with the first database operation monitoring coefficient threshold and the second database operation monitoring coefficient threshold to obtain database operation status classification data;

[0048] Step S45: Optimize the performance of the group cloud database according to the database operation status classification data.

[0049] Furthermore, the step S44: obtaining database operation status classification data, specifically includes the following steps:

[0050] Step S441: when the database operation monitoring coefficient is less than or equal to the first database operation monitoring coefficient threshold, it is determined that the database is in the first operation state interval;

[0051] Step S442: when the database operation monitoring coefficient is greater than the first database operation monitoring coefficient threshold and less than the second database operation monitoring coefficient threshold, it is determined that the database is in the second operation state interval;

[0052] Step S443: When the database operation monitoring coefficient is greater than or equal to the second database operation monitoring coefficient threshold, it is determined that the database is in the third operation state interval.

[0053] Furthermore, the step S45: optimizing the performance of the group cloud database, specifically includes the following steps:

[0054] Step S451: for the first operation state interval, a low-cost storage solution is implemented by reducing the CPU and memory performance specifications of the cloud database instance;

[0055] Step S452: Optimizing database index and query for the second operation state interval to improve performance and response speed;

[0056] Step S453: For the third operation state interval, the specifications and capacity of the database instance are automatically increased through load balancing technology to achieve read-write separation and improve the performance of the cloud database.

[0057] Furthermore, the management system includes a demand classification module, a database creation module, an index establishment module, an operation monitoring module and a server, as follows:

[0058] Demand grading module: divides the group companies into the first performance demand judgment interval and the second performance demand judgment interval, performs performance demand judgment on the group companies corresponding to the first performance demand judgment interval and the second performance demand judgment interval, and obtains performance demand grading data;

[0059] Database creation module: Create a group cloud database according to the performance requirement classification data, use the high-performance parameter template to create cloud data for the group companies that meet the first database performance requirement, and use the common performance template to create cloud data for the group companies that meet the second database performance requirement, and obtain the group cloud database;

[0060] Index building module: obtains the file to be stored, the file type data to be stored and the timestamp of the file to be stored, and builds a composite index for the file to be stored according to the file type data to be stored and the timestamp of the file to be stored;

[0061] Operation monitoring module: The average CPU utilization, average memory utilization and average network traffic of the group cloud database are obtained respectively, and the database operation monitoring coefficient is calculated. By dividing the database operation monitoring coefficient by threshold, the database operation status classification data is obtained, and the performance of the group cloud database is optimized according to the database operation status classification data.

[0062] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0063] 1. The present invention divides the group companies into a first performance demand judgment interval and a second performance demand judgment interval, respectively performs performance demand judgment on the group companies corresponding to the first performance demand judgment interval and the second performance demand judgment interval, obtains performance demand classification data, selects a cloud data instance template according to the demand, improves the utilization efficiency of database resources, and reduces the company's operating costs;

[0064] 2. The present invention establishes a composite index for the files to be stored according to the file type data to be stored and the timestamp of the files to be stored, which can effectively increase the data retrieval speed and improve the query efficiency of data resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] In order to facilitate understanding by those skilled in the art, the present invention is further described below with reference to the accompanying drawings.

[0066] Figure 1 It is a diagram of the implementation steps of the present invention;

[0067] Figure 2 It is the overall framework diagram of the present invention;

[0068] Figure 3 A schematic diagram of selecting a cloud database instance template in the present invention. DETAILED DESCRIPTION

[0069] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0070] Embodiment 1

[0071] See also Figure 1 and Figure 2 , the present invention provides a technical solution: a cloud database construction and management system of a group company, including a demand classification module, a database creation module, an index establishment module and an operation monitoring module, wherein the demand classification module, the database creation module, the index establishment module and the operation monitoring module are respectively connected to a server;

[0072] Also includes a database, the data stored in the database includes the data to be stored;

[0073] It should be noted here that the data to be stored is

[0074] It should be noted here that the original database involved here is the original self-built database of the group company;

[0075] The demand classification module determines the performance requirements of the cloud database and obtains performance requirement classification data;

[0076] The group companies building the cloud database are divided into the first performance demand judgment interval and the second performance demand judgment interval;

[0077] Among them, the group companies corresponding to the first performance requirement judgment interval have self-built databases, and the group companies corresponding to the second performance requirement judgment interval do not have self-built databases;

[0078] The performance requirement judgment is performed on the group companies corresponding to the first performance requirement judgment interval, as follows:

[0079] Get the storage capacity value of the self-built database, get the concurrent access volume of the self-built database per second, get the number of operations per second of the self-built database and the amount of data corresponding to each operation;

[0080] It should be noted here that: in this embodiment, the concurrent access volume, number of operations per second and the amount of data corresponding to each operation obtained are the average values ​​of the relevant data counted by the database monitoring tool;

[0081] The storage capacity value, concurrent access volume, number of operations per second and the amount of data corresponding to each operation are calculated using the first performance requirement reference coefficient calculation formula to obtain a first performance requirement reference coefficient;

[0082] The specific configuration of the calculation formula for the first performance requirement reference coefficient is:

[0083] Xn1=Rl+Fw*a1+Cs*Sl;

[0084] Wherein, Xn1 is the first performance requirement reference coefficient, Rl is the storage capacity value, Fw is the concurrent access volume, Cs is the number of operations per second, Sl is the amount of data corresponding to each operation, a1 is the set proportional coefficient and a1 is greater than 0;

[0085] Obtaining a first performance requirement reference coefficient threshold, comparing the first performance requirement reference coefficient with the first performance requirement reference coefficient threshold, and obtaining first performance requirement classification data;

[0086] The threshold value of the first performance requirement reference coefficient is judged as follows:

[0087] When the first performance requirement reference coefficient is greater than or equal to the first performance requirement reference coefficient threshold, it is determined to be a first database performance requirement interval;

[0088] When the first performance requirement reference coefficient is less than the first performance requirement reference coefficient threshold, it is determined to be in the second database performance requirement range;

[0089] The performance requirement judgment is performed on the group companies corresponding to the second performance requirement judgment interval, as follows:

[0090] Obtain the company's monthly business volume, number of company employees, and single business data volume;

[0091] It should be noted here that the single business storage involved here refers to the average storage data volume required for a single business or a single transaction of the group company;

[0092] The company's monthly business volume, the number of company employees, and the amount of single business data are calculated using the second performance requirement reference coefficient calculation formula to obtain the second performance requirement reference coefficient;

[0093] The specific configuration of the calculation formula of the second performance requirement reference coefficient is: Xn2 = Yw*Cc*a2*lnYg;

[0094] Among them, Xn2 is the second performance requirement reference coefficient, Yw is the amount of single business data, Cc is the company's monthly business volume, Yg is the number of company employees, a2 is the set proportional coefficient and a2 is greater than 0;

[0095] Obtaining a second performance requirement reference coefficient threshold, comparing the second performance requirement reference coefficient with the second performance requirement reference coefficient threshold, and obtaining second performance requirement classification data;

[0096] The threshold value of the second performance requirement reference coefficient is determined as follows:

[0097] When the second performance requirement reference coefficient is greater than or equal to the second performance requirement reference coefficient threshold, it is determined to be the first database performance requirement interval;

[0098] When the second performance requirement reference coefficient is less than the second performance requirement reference coefficient threshold, it is determined to be a second database performance requirement interval;

[0099] It should be noted here that:

[0100] The first performance requirement reference coefficient threshold and the second performance requirement reference coefficient threshold involved here are both set according to cloud database related parameters;

[0101] The database performance requirement corresponding to the first database performance requirement interval is higher than the database performance requirement corresponding to the second database performance requirement interval;

[0102] The group companies corresponding to the first database performance requirement interval and the second database performance requirement interval are defined as performance requirement classification data;

[0103] The database creation module creates the group cloud database according to the performance requirements and classified data, as follows:

[0104] Select the cloud database RDS service through the cloud service provider's console, choose to create an instance through the cloud database RDS management console, and select the instance parameter template;

[0105] Configure the cloud database instance according to the cloud database installation wizard. The configuration content includes basic information of the instance, performance specifications, network security, and backup strategy.

[0106] Use the Data Transfer Service (DTS) to migrate and import data, and update the database connection information in the application configuration file to the cloud database information.

[0107] Define the created cloud database as the group cloud database;

[0108] See also Figure 3 , in the process of creating an instance, the specific parameter template selection is as follows:

[0109] For the first database performance requirement range, the instance parameter template selected is a high-performance parameter template;

[0110] For the performance requirement range of the second database, the instance parameter template selected is the common performance template;

[0111] It should be noted here that:

[0112] In the specific implementation, the high-performance template is specifically defined as MySQL_InnoDB_8.0_Standard Edition_High-Performance Parameter Template, and the ordinary performance template is specifically defined as MySQL_InnoDB_8.0_Standard Edition_Default Parameter Template;

[0113] In this embodiment, the selected cloud service provider is Alibaba Cloud, and the cloud database RDS service, cloud database installation wizard, and data transmission service DTS are all built-in services of Alibaba Cloud;

[0114] The index building module builds a composite index in the group cloud database;

[0115] Obtain the data to be stored according to the database;

[0116] Use a file manager to classify the file types of the data to be stored, and obtain the file type data to be stored;

[0117] The specific types include BLOB type, CLOB type, TEXT type, Image type, XML type and JSON type;

[0118] Obtain the timestamp corresponding to the stored file type data through the file extension name to obtain the timestamp of the file to be stored;

[0119] Create a table in the group cloud database to store the file type data and the timestamp of the file to be stored;

[0120] The specific code implementation is as follows:

[0121]

[0122] In the group cloud database, a composite index is established based on the file type data and the timestamp of the file to be stored;

[0123] The specific code implementation is as follows:

[0124] CREATE INDEX file_type_creation_time_index ON FileIndex(file_type,creation_time);

[0125] The operation monitoring module monitors the operation of the group cloud database;

[0126] Select m time points when the group cloud data is running as characteristic time points, and use the cloud database monitoring tool to obtain the CPU utilization, memory utilization, and network traffic at the characteristic time points;

[0127] The average values ​​of CPU utilization, memory utilization, and network traffic at characteristic time points are calculated to obtain the average CPU utilization, average memory utilization, and average network traffic.

[0128] It should be noted here that the cloud database monitoring tool involved here is the built-in monitoring tool of cloud data, which is specifically limited to CloudMonitor.

[0129] The average CPU utilization, average memory utilization and average network traffic are calculated using the database operation monitoring coefficient formula to obtain the database operation monitoring coefficient;

[0130] The specific configuration of the database operation monitoring coefficient formula is:

[0131] Among them, Sj is the database operation monitoring coefficient, Cy is the average CPU utilization, Nc is the average memory utilization, Wl is the average network traffic, a3 is the set proportional coefficient and a3 is greater than 0;

[0132] Obtaining a first database operation monitoring coefficient threshold and a second database operation monitoring coefficient threshold, performing numerical comparison between the database operation monitoring coefficient and the first database operation monitoring coefficient threshold and the second database operation monitoring coefficient threshold, and obtaining database operation status classification data;

[0133] It should be noted here that: the first database operation monitoring coefficient threshold and the second database operation monitoring coefficient threshold are both set according to the cloud database operation status, wherein the first database operation monitoring coefficient threshold is less than the second database operation monitoring coefficient threshold, and the first database operation monitoring coefficient threshold and the second database operation monitoring coefficient threshold are both greater than 0;

[0134] The threshold value of the database monitoring operation coefficient is judged as follows:

[0135] When the database operation monitoring coefficient is less than or equal to the first database operation monitoring coefficient threshold, it is determined that the database is in the first operation state interval;

[0136] When the database operation monitoring coefficient is greater than the first database operation monitoring coefficient threshold and less than the second database operation monitoring coefficient threshold, it is determined that the database is in the second operation state interval;

[0137] When the database operation monitoring coefficient is greater than or equal to the second database operation monitoring coefficient threshold, it is determined that the database is in a third operation state interval;

[0138] The operation load of the database corresponding to the third operation state interval is greater than that of the database corresponding to the second operation state interval, and the operation load of the database corresponding to the second operation state interval is greater than that of the database corresponding to the first operation state interval;

[0139] The performance of the group cloud database is optimized according to the database operation status classification data, as follows:

[0140] For the first operation state interval, a low-cost storage solution is implemented by reducing the CPU and memory performance specifications of the cloud database instance;

[0141] For the second operation state interval, optimize database index and query to improve performance and response speed;

[0142] For the third operating status range, load balancing technology is used to automatically increase the specifications and capacity of the database instance, achieve read-write separation, and improve the performance of the cloud database.

[0143] In this application, if corresponding calculation formulas appear, the above calculation formulas are all dimensionless and take their numerical calculations. The weight coefficients, proportional coefficients and other coefficients in the formulas are set to a result value obtained by quantifying each parameter. The size of the weight coefficient and the proportional coefficient can be determined as long as it does not affect the proportional relationship between the parameter and the result value.

[0144] Embodiment 2

[0145] Based on another concept of the same invention, a method for building and managing a cloud database of a group company is now proposed, comprising the following steps:

[0146] Step S1: determine the performance requirements of the cloud database and obtain performance requirement classification data;

[0147] Step S11: Group companies that build cloud databases are divided into a first performance requirement judgment interval and a second performance requirement judgment interval, wherein group companies corresponding to the first performance requirement judgment interval have self-built databases, and group companies corresponding to the second performance requirement judgment interval do not have self-built databases;

[0148] Step S111: Perform performance requirement judgment on the group company corresponding to the first performance requirement judgment interval, as follows:

[0149] Step S1111: obtaining the storage capacity value of the self-built database, obtaining the concurrent access volume corresponding to the self-built database per second, obtaining the number of operations per second of the self-built database and the amount of data corresponding to each operation;

[0150] Step S1112: Calculate the storage capacity value, concurrent access volume, number of operations per second, and the amount of data corresponding to each operation to obtain a first performance requirement reference coefficient;

[0151] Step S1113: obtaining a first performance requirement reference coefficient threshold, performing numerical comparison between the first performance requirement reference coefficient and the first performance requirement reference coefficient threshold, and obtaining first performance requirement classification data;

[0152] Step S11131: when the first performance requirement reference coefficient is greater than or equal to the first performance requirement reference coefficient threshold, it is determined to be a first database performance requirement interval;

[0153] Step S11132: when the first performance requirement reference coefficient is less than the first performance requirement reference coefficient threshold, it is determined to be in the second database performance requirement range;

[0154] Step S112: Perform performance requirement judgment on the group company corresponding to the second performance requirement judgment interval, as follows:

[0155] Step S1121: Obtain the company's monthly business volume, the number of company employees, and the amount of single business data;

[0156] Step S1122: Calculate the company's monthly business volume, the number of company employees, and the amount of single business data to obtain a second performance requirement reference coefficient;

[0157] Step S1123: obtaining a second performance requirement reference coefficient threshold, performing numerical comparison between the second performance requirement reference coefficient and the second performance requirement reference coefficient threshold, and obtaining second performance requirement classification data;

[0158] Step S11231: when the second performance requirement reference coefficient is greater than or equal to the second performance requirement reference coefficient threshold, it is determined to be the first database performance requirement interval;

[0159] Step S11232: when the second performance requirement reference coefficient is less than the second performance requirement reference coefficient threshold, it is determined to be a second database performance requirement interval;

[0160] Step S12: defining the group companies corresponding to the first database performance requirement interval and the second database performance requirement interval respectively as performance requirement classification data;

[0161] Step S2: Create a group cloud database based on performance requirement classification data, as follows:

[0162] Step S21: Select the cloud database RDS service through the cloud service provider's console, select to create an instance through the cloud database RDS management console, and select an instance parameter template;

[0163] Step S211: for the first database performance requirement interval, the instance parameter template selected is a high-performance parameter template;

[0164] Step S212: for the second database performance requirement interval, the instance parameter template selected is a common performance template;

[0165] Step S22: configuring the cloud database instance according to the cloud database installation wizard, where the configuration content includes basic information of the instance, performance specifications, network security, and backup strategy;

[0166] Step S23: Use the data transfer service DTS to migrate and import data, and update the database connection information in the application configuration file to the cloud database information;

[0167] Step S24: defining the created cloud database as a group cloud database;

[0168] Step S3: Create a composite index in the group cloud database;

[0169] Step S31: Obtaining data to be stored from a database;

[0170] Step S32: using a file manager to classify the data to be stored into file types, and obtaining data of the file types to be stored;

[0171] Step S33: Obtain the timestamp corresponding to the stored file type data through the file extension name to obtain the timestamp of the file to be stored;

[0172] Step S34: creating a table in the group cloud database to store the file type data and the timestamp of the file to be stored;

[0173] Step S35: creating a composite index in the group cloud database according to the type data of the file to be stored and the timestamp of the file to be stored;

[0174] Step S4: monitor the operation of the group cloud database;

[0175] Step S41: select m time points when the group cloud data is running as characteristic time points, and obtain the CPU utilization, memory utilization and network traffic at the characteristic time points through the cloud database monitoring tool;

[0176] Step S42: Calculate the average values ​​of the CPU utilization, memory utilization and network traffic at the characteristic time points respectively to obtain the average CPU utilization, average memory utilization and average network traffic;

[0177] Step S43: Calculate the average CPU utilization, the average memory utilization and the average network traffic to obtain a database operation monitoring coefficient;

[0178] Step S44: obtaining a first database operation monitoring coefficient threshold and a second database operation monitoring coefficient threshold, comparing the database operation monitoring coefficient with the first database operation monitoring coefficient threshold and the second database operation monitoring coefficient threshold to obtain database operation status classification data;

[0179] Step S441: when the database operation monitoring coefficient is less than or equal to the first database operation monitoring coefficient threshold, it is determined that the database is in the first operation state interval;

[0180] Step S442: when the database operation monitoring coefficient is greater than the first database operation monitoring coefficient threshold and less than the second database operation monitoring coefficient threshold, it is determined that the database is in the second operation state interval;

[0181] Step S443: when the database operation monitoring coefficient is greater than or equal to the second database operation monitoring coefficient threshold, it is determined that the database is in the third operation state interval;

[0182] Step S45: Optimize the performance of the group cloud database according to the database operation status classification data, as follows:

[0183] Step S451: for the first operation state interval, a low-cost storage solution is implemented by reducing the CPU and memory performance specifications of the cloud database instance;

[0184] Step S452: Optimizing database index and query for the second operation state interval to improve performance and response speed;

[0185] Step S453: For the third operation state interval, the specifications and capacity of the database instance are automatically increased through load balancing technology to achieve read-write separation and improve the performance of the cloud database.

[0186] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A method for building and managing a cloud database of a group company, characterized in that: include: Step S1: Divide the group companies into a first performance demand judgment interval and a second performance demand judgment interval, perform performance demand judgment on the group companies corresponding to the first performance demand judgment interval and the second performance demand judgment interval, and obtain performance demand classification data; Step S2: Create a group cloud database according to the performance requirement classification data, use a high-performance parameter template to create cloud data for group companies that meet the first database performance requirement, and use a common performance template to create cloud data for group companies that meet the second database performance requirement, to obtain a group cloud database; Step S3: obtaining the file to be stored, the type data of the file to be stored and the timestamp of the file to be stored, and establishing a composite index for the file to be stored according to the type data of the file to be stored and the timestamp of the file to be stored respectively; Step S4: respectively obtain the average CPU utilization, average memory utilization and average network traffic of the group cloud database, calculate the database operation monitoring coefficient, divide the database operation monitoring coefficient into thresholds, obtain database operation status classification data, and optimize the performance of the group cloud database according to the database operation status classification data; The step S1: judging the performance requirements of the cloud database to obtain performance requirement classification data, the specific steps are as follows: Step S11: Group companies that build cloud databases are divided into a first performance requirement judgment interval and a second performance requirement judgment interval, wherein group companies corresponding to the first performance requirement judgment interval have self-built databases, and group companies corresponding to the second performance requirement judgment interval do not have self-built databases; Step S111: performing performance requirement judgment on the group company corresponding to the first performance requirement judgment interval; Step S112: performing performance requirement judgment on the group company corresponding to the second performance requirement judgment interval; Step S12: defining the group companies corresponding to the first database performance requirement interval and the second database performance requirement interval respectively as performance requirement classification data; The step S111: performing performance requirement judgment on the first performance requirement judgment interval, the specific steps are as follows: Step S1111: obtaining the storage capacity value of the self-built database, obtaining the concurrent access volume corresponding to the self-built database per second, obtaining the number of operations per second of the self-built database and the amount of data corresponding to each operation; Step S1112: The storage capacity value, the concurrent access volume, the number of operations per second, and the amount of data corresponding to each operation are calculated to obtain a first performance requirement reference coefficient; the storage capacity value, the concurrent access volume, the number of operations per second, and the amount of data corresponding to each operation are calculated using the first performance requirement reference coefficient calculation formula to obtain a first performance requirement reference coefficient; The specific configuration of the calculation formula for the first performance requirement reference coefficient is: ； Wherein, Xn1 is the first performance requirement reference coefficient, Rl is the storage capacity value, Fw is the concurrent access volume, Cs is the number of operations per second, Sl is the amount of data corresponding to each operation, a1 is the set proportional coefficient and a1 is greater than 0; Step S1113: obtaining a first performance requirement reference coefficient threshold, performing numerical comparison between the first performance requirement reference coefficient and the first performance requirement reference coefficient threshold, and obtaining first performance requirement classification data; Step S11131: when the first performance requirement reference coefficient is greater than or equal to the first performance requirement reference coefficient threshold, it is determined to be a first database performance requirement interval; Step S11132: when the first performance requirement reference coefficient is less than the first performance requirement reference coefficient threshold, it is determined to be in the second database performance requirement range; The step S112: performing performance requirement judgment on the second performance requirement judgment interval, the specific steps are as follows: Step S1121: Obtain the company's monthly business volume, the number of company employees, and the amount of single business data; Step S1122: Calculate the company's monthly business volume, the number of company employees, and the amount of single business data to obtain a second performance requirement reference coefficient; The specific configuration of the calculation formula for the second performance requirement reference coefficient is: ; Among them, Xn2 is the second performance requirement reference coefficient, Yw is the amount of single business data, Cc is the company's monthly business volume, Yg is the number of company employees, a2 is the set proportional coefficient and a2 is greater than 0; Step S1123: obtaining a second performance requirement reference coefficient threshold, performing numerical comparison between the second performance requirement reference coefficient and the second performance requirement reference coefficient threshold, and obtaining second performance requirement classification data; Step S11231: when the second performance requirement reference coefficient is greater than or equal to the second performance requirement reference coefficient threshold, it is determined to be the first database performance requirement interval; Step S11232: When the second performance requirement reference coefficient is less than the second performance requirement reference coefficient threshold, it is determined to be the second database performance requirement interval.

2. The method for building and managing a cloud database of a group company according to claim 1, characterized in that: The step S2: creating a group cloud database according to the performance requirement classification data, the specific steps are as follows: Step S21: Select the cloud database RDS service through the cloud service provider's console, select to create an instance through the cloud database RDS management console, and select an instance parameter template; Step S211: for the first database performance requirement interval, the instance parameter template selected is a high-performance parameter template; Step S212: for the second database performance requirement interval, the instance parameter template selected is a common performance template; Step S22: configuring the cloud database instance according to the cloud database installation wizard, where the configuration content includes basic information of the instance, performance specifications, network security, and backup strategy; Step S23: Use the data transfer service DTS to migrate and import data, and update the database connection information in the application configuration file to the cloud database information; Step S24: define the created cloud database as a group cloud database.

3. The method for building and managing a cloud database of a group company according to claim 1, characterized in that: The step S3: establishing a composite index in the group cloud database, the specific steps are as follows: Step S31: Obtaining data to be stored from a database; Step S32: using a file manager to classify the data to be stored into file types, and obtaining data of the file types to be stored; Step S33: Obtain the timestamp corresponding to the stored file type data through the file extension name to obtain the timestamp of the file to be stored; Step S34: creating a table in the group cloud database to store the file type data and the timestamp of the file to be stored; Step S35: Create a composite index in the group cloud database based on the file type data to be stored and the file timestamp to be stored.

4. The method for building and managing a cloud database of a group company according to claim 1, characterized in that: The step S4: monitoring the operation of the group cloud database, the specific steps are as follows: Step S41: select m time points when the group cloud data is running as characteristic time points, and obtain the CPU utilization, memory utilization and network traffic at the characteristic time points through the cloud database monitoring tool; Step S42: Calculate the average values ​​of the CPU utilization, memory utilization and network traffic at the characteristic time points respectively to obtain the average CPU utilization, average memory utilization and average network traffic; Step S43: Calculate the average CPU utilization, the average memory utilization and the average network traffic to obtain a database operation monitoring coefficient; Step S44: obtaining a first database operation monitoring coefficient threshold and a second database operation monitoring coefficient threshold, comparing the database operation monitoring coefficient with the first database operation monitoring coefficient threshold and the second database operation monitoring coefficient threshold to obtain database operation status classification data; Step S45: Optimize the performance of the group cloud database according to the database operation status classification data.

5. The method for building and managing a cloud database of a group company according to claim 4, characterized in that: The step S44: obtaining database operation status classification data, the specific steps are as follows: Step S441: when the database operation monitoring coefficient is less than or equal to the first database operation monitoring coefficient threshold, it is determined that the database is in the first operation state interval; Step S442: when the database operation monitoring coefficient is greater than the first database operation monitoring coefficient threshold and less than the second database operation monitoring coefficient threshold, it is determined that the database is in the second operation state interval; Step S443: When the database operation monitoring coefficient is greater than or equal to the second database operation monitoring coefficient threshold, it is determined that the database is in the third operation state interval.

6. The method for building and managing a cloud database of a group company according to claim 5, characterized in that: The step S45: optimizing the performance of the group cloud database, the specific steps are as follows: Step S451: for the first operation state interval, a low-cost storage solution is implemented by reducing the CPU and memory performance specifications of the cloud database instance; Step S452: Optimizing database index and query for the second operation state interval to improve performance and response speed; Step S453: For the third operation state interval, the specifications and capacity of the database instance are automatically increased through load balancing technology to achieve read-write separation and improve the performance of the cloud database.

7. A cloud database construction and management system for a group company, applicable to a cloud database construction and management method for a group company as claimed in any one of claims 1 to 6, characterized in that: The management system includes a demand classification module, a database creation module, an index establishment module, an operation monitoring module and a server, as follows: Demand grading module: obtain performance demand grading data; Database creation module: Create a group cloud database based on performance requirements and hierarchical data; Index creation module: Create composite indexes in the group cloud database; Operation monitoring module: optimize the performance of the group cloud database.

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