CN117389840A - Database running state monitoring method and device and computer equipment - Google Patents
Database running state monitoring method and device and computer equipment Download PDFInfo
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/3055—Monitoring arrangements for monitoring the status of the computing system or of the computing system component, e.g. monitoring if the computing system is on, off, available, not available
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- G—PHYSICS
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/34—Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation ; Recording or statistical evaluation of user activity, e.g. usability assessment
- G06F11/3409—Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation ; Recording or statistical evaluation of user activity, e.g. usability assessment for performance assessment
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Abstract
The present invention relates to the field of big data technologies, and in particular, to a method, an apparatus, a computer device, a storage medium, and a computer program product for monitoring a database running state. The method comprises the following steps: acquiring operation state data of a target database to be monitored, wherein the operation state data comprises a plurality of operation index parameters related to the operation state of the target database; judging the running state data through a pre-constructed health grade evaluation model to obtain a first judging result, wherein the health grade evaluation model is judged based on a single running index parameter; judging the running state data through a pre-constructed combined index diagnosis model to obtain a second judging result, wherein the combined index diagnosis model is used for judging based on the combination of at least two running index parameters; and determining the running state of the target database according to the first judging result and the second judging result. By adopting the method, the accuracy and the monitoring efficiency of the database state monitoring can be improved.
Description
Technical Field
The present invention relates to the field of big data technologies, and in particular, to a method, an apparatus, a computer device, a storage medium, and a computer program product for monitoring a database running state.
Background
Databases (databases) are sharable collections of data that are stored in a computer for a long period of time, organized, and capable of being presented in a variety of forms. The term "share" refers to the data in the database, which can be accessed simultaneously by a plurality of different users and for different purposes by using a plurality of different languages, and even the same block of data can be accessed simultaneously, while the term "aggregate" refers to the data of various applications and the links (links are also one type of data) between the data in a specific application environment are all stored in a centralized manner according to a certain structural form. A database management system (Database Management System, DBMS) is a large piece of software that manipulates and manages databases, such as building, using, and maintaining databases. The method and the system perform unified management and control on the database so as to ensure the safety and the integrity of the database. The user accesses the data in the database through the DBMS, and the database manager also performs maintenance work of the database through the DBMS.
The table of the relational database uses a two-dimensional table to store data, a logical group of related information arranged in rows and columns, similar to an Excel worksheet. A database may contain any number of data tables. One row in the table is a record. Each column in a data table is called a field, the table is defined by the various fields it contains, each field describes the meaning of the data it contains, and the design of the data table is actually the design of the field. When creating the data table, each field is assigned a data type defining their data length and other attributes.
In the related technology, when the database is frequently in a high concurrency of the platform, the bottleneck of the system is located, so that the problem can be timely identified and found, and the method is more and more important for the stable operation of the platform. Therefore, a certain monitoring program is usually set to monitor the whole running state of the database and identify and early warn abnormal conditions.
However, the existing database monitoring method has the following technical problems:
the existing monitoring program generally collects data, judges between normal and abnormal by means of a threshold value, and the judging process is based on single data and simple logic, so that the monitoring effect is poor.
Disclosure of Invention
In view of the foregoing, it is desirable to provide a database operating state monitoring method, apparatus, computer device, computer-readable storage medium, and computer program product that can improve accuracy and efficiency of monitoring a database state.
In a first aspect, the present application provides a method for monitoring an operating state of a database. The method comprises the following steps:
acquiring operation state data of a target database to be monitored, wherein the operation state data comprises a plurality of operation index parameters related to the operation state of the target database;
judging the running state data through a pre-constructed health grade evaluation model to obtain a first judging result, wherein the health grade evaluation model is judged based on a single running index parameter;
judging the running state data through a pre-constructed combined index diagnosis model to obtain a second judging result, wherein the combined index diagnosis model is used for judging based on the combination of at least two running index parameters;
and determining the running state of the target database according to the first judging result and the second judging result.
In one embodiment, the determining the operation state data by using a pre-built health grade evaluation model, to obtain a first determination result, where before the determining by using the health grade evaluation model based on the single operation index parameter, further includes:
acquiring historical operating state data of a database, wherein the historical operating state data comprises historical operating index parameters and associated historical operating states;
sampling the historical running state data based on a first preset sampling rule, and constructing a first training set;
and constructing the health grade evaluation model based on a decision tree algorithm, and training the health grade evaluation model to be converged by applying the first training set, wherein the health grade evaluation model determines the evaluation grade of the running state of the database based on a single decision result of the running index parameters.
In one embodiment, the determining the operation state data by using a pre-constructed combined index diagnostic model to obtain a second determination result, where before the determining by using the combined index diagnostic model based on the combination of at least two operation index parameters, the method further includes:
sampling the historical running state data based on a second preset sampling rule, and constructing a second training set;
and constructing the combined index diagnostic model based on the decision tree algorithm, training the combined index diagnostic model to be converged by applying the second training set, wherein the combined index diagnostic model determines an operation state set of the database based on a decision result of combination of a plurality of operation index parameters, and the operation state set comprises a plurality of candidate operation states and corresponding confidence parameters.
In one embodiment, the determining the operation state of the target database according to the first discrimination result and the second discrimination result includes:
and respectively weighting the first discrimination result and the second discrimination result to obtain the running state.
In one embodiment, the acquiring the operation state data of the target database to be monitored, where the operation state data includes a plurality of operation index parameters associated with the operation state of the target database, further includes:
performing data preprocessing on the running state data, wherein the data preprocessing comprises data cleaning and data normalization;
acquiring the data specification requirements of the health grade evaluation model and the combined index diagnosis model;
and carrying out format conversion on the running state data based on the data specification requirement so that the running state data after format conversion meets the data specification requirement.
In one embodiment, after determining the operation state of the target database according to the first discrimination result and the second discrimination result, the method further includes:
and filling a preset patrol report template based on a judging result of the running state of the target database, and generating a database patrol report conforming to a preset format.
In a second aspect, the present application further provides a database operation status monitoring device. The device comprises:
the system comprises an operation data acquisition module, a monitoring module and a control module, wherein the operation data acquisition module is used for acquiring operation state data of a target database to be monitored, and the operation state data comprises a plurality of operation index parameters associated with the operation state of the target database;
the health grade evaluation model module is used for judging the running state data through a pre-constructed health grade evaluation model to obtain a first judging result, and the health grade evaluation model is judged based on a single running index parameter;
the combined index diagnosis model module is used for judging the running state data through a pre-constructed combined index diagnosis model to obtain a second judging result, and the combined index diagnosis model is used for judging based on the combination of at least two running index parameters;
and the running state determining module is used for determining the running state of the target database according to the first judging result and the second judging result.
In one embodiment, before the health grade evaluation model module, the method further includes:
the historical operation data module is used for acquiring historical operation state data of the database, wherein the historical operation state data comprises historical operation index parameters and associated historical operation states;
the first training set module is used for sampling the historical running state data based on a first preset sampling rule and constructing a first training set;
the first model training module is used for constructing the health grade evaluation model based on a decision tree algorithm, training the health grade evaluation model to be converged by applying the first training set, and determining the evaluation grade of the running state of the database based on a single decision result of the running index parameter by the health grade evaluation model.
In one embodiment, before the combined index diagnostic model module, the method further includes:
the second training set module is used for sampling the historical running state data based on a second preset sampling rule and constructing a second training set;
and the second model training module is used for constructing the combined index diagnosis model based on the decision tree algorithm, training the combined index diagnosis model to be converged by applying the second training set, and determining an operation state set of the database based on a decision result of combination of a plurality of operation index parameters by the combined index diagnosis model, wherein the operation state set comprises a plurality of candidate operation states and corresponding confidence parameters.
In one embodiment, the operation state determination module includes:
and the weighting processing module is used for respectively carrying out weighting processing on the first judging result and the second judging result to obtain the running state.
In one embodiment, after the operation data acquisition module, the method further includes:
the data preprocessing module is used for carrying out data preprocessing on the running state data, wherein the data preprocessing comprises data cleaning and data normalization;
the data specification module is used for acquiring the data specification requirements of the health grade evaluation model and the combined index diagnosis model;
and the data specification conversion module is used for carrying out format conversion on the running state data based on the data specification requirements so that the running state data after format conversion meets the data specification requirements.
In one embodiment, after the operation state determining module, the method further includes:
and the inspection report generating module is used for filling a preset inspection report template based on the judging result of the running state of the target database to generate a database inspection report conforming to a preset format.
In a third aspect, the present application also provides a computer device. The computer device comprises a memory storing a computer program and a processor implementing the steps of a method for monitoring the operation state of a database according to any one of the embodiments of the first aspect when the processor executes the computer program.
In a fourth aspect, the present application also provides a computer-readable storage medium. The computer readable storage medium has stored thereon a computer program which, when executed by a processor, implements the steps of a method for monitoring the running state of a database according to any one of the embodiments of the first aspect.
In a fifth aspect, the present application also provides a computer program product. The computer program product comprises a computer program which, when executed by a processor, implements the steps of a method for monitoring the running state of a database according to any one of the embodiments of the first aspect.
The database running state monitoring method, the device, the computer equipment, the storage medium and the computer program product can achieve the following beneficial effects corresponding to the technical problems in the background technology through deducing the technical characteristics in the independent right:
in the process of monitoring the running state of the database, firstly, the running state data of a target database to be monitored are acquired, the running state data are respectively input into a health grade evaluation model and a combined index diagnosis model, so that output results of the two models are obtained, wherein the health grade evaluation model obtains results based on the decision of a single running index parameter, and the combined index diagnosis model obtains results based on the decision of the combined running index parameter. And finally, carrying out merging analysis on the output results of the two models to jointly obtain the running state of monitoring the database. In implementation, the analysis results of the operation state data are obtained together to obtain the result of operation state monitoring of the database through the two models, which is helpful for quickly obtaining a preliminary result through decision of single data, and then further judging the operation state of the database through the judgment result of the combination parameters, is helpful for carrying out supplementary judgment and verification on the state of the database through the combination parameters, and is helpful for improving the accuracy of the database monitoring result.
Drawings
FIG. 1 is a diagram of an application environment for a database operating state monitoring method in one embodiment;
FIG. 2 is a schematic diagram of a first process of a method for monitoring an operating state of a database according to one embodiment;
FIG. 3 is a schematic diagram of a second flow chart of a method for monitoring the operation state of a database according to another embodiment;
FIG. 4 is a schematic diagram of a third flow chart of a method for monitoring the operation state of a database according to another embodiment;
FIG. 5 is a fourth flowchart of a method for monitoring an operating state of a database according to another embodiment;
FIG. 6 is a fifth flowchart of a method for monitoring the operation status of a database according to another embodiment;
FIG. 7 is a sixth flowchart of a method for monitoring an operating state of a database according to another embodiment;
FIG. 8 is a block diagram of a database operating condition monitoring device in one embodiment;
fig. 9 is an internal structural diagram of a computer device in one embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be further described in detail with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the present application.
In the related technology, when the database is frequently in a high concurrency of the platform, the bottleneck of the system is located, so that the problem can be timely identified and found, and the method is more and more important for the stable operation of the platform. Therefore, a certain monitoring program is usually set to monitor the whole running state of the database and identify and early warn abnormal conditions.
However, the existing database monitoring method has the following technical problems:
the existing monitoring program generally collects data, judges between normal and abnormal by means of a threshold value, and the judging process is based on single data and simple logic, so that the monitoring effect is poor.
Based on this, the method for monitoring the running state of the database provided in the embodiment of the application can be applied to an application environment as shown in fig. 1. Wherein the terminal 102 communicates with the server 104 via a network. The data storage system may store data that the server 104 needs to process. The data storage system may be integrated on the server 104 or may be located on a cloud or other network server. The terminal 102 may be, but not limited to, various personal computers, notebook computers, smart phones, tablet computers, internet of things devices, and portable wearable devices, where the internet of things devices may be smart speakers, smart televisions, smart air conditioners, smart vehicle devices, and the like. The portable wearable device may be a smart watch, smart bracelet, headset, or the like. The server 104 may be implemented as a stand-alone server or as a server cluster of multiple servers.
In one embodiment, as shown in fig. 2, a method for monitoring the running state of a database is provided, and the method is applied to the server in fig. 1 for illustration, and includes the following steps:
step 202: and acquiring the running state data of the target database to be monitored, wherein the running state data comprises a plurality of running index parameters related to the running state of the target database.
The operation state data may refer to data collected during the operation of the database, which may embody the operation performance of the database, and the operation state data may include a plurality of operation index parameters associated with the operation state of the target database. The operation index parameters may include CPU usage, application CPU duty, memory usage, swap space usage, disk io latency, etc. The operation index parameters may also include system operation index, operation status index, master-slave synchronization index, backup status index, etc.
For example, the server may obtain the operating state data of the target database to be monitored on the premise of obtaining sufficient authorization and permission. In addition, the server may further obtain configuration parameters of the target database, so as to determine basic performances of the target database, for example: maximum connection number, cache pool size, closing query cache, binlog format, log flush, undo independent table space, etc. In addition, based on a complex database architecture, in a scenario associated with multiple databases, the server may also obtain a state index of an active database, a state index of a backup database, and the like of the target database.
Step 204: and judging the running state data through a pre-constructed health grade evaluation model to obtain a first judging result, wherein the health grade evaluation model is judged based on a single running index parameter.
The health grade evaluation model may refer to a neural network model that makes a determination based on a single operation index parameter.
The server may determine the operation state data of the target server through a pre-constructed health level evaluation model, to obtain a first determination result, where the first determination result may be determined based on a single operation index parameter. For example, the server may input the operation state data to the health level evaluation model, determine each operation index parameter by the health level evaluation model, determine and classify the operation state data by means of a threshold value, a section, or the like, and output an overall evaluation result of the database state, where the evaluation result may be classified according to scores, for example, into a health level, a focus level, an alarm level, a severity level, or the like.
Step 206: and judging the running state data through a pre-constructed combined index diagnosis model to obtain a second judging result, wherein the combined index diagnosis model is used for judging based on the combination of at least two running index parameters.
The combined index diagnostic model may refer to a neural network model that determines based on a combination of a plurality of operating index parameters.
The server may determine the operation state data by using a pre-constructed combined index diagnostic model, to obtain a second determination result, where the combined index diagnostic model determines based on a combination of at least two of the operation index parameters. The server may input the operation state data to a combined index diagnostic model, and the combined index diagnostic model may combine the operation index parameters according to the requirements and determine the combined operation index parameters, and when each type of operation index parameter in the combination meets the parameter requirements of a certain result, may determine that the database is in a state indicated by the corresponding result.
Step 208: and determining the running state of the target database according to the first judging result and the second judging result.
For example, after the server obtains the first discrimination result and the second discrimination result, the server may determine the running state of the database according to the first discrimination result and the second discrimination result. For example, when the first discrimination result is the same as the second discrimination result, the final discrimination result is the corresponding result; and when the two states are inconsistent, judging according to the confidence degrees of the two states, and determining the final state.
In the database running state monitoring method, the technical characteristics in the embodiment are combined to carry out reasonable deduction, so that the beneficial effects of solving the technical problems in the background technology can be realized:
in the process of monitoring the running state of the database, firstly, the running state data of a target database to be monitored are acquired, the running state data are respectively input into a health grade evaluation model and a combined index diagnosis model, so that output results of the two models are obtained, wherein the health grade evaluation model obtains results based on the decision of a single running index parameter, and the combined index diagnosis model obtains results based on the decision of the combined running index parameter. And finally, carrying out merging analysis on the output results of the two models to jointly obtain the running state of monitoring the database. In implementation, the analysis results of the operation state data are obtained together to obtain the result of operation state monitoring of the database through the two models, which is helpful for quickly obtaining a preliminary result through decision of single data, and then further judging the operation state of the database through the judgment result of the combination parameters, is helpful for carrying out supplementary judgment and verification on the state of the database through the combination parameters, and is helpful for improving the accuracy of the database monitoring result.
In one embodiment, as shown in FIG. 3, prior to step 204, comprising:
step 302: historical operating state data of a database is obtained, the historical operating state data including historical operating index parameters and associated historical operating states.
Wherein the historical operating state data may include historical operating index parameters and associated historical operating states. The historical operating state may be manually noted by a technician.
For example, the server may obtain historical operating state data for the database.
Step 304: and sampling the historical running state data based on a first preset sampling rule, and constructing a first training set.
For example, the server may sample the historical operating state data based on a first preset sampling rule, and construct a first training set.
Step 306: and constructing the health grade evaluation model based on a decision tree algorithm, and training the health grade evaluation model to be converged by applying the first training set, wherein the health grade evaluation model determines the evaluation grade of the running state of the database based on a single decision result of the running index parameters.
The decision tree algorithm may refer to a machine learning algorithm based on a tree structure, which is used for solving the classification and regression problems. The data is divided to construct a tree-shaped decision flow, so that prediction or decision is performed. The health rating model may determine a rating of the operational status of the database based on a single decision result for the operational index parameter.
For example, the server may construct a health rating model based on a decision tree algorithm and apply a first training set to train the health rating model to converge.
In this embodiment, the construction of the training set through the historical running state data helps to ensure the reliability of the health grade evaluation model, and the health grade evaluation model makes a decision based on a single parameter, which helps to improve the efficiency of monitoring the database.
In one embodiment, as shown in FIG. 4, prior to step 206, it may include
Step 402: and sampling the historical running state data based on a second preset sampling rule, and constructing a second training set.
For example, the server may sample the historical operating state data based on a second preset sampling rule and construct a second training set. The second preset sampling rule may refer to a sampling manner of acquiring a plurality of data combinations.
Step 404: and constructing the combined index diagnostic model based on the decision tree algorithm, training the combined index diagnostic model to be converged by applying the second training set, wherein the combined index diagnostic model determines an operation state set of the database based on a decision result of combination of a plurality of operation index parameters, and the operation state set comprises a plurality of candidate operation states and corresponding confidence parameters.
Wherein a combined index diagnostic model may determine a set of operating conditions of the database based on a combined decision result for a plurality of the operating index parameters. The set of operating states may include a plurality of candidate operating states and corresponding confidence parameters. The confidence parameters may be used to characterize the confidence level of the current result.
For example, the server may construct the combined index diagnostic model based on the decision tree algorithm, and apply the second training set to train the combined index diagnostic model to converge.
In the embodiment, under the support of the combined index diagnosis model, different operation index parameters are mutually verified and supplemented, and finally the effect of improving the accuracy of the model is realized.
In one embodiment, as shown in FIG. 5, step 208 may include:
step 502: determining a database health grade corresponding to the running state according to the first judging result;
step 504: and determining a database abnormality diagnosis result corresponding to the running state according to the second discrimination result.
For example, the server may perform a merging analysis on the first discrimination result and the second discrimination result to obtain the running state of the target server.
In this embodiment, the server may perform a merging analysis on the first discrimination result and the second discrimination result to obtain the running state of the target server.
In one embodiment, as shown in fig. 6, step 202 further includes:
step 602: and carrying out data preprocessing on the running state data, wherein the data preprocessing comprises data cleaning and data normalization.
The data preprocessing can comprise data emotion and normalization, and the data cleaning refers to preprocessing and repairing of original data to remove errors, incompleteness, inconsistency, repeatability and other problems in the data, so that the data is more accurate, reliable and suitable for subsequent analysis and application. The normalization process maps the data of different ranges into a unified standard range to eliminate the dimension difference between the data, so that the comparability between different features is realized.
For example, the server may perform data preprocessing on the operating state data, where the data preprocessing includes data cleansing and data normalization.
Step 604: and acquiring the data specification requirements of the health grade evaluation model and the combined index diagnosis model.
For example, the server may obtain the health rating assessment model and the data specification requirements of the combined indicator diagnostic model.
Step 606: and carrying out format conversion on the running state data based on the data specification requirement so that the running state data after format conversion meets the data specification requirement.
For example, the server may format the operational state data based on the data specification requirements such that the formatted operational state data meets the data specification requirements.
In this embodiment, the stability of processing and analyzing the running state data by the two evaluation models is improved by the processing such as data cleaning, normalization first-order, format conversion and the like.
In one embodiment, as shown in FIG. 7, step 208 includes:
step 702: and filling a preset patrol report template based on a judging result of the running state of the target database, and generating a database patrol report conforming to a preset format.
The preset format may refer to an EXCEL, PDF, or other format that is easy to read.
The server may fill a preset inspection report template based on a discrimination result of the operation state of the target database, and generate a database inspection report conforming to a preset format.
In this embodiment, after the monitoring result is obtained, a patrol report is generated, and the patrol report also accords with a preset scheme of several formats with better reading experience, so that the transmission efficiency of the database monitoring result can be improved.
It should be understood that, although the steps in the flowcharts related to the embodiments described above are sequentially shown as indicated by arrows, these steps are not necessarily sequentially performed in the order indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in the flowcharts described in the above embodiments may include a plurality of steps or a plurality of stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of the steps or stages is not necessarily performed sequentially, but may be performed alternately or alternately with at least some of the other steps or stages.
Based on the same inventive concept, the embodiment of the application also provides a database running state monitoring device for realizing the above related database running state monitoring method. The implementation of the solution provided by the device is similar to the implementation described in the above method, so the specific limitation in one or more embodiments of the database operation state monitoring device provided below may refer to the limitation in the above description about a database operation state monitoring method, which is not repeated herein.
In one embodiment, as shown in fig. 8, there is provided a database operation state monitoring apparatus, including: the system comprises an operation data acquisition module, a health grade evaluation model module, a combined index diagnosis model module and an operation state determination module, wherein:
the system comprises an operation data acquisition module, a monitoring module and a control module, wherein the operation data acquisition module is used for acquiring operation state data of a target database to be monitored, and the operation state data comprises a plurality of operation index parameters associated with the operation state of the target database;
the health grade evaluation model module is used for judging the running state data through a pre-constructed health grade evaluation model to obtain a first judging result, and the health grade evaluation model is judged based on a single running index parameter;
the combined index diagnosis model module is used for judging the running state data through a pre-constructed combined index diagnosis model to obtain a second judging result, and the combined index diagnosis model is used for judging based on the combination of at least two running index parameters;
and the running state determining module is used for determining the running state of the target database according to the first judging result and the second judging result.
In one embodiment, before the health grade evaluation model module, the method further includes:
the historical operation data module is used for acquiring historical operation state data of the database, wherein the historical operation state data comprises historical operation index parameters and associated historical operation states;
the first training set module is used for sampling the historical running state data based on a first preset sampling rule and constructing a first training set;
the first model training module is used for constructing the health grade evaluation model based on a decision tree algorithm, training the health grade evaluation model to be converged by applying the first training set, and determining the evaluation grade of the running state of the database based on a single decision result of the running index parameter by the health grade evaluation model.
In one embodiment, before the combined index diagnostic model module, the method further includes:
the second training set module is used for sampling the historical running state data based on a second preset sampling rule and constructing a second training set;
and the second model training module is used for constructing the combined index diagnosis model based on the decision tree algorithm, training the combined index diagnosis model to be converged by applying the second training set, and determining an operation state set of the database based on a decision result of combination of a plurality of operation index parameters by the combined index diagnosis model, wherein the operation state set comprises a plurality of candidate operation states and corresponding confidence parameters.
In one embodiment, the operation state determination module includes:
and the weighting processing module is used for respectively carrying out weighting processing on the first judging result and the second judging result to obtain the running state.
In one embodiment, after the operation data acquisition module, the method further includes:
the data preprocessing module is used for carrying out data preprocessing on the running state data, wherein the data preprocessing comprises data cleaning and data normalization;
the data specification module is used for acquiring the data specification requirements of the health grade evaluation model and the combined index diagnosis model;
and the data specification conversion module is used for carrying out format conversion on the running state data based on the data specification requirements so that the running state data after format conversion meets the data specification requirements.
In one embodiment, after the operation state determining module, the method further includes:
and the inspection report generating module is used for filling a preset inspection report template based on the judging result of the running state of the target database to generate a database inspection report conforming to a preset format.
Each module in the database running state monitoring device can be fully or partially implemented by software, hardware and a combination thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
In one embodiment, a computer device is provided, which may be a server, and the internal structure of which may be as shown in fig. 9. The computer device includes a processor, a memory, an Input/Output interface (I/O) and a communication interface. The processor, the memory and the input/output interface are connected through a system bus, and the communication interface is connected to the system bus through the input/output interface. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer device is for storing data. The input/output interface of the computer device is used to exchange information between the processor and the external device. The communication interface of the computer device is used for communicating with an external terminal through a network connection. The computer program, when executed by a processor, implements a database operating state monitoring method.
It will be appreciated by those skilled in the art that the structure shown in fig. 9 is merely a block diagram of a portion of the structure associated with the present application and is not limiting of the computer device to which the present application applies, and that a particular computer device may include more or fewer components than shown, or may combine some of the components, or have a different arrangement of components.
In an embodiment, there is also provided a computer device comprising a memory and a processor, the memory having stored therein a computer program, the processor implementing the steps of the method embodiments described above when the computer program is executed.
In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored which, when executed by a processor, carries out the steps of the method embodiments described above.
In an embodiment, a computer program product is provided, comprising a computer program which, when executed by a processor, implements the steps of the method embodiments described above.
It should be noted that, the user information (including, but not limited to, user equipment information, user personal information, etc.) and the data (including, but not limited to, data for analysis, stored data, presented data, etc.) referred to in the present application are information and data authorized by the user or sufficiently authorized by each party, and the collection, use and processing of the related data are required to comply with the related laws and regulations and standards of the related countries and regions.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, database, or other medium used in the various embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, high density embedded nonvolatile Memory, resistive random access Memory (ReRAM), magnetic random access Memory (Magnetoresistive Random Access Memory, MRAM), ferroelectric Memory (Ferroelectric Random Access Memory, FRAM), phase change Memory (Phase Change Memory, PCM), graphene Memory, and the like. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory, and the like. By way of illustration, and not limitation, RAM can be in the form of a variety of forms, such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM), and the like. The databases referred to in the various embodiments provided herein may include at least one of relational databases and non-relational databases. The non-relational database may include, but is not limited to, a blockchain-based distributed database, and the like. The processors referred to in the embodiments provided herein may be general purpose processors, central processing units, graphics processors, digital signal processors, programmable logic units, quantum computing-based data processing logic units, etc., without being limited thereto.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The above examples only represent a few embodiments of the present application, which are described in more detail and are not to be construed as limiting the scope of the present application. It should be noted that it would be apparent to those skilled in the art that various modifications and improvements could be made without departing from the spirit of the present application, which would be within the scope of the present application. Accordingly, the scope of protection of the present application shall be subject to the appended claims.
Claims (10)
1. A method for monitoring the running state of a database, the method comprising:
acquiring operation state data of a target database to be monitored, wherein the operation state data comprises a plurality of operation index parameters related to the operation state of the target database;
judging the running state data through a pre-constructed health grade evaluation model to obtain a first judging result, wherein the health grade evaluation model is judged based on a single running index parameter;
judging the running state data through a pre-constructed combined index diagnosis model to obtain a second judging result, wherein the combined index diagnosis model is used for judging based on the combination of at least two running index parameters;
and determining the running state of the target database according to the first judging result and the second judging result.
2. The method according to claim 1, wherein the determining the operation state data by the pre-constructed health grade evaluation model, to obtain a first determination result, further comprises, before the determining based on the single operation index parameter:
acquiring historical operating state data of a database, wherein the historical operating state data comprises historical operating index parameters and associated historical operating states;
sampling the historical running state data based on a first preset sampling rule, and constructing a first training set;
and constructing the health grade evaluation model based on a decision tree algorithm, and training the health grade evaluation model to be converged by applying the first training set, wherein the health grade evaluation model determines the evaluation grade of the running state of the database based on a single decision result of the running index parameters.
3. The method of claim 1, wherein said determining said operating state data by a pre-constructed combined index diagnostic model yields a second determination result, said combined index diagnostic model further comprising, prior to determining based on a combination of at least two of said operating index parameters:
sampling historical running state data based on a second preset sampling rule, and constructing a second training set;
and constructing the combined index diagnostic model based on a decision tree algorithm, and training the combined index diagnostic model to be converged by applying the second training set, wherein the combined index diagnostic model determines an operation state set of the database based on a decision result of combination of a plurality of operation index parameters, and the operation state set comprises a plurality of candidate operation states and corresponding confidence parameters.
4. The method of claim 1, wherein determining the operational status of the target database based on the first and second discrimination results comprises:
determining a database health grade corresponding to the running state according to the first judging result;
and determining a database abnormality diagnosis result corresponding to the running state according to the second discrimination result.
5. The method according to any one of claims 1 to 4, wherein the acquiring the operation state data of the target database to be monitored, the operation state data including a plurality of operation index parameters associated with the operation state of the target database, further includes:
performing data preprocessing on the running state data, wherein the data preprocessing comprises data cleaning and data normalization;
acquiring the data specification requirements of the health grade evaluation model and the combined index diagnosis model;
and carrying out format conversion on the running state data based on the data specification requirement so that the running state data after format conversion meets the data specification requirement.
6. The method according to claim 1, wherein after determining the operation state of the target database according to the first discrimination result and the second discrimination result, further comprising:
and filling a preset patrol report template based on a judging result of the running state of the target database, and generating a database patrol report conforming to a preset format.
7. A database operating condition monitoring device, the device comprising:
the system comprises an operation data acquisition module, a monitoring module and a control module, wherein the operation data acquisition module is used for acquiring operation state data of a target database to be monitored, and the operation state data comprises a plurality of operation index parameters associated with the operation state of the target database;
the health grade evaluation model module is used for judging the running state data through a pre-constructed health grade evaluation model to obtain a first judging result, and the health grade evaluation model is judged based on a single running index parameter;
the combined index diagnosis model module is used for judging the running state data through a pre-constructed combined index diagnosis model to obtain a second judging result, and the combined index diagnosis model is used for judging based on the combination of at least two running index parameters;
and the running state determining module is used for determining the running state of the target database according to the first judging result and the second judging result.
8. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any of claims 1 to 6 when the computer program is executed.
9. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 6.
10. A computer program product comprising a computer program, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 6.
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| CN202311636724.0A CN117389840A (en) | 2023-12-01 | 2023-12-01 | Database running state monitoring method and device and computer equipment |
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| CN202311636724.0A CN117389840A (en) | 2023-12-01 | 2023-12-01 | Database running state monitoring method and device and computer equipment |
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