A method, device and medium for running analysis of an Oracle database

Abstract

The embodiments of this specification disclose a method, device, and medium for running analysis of an Oracle database, relating to the technical field of database analysis, and are used to solve the problem that existing evaluations cannot comprehensively reflect the actual situation of the database during operation. The method includes: connecting to the Oracle database to be evaluated based on a preset protocol to collect and obtain the metadata and log files of the Oracle database to be evaluated; preprocessing the metadata and the log files to obtain processed data, and storing the processed data in partitions based on a preset time interval and log type; performing real-time stream processing on the processed data based on the bottleneck query identifiers corresponding to each partition to obtain the real-time stream data of the Oracle database to be evaluated; according to the analysis items triggered by the Oracle database to be evaluated, calling the real-time stream data corresponding to the analysis items, and determining the analysis results of the Oracle database to be evaluated based on the real-time stream data and the analysis process corresponding to the analysis items.

Description

Technical Field

[0001] This specification relates to the technical field of database evaluation, and particularly to a method, device, and medium for running analysis of an Oracle database. Background Art

[0002] The database is the core of enterprise data management. Its performance directly affects the response speed of the business system and the user experience, and its stability is also directly related to the business continuity of the enterprise. Therefore, the evaluation of the database is an important link to ensure the efficient operation of the database.

[0003] Current evaluation methods for databases often focus on collecting basic metadata of the database, such as the definitions (DDL), status, memory, and dependencies between objects of database objects. However, these pieces of information are only one-sided reflections of the database's operating conditions and lack the collection of real-time information such as log files, error logs, and audit logs. Such log files, such as audit logs and slow query logs, record the detailed operations and events during the operation of the database and contain rich runtime information, which is crucial for comprehensively evaluating the performance, security, and reliability of the database. However, due to the characteristics of log files, such as large data volume, complex format, and fast generation speed, traditional methods that rely on manual experience for query evaluation are difficult to effectively collect and process this information, resulting in information missing in the evaluation results and being unable to fully reflect the actual conditions of the database during operation. Summary of the Invention

[0004] To solve the above technical problems, one or more embodiments of this specification provide a method, device, and medium for running analysis of an Oracle database.

[0005] One or more embodiments of this specification adopt the following technical solutions:

[0006] One or more embodiments of this specification provide a method for running analysis of an Oracle database. The method includes:

[0007] Connect to the Oracle database to be evaluated based on a preset protocol to collect and obtain the metadata and log files of the Oracle database to be evaluated;

[0008] Preprocess the metadata and the log files to obtain processed data, and partition and store the processed data based on a preset time interval and log type;

[0009] Perform real-time stream processing on the processed data based on the bottleneck query identifiers corresponding to each partition to obtain the real-time stream data of the Oracle database to be evaluated;

[0010] Based on the analysis items triggered by the Oracle database to be evaluated, call the real-time stream data corresponding to the analysis items, and determine the analysis result of the Oracle database to be evaluated based on the real-time stream data and the analysis process corresponding to the analysis items.

[0011] Optionally, in one or more embodiments of this specification, connect to the Oracle database to be evaluated based on a preset protocol to collect and obtain the metadata and log files of the Oracle database to be evaluated, specifically including:

[0012] Add the driver dependencies corresponding to the preset protocol to the specified project file corresponding to the Oracle database to be evaluated, so as to connect to the Oracle database to be evaluated based on the preset protocol; wherein, the preset protocol is the JDBC protocol;

[0013] Extract the metadata and running status time-series data of the Oracle database to be evaluated; wherein, the metadata includes: static metadata, dynamic metadata;

[0014] Based on a preset log collection tool, monitor the Oracle database to be evaluated in real time to obtain the log files of the Oracle database to be evaluated.

[0015] Optionally, in one or more embodiments of this specification, preprocess the metadata and the log files to obtain processed data, and perform partition storage on the processed data based on a preset time interval and log type, specifically including:

[0016] Convert the format of the metadata and the log information in the log files to obtain data in a fixed format;

[0017] Clean the data in the fixed format to remove duplicate data existing in the data in the fixed format, and obtain processed data;

[0018] Determine the corresponding preset time interval according to the business requirement data corresponding to the Oracle database to be evaluated, so as to determine the main partition corresponding to the processed data based on the preset time interval;

[0019] Perform sub-partitioning on the processed data based on the log type on the basis of the main partition, so as to perform partition storage on the processed data;

[0020] Wherein, after obtaining the processed data, the method further includes:

[0021] Based on the timestamp corresponding to the log information, associate the running status time-series data with the log information in the processed data.

[0022] Optionally, in one or more embodiments of this specification, before performing real-time stream processing on the processed data based on the bottleneck query identifiers corresponding to each partition to obtain the real-time stream data of the Oracle database to be evaluated, the method further includes:

[0023] Based on the historical evaluation data of the Oracle database to be evaluated, determine the high-risk data corresponding to the processed data corresponding to different log types;

[0024] Obtain the identification statements corresponding to the high-risk data, and associate the identification statements with the data partitions according to the data partitions corresponding to each high-risk data;

[0025] Summarize the identification statements corresponding to each data partition to determine the first bottleneck query identifier corresponding to each partition;

[0026] According to the evaluation requirement information of the current Oracle database to be evaluated, determine the second bottleneck query identifier for specified data analysis;

[0027] According to the first bottleneck query identifier and the second bottleneck query identifier, determine the bottleneck query identifier corresponding to each partition.

[0028] Optionally, in one or more embodiments of this specification, based on the bottleneck query identifiers corresponding to each partition, performing real-time stream processing on the processed data to obtain the real-time stream data of the Oracle database to be evaluated specifically includes:

[0029] Establish multi-level processing channels according to predefined bottleneck level tags, and perform real-time extraction on the processed data according to the bottleneck query identifiers corresponding to each partition, and add the extracted data to the corresponding processing channels;

[0030] Generate the real-time performance index of each data partition according to the historical baseline of the Oracle database to be evaluated, and determine the health score of each data partition according to the real-time performance index and the real-time load data of each data partition;

[0031] Based on the real-time stream processing strategies corresponding to each bottleneck query identifier and the bottleneck level tags corresponding to each bottleneck query identifier, construct a real-time stream processing waiting time tree, and adjust the real-time stream processing waiting time tree based on the health scores of each data partition;

[0032] Based on the order of the real-time stream processing waiting time tree, obtain the real-time stream processing strategies corresponding to each bottleneck query identifier, and process the data in the corresponding processing channels to obtain the real-time stream data of the Oracle database to be evaluated; wherein, the real-time stream processing strategy includes: threat detection and high-risk association.

[0033] Optionally, in one or more embodiments of the present specification, according to the analysis items triggered by the Oracle database to be evaluated, real-time streaming data corresponding to the analysis items is called to determine the analysis result of the Oracle database to be evaluated based on the real-time streaming data and the analysis process corresponding to the analysis items, which specifically includes:

[0034] According to the analysis items triggered by the Oracle database to be evaluated, locate and call the corresponding real-time streaming data according to the analysis requirement information corresponding to the analysis items; wherein, the analysis items include: performance analysis, security compliance analysis, and compatibility analysis;

[0035] Process the corresponding real-time streaming data based on the analysis processes corresponding to each analysis item to obtain the analysis result of the Oracle database to be evaluated.

[0036] Optionally, in one or more embodiments of the present specification, after determining the analysis result of the Oracle database to be evaluated based on the real-time streaming data and the analysis process corresponding to the analysis items, the method further includes:

[0037] Input each of the analysis results into a preset visualization platform to perform data modeling on the analysis results based on the preset visualization platform to generate visualized modeling data;

[0038] Construct a display interface corresponding to the analysis result according to the visualized modeling data and the visualized interface data to realize the visualized display of the analysis result of the Oracle database to be evaluated.

[0039] Optionally, in one or more embodiments of the present specification, after determining the analysis result of the Oracle database to be evaluated based on the real-time streaming data and the analysis process corresponding to the analysis items, the method further includes:

[0040] Match the analysis result with the current business requirements of the Oracle database to be evaluated to determine the real-time streaming data that exceeds the coverage range of the current business requirements as decision analysis data;

[0041] Determine the decision target of the Oracle database to be evaluated based on the difference between the decision analysis data and the current business requirements;

[0042] Obtain a decision support model of the corresponding type based on the current business requirements, and input the decision target and the decision analysis data into the decision support model to obtain corresponding decision suggestions; wherein, the decision suggestions include: database selection, database optimization, and database migration.

[0043] One or more embodiments of this specification provide an operation analysis device for an Oracle database. The device includes:

[0044] At least one processor; and,

[0045] A memory communicatively connected to the at least one processor; wherein,

[0046] The memory stores instructions executable by the at least one processor. When the instructions are executed by the at least one processor, the at least one processor is enabled to: execute any one of the above-mentioned methods.

[0047] A non-volatile computer storage medium provided by one or more embodiments of this specification stores computer-executable instructions, and the computer-executable instructions are configured to: be capable of executing any one of the above-mentioned methods.

[0048] The above at least one technical solution adopted by the embodiments of this specification can achieve the following beneficial effects:

[0049] By pre-setting a protocol to connect to the Oracle database to be evaluated to collect metadata and log files, the stability and reliability of the connection are ensured. Comprehensively collecting metadata and log files provides sufficient information for in-depth analysis of the database structure, performance, and operating conditions, which helps to perform accurate evaluation and optimization. By partitioning and storing data, the data access efficiency can be significantly improved. When performing real-time stream processing and analysis, the required data can be quickly obtained, saving a large amount of time and computing resources, enabling the system to respond to analysis requests more promptly. By identifying bottleneck queries, relevant data in each data partition can be obtained in real time, which helps to target and obtain potentially high-risk data, improving the accuracy of subsequent evaluations. According to the analysis items triggered by the Oracle database to be evaluated, calling the corresponding real-time stream data and combining it with a specific analysis process for analysis can adapt to various complex analysis scenarios and meet the diverse needs of different users for database analysis. Description of the Drawings

[0050] To more clearly illustrate the technical solutions in the embodiments of this specification or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments recorded in this specification. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings. In the drawings:

[0051] Figure 1 It is a schematic flowchart of an operation analysis method for an Oracle database provided by an embodiment of this specification;

[0052] Figure 2 It is a logical schematic diagram of an evaluation method for an Oracle database in an application scenario provided by an embodiment of this specification;

[0053] Figure 3 It is a structural schematic diagram of an operation analysis device for an Oracle database provided by an embodiment of this specification;

[0054] Figure 4 It is a structural schematic diagram of a non - volatile storage medium provided by an embodiment of this specification. Detailed implementation manners

[0055] An embodiment of this specification provides an operation analysis method, device, and medium for an Oracle database.

[0056] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of this specification. Obviously, the described embodiments are only a part of the embodiments of this specification, rather than all the embodiments. Based on the embodiments of this specification, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of this specification.

[0057] As Figure 1 shown, an embodiment of this specification provides a method flow schematic diagram of an operation analysis method for an Oracle database. It can be seen that an embodiment of this specification provides an operation analysis method for an Oracle database, and the method includes: Figure 1

[0058] S101: Connect to the Oracle database to be evaluated based on a preset protocol to collect and obtain metadata and log files of the Oracle database to be evaluated.

[0059] In order to comprehensively collect the static metadata and dynamic logs of the database, covering all-dimensional data such as DDL, object dependencies, CPU / memory status, audit logs, execution plans, etc., and achieve a comprehensive evaluation, in the embodiments of this specification, the Oracle database to be evaluated will be connected according to a preset protocol, so as to collect and obtain the metadata and log files of the Oracle database to be evaluated. For example: in a certain application scenario, the Oracle database will be connected through the JDBC protocol, and the following metadata will be extracted using the built-in metadata management tool and SQL query statements of the database: Static metadata: DDL statements of table structures, indexes, views, stored procedures, and triggers; Dynamic metadata: object dependency relationships (through the DBA_DEPENDENCIES view), tablespace utilization rates (through DBA_TABLESPACES), and lock statuses (through the V$LOCK view). In addition, time-series data of the running status will also be collected. The time-series data of the running status includes: deploying a lightweight proxy program (such as Prometheus Exporter) to capture in real time the time-series data corresponding to performance metrics such as CPU utilization rate (through V$SYSTEM_EVENT), memory allocation (through V$SGASTAT), and I / O throughput (through V$FILESTAT). The collection of log files uses Apache Flume to monitor Oracle logs in real time, including audit logs, slow query logs, error logs, execution plans, etc. Based on the above process, the comprehensive collection of multi-dimensional data can be achieved, and connecting to the database according to the preset protocol helps to obtain various status information and log data in real time and dynamically during the operation of the database, ensuring the timeliness and timeliness of the data.

[0060] Specifically, in one or more embodiments of this specification, connecting to the Oracle database to be evaluated based on a preset protocol to collect and obtain the metadata and log files of the Oracle database to be evaluated specifically includes:

[0061] Add the driver dependencies corresponding to the preset protocol to the specified project file corresponding to the Oracle database to be evaluated, so as to connect to the Oracle database to be evaluated based on the preset protocol; among them, it should be noted that the preset protocol is the JDBC protocol. Then extract the metadata and runtime status time series data of the Oracle database to be evaluated. Among them, the metadata includes: static metadata, dynamic metadata. At the same time, based on the preset log collection tool, monitor the Oracle database to be evaluated in real time to obtain the log file of the Oracle database to be evaluated. Among them, it should be noted that: JDBC is a Java standard database connection technology with wide compatibility and cross-platformness. Therefore, connecting to the Oracle database to be evaluated through the JDBC protocol helps to adapt to diverse deployment scenarios. In addition, the above process extracts rich metadata covering both static and dynamic aspects, as well as runtime status time series data and various log files. Comprehensive data acquisition provides sufficient information for in-depth analysis of the database structure, performance, and operating conditions, which helps to perform accurate evaluation and optimization.

[0062] S102: Preprocess the metadata and the log file to obtain processed data, and partition and store the processed data based on a preset time interval and log type.

[0063] After completing the data collection for the Oracle database to be evaluated based on the above step S101, it is necessary to preprocess the collected metadata and log file to obtain the processed data, and partition and store the processed data according to the preset time interval and log type. Specifically, in one or more embodiments of the present specification, preprocessing the metadata and the log file to obtain processed data, and partitioning and storing the processed data based on a preset time interval and log type specifically includes the following process:

[0064] First, convert the format of the log information of the metadata and the log file to obtain data in a fixed format. For example, convert it to a fixed format JSON to facilitate subsequent big data processing. Then, perform data cleaning on the data in the fixed format to remove duplicate data existing in the data in the fixed format, and obtain the processed data. Then, determine the corresponding preset time interval according to the business requirement data corresponding to the Oracle database to be evaluated, and determine the corresponding main partition for the processed data based on the preset time interval. For example, partition the processed data by hour or day to obtain the main partition. Then, based on the log type such as: audit, slow query, and error, etc., perform sub-partitioning on the processed data on the basis of the main partition to partition and store the processed data. Among them, it should be noted that after obtaining the processed data, the method further includes:

[0065] Based on the timestamps corresponding to the log information, associate the running status time-series data with the log information in the processed data, so as to locate the root cause of resource contention during subsequent evaluation processes.

[0066] S103: Perform real-time stream processing on the processed data based on the bottleneck query identifiers corresponding to each partition to obtain the real-time stream data of the Oracle database to be evaluated.

[0067] In order to deeply mine valuable information in the processed data for subsequent evaluation to discover potential risks. In the embodiments of this specification, real-time stream processing will be performed on the processed data according to the bottleneck query identifiers corresponding to each partition to obtain the real-time stream data of the Oracle database to be evaluated.

[0068] Further, in order to determine the bottleneck query identifiers corresponding to each partition, in one or more embodiments of this specification, before performing real-time stream processing on the processed data based on the bottleneck query identifiers corresponding to each partition to obtain the real-time stream data of the Oracle database to be evaluated, the method further includes the following processes:

[0069] First, based on the historical evaluation data of the Oracle database to be evaluated, analyze the processed data corresponding to different log types, and find out the high-risk data. These high-risk data may refer to those data that have been found to be related to database performance problems, potential risks, or abnormal situations in past evaluations.

[0070] Then, for the identified high-risk data, obtain the corresponding identification statements. It can be understood that these identification statements can represent or point to the specific locations or related operations of these high-risk data in the database. Then, according to the data partitions corresponding to each high-risk data, associate the identification statements with the data partitions to clarify the possible high-risk data and their corresponding identifications in each data partition. Summarize the identification statements corresponding to each data partition, and by analyzing and processing these summarized identification statements, determine the first bottleneck query identification corresponding to each data partition. It can be understood that the first bottleneck query identification is summarized from historical evaluation data and may represent the query types or operations that often caused performance bottlenecks or problems in each data partition in the past. Then, according to the evaluation requirement information of the current Oracle database to be evaluated, such as the performance metrics that the current business focuses on, specific business scenario requirements, or special problems that have occurred recently, determine the second bottleneck query identification for specified data analysis. It can be understood that the second bottleneck query identification is specifically determined for the current evaluation requirements and focuses more on meeting the current business needs and concerns. Finally, according to the first bottleneck query identification and the second bottleneck query identification, determine the bottleneck query identification corresponding to each partition. By comprehensively considering the first bottleneck query identification and the second bottleneck query identification, which takes into account both historical common problems and current evaluation requirements, it can more comprehensively and accurately reflect the possible bottleneck query situations in each data partition.

[0071] Specifically, in one or more embodiments of the present specification, based on the bottleneck query identifications corresponding to each partition, perform real-time stream processing on the processed data to obtain the real-time stream data of the Oracle database to be evaluated, which specifically includes:

[0072] Establish multi-level processing channels based on predefined bottleneck level tags to extract the processed data in real time according to the bottleneck query identifiers corresponding to each partition, and add the extracted data to the corresponding processing channels. By establishing multi-level processing channels based on predefined bottleneck level tags, the processed data can be classified and extracted according to different bottleneck levels. This can target problems of different severities for targeted processing, improving processing efficiency and the rationality of resource allocation. Then, based on the historical baseline of the Oracle database to be evaluated, generate the real-time performance index for each data partition, and thus determine the health score for each data partition according to the real-time performance index and the real-time load data of each data partition. Among them, it should be noted that the historical baseline provides a reference standard. By comparing with real-time data, the performance changes of data partitions can be discovered in a timely manner. The health score is a comprehensive indicator that can help administrators quickly understand the overall health status of each data partition and provide a basis for subsequent processing. Therefore, generating the real-time performance index for each data partition based on the historical baseline of the Oracle database to be evaluated and determining the health score in combination with the real-time load data can comprehensively evaluate the operating conditions of each data partition. Then, based on the real-time stream processing strategy corresponding to each bottleneck query identifier and the bottleneck level tag corresponding to each bottleneck query identifier, construct a real-time stream processing waiting time tree to adjust the real-time stream processing waiting time tree based on the health score of each data partition. It can be understood that: the waiting time tree can determine the priority and order of data processing according to different bottleneck levels and processing strategies. And adjusting according to the health score can dynamically optimize the processing order according to the actual conditions of the data partition to ensure that critical data partitions with greater performance impact can be processed in a timely manner. Then, according to the order of the real-time stream processing waiting time tree, obtain the corresponding real-time stream processing strategy to process the data in the corresponding processing channel, and finally obtain the real-time stream data of the Oracle database to be evaluated. This process can adopt corresponding processing strategies according to different bottleneck situations, such as threat detection and high-risk association, to discover and handle potential problems in a timely manner, thus providing strong support for database monitoring and optimization.

[0073] In a certain application scenario of this specification, Apache Flink can be used to build a real-time processing engine to complete the following real-time stream processing: Log event extraction: Extract "high-risk operations" (such as DROP TABLE) from audit logs and trigger alarms; Extract high-time-consuming SQL statements from slow query logs and associate their execution plans, etc. Multi-source association: Associate the SQL_ID of slow queries with table / index information in metadata to determine whether performance problems are caused by missing indexes; Combine log events during CPU peak periods to locate the root cause of resource contention (such as lock conflicts).

[0074] S104: According to the analysis items triggered by the Oracle database to be evaluated, call the real-time stream data corresponding to the analysis items, and determine the analysis result of the Oracle database to be evaluated based on the real-time stream data and the analysis process corresponding to the analysis items.

[0075] After obtaining the real-time stream data based on the above steps, according to the analysis items triggered by the Oracle database to be evaluated, call the real-time stream data corresponding to the analysis items, so as to determine the analysis result of the Oracle database to be evaluated according to the real-time stream data and the analysis process corresponding to the analysis items.

[0076] Specifically, in one or more embodiments of the present specification, according to the analysis items triggered by the Oracle database to be evaluated, call the real-time stream data corresponding to the analysis items, and determine the analysis result of the Oracle database to be evaluated based on the real-time stream data and the analysis process corresponding to the analysis items, which specifically includes:

[0077] According to the analysis items triggered by the Oracle database to be evaluated, locate and call the corresponding real-time stream data according to the analysis requirement information corresponding to the analysis items; among them, as Figure 2 shown, the analysis items include: performance analysis, security compliance analysis, and compatibility analysis. Then, process the corresponding real-time stream data based on the analysis processes corresponding to each analysis item to obtain the analysis result of the Oracle database to be evaluated. For example: when the analysis item is performance analysis: the processing process is: extract the operation type, estimated cost (COST), actual execution time, and physical read / logical read times from the execution plan; extract the SQL text, execution frequency, and execution time distribution from the slow query log; use the K-Means algorithm to cluster the slow queries according to execution characteristics such as high physical reads and long execution times, and identify high-frequency inefficient patterns such as full table scans without valid indexes; based on association rules such as the Apriori algorithm, analyze the co-occurrence relationship between slow queries and table space fragmentation rate, lock wait events; if there is a high-cost full table scan and the table has no valid index, recommend creating a composite index, and if frequent lock conflicts are detected, recommend optimizing the transaction isolation level or splitting the transaction; finally, automatically output the recommended items.

[0078] Further, in one or more embodiments of this specification, after determining the analysis result of the Oracle database to be evaluated based on the real-time stream data and the analysis process corresponding to the analysis item, the method further includes: inputting each analysis result into a preset visualization platform to perform data modeling on the analysis result based on the preset visualization platform to generate visualized modeling data; constructing a display interface corresponding to the analysis result according to the visualized modeling data and the visualized interface data to implement the visualized display of the analysis result of the Oracle database to be evaluated. By presenting the analysis result in an intuitive form such as graphs and charts through visualized display, it enables users to more quickly and accurately understand the operating conditions and analysis conclusions of the database.

[0079] Further, in one or more embodiments of this specification, after determining the analysis result of the Oracle database to be evaluated based on the real-time stream data and the analysis process corresponding to the analysis item, the method further includes:

[0080] Matching the analysis result with the current business requirements of the Oracle database to be evaluated to determine the real-time stream data that exceeds the coverage range of the current business requirements as decision analysis data. At the same time, based on the difference between the decision analysis data and the current business requirements, determine the decision goal of the Oracle database to be evaluated. Obtain a corresponding type of decision support model based on the current business requirements, and input the decision goal and the decision analysis data into the decision support model to obtain corresponding decision suggestions. The decision suggestions include: database selection, database optimization, and database migration. In this process, by matching the analysis result with the current business requirements, it is possible to accurately find the real-time stream data that exceeds the scope of business requirements, that is, decision analysis data. This helps to focus on key problem data, avoid blindly searching in a large amount of data, and improve the pertinence and efficiency of data analysis. By using a corresponding type of decision support model, decision suggestions covering aspects such as database selection, database optimization, and database migration are generated based on the decision goal and the decision analysis data, providing users with comprehensive and diverse solutions. Users can select the most suitable decision direction according to the actual situation to meet the optimization and management requirements of the database in different business scenarios.

[0081] As Figure 3 shown, an embodiment of this specification provides a schematic structural diagram of an operating analysis device for an Oracle database. It can be seen that in one or more embodiments of this specification, an operating analysis device for an Oracle database includes: Figure 3 At least one processor; and,

[0082] A memory communicatively connected to the at least one processor; wherein,

[0083] The

[0084] The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to: execute any one of the above-mentioned methods.

[0085] As Figure 4 shown, the embodiments of this specification provide a structural schematic diagram of a non-volatile storage medium. It can be Figure 4 seen that in one or more embodiments of this specification, a non-volatile storage medium stores computer-executable instructions 401, and the computer-executable instructions 401 can: execute any one of the above-mentioned methods.

[0086] The various embodiments in this specification are all described in a progressive manner. For the same or similar parts between the various embodiments, reference can be made to each other. Each embodiment focuses on the differences from other embodiments. In particular, for the embodiments of the device, equipment, and non-volatile computer storage medium, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can refer to the partial description of the method embodiments.

[0087] The above describes specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be executed in a different order than in the embodiments and still achieve the desired result. Additionally, the processes depicted in the figures do not necessarily require the particular order or sequential order shown to achieve the desired result. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0088] The above is only one or more embodiments of this specification and is not intended to limit this specification. For those skilled in the art, one or more embodiments of this specification can have various changes and modifications. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of one or more embodiments of this specification shall be included within the scope of the claims of this specification.

Claims

1. A method for running analysis of an Oracle database, characterized in that, The method includes: Connecting to the Oracle database to be evaluated based on a preset protocol to collect and obtain the metadata and log files of the Oracle database to be evaluated; Preprocessing the metadata and the log files to obtain processed data, and storing the processed data in partitions based on a preset time interval and log type; Performing real-time stream processing on the processed data based on the bottleneck query identifiers corresponding to each partition to obtain the real-time stream data of the Oracle database to be evaluated; According to the analysis items triggered by the Oracle database to be evaluated, calling the real-time stream data corresponding to the analysis items, and determining the analysis result of the Oracle database to be evaluated based on the real-time stream data and the analysis process corresponding to the analysis items; Wherein, before performing real-time stream processing on the processed data based on the bottleneck query identifiers corresponding to each partition to obtain the real-time stream data of the Oracle database to be evaluated, the method further includes: Determining the high-risk data corresponding to the processed data corresponding to different log types based on the historical evaluation data of the Oracle database to be evaluated; Obtaining the identification statements corresponding to the high-risk data, and associating the identification statements with the data partitions according to the data partitions corresponding to each high-risk data; Summarizing the identification statements corresponding to each data partition to determine the first bottleneck query identifier corresponding to each partition; Determining the second bottleneck query identifier for specified data analysis according to the evaluation requirement information of the current Oracle database to be evaluated; Determining the bottleneck query identifier corresponding to each partition according to the first bottleneck query identifier and the second bottleneck query identifier; 2. The operation analysis method of an Oracle database according to claim 1, characterized in that Connecting to the Oracle database to be evaluated based on a preset protocol to collect and obtain the metadata and log files of the Oracle database to be evaluated, specifically including: Adding the driver dependency corresponding to the preset protocol to the specified project file corresponding to the Oracle database to be evaluated, so as to connect to the Oracle database to be evaluated based on the preset protocol; wherein, the preset protocol is the JDBC protocol; Extracting the metadata and the running state time-series data of the Oracle database to be evaluated; wherein, the metadata includes: static metadata, dynamic metadata; Real-time monitoring the Oracle database to be evaluated based on a preset log collection tool to obtain the log files of the Oracle database to be evaluated; 3. The operation analysis method of an Oracle database according to claim 2, wherein Preprocessing the metadata and the log files to obtain processed data, and storing the processed data in partitions based on a preset time interval and log type, specifically including: Converting the format of the log information of the metadata and the log files to obtain data in a fixed format; Performing data cleaning on the data in the fixed format to remove the duplicate data existing in the data in the fixed format to obtain the processed data; Determine the corresponding preset time interval according to the business requirement data corresponding to the Oracle database to be evaluated, so as to determine the processed data based on the preset time interval and perform the corresponding main partition; Based on the log type, perform sub-partitioning on the processed data on the basis of the main partition, so as to store the processed data in partitions; Wherein, after obtaining the processed data, the method further includes: Based on the time stamp corresponding to the log information, associate the running state time series data with the log information in the processed data.

4. A method for running analysis of an Oracle database according to claim 1, characterized in that, Based on the bottleneck query identifier corresponding to each partition, perform real-time stream processing on the processed data to obtain the real-time stream data of the Oracle database to be evaluated, specifically including: Establish multi-level processing channels according to predefined bottleneck level labels, so as to perform real-time extraction on the processed data according to the bottleneck query identifier corresponding to each partition, and add the extracted data to the corresponding processing channel; Generate the real-time performance index of each data partition according to the historical baseline of the Oracle database to be evaluated, so as to determine the health score of each data partition according to the real-time performance index and the real-time load data of each data partition; Based on the real-time stream processing strategy corresponding to each bottleneck query identifier and the bottleneck level label corresponding to each bottleneck query identifier, construct a real-time stream processing waiting time tree, so as to adjust the real-time stream processing waiting time tree based on the health score of each data partition; Based on the order of the real-time stream processing waiting time tree, obtain the real-time stream processing strategy corresponding to each bottleneck query identifier, and process the data in the corresponding processing channel to obtain the real-time stream data of the Oracle database to be evaluated; wherein, the real-time stream processing strategy includes: threat detection and high-risk association.

5. A method for running analysis of an Oracle database according to claim 1, characterized in that, According to the analysis items triggered by the Oracle database to be evaluated, call the corresponding real-time stream data corresponding to the analysis items, so as to determine the analysis result of the Oracle database to be evaluated based on the real-time stream data and the analysis process corresponding to the analysis items, specifically including: According to the analysis items triggered by the Oracle database to be evaluated, locate and call the corresponding real-time stream data according to the analysis requirement information corresponding to the analysis items; wherein, the analysis items include: performance analysis, security compliance analysis, compatibility analysis; Process the corresponding real-time stream data based on the analysis process corresponding to each analysis item to obtain the analysis result of the Oracle database to be evaluated.

6. A method for running analysis of an Oracle database according to claim 1, characterized in that, After determining the analysis result of the Oracle database to be evaluated based on the real-time stream data and the analysis process corresponding to the analysis items, the method further includes: Input each analysis result into a preset visualization platform, so as to perform data modeling on the analysis result based on the preset visualization platform to generate visualization modeling data; Construct a display interface corresponding to the analysis result according to the visualization modeling data and the visualization interface data, and realize the visualization display of the analysis result of the Oracle database to be evaluated.

7. A method for running analysis of an Oracle database according to claim 1, characterized in that, After determining the analysis result of the Oracle database to be evaluated based on the real-time stream data and the analysis process corresponding to the analysis project, the method further includes: Matching the analysis result with the current business requirements of the Oracle database to be evaluated to determine the real-time stream data that exceeds the coverage of the current business requirements as decision analysis data; Determining the decision target of the Oracle database to be evaluated based on the difference between the decision analysis data and the current business requirements; Obtaining a decision support model of the corresponding type based on the current business requirements, and inputting the decision target and the decision analysis data into the decision support model to obtain corresponding decision suggestions; wherein, the decision suggestions include: database selection, database optimization, and database migration.

8. An operating analysis device for an Oracle database, characterized in that, The device includes: At least one processor; and, A memory communicatively connected to the at least one processor; wherein, The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to: execute the method according to any one of claims 1-7 above.

9. A non-volatile memory stores computer-executable instructions, characterized in that, The computer-executable instructions: can execute the method according to any one of claims 1-7 above.

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