CN115203229A - Process query system and method - Google Patents

Abstract

The invention discloses a process query system and method, belonging to the technical field of process query. In the present invention, a query interface module, a language conversion module and a query optimization module are set in the process query system; the query interface module is used for receiving the process query conditions input by the user, and performs language classification according to the process query conditions to generate different query conditions. Types of process query languages; the language conversion module is used to parse different types of process query languages, and perform corresponding language conversion for each process query language according to the parsing results to obtain multiple converted process query languages; The query optimization module is used to optimize the converted process query language and the process query conditions, and can perform query according to the optimized process to improve the efficiency of process query.

Description

Process query system and method

technical field

The invention relates to the technical field of process query, in particular to a process query system and method.

Background technique

The existing process query system mainly operates on the general SQL database (Structured Query Language server database, Structured Query Language database) and its derivatives, which is not suitable for the use or optimization of process query, and the process query implemented by programming. The scheme is cumbersome to operate and has low utilization, and is inefficient when performing process query.

SUMMARY OF THE INVENTION

The main purpose of the present invention is to provide a process query system and method, aiming at solving the technical problem of low process query efficiency in the prior art.

In order to achieve the above object, the present invention provides a process query system, the process query system includes: a query interface module, a language conversion module and a query optimization module;

The query interface module is configured to receive the process query conditions input by the user, and perform language classification according to the process query conditions to generate different types of process query languages;

The language conversion module is used to parse different types of process query languages, and perform corresponding language conversion for each process query language according to the analysis results, so as to obtain multiple converted process query languages;

The query optimization module is configured to optimize the converted process query language and the process query conditions.

Optionally, the language conversion module includes: a language interpreter;

The language interpreter is used for receiving different kinds of process query languages, and performing corresponding language conversion on different kinds of process query languages;

The language interpreter is further configured to convert the time flow query language logic into a time dimension language interception logic when the flow query language is a time flow query language, so as to complete the language conversion of the time flow query.

Optionally, the language interpreter is further configured to obtain a case identifier and case time information when the process query language is a case process query, and generate a chronological order according to the case identifier and the case time information. Sequence of steps and sequence of timestamps to complete language translation of case flow queries.

Optionally, the language interpreter is further configured to generate corresponding algorithm logic according to the process query condition;

The language interpreter is further configured to, when the process query condition is a node query, determine whether the sequence of steps matches the corresponding node, and when the sequence of steps matches the node, obtain a query matching the node. Sequence of steps to complete language translation of node queries.

Optionally, the language interpreter is further configured to find out whether there is an associated segment node in the step sequence when the process query condition is a segment node query, and when there is an associated segment node in the step sequence, Intercept the sequence of steps associated with the segment node to complete the language conversion of the segment node query.

Optionally, the language interpreter is also used to generate a query code associated with the time sequence of the step sequence when the process query condition is a time-consuming query, so as to perform a time-consuming query according to the query code to complete the query code. Language conversion for time-consuming queries;

The language interpreter is further configured to match the sequence of steps with a path when the process query condition is a path query, so as to complete the language conversion of the path query.

Optionally, the language interpreter is further configured to determine the type of the edge query when the process query condition is an edge query, and perform language conversion on the edge query according to the type of the edge query and the sequence of steps.

Optionally, the query optimization module is further configured to obtain a time range when the process query condition is a time process query, and advance the query of the time range;

The query optimization module is further configured to advance the query condition of the associated log and process the log data when the process query condition is a log query;

The query optimization module is further configured to combine the multiple case queries when the process query conditions are multiple case queries;

The query optimization module is further configured to advance the query language corresponding to the fragment node query or the query language corresponding to the time-consuming query when the process query condition is a fragment node query or a time-consuming query.

Optionally, the query interface module is further configured to receive a process query field input by a user, and combine the process query fields through a logical operator to obtain a process query condition.

In addition, in order to achieve the above object, the present invention also proposes a process query method. The process query method is applied to the process query system described above. The process query system includes: a query interface module, a language conversion module, and a query optimization module. module, the method includes:

The query interface module receives the process query conditions input by the user, and performs language classification according to the process query conditions to generate different types of process query languages;

The language conversion module parses different types of process query languages, and performs corresponding language conversion for each process query language according to the analysis results, so as to obtain multiple converted process query languages;

The query optimization module optimizes the converted process query language and the process query conditions.

In the present invention, a query interface module, a language conversion module and a query optimization module are set in the process query system; the query interface module is used for receiving the process query conditions input by the user, and performs language classification according to the process query conditions to generate different query conditions. Types of process query languages; the language conversion module is used to parse different types of process query languages, and perform corresponding language conversion for each process query language according to the parsing results to obtain multiple converted process query languages; The query optimization module is used to optimize the converted process query language and the process query conditions, and can perform query according to the optimized process to improve the efficiency of process query.

Description of drawings

Fig. 1 is the structural block diagram of the first embodiment of the process query system of the present invention;

Fig. 2 is the structural block diagram of the second embodiment of the process query system of the present invention;

FIG. 3 is a schematic flowchart of a first embodiment of a process query method according to the present invention.

The realization, functional characteristics and advantages of the present invention will be further described with reference to the accompanying drawings in conjunction with the embodiments.

Description of reference numbers:

label name label name 1 Query interface module 20 language interpreter 2 language conversion module 3 query optimization module

Detailed ways

It should be understood that the specific embodiments described herein are only used to explain the present invention, but not to limit the present invention.

Referring to FIG. 1, FIG. 1 is a structural block diagram of a first embodiment of a process query system of the present invention.

In this embodiment, the process query system includes: a query interface module 1, a language conversion module 2 and a query optimization module 3; the query interface module 1 is used to receive the process query conditions input by the user, and according to the process The query conditions are classified into languages, and different types of process query languages are generated; the language conversion module 2 is used to parse different types of process query languages, and perform corresponding language conversion for each process query language according to the parsing results, so as to obtain multiple query languages. A converted process query language; the query optimization module 3 is configured to optimize the converted process query language and the process query conditions.

It should be understood that the query interface module 1 is used to receive the process query conditions input by the user, and the process query conditions are the process query conditions obtained by the user according to the combination of logical operators. The logical operators include AND, OR, NOT, etc. This embodiment There is no restriction on this.

In a specific implementation, the query interface module 1 is further configured to receive the process query fields input by the user, and combine the process query fields through logical operators to obtain the process query conditions. The user inputs query fields through the defined query interface module 1, and combines various queries through logical operators to obtain corresponding process query conditions. After obtaining the process query conditions, the query interface module 1 performs language classification according to the process query conditions to generate different types of process query languages.

It should be noted that the language conversion module 2 is used to parse different types of process query languages, and perform corresponding language conversion for each process query language according to the analysis results, and obtain multiple converted process query languages. The language conversion module 2 Including language interpreters, by obtaining different kinds of query languages, inputting them to the corresponding query language interpreters for language parsing and conversion, and obtaining a variety of converted process query languages.

It can be understood that the query optimization module 3 is used to optimize the converted process query language and process query conditions, and obtain the optimized process query language and optimized process query conditions, which can convert the time range in the process query language. Querying in advance, or putting the query conditions based on the log level in the front, can quickly filter out unnecessary log data, achieve the optimized results of process query, and improve the efficiency of process query.

Specifically, the query optimization module 3 is further configured to obtain the corresponding time range when the process query condition is a time process query, and advance the query condition of the time range, because the bottom layer of the process mining system of the process query system is designed based on time , so the query of the time range can be advanced. The query optimization module 3 is further configured to advance the query condition of the associated log when the process query condition is a log query, process the log data, and put the relevant query condition based on the log level in the front, which can quickly Filter out unnecessary log data.

The query optimization module 3 is further configured to combine the multiple case queries when the process query conditions are multiple case queries; the query optimization module 3 is further configured to use the process query conditions as: When querying a segment node or a time-consuming query, the query language corresponding to the segment node query or the query language corresponding to the time-consuming query is advanced.

It should be understood that the query optimization module 3 is also used to combine multiple case queries when the process query conditions are multiple case queries. This case A and case B are combined into one case query, which improves the efficiency of case query. The query optimization module 3 is also used to filter the query language corresponding to the fragment node query or the query language corresponding to the time-consuming query in advance when the process query condition is a fragment node or a time-consuming query, so as to ensure the correctness of the screening.

In the present invention, a query interface module, a language conversion module and a query optimization module are set in the process query system; the query interface module is used for receiving the process query conditions input by the user, and performs language classification according to the process query conditions to generate different query conditions. Types of process query languages; the language conversion module is used to parse different types of process query languages, and perform corresponding language conversion for each process query language according to the parsing results to obtain multiple converted process query languages; The query optimization module is used to optimize the converted process query language and the process query conditions, and can perform query according to the optimized process to improve the efficiency of process query.

Referring to FIG. 2, FIG. 2 is a structural block diagram of the second embodiment of the process query system of the present invention.

In this embodiment, the language conversion module 2 includes: a language interpreter 20; the language interpreter 20 is configured to receive different types of process query languages, and perform corresponding language conversions on different types of process query languages; The language interpreter 20 is further configured to convert the time flow query language logic into a time dimension language interception logic when the process query language is a time flow query language, so as to complete the language conversion of the time flow query.

It should be understood that the query language interpreter 20 is configured to receive different types of process query languages classified by the query interface module 1, and perform corresponding language conversion on the different types of process query languages. The relevant query types are converted according to the interface provided by the underlying process mining system, and the language interpreter 20 is also used to convert the logic of the time process query language into the language interception of the time dimension when the process query language is the time process query language Logic to complete the language conversion of time flow queries.

The language interpreter 20 is further configured to obtain a case identifier and case time information when the process query language is a case process query, and generate a time-ordered step sequence and Timestamp sequence to complete language translation of case flow queries. The language interpreter 20 is further configured to generate corresponding algorithm logic according to the process query condition; the language interpreter 20 is further configured to judge whether the step sequence matches when the process query condition is a node query corresponding node, and when the step sequence matches the node, obtain the step sequence matching the node, so as to complete the language conversion of the node query.

It should be noted that when the process query language is case process query, the case ID and case time information can be obtained, and a time-ordered step sequence and timestamp sequence can be generated according to the case ID and case time information. Then, the corresponding algorithm logic is generated according to the process query conditions.

The language interpreter 20 is further configured to judge whether there is a matching node in the sequence of steps sorted by time when the process query condition is a node query, the node query includes a start node query or an end node query, and the matching node includes a start node and end node, when there is a matching node in the step sequence sorted by time, obtain the step sequence matching the start node or end node, and complete the language conversion of the node query according to this step sequence.

The language interpreter 20 is further configured to find out whether there is an associated segment node in the step sequence when the process query condition is a segment node query, and when there is an associated segment node in the step sequence, intercept and intercept the segment node associated with the step sequence. Describe the sequence of steps associated with fragment nodes to complete the language conversion of fragment node queries.

It should be understood that when the process query condition is a segment node query, it can be searched whether there is an associated segment node in the current step sequence, and the segment node includes a start node and an end node. When the step sequence has an associated start node or end node. , intercept the step sequence associated with the segment node, and complete the language conversion of the segment node query through the intercepted associated step sequence.

The language interpreter 20 is further configured to generate a query code associated with the step sequence and time when the process query condition is a time-consuming query, so as to perform a time-consuming query according to the query code to complete the time-consuming query The language interpreter 20 is further configured to match the sequence of steps with the path when the process query condition is a path query, so as to complete the language conversion of the path query.

In a specific implementation, when the process query condition is a time-consuming query, the language interpreter 20 generates a query code associated with the step sequence and time, and performs a time-consuming query according to the generated query code, so as to complete the language conversion of the time-consuming query, When the process query is a path query, the language interpreter 20 is used to match the step sequence with the path, and when the step sequence matches the path, obtain the step sequence matching the path to complete the language conversion of the path query.

Further, the language interpreter 20 is further configured to determine the type of the edge query when the process query condition is an edge query, and perform language conversion on the edge query according to the type of the edge query and the sequence of steps. The types of edge queries include direct edge query, non-connect edge query, arbitrary edge query, and no edge query. The language interpreter 20 can determine the type of edge query, and perform language conversion on the edge query according to the type of edge query and the sequence of steps. When the type of the edge query is a directly connected edge, it can determine whether there are two adjacent steps in the sequence of steps. When two adjacent steps occur, the edge query is linguistically transformed according to the two adjacent steps in the sequence of steps. When the edge query type is non-connected edge, it can be judged whether there are two steps in the step sequence and they are not adjacent. Language conversion. When the type of the edge query is any edge query, it is judged whether there are two steps in the step sequence, and when there are two steps in the step sequence, the language conversion is performed on the edge query through the two steps. When the edge query type is not in any edge query, it is judged whether there are no two steps in the step sequence, and when there are no two steps in the step sequence, language conversion is performed on the edge query. It can quickly enter different types of query language interpreters 20 according to different query classifications to realize language conversion.

In this embodiment, the language conversion module is provided with: a language interpreter; the language interpreter is used to receive different kinds of process query languages, and perform corresponding language conversion for different kinds of process query languages; the language interpreter , and is also used to convert the time flow query language logic into the language interception logic of the time dimension when the process query language is the time flow query language, so as to complete the language conversion of the time flow query, which can be quickly performed according to the type of the process query language. Corresponding language conversion improves the efficiency of process query.

An embodiment of the present invention provides a process query method. Referring to FIG. 3 , FIG. 3 is a schematic flowchart of the first embodiment of the process query method of the present invention.

In this embodiment, the process query method includes the following steps:

Step S10: The query interface module receives the process query conditions input by the user, and performs language classification according to the process query conditions to generate different types of process query languages.

It should be understood that the query interface module is used to receive the process query conditions input by the user, and the process query conditions are the process query conditions obtained by the user according to the combination of logical operators. The logical operators include AND OR NOT, etc., which are not made in this embodiment. limit.

In a specific implementation, the query interface module is further configured to receive the process query fields input by the user, and combine the process query fields through logical operators to obtain the process query conditions. The user enters the query field through the defined query interface module, and combines various queries through logical operators to obtain the corresponding process query conditions. After obtaining the process query conditions, the query interface module performs language classification according to the process query conditions to generate different types of process query languages.

Step S20: The language conversion module parses different types of process query languages, and performs corresponding language conversion for each process query language according to the parsing results to obtain multiple converted process query languages.

It should be noted that the language conversion module is used to parse different types of process query languages, and perform corresponding language conversion for each process query language according to the analysis results to obtain multiple converted process query languages. The language conversion module includes: The language interpreter obtains different kinds of query languages and inputs them to the corresponding query language interpreter for language analysis and conversion, and obtains a variety of converted process query languages.

Step S30: The query optimization module optimizes the converted process query language and the process query conditions.

It can be understood that the query optimization module is used to optimize the converted process query language and process query conditions to obtain the optimized process query language and optimized process query conditions, which can query the time range in the process query language. In advance, or put the query conditions based on the log level in the front, you can quickly filter out unnecessary log data, achieve the optimized results of the process query, and improve the efficiency of the process query.

Specifically, the query optimization module is further configured to obtain a corresponding time range when the process query condition is a time process query, and advance the query condition of the time range. Since the bottom layer of the process mining of the process query system is designed based on time, Therefore, the query of the time range can be advanced. The query optimization module is also used to advance the query conditions of the associated logs when the process query conditions are log queries, process the log data, and put the relevant query conditions based on the log level in the front, which can quickly filter Delete unnecessary log data.

The query optimization module is further configured to combine the multiple case queries when the process query conditions are multiple case queries; the query optimization module is further configured to combine the process query conditions as fragment nodes When querying or time-consuming query, the query language corresponding to the fragment node query or the query language corresponding to the time-consuming query is advanced.

It should be understood that the query optimization module is also used to combine multiple case queries when the process query conditions are multiple case queries. For example, if two query conditions of query case A and query case B are required, then This case A and case B are merged into one case query, which improves the efficiency of case query. The query optimization module is also used to filter the query language corresponding to the fragment node query or the query language corresponding to the time-consuming query in advance when the process query condition is a fragment node or a time-consuming query, so as to ensure the correctness of the screening.

In this embodiment, a query interface module, a language conversion module and a query optimization module are set in the process query system; the query interface module is used to receive the process query conditions input by the user, and perform language classification according to the process query conditions, and generate Different types of process query languages; the language conversion module is used to parse different types of process query languages, and perform corresponding language conversion for each process query language according to the parsing results to obtain multiple converted process query languages; The query optimization module is configured to optimize the converted process query language and the process query conditions, and can perform query according to the optimized process to improve the efficiency of process query.

It should be understood that the above are only examples, and do not constitute any limitation to the technical solutions of the present invention. In specific applications, those skilled in the art can make settings as required, which is not limited by the present invention.

It should be noted that the above-described workflow is only illustrative, and does not limit the protection scope of the present invention. In practical applications, those skilled in the art can select some or all of them to implement according to actual needs. The purpose of the solution in this embodiment is not limited here.

In addition, for technical details not described in detail in this embodiment, reference may be made to the process query method provided by any embodiment of the present invention, and details are not described herein again.

Furthermore, it should be noted that, herein, the terms "comprising", "comprising" or any other variation thereof are intended to encompass non-exclusive inclusion, such that a process, method, article or system comprising a series of elements includes not only those elements, but also other elements not expressly listed or inherent to such a process, method, article or system. Without further limitation, an element qualified by the phrase "comprising a..." does not preclude the presence of additional identical elements in the process, method, article or system that includes the element.

The above-mentioned serial numbers of the embodiments of the present invention are only for description, and do not represent the advantages or disadvantages of the embodiments.

From the description of the above embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus a necessary general hardware platform, and of course hardware can also be used, but in many cases the former is better implementation. Based on such understanding, the technical solutions of the present invention can be embodied in the form of software products in essence or the parts that make contributions to the prior art, and the computer software products are stored in a storage medium (such as a read-only memory). , ROM)/RAM, magnetic disk, optical disk), including several instructions to make a terminal device (which may be a mobile phone, a computer, a server, or a network device, etc.) execute the methods described in the various embodiments of the present invention.

The above are only preferred embodiments of the present invention, and are not intended to limit the scope of the present invention. Any equivalent structure or equivalent process transformation made by using the contents of the description and drawings of the present invention, or directly or indirectly applied in other related technical fields , are similarly included in the scope of patent protection of the present invention.

Claims (10)

1. A process query system, comprising: the query interface module, the language conversion module and the query optimization module;

the query interface module is used for receiving process query conditions input by a user, performing language classification according to the process query conditions and generating different types of process query languages;

the language conversion module is used for analyzing different types of process query languages, and performing corresponding language conversion on each process query language according to an analysis result to obtain multiple converted process query languages;

and the query optimization module is used for optimizing the converted process query language and the process query condition.

2. The process query system of claim 1, wherein said language translation module comprises: a language interpreter;

the language interpreter is used for receiving different types of process query languages and performing corresponding language conversion on the different types of process query languages;

the language interpreter is further configured to convert the time flow query language logic into a time dimension language interception logic when the flow query language is a time flow query language, so as to complete language conversion of the time flow query.

3. The process query system of claim 2, wherein the language interpreter is further configured to obtain case identifications and case time information when the process query language is a case process query, and generate a time-ordered sequence of steps and a time stamp sequence according to the case identifications and the case time information to complete language conversion of the case process query.

4. The process query system of claim 3, wherein said language interpreter is further configured to generate corresponding algorithmic logic based on said process query criteria;

and the language interpreter is also used for judging whether the step sequence is matched with the corresponding node or not when the process query condition is node query, and acquiring the step sequence matched with the node when the step sequence is matched with the node so as to complete the language conversion of the node query.

5. The process query system of claim 4, wherein the language interpreter is further configured to, when the process query condition is a segment node query, find whether there is an associated segment node in the step sequence, and, when there is an associated segment node in the step sequence, intercept the step sequence associated with the segment node to complete the language conversion of the segment node query.

6. The process query system of claim 4, wherein the language interpreter is further configured to generate a query code associated with the step sequence and time when the process query condition is a time-consuming query, so as to perform the time-consuming query according to the query code to complete language conversion of the time-consuming query;

and the language interpreter is also used for matching the step sequence with the path when the process query condition is path query so as to complete the language conversion of the path query.

7. The process query system of claim 4, wherein the language interpreter is further configured to determine an edge query type when the process query condition is an edge query, and perform language conversion on the edge query according to the edge query type and the step sequence.

8. The process query system of claim 1, wherein the query optimization module is further configured to obtain a time range and advance the query of the time range when the process query condition is a time process query;

the query optimization module is further configured to advance query conditions of the associated logs and process log data when the process query conditions are log queries;

the query optimization module is further configured to merge the multiple case queries when the process query condition is multiple case queries;

the query optimization module is further configured to advance a query language corresponding to the segment node query or a query language corresponding to the time-consuming query when the process query condition is the segment node query or the time-consuming query.

9. The process query system of any one of claims 1-8, wherein the query interface module is further configured to receive process query fields input by a user, and combine the process query fields through logical operators to obtain process query conditions.

10. A process query method applied to the process query system of any one of claims 1 to 9, the process query system comprising: the method comprises a query interface module, a language conversion module and a query optimization module, and comprises the following steps:

the query interface module receives a process query condition input by a user, and performs language classification according to the process query condition to generate different types of process query languages;

the language conversion module analyzes different types of process query languages, and performs corresponding language conversion on each process query language according to an analysis result to obtain multiple converted process query languages;

and the query optimization module optimizes the converted process query language and the process query condition.

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