CN116775957A - Data query method, electronic device and readable storage medium - Google Patents
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Abstract
The application discloses a data query method, electronic equipment and a readable storage medium, and relates to the technical field of data management, wherein the data query method comprises the steps of responding to a data query instruction, and disassembling a target query task to obtain a plurality of sub-query tasks; matching each sub-query task with a preset pre-query rule base; if a target pre-query rule matched with the sub-query task exists in the pre-query rule library, checking whether a target pre-query result of the sub-query task exists in a target data storage area associated with the target pre-query rule; if yes, taking the target pre-query result as a data query result of the sub-query task; if not, executing the sub-query task to obtain a data query result. The problems of low data query efficiency and resource waste in idle time in the prior art are solved.
Description
Technical Field
The present application relates to the field of data management technologies, and in particular, to a data query method, an electronic device, and a readable storage medium.
Background
In recent years, with the rapid development of information technology, the storage amount of information data is increasing, and the requirements for data management and analysis are spread over various application scenarios, and in the process of data management and analysis, statistical query is required for data objects. At present, when data query is performed, generally, a query engine in a server converts a query request of a user into an executable query calculation task, and a query result can be obtained by executing the query calculation task in real time.
However, since the response time of executing the query computing task is completely dependent on the computing performance of the server, and when the number of the query computing tasks to be executed is too large, a large number of query computing tasks mutually occupy the computing resources of the server, thereby increasing the shortage of the computing resources of the server, this brings about a technical problem of low data query efficiency.
Disclosure of Invention
The application mainly aims to provide a data query method, a data query device, electronic equipment and a readable storage medium, and aims to solve the technical problem of low data query efficiency in the prior art.
In order to achieve the above object, the present application provides a data query method, including:
responding to the data query instruction, and disassembling the target query task to obtain a plurality of sub-query tasks;
matching each sub-query task with a preset pre-query rule base;
If a target pre-query rule matched with the sub-query task exists in the pre-query rule library, checking whether a target pre-query result of the sub-query task exists in a target data storage area associated with the target pre-query rule;
if yes, the target pre-query result is used as the data query result of the sub-query task;
if not, executing the sub-query task to obtain a data query result.
Optionally, after the step of executing the sub-query task to obtain the data query result, the data query method further includes:
and storing the data query result as the target pre-query result to the target data storage area.
Optionally, before the step of responding to the data query instruction and disassembling the target query task to obtain the plurality of sub-query tasks, the data query method further includes:
acquiring inquiry tasks contained in each pre-inquiry rule in the pre-inquiry rule base, and acquiring the size of a pre-occupied resource space of each inquiry task and the size of the residual resource space of an inquiry engine;
generating a query task set consisting of a plurality of query tasks according to the size of the residual resource space and the size of each pre-occupied resource space, wherein the total size of the occupied resource space of the query task set is smaller than or equal to the size of the residual resource space;
The pre-query results of the pre-query tasks are obtained by calling the pre-query rules corresponding to the pre-query tasks in the query task set to execute the pre-query tasks;
and if the pre-query result of the pre-query task does not exist in the data storage area associated with the pre-query task, storing the pre-query result into the data storage area.
Optionally, before the step of obtaining the query task included in each pre-query rule in the pre-query rule base, the data query method further includes:
acquiring the total resource space size and the occupied resource space size of the query engine, and calculating the ratio between the occupied resource space size and the total resource space to obtain the resource occupancy rate of the query engine;
and if the resource occupancy rate is checked to be smaller than the preset resource occupancy rate threshold value, executing the step of acquiring the query task contained in each preset query rule in the preset query rule library.
Optionally, before the step of obtaining the query task included in each pre-query rule in the pre-query rule base, the data query method further includes:
Acquiring an initial query data set, and obtaining a query grammar corresponding to each initial query data by analyzing common data characteristics of each initial query data in the initial query data set;
acquiring a data access interface corresponding to each initial query data, associating all the initial query data with the query grammar and the data access interface corresponding to each initial query data, and generating each target query rule;
and in response to a pre-query rule base updating instruction, inserting each target query rule into the pre-query rule base to update the pre-query rule base.
Optionally, before the step of obtaining the query task included in each pre-query rule in the pre-query rule base, the data query method further includes:
acquiring a historical query task set of the query engine in a first preset period, wherein the historical query task set consists of a plurality of historical query tasks;
disassembling each history inquiry task to obtain a plurality of history sub inquiry tasks, and counting the number of each history sub inquiry task;
for any historical sub-query task, if the number of the historical sub-query tasks is verified to be larger than a preset number threshold, generating a target query rule based on the historical sub-query tasks and data access interfaces corresponding to the historical sub-query tasks;
And in response to a pre-query rule base updating instruction, inserting the target query rule into the pre-query rule base to update the pre-query rule base.
Optionally, the data query method further includes:
if the abnormal pre-query rule with the calling frequency smaller than the preset calling frequency threshold value exists in the pre-query rule base in the second preset period, checking whether the priority of the abnormal pre-query rule is smaller than the preset priority threshold value or not;
if yes, deleting the abnormal pre-query rule in the pre-query rule base;
if not, the priority of the abnormal pre-query rule is reduced.
Optionally, after the step of matching each sub-query task with a preset pre-query rule base, the data query method further includes:
checking whether a target pre-query rule matched with the sub-query task exists in the pre-query rule library;
and if the fact that the target pre-query rule matched with the sub-query task does not exist in the pre-query rule base is verified, executing the sub-query task to obtain a data query result.
The application also provides a data query device, which comprises:
The disassembly module is used for responding to the data query instruction and disassembling the target query task to obtain a plurality of sub-query tasks;
the matching module is used for matching each sub-query task with a preset pre-query rule base;
the verification module is used for verifying whether a target pre-query result of the sub-query task exists in a target data storage area associated with the target pre-query rule if the target pre-query rule matched with the sub-query task exists in the pre-query rule library;
the pre-query module is used for taking the target pre-query result as the data query result of the sub-query task if yes;
and the query module is used for executing the sub-query task if not, and obtaining a data query result.
The application also provides an electronic device, which is entity equipment, comprising: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the steps of the data query method as described above.
The present application also provides a readable storage medium which is a computer readable storage medium having stored thereon a program for realizing the data query method, the program for realizing the data query method being executed by a processor to realize the steps of the data query method as described above
The application also provides a computer program product comprising a computer program which, when executed by a processor, implements the steps of a data query method as described above.
The application provides a data query method, firstly, responding to a data query instruction, dismantling a target query task to obtain a plurality of sub-query tasks which can not be dismantled again, then matching preset pre-query rules of each sub-query task, if a target pre-query rule matched with the sub-query task exists in a pre-query database, namely, if the query task contained in the target pre-query rule is the same as the sub-query task, checking whether a target pre-query result of the sub-query task exists in a target data storage area associated with the target pre-query rule, if the target pre-query result of the sub-query task exists in the target data storage area associated with the target pre-query rule, indicating that the sub-query task is pre-queried in advance before a user formally queries, and directly taking the target pre-query result as the query result of the sub-query task without executing the sub-query task at the moment, thereby improving the query efficiency; if the target pre-query result of the sub-query task does not exist in the target data storage area associated with the target pre-query rule, the fact that the sub-query task does not pre-query in advance before the user formally queries is indicated, at the moment, the sub-query task needs to be executed to obtain the data query result, and the technical problem of low data query efficiency in the prior art is solved. In addition, the query engine can respond quickly to the query, so that the use of resources can be smoothed, the query engine is not too busy when busy and is too idle when idle, the investment cost of enterprises on computing resources is saved, and the resource waste in idle time is reduced.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the application and together with the description, serve to explain the principles of the application.
In order to more clearly illustrate the embodiments of the application or the technical solutions of the prior art, the drawings which are used in the description of the embodiments or the prior art will be briefly described, and it will be obvious to a person skilled in the art that other drawings can be obtained from these drawings without inventive effort.
FIG. 1 is a schematic flow chart of a data query method according to an embodiment of the present application;
FIG. 2 is a schematic diagram of a general flow chart of a first embodiment of a data query method according to the present application;
FIG. 3 is a schematic flow chart of a second embodiment of the data query method of the present application;
FIG. 4 is a schematic flow chart of a third embodiment of a data query method according to the present application;
FIG. 5 is a schematic flow chart of a third embodiment of a data query method according to the present application;
FIG. 6 is a schematic block diagram of a data query device according to an embodiment of the present application;
fig. 7 is a schematic device structure diagram of a hardware operating environment related to a data query device in an embodiment of the present application.
The achievement of the objects, functional features and advantages of the present application will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
In order to make the above objects, features and advantages of the present application more comprehensible, the following description of the embodiments accompanied with the accompanying drawings will be given in detail. It will be apparent that the described embodiments are only some, but not all, embodiments of the application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
Example 1
In recent years, with the rapid development of information technology, the storage amount of information data is increasing, and the requirements for data management and analysis are spread over various application scenarios, and in the process of data management and analysis, statistical query is required for data objects. At present, when data query is performed, generally, a query engine in a server converts a query request of a user into an executable query calculation task, and a query result can be obtained by executing the query calculation task in real time.
However, since the response time of executing the query computing task is completely dependent on the computing performance of the server, and when the number of the query computing tasks to be executed is too large, a large number of query computing tasks mutually occupy the computing resources of the server, thereby increasing the shortage of the computing resources of the server, this brings about a technical problem of low data query efficiency.
Based on this, the present application proposes a data query method of the first embodiment, referring to fig. 1 and fig. 2, the data query method includes:
step S10, responding to a data query instruction, and disassembling a target query task to obtain a plurality of sub-query tasks;
it should be noted that, the sub-query task is the lowest task that cannot be disassembled continuously, it can be understood that, assuming that the target query task is the total number of the query accidents, the study engagements and the doctor engagements, after the target query task is disassembled, the sub-query task a can be obtained as the number of the query accidents user, the sub-query task B is the number of the query study engagements, and the sub-query task C is the number of the query doctor engagements.
Step S20, matching each sub-query task with a preset pre-query rule base;
it should be noted that, the pre-query rule base records a plurality of pre-query rules, where the pre-query rules include a query task, a data access interface, and the matching of the sub-query task with the pre-query rule base refers to searching for a target pre-query task matching with the sub-query task in the pre-query rule base.
Step S30, if a target pre-query rule matched with the sub-query task exists in the pre-query rule base, checking whether a target pre-query result of the sub-query task exists in a target data storage area associated with the target pre-query rule;
it should be noted that, the query task included in the target pre-query rule is the same as the sub-query task, for example, if the sub-query task is a number of people with a query age of 5, and if the query task with a pre-query rule a in the pre-query rule base is also a number of people with a query age of 5, the sub-query task is matched with the pre-query rule a.
Additionally, it should be noted that, the target data storage area is used for storing target pre-query results obtained when the query task included in the target pre-query rule is executed in advance in the query engine before the user formally queries.
Step S40, if yes, the target pre-query result is used as the data query result of the sub-query task;
it can be understood that if the target pre-query result of the sub-query task exists in the target data storage area associated with the target pre-query rule, which indicates that the same query task as the sub-query task performs pre-query in advance before the user formally performs query, and the target pre-query result can be directly used as the data query result of the sub-query task because the task content of the target pre-query result is the same as the task content of the sub-query task.
And S50, if not, executing the sub-query task to obtain a data query result.
As an example, the step of obtaining the data query result by calling the pre-query rule corresponding to the sub-query task to execute the sub-query task includes: and calling a data access interface and a query grammar in a pre-query rule corresponding to the sub-query task, connecting the data access interface based on the query grammar, and performing data query by accessing a data source to execute the sub-query task to obtain a data query result.
The embodiment is simultaneously suitable for high summary query, light summary query and detail query, and corresponding changes are needed when the configuration of a pre-query rule base is carried out according to different query types, wherein the high summary query needs to count a large amount of detail data to obtain a final summary result, the pre-query only stores the statistics result, the query result needs to occupy smaller storage space of a query engine, and the query efficiency of secondary query of the statistics data can be improved, so that a smaller range threshold can be set for the pre-query rule base, for example, the query range of one pre-query rule in the original pre-query rule base is 1 to 10, and the query range of the pre-query rule can be set to 1 to 2; although the light summarized query needs to query more results than summarized query, and the query results need to occupy larger storage space of the query engine, the secondary query has a certain improvement compared with the query efficiency of direct query, so that the priority can be set for each pre-query rule in the pre-query rule library, and the higher the use frequency is, the higher the priority of the pre-query rule is; although the detail query needs to obtain more query results, the original detail needs to be screened when the detail query is performed, so that the query efficiency can be improved to a certain extent, and therefore, a larger range threshold can be set for the pre-query rule base, for example, the range of one pre-query rule query in the original pre-query rule base is 1 to 10, and the query range of the pre-query rule can be set to 1 to 20.
It will be appreciated that the same query requirements often occur for different analysts, for example, the number of records in the lookup table, the null rate, etc. are often required when data exploration is performed; the same analyst may need to perform a fixed query every day, e.g., daily query the record count, empty rate, enumeration, etc. of the data; data characteristics need to be queried permanently daily in monitoring them, for example, daily query log number, value rate, data extremum, distribution of individual enumerations, and monitoring their fluctuation with respect to historical partitions.
For example, for daily updated data, after the daily data is ready, when the query engine is in an idle state, the ready query data can be pre-calculated by the query engine, so that when a user queries the query data, the pre-calculated data can be directly returned.
The embodiment of the application provides a data query method, which comprises the steps of firstly, responding to a data query instruction, disassembling a target query task to obtain a plurality of sub-query tasks which can not be disassembled again, then matching preset pre-query rules of each sub-query task, and if a target pre-query rule matched with the sub-query task exists in a pre-query database, namely if the query task contained in the target pre-query rule is the same as the sub-query task, checking whether a target pre-query result of the sub-query task exists in a target data storage area associated with the target pre-query rule, if the target pre-query result of the sub-query task exists in the target data storage area associated with the target pre-query rule, indicating that the sub-query task is pre-queried before a user formally queries, directly taking the target pre-query result as the query result of the sub-query task without executing the sub-query task, thereby improving the query efficiency; if the target pre-query result of the sub-query task does not exist in the target data storage area associated with the target pre-query rule, the fact that the sub-query task does not pre-query in advance before the user formally queries is indicated, at the moment, the sub-query task needs to be executed to obtain the data query result, and the technical problem of low data query efficiency in the prior art is solved. In addition, the query engine can respond quickly to the query, so that the use of resources can be smoothed, the query engine is not too busy when busy and is too idle when idle, the investment cost of enterprises on computing resources is saved, and the resource waste in idle time is reduced.
In a possible implementation manner, after the step of performing the sub-query task to obtain a data query result, the data query method further includes:
and step S51, storing the data query result as the target pre-query result to the target data storage area.
In this embodiment, after the data query result of the sub-query task is obtained, the data query result is stored as the target pre-query result of the sub-query task in the target data storage area, so that when the same sub-query task needs to be executed later, the corresponding query result can be found in the target data storage area, and the query efficiency of the target query task with the same sub-query task is improved.
In one possible implementation manner, before the step of responding to the data query instruction and disassembling the target query task to obtain the plurality of sub-query tasks, the data query method further includes:
step S11, acquiring query tasks contained in each pre-query rule in the pre-query rule base, and acquiring the size of a pre-occupied resource space of each query task and the size of a residual resource space of a query engine;
It should be noted that, the remaining resource space size refers to the space size of the executable query task currently remaining by the query engine.
Step S12, generating a query task set consisting of a plurality of query tasks according to the size of the residual resource space and the size of each pre-occupied resource space, wherein the total size of the occupied resource space of the query task set is smaller than or equal to the size of the residual resource space;
as an example, the step of generating the query task set including a plurality of query tasks according to the remaining resource space size and the pre-occupied resource space size may set a priority for each pre-query rule in the pre-query rule base according to a calling frequency of each pre-query rule, and then includes: and selecting the query tasks according to the residual resource space size and the pre-occupied resource space size and the priority order of the pre-query rules corresponding to the query tasks so as to generate a query task set consisting of a plurality of query tasks.
As another example, the sorting of the query tasks may be performed according to the size of the pre-occupied resource space of each query task, and the selection of the pre-query tasks in the query task set may be performed in the order of the size of the pre-occupied resource space from small to large, or the selection of the pre-query tasks in the query task set may be performed in the order of the size of the pre-occupied resource space from large to small, which is not limited in this example.
For example, assuming that the size of the remaining resource space of the query engine is 10, there is a pre-occupied resource space of query task a of 2, a pre-occupied resource space of query task B of 3, and a pre-occupied resource space of query task C of 5, and when the total occupied resource space is 6, the query task set is composed of query task a and query task B; when the total occupied resource space is 10, the query task set consists of a query task A, a query task B and a query task C.
Step S13, executing each pre-query task by calling a pre-query rule corresponding to each pre-query task in the query task set to obtain a pre-query result of each pre-query task;
step S14, if there is no pre-query result of the pre-query task in the data storage area associated with the pre-query task, storing the pre-query result in the data storage area.
It should be noted that after each pre-query task is executed to obtain a pre-query result of each pre-query task, if it is detected that a data source corresponding to a certain pre-query task is updated, the pre-query result of the pre-query task in a data storage area associated with the pre-query task needs to be deleted, and the pre-query task is re-executed based on the updated data source to obtain a new pre-query result.
In this embodiment, firstly, the query task included in each pre-query rule recorded in the pre-query rule base is obtained, and the pre-occupied resource space size of each query task and the current residual resource space size of the query engine are obtained, then, according to the current residual resource space size of the query engine and the pre-occupied resource space size of each query task, a proper amount of query tasks are selected to form a query task set, and then, the pre-query rules corresponding to each pre-query task in the query task set are called to execute each pre-query task, so as to obtain the pre-query result of each pre-query task, if the pre-query result of the pre-query task does not exist in the data storage area associated with the pre-query task, the pre-query result is stored in the target data storage area, so that the pre-query result of each pre-query task included in each pre-query rule base is obtained by utilizing the residual resource space of the query engine in advance, thereby, the resource space utilization rate of the query engine can be fully utilized, and at the same time, the result is saved, and if the pre-query result is the same, the pre-query result can be directly returned to the target query result.
In one possible implementation manner, before the step of obtaining the query task included in each pre-query rule in the pre-query rule base, the data query method further includes:
step S111, obtaining the total resource space size and the occupied resource space size of the query engine, and calculating the ratio between the occupied resource space size and the total resource space to obtain the resource occupancy rate of the query engine;
it should be noted that, the resource occupancy rate refers to a ratio of the occupied resource space size of the query engine to the total resource space size of the query engine.
As an example, the step of obtaining the total resource space size and the occupied resource space size of the query engine may be to obtain the total resource space size and the occupied resource space size of the query engine in real time, or may set to periodically obtain the total resource space size and the occupied resource space size of the query engine in every other preset time period, which is not limited in this example.
And step S112, if the resource occupancy rate is checked to be smaller than a preset resource occupancy rate threshold value, executing the step of acquiring the query task contained in each pre-query rule in the pre-query rule base.
It should be noted that, the preset resource occupancy rate threshold is used for representing the idle busy state of the query engine, the idle busy state includes an idle state and a busy state, when the resource occupancy rate of the query engine is smaller than the preset resource occupancy rate threshold, the query engine is in a space state, and when the resource occupancy rate of the query engine is greater than or equal to the preset resource occupancy rate threshold, the query engine is in a busy state.
In this embodiment, the total resource space size and the occupied space size of the query engine are obtained first, then the ratio between the occupied space size and the total resource space size is calculated to obtain the resource occupancy rate of the query engine, and then whether the resource occupancy rate is smaller than a preset resource occupancy rate threshold used for representing the idle state of the query engine is checked, if the resource occupancy rate is smaller than the preset resource occupancy rate threshold, it is indicated that the query engine is in a space state, and at this time, a large amount of idle resource space exists in the query engine for use, so that the operation of obtaining the query task contained in each pre-query rule in the pre-query rule library can be normally executed, so as to improve the resource space utilization rate of the query engine.
In one possible implementation manner, after the step of matching each sub-query task with a preset pre-query rule base, the data query method further includes:
step S201, checking whether a target pre-query rule matched with the sub-query task exists in the pre-query rule base;
step S202, if it is verified that the target pre-query rule matched with the sub-query task does not exist in the pre-query rule base, the sub-query task is executed, and a data query result is obtained.
It can be understood that if there is no target pre-query rule matching with the sub-query task in the pre-query rule base, that is, the query task included in each pre-query rule in the pre-query rule base is different from the sub-query task, it is indicated that the sub-query task is not a conventional query task, that is, a query task with a small occurrence number, for example, the sub-query task may be executed less than 3 times in one year, where the sub-query task is normally executed to obtain a data query result, and in addition, since there is no target pre-query rule matching with the sub-query task in the pre-query rule base, there is no need to store the data query result in a target data storage area associated with the sub-query task.
Example two
In another embodiment of the present application, the same or similar content as that of the first embodiment may be referred to the description above, and will not be repeated. On this basis, referring to fig. 3, before the step of obtaining the query task included in each pre-query rule in the pre-query rule base, the data query method further includes:
step A10, acquiring an initial query data set, and obtaining a query grammar corresponding to each initial query data by analyzing common data features of each initial query data in the initial query data set;
it should be noted that, each initial query data in the initial query data set refers to query data preset in the query engine before the query engine is provided to a user, which may be understood as factory data, where the initial query data may be continuous data, enumerated data or date data, common data features of the continuous data include a maximum value, a minimum value, an average number, a median, a special quantile (quartered bit, the next quarter bit, etc.), common data features of the enumerated data include an enumerated value list, an enumerated record number, an empty character number, etc., common data features of the continuous data, the enumerated data and the date data are empty record numbers, and the query grammar may include an average value, an empty character number, a non-empty record number, etc., where the query grammar needs to be determined according to the data features of the initial query data.
Step A20, obtaining a data access interface corresponding to each initial query data, associating all the initial query data with the query grammar and the data access interface corresponding to each initial query data, and generating each target query rule;
it is understood that the target query rule is composed of the initial query data, the query grammar, and a data access interface corresponding to the initial query data.
And step A30, responding to a pre-query rule base updating instruction, and inserting each target query rule into the pre-query rule base to update the pre-query rule base.
In this embodiment, first, an initial query data set in the query engine, that is, factory data preset in the query engine, is required to be obtained, and common data features of each initial query data in the initial query data set are analyzed to obtain query grammars corresponding to each initial query data, then all the initial query data are associated with query grammars and data access interfaces corresponding to each initial query data, target query rules including the initial query data, the query grammars and the data access interfaces are generated, and finally, in response to an update instruction of a pre-query rule base, each target query rule is inserted into the pre-query rule base to dynamically update the pre-query rule base, so that not only can dynamic update of the pre-query rule base be realized, but also the pre-query rules in the pre-query rule base can be set by default before the query engine is provided for a user, so that technical defects that query efficiency cannot be improved due to the fact that the pre-query rule base is empty when the user just begins to use the query engine are avoided.
In a possible implementation manner, the data query method further includes, before the step of inserting each target query rule into the pre-query rule base in response to a pre-query rule base update instruction:
step A31, checking whether the target query rule exists in the pre-query rule base;
a32, if yes, invalidating the pre-query rule base updating instruction;
and step A33, if not, executing the step of inserting each target query rule into the pre-query rule base in response to the pre-query rule base updating instruction.
In this embodiment, before inserting the target query rule into the pre-query rule base, it is required to check whether the pre-query rule base has the same pre-query rule as the target query rule, if the pre-query rule base has the same pre-query rule as the target query rule, the updating instruction of the pre-query rule base is not required to be invalid, and if the pre-query rule base does not have the same pre-query rule as the target query rule, the target query rule is inserted into the pre-query rule base in response to the updating instruction of the pre-query rule base, so as to dynamically update the pre-query rule base, thereby overcoming the technical defects that repeated query rules are repeatedly stored in the pre-query rule base, resulting in redundancy of data in the pre-query rule base and waste of storage resources.
In one possible implementation manner, the data query method further includes:
e10, if the abnormal pre-query rule with the calling frequency smaller than the preset calling frequency threshold value exists in the pre-query rule base in the second preset period, checking whether the priority of the abnormal pre-query rule is smaller than the preset priority threshold value or not;
it can be understood that, when the pre-query rule matches a sub-query task in the target query task, the corresponding call frequency is increased by one, and the preset call frequency threshold is used for indicating whether the pre-query rule has the condition of too low call frequency.
E20, if yes, deleting the abnormal pre-query rule in the pre-query rule base;
and E30, if not, reducing the priority of the abnormal pre-query rule.
As an example, the step of reducing the priority of the abnormal pre-query rule may be reducing the priority of the abnormal pre-query rule by a certain value; the priority of the abnormal pre-query rule may be reduced by a certain reduction ratio, which is not limited in this example.
In this embodiment, if it is verified that an abnormal pre-query rule whose call frequency is smaller than a preset call frequency threshold exists in the pre-query rule base within a second preset period, this indicates that the call frequency of the abnormal pre-query rule is too low, if it is verified that the priority of the abnormal pre-query rule is smaller than a preset priority threshold, this indicates that the call frequency of the abnormal pre-query rule is not only too low, and the priority of the abnormal pre-query rule is not high, so that the probability of using the abnormal pre-query rule in a subsequent query is relatively low, so that the abnormal pre-query rule can be deleted directly in the pre-query rule base to release the storage space of the pre-query rule base; if the abnormal pre-query rule is verified to be not smaller than the preset priority threshold, the abnormal pre-query rule is indicated to have too low calling frequency, but the abnormal pre-query rule is higher in priority and possibly only has too low calling frequency in the current verified time period, and the calling frequency of the abnormal pre-query rule becomes higher in the subsequent query, so that the priority of the abnormal pre-query rule can be reduced first, the technical effect of flexibly adjusting the pre-query rule in the pre-query rule library is achieved, and the technical defect that a large number of abnormal pre-query rules with too low calling frequency exist in the pre-query rule library and occupy the storage space of the large number of pre-query rule library is overcome.
Example III
In another embodiment of the present application, the same or similar content as that of the first embodiment may be referred to the description above, and will not be repeated. On this basis, referring to fig. 4, before the step of obtaining the query task included in each pre-query rule in the pre-query rule base, the data query method further includes:
step B10, acquiring a historical query task set of the query engine in a first preset period, wherein the historical query task set consists of a plurality of historical query tasks;
step B20, disassembling each history inquiry task to obtain a plurality of history sub inquiry tasks, and counting the number of each history sub inquiry task;
note that, the present application is not limited to the above-described embodiments. The history sub-query task is the lowest task that cannot be disassembled.
For example, assuming that the history query task set includes a history query task a and a history query task B, the history query task a is disassembled to obtain a history sub-query task a1 (the number of people with an age of 5), a history sub-query task a2 (the number of people with an age of 6), and a history sub-query task a3 (the number of people with an age of 7), and the history query task B is disassembled to obtain a history sub-query task B1 (the number of people with an age of 7) and a history sub-query task B2 (the number of people with an age of 8), it can be seen that the history sub-query task a3 and the history sub-query task B1 are actually the same history sub-query task.
Step B30, for any historical sub-query task, if the number of the historical sub-query tasks is verified to be larger than a preset number threshold, generating a target query rule based on the historical sub-query task and a data access interface corresponding to the historical sub-query task;
it should be noted that, the preset number threshold is used to characterize whether the update of the pre-query rule base is needed, that is, whether a new pre-query rule needs to be generated based on the history sub-query task.
And step B40, in response to a pre-query rule base updating instruction, inserting the target query rule into the pre-query rule base to update the pre-query rule base.
In order to facilitate understanding of the update flow of the pre-query rule base in the second and third embodiments, please refer to fig. 5, fig. 5 provides a brief update flow of the pre-query rule base, in which step 1.1 corresponds to step a10, step 1.2 corresponds to step a20, step 2.1 corresponds to step B10, step 2.2 corresponds to step B20, step 2.3 corresponds to step B30, step 3 corresponds to step a30 and step B40, and step 4 corresponds to step E20 in fig. 5.
In this embodiment, by acquiring all the history query tasks of the query engine in the first preset period, disassembling each history query task to obtain each history sub-query task that cannot be disassembled, counting the number of each history sub-query task, for any history sub-query task, if the number of the history sub-query tasks is verified to be greater than the preset number threshold, it is indicated that the number of occurrence times of the history sub-query task is frequent in the first preset period, a target query rule needs to be generated based on the history sub-query task and a data access interface corresponding to the history sub-query task, and finally, in response to a pre-query rule library update instruction, the target query rule is inserted into a pre-query rule library to dynamically update the pre-query rule library, thereby achieving the technical effect of dynamically updating the pre-query rule library.
In one possible implementation manner, the step of generating the target query rule based on the historical sub-query task and the data access interface corresponding to the historical sub-query task includes:
step B31, acquiring data to be queried in the history sub-query task, and determining the data type of the data to be queried, wherein the data type comprises continuous data, enumeration data or date data;
step B32, determining a target data characteristic query grammar of the data to be queried based on each data characteristic query grammar corresponding to the data type and the data to be queried;
it should be noted that, the data feature query grammar is a query grammar for implementing the data to be queried, where the data feature query grammar changes along with the data type, for example, there is a data feature query grammar for calculating the average data in the continuous data, and the data feature query grammar for calculating the average data cannot be applied in the date data, so in order to improve the determining efficiency and accuracy of the target data feature query grammar of the data to be queried, it is necessary to determine the data type of the data to be queried first, and then determine the target data feature query grammar of the data to be queried according to each data feature query grammar corresponding to the data type.
And step B33, associating the data to be queried with the target data characteristic query grammar and the data access interface to generate the target query rule.
In this embodiment, first, data to be queried in the history sub-query task is obtained, a data type of the data to be queried is determined, then, determination of a target data feature query grammar of the data to be queried is performed based on each data feature query grammar corresponding to the data type, finally, association is performed between the data to be queried and the target data feature query grammar as well as a data access interface corresponding to the history sub-query task, and a target query rule simultaneously containing the data to be queried, the target data feature query grammar and the data access interface corresponding to the history sub-query task is generated, so that the integrity of the query rule is ensured, and the technical defect that the pre-query cannot be performed normally due to lack of part of content of the pre-query rule and influence on determination of a pre-query result is avoided.
Example IV
The embodiment of the invention also provides a data query device, referring to fig. 6, the data query device includes:
the disassembly module 10 is configured to disassemble a target query task in response to a data query instruction, so as to obtain a plurality of sub-query tasks;
The matching module 20 is configured to match each sub-query task with a preset pre-query rule base;
a checking module 30, configured to check whether a target pre-query result of the sub-query task exists in a target data storage area associated with the target pre-query rule if a target pre-query rule matched with the sub-query task exists in the pre-query rule library;
a pre-query module 40, configured to take the target pre-query result as a data query result of the sub-query task if yes;
and the query module 50 is configured to execute the sub-query task if not, and obtain a data query result.
Optionally, the data query device further includes:
and storing the data query result as the target pre-query result to the target data storage area.
Optionally, the data query device further includes:
acquiring inquiry tasks contained in each pre-inquiry rule in the pre-inquiry rule base, and acquiring the size of a pre-occupied resource space of each inquiry task and the size of the residual resource space of an inquiry engine;
generating a query task set consisting of a plurality of query tasks according to the size of the residual resource space and the size of each pre-occupied resource space, wherein the total size of the occupied resource space of the query task set is smaller than or equal to the size of the residual resource space;
The pre-query results of the pre-query tasks are obtained by calling the pre-query rules corresponding to the pre-query tasks in the query task set to execute the pre-query tasks;
and if the pre-query result of the pre-query task does not exist in the data storage area associated with the pre-query task, storing the pre-query result into the data storage area.
Optionally, the data query device further includes:
acquiring the total resource space size and the occupied resource space size of the query engine, and calculating the ratio between the occupied resource space size and the total resource space to obtain the resource occupancy rate of the query engine;
and if the resource occupancy rate is checked to be smaller than the preset resource occupancy rate threshold value, executing the step of acquiring the query task contained in each preset query rule in the preset query rule library.
Optionally, the data query device further includes:
acquiring an initial query data set, and obtaining a query grammar corresponding to each initial query data by analyzing common data characteristics of each initial query data in the initial query data set;
acquiring a data access interface corresponding to each initial query data, associating all the initial query data with the query grammar and the data access interface corresponding to each initial query data, and generating each target query rule;
And in response to a pre-query rule base updating instruction, inserting each target query rule into the pre-query rule base to update the pre-query rule base.
Optionally, the data query device further includes:
acquiring a historical query task set of the query engine in a first preset period, wherein the historical query task set consists of a plurality of historical query tasks;
disassembling each history inquiry task to obtain a plurality of history sub inquiry tasks, and counting the number of each history sub inquiry task;
for any historical sub-query task, if the number of the historical sub-query tasks is verified to be larger than a preset number threshold, generating a target query rule based on the historical sub-query tasks and data access interfaces corresponding to the historical sub-query tasks;
and in response to a pre-query rule base updating instruction, inserting the target query rule into the pre-query rule base to update the pre-query rule base.
Optionally, the data query device further includes:
if the abnormal pre-query rule with the calling frequency smaller than the preset calling frequency threshold value exists in the pre-query rule base in the second preset period, checking whether the priority of the abnormal pre-query rule is smaller than the preset priority threshold value or not;
If yes, deleting the abnormal pre-query rule in the pre-query rule base;
if not, the priority of the abnormal pre-query rule is reduced.
Optionally, the data query device further includes:
checking whether a target pre-query rule matched with the sub-query task exists in the pre-query rule library;
and if the fact that the target pre-query rule matched with the sub-query task does not exist in the pre-query rule base is verified, executing the sub-query task to obtain a data query result.
The data query device provided by the invention adopts the data query method in the first embodiment or the second embodiment, and can solve the technical problem of low data query efficiency in the prior art. Compared with the prior art, the beneficial effects of the data query device provided by the embodiment of the invention are the same as those of the data query method provided by the embodiment, and other technical features in the data query device are the same as those disclosed by the method of the previous embodiment, so that the description is omitted herein.
Example five
The embodiment of the invention provides electronic equipment, which comprises: at least one processor; and a memory communicatively coupled to the at least one processor; the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor, so that the at least one processor can execute the data query method in the first embodiment.
Referring now to fig. 7, a schematic diagram of an electronic device suitable for use in implementing embodiments of the present disclosure is shown. The electronic devices in embodiments of the present disclosure may include, but are not limited to, mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (Personal Digital Assistant: personal digital assistants), PADs (Portable Application Description: tablet computers), PMPs (Portable Media Player: portable multimedia players), vehicle terminals (e.g., car navigation terminals), and the like, as well as stationary terminals such as digital TVs, desktop computers, and the like. The electronic device shown in fig. 7 is merely an example and should not be construed to limit the functionality and scope of use of the disclosed embodiments.
As shown in fig. 7, the electronic apparatus may include a processing device 1001 (e.g., a central processing unit, a graphics processor, or the like) that can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM) 1002 or a program loaded from a storage device 1003 into a random access Memory (RAM: random Access Memory) 1004. In the RAM1004, various programs and data required for the operation of the electronic device are also stored. The processing device 1001, the ROM1002, and the RAM1004 are connected to each other by a bus 1005. An input/output (I/O) interface 1006 is also connected to the bus. In general, the following systems may be connected to the I/O interface 1006: input devices 1007 including, for example, a touch screen, touchpad, keyboard, mouse, image sensor, microphone, accelerometer, gyroscope, and the like; an output device 1008 including, for example, a liquid crystal display (LCD: liquid Crystal Display), a speaker, a vibrator, and the like; storage device 1003 including, for example, a magnetic tape, a hard disk, and the like; and communication means 1009. The communication means 1009 may allow the electronic device to communicate with other devices wirelessly or by wire to exchange data. While electronic devices having various systems are shown in the figures, it should be understood that not all of the illustrated systems are required to be implemented or provided. More or fewer systems may alternatively be implemented or provided.
In particular, according to embodiments of the present disclosure, the processes described above with reference to flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method shown in the flowcharts. In such an embodiment, the computer program may be downloaded and installed from a network through a communication device, or installed from the storage device 1003, or installed from the ROM 1002. The above-described functions defined in the method of the embodiment of the present disclosure are performed when the computer program is executed by the processing device 1001.
The electronic equipment provided by the invention adopts the data query method in the embodiment, and can solve the technical problem of low data query efficiency in the prior art. Compared with the prior art, the electronic device provided by the embodiment of the invention has the same beneficial effects as the data query method provided by the embodiment, and other technical features in the electronic device are the same as the features disclosed by the method of the previous embodiment, and are not repeated herein.
It should be understood that portions of the present disclosure may be implemented in hardware, software, firmware, or a combination thereof. In the description of the above embodiments, particular features, structures, materials, or characteristics may be combined in any suitable manner in any one or more embodiments or examples.
The foregoing is merely illustrative of the present invention, and the present invention is not limited thereto, and any person skilled in the art will readily recognize that variations or substitutions are within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Example six
An embodiment of the present invention provides a computer readable storage medium having computer readable program instructions stored thereon for performing the data query method of the first embodiment.
The computer readable storage medium according to the embodiments of the present invention may be, for example, a usb disk, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, or device, or a combination of any of the foregoing. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access Memory (RAM: random Access Memory), a Read-Only Memory (ROM: read Only Memory), an erasable programmable Read-Only Memory (EPROM: erasable Programmable Read Only Memory or flash Memory), an optical fiber, a portable compact disc Read-Only Memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In this embodiment, a computer-readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, or device. Program code embodied on a computer readable storage medium may be transmitted using any appropriate medium, including but not limited to: wire, fiber optic cable, RF (Radio Frequency), and the like, or any suitable combination of the foregoing.
The above-described computer-readable storage medium may be contained in an electronic device; or may exist alone without being assembled into an electronic device.
The computer-readable storage medium carries one or more programs that, when executed by an electronic device, cause the electronic device to: responding to the data query instruction, and disassembling the target query task to obtain a plurality of sub-query tasks; matching each sub-query task with a preset pre-query rule base; if a target pre-query rule matched with the sub-query task exists in the pre-query rule library, checking whether a target pre-query result of the sub-query task exists in a target data storage area associated with the target pre-query rule; if yes, the target pre-query result is used as the data query result of the sub-query task; if not, executing the sub-query task to obtain a data query result.
Computer program code for carrying out operations of the present disclosure may be written in one or more programming languages, including an object oriented programming language such as Java, smalltalk, C ++ and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a local area network (LAN: local Area Network) or a wide area network (WAN: wide Area Network), or may be connected to an external computer (for example, through the Internet using an Internet service provider).
The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The modules described in the embodiments of the present disclosure may be implemented in software or hardware. Wherein the name of the module does not constitute a limitation of the unit itself in some cases.
The readable storage medium provided by the application is a computer readable storage medium, and the computer readable storage medium stores computer readable program instructions for executing the data query method, so that the technical problem of low data query efficiency in the prior art can be solved. Compared with the prior art, the beneficial effects of the computer readable storage medium provided by the embodiment of the present application are the same as those of the data query method provided by the first embodiment or the second embodiment, and are not described herein.
Example seven
The embodiment of the application also provides a computer program product, which comprises a computer program, wherein the computer program realizes the steps of the data query method when being executed by a processor.
The computer program product provided by the application can solve the technical problem of low data query efficiency in the prior art. Compared with the prior art, the beneficial effects of the computer program product provided by the embodiment of the present application are the same as those of the data query method provided by the first embodiment or the second embodiment, and are not described herein.
The foregoing description is only of the preferred embodiments of the present application, and is not intended to limit the scope of the application, but rather is intended to cover any equivalents of the structures or equivalent processes disclosed herein, or any application, directly or indirectly, within the scope of the application.
Claims (10)
1. A data query method, the data query method comprising:
responding to the data query instruction, and disassembling the target query task to obtain a plurality of sub-query tasks;
matching each sub-query task with a preset pre-query rule base;
if a target pre-query rule matched with the sub-query task exists in the pre-query rule library, checking whether a target pre-query result of the sub-query task exists in a target data storage area associated with the target pre-query rule;
if yes, the target pre-query result is used as the data query result of the sub-query task;
if not, executing the sub-query task to obtain a data query result.
2. The data query method of claim 1, wherein after the step of performing the sub-query task to obtain a data query result, the data query method further comprises:
and storing the data query result as the target pre-query result to the target data storage area.
3. The data query method of claim 1, wherein, before the step of disassembling the target query task to obtain a plurality of sub-query tasks in response to the data query instruction, the data query method further comprises:
Acquiring inquiry tasks contained in each pre-inquiry rule in the pre-inquiry rule base, and acquiring the size of a pre-occupied resource space of each inquiry task and the size of the residual resource space of an inquiry engine;
generating a query task set consisting of a plurality of query tasks according to the size of the residual resource space and the size of each pre-occupied resource space, wherein the total size of the occupied resource space of the query task set is smaller than or equal to the size of the residual resource space;
the pre-query results of the pre-query tasks are obtained by calling the pre-query rules corresponding to the pre-query tasks in the query task set to execute the pre-query tasks;
and if the pre-query result of the pre-query task does not exist in the data storage area associated with the pre-query task, storing the pre-query result into the data storage area.
4. The data query method of claim 3, wherein prior to the step of obtaining the query task contained in each pre-query rule in the pre-query rule base, the data query method further comprises:
acquiring the total resource space size and the occupied resource space size of the query engine, and calculating the ratio between the occupied resource space size and the total resource space to obtain the resource occupancy rate of the query engine;
And if the resource occupancy rate is checked to be smaller than the preset resource occupancy rate threshold value, executing the step of acquiring the query task contained in each preset query rule in the preset query rule library.
5. The data query method of claim 3, wherein prior to the step of obtaining the query task contained in each pre-query rule in the pre-query rule base, the data query method further comprises:
acquiring an initial query data set, and obtaining a query grammar corresponding to each initial query data by analyzing common data characteristics of each initial query data in the initial query data set;
acquiring a data access interface corresponding to each initial query data, associating all the initial query data with the query grammar and the data access interface corresponding to each initial query data, and generating each target query rule;
and in response to a pre-query rule base updating instruction, inserting each target query rule into the pre-query rule base to update the pre-query rule base.
6. The data query method of claim 3, wherein prior to the step of obtaining the query task contained in each pre-query rule in the pre-query rule base, the data query method further comprises:
Acquiring a historical query task set of the query engine in a first preset period, wherein the historical query task set consists of a plurality of historical query tasks;
disassembling each history inquiry task to obtain a plurality of history sub inquiry tasks, and counting the number of each history sub inquiry task;
for any historical sub-query task, if the number of the historical sub-query tasks is verified to be larger than a preset number threshold, generating a target query rule based on the historical sub-query tasks and data access interfaces corresponding to the historical sub-query tasks;
and in response to a pre-query rule base updating instruction, inserting the target query rule into the pre-query rule base to update the pre-query rule base.
7. The data query method of claim 5 or 6, wherein the data query method further comprises:
if the abnormal pre-query rule with the calling frequency smaller than the preset calling frequency threshold value exists in the pre-query rule base in the second preset period, checking whether the priority of the abnormal pre-query rule is smaller than the preset priority threshold value or not;
if yes, deleting the abnormal pre-query rule in the pre-query rule base;
If not, the priority of the abnormal pre-query rule is reduced.
8. The data query method of claim 1, wherein after the step of matching each sub-query task with a preset pre-query rule base, the data query method further comprises:
checking whether a target pre-query rule matched with the sub-query task exists in the pre-query rule library;
and if the fact that the target pre-query rule matched with the sub-query task does not exist in the pre-query rule base is verified, executing the sub-query task to obtain a data query result.
9. An electronic device, the electronic device comprising:
at least one processor; the method comprises the steps of,
a memory communicatively coupled to the at least one processor; wherein, the liquid crystal display device comprises a liquid crystal display device,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the steps of the data query method of any one of claims 1 to 8.
10. A readable storage medium, characterized in that the readable storage medium is a computer readable storage medium having stored thereon a program for realizing a data query method, the program for realizing the data query method being executed by a processor to realize the steps of the data query method according to any one of claims 1 to 8.
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