CN113220706A - Component product query method, device, equipment and medium - Google Patents
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Abstract
The invention discloses a component product query method, which comprises the following steps: by building a search server cluster, the traditional database integration data is firstly integrated into the search server cluster, and an interface is provided to realize high concurrency and quick query. The method is suitable for data query of tens of millions of levels in the component industry, and greatly improves the flexibility and accuracy of query. In addition, a device for querying a component product, equipment and a storage medium are also provided.
Description
Technical Field
The invention relates to the field of computer technology, in particular to a component product query method, a device, equipment and a medium.
Background
The semiconductor element is made of silicon, germanium or gallium arsenide, and can be used as a rectifier, an oscillator, a light emitter, an amplifier, a light detector and the like. Due to different functions of materials, the types of semiconductor devices are numerous, and parameters are different, so that it is very difficult for users to select proper semiconductor devices from the large number.
Disclosure of Invention
In view of the above, there is a need to provide a method, an apparatus, a device and a medium for querying a component product, which can quickly and accurately complete the query.
A method of component product querying, the method comprising:
building a search server cluster;
acquiring database integration data, and synchronizing a target index field in the database integration data with the search server cluster;
and calling an inquiry interface of the search server cluster to obtain input component keywords, splicing the component keywords into component inquiry sentences, sending the component inquiry sentences to the search server cluster for inquiry, and obtaining a component inquiry result returned by the search server cluster.
In one embodiment, the building a search server cluster includes:
deploying a development kit, and configuring system environment variables of the development kit;
downloading a search server installation package, decompressing and installing the search server installation package, and configuring a first configuration file of the search server cluster;
downloading a visual platform installation package, decompressing and installing the visual platform installation package, and modifying the second configuration file so as to search and view the index data of the search server cluster on the visual platform.
In one embodiment, the building a search server cluster further includes:
deleting the full-text index which cannot be associated to the directory as a waste index;
and acquiring a preset target capacity, and setting the number of fragments and the number of copies of the index set in the search server cluster according to the target capacity.
In one embodiment, the building a search server cluster further includes:
and installing a word segmentation device, and adjusting the step length of the word segmentation device to a target step length so as to delete the space word segmentation in the index data.
In one embodiment, the synchronizing the target index field in the database integration data with the search server cluster includes:
associating model, brand, parameter and stock keeping unit codes in the database consolidation data with model, brand, parameter and stock keeping unit codes in the cluster of search servers for full text indexing.
In one embodiment, the synchronizing the target index field in the database integration data with the search server cluster includes:
using a query statement to perform inter-partition query on the database integration data through a full synchronization plug-in, and synchronously outputting a query result to the search server cluster; or the like, or, alternatively,
and establishing a message monitoring queue, recording newly added component data different from the database integration data, and synchronizing a target index field in the newly added component data with the search server cluster.
In one embodiment, the step of splicing the component keywords into component query statements and sending the component query statements to the search server cluster for querying includes
Splicing the key words of the components into expressions in a specified form, and analyzing and assembling the expressions in the specified form to obtain query sentences of the components;
and sending the component query statement to the search server cluster for query.
A component product interrogation apparatus, the apparatus comprising:
the cluster building module is used for building a search server cluster;
the data synchronization module is used for acquiring database integration data and synchronizing a target index field in the database integration data with the search server cluster;
and the query module is used for calling a query interface of the search server cluster, acquiring input component keywords, splicing the component keywords into component query statements, sending the component query statements to the search server cluster for querying, and acquiring a component query result returned by the search server cluster.
A computer-readable storage medium storing a computer program which, when executed by a processor, causes the processor to perform the steps of:
building a search server cluster;
acquiring database integration data, and synchronizing a target index field in the database integration data with the search server cluster;
and calling an inquiry interface of the search server cluster to obtain input component keywords, splicing the component keywords into component inquiry sentences, sending the component inquiry sentences to the search server cluster for inquiry, and obtaining a component inquiry result returned by the search server cluster.
A computer device comprising a memory and a processor, the memory storing a computer program that, when executed by the processor, causes the processor to perform the steps of:
building a search server cluster;
acquiring database integration data, and synchronizing a target index field in the database integration data with the search server cluster;
and calling an inquiry interface of the search server cluster to obtain input component keywords, splicing the component keywords into component inquiry sentences, sending the component inquiry sentences to the search server cluster for inquiry, and obtaining a component inquiry result returned by the search server cluster.
The invention provides a method, a device, equipment and a medium for inquiring a component product. The method is suitable for data query of tens of millions of levels in the component industry, and greatly improves the flexibility and accuracy of query.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Wherein:
FIG. 1 is a schematic flow chart diagram illustrating a method for querying a device product, according to an embodiment;
FIG. 2 is a schematic diagram of a device for querying a component product according to an embodiment;
FIG. 3 is a block diagram of a computer device in one embodiment.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1, fig. 1 is a schematic flow chart of a component product query method in an embodiment, where the component product query method in this embodiment provides steps including:
and 102, building a search server cluster.
The built search server cluster in the embodiment is an elastic search (hereinafter referred to as es) cluster, and es is a Lucene-based distributed search engine, so that the distributed full-text search engine with multi-user capability is provided, and the near-real-time reliable query efficiency can be realized. The es cluster depends on JDK and NodeJS, and needs to firstly deploy a JVM development toolkit and configure system environment variables of the JVM development toolkit.
Then download the es installation package of the latest edition again, decompress the es installation package in installing the catalogue, run the executable file of elastic search. Whether the executable file was launched successfully is determined by the browser accessing a particular query page. But the display effect of the viewed content of the webpage is not friendly, the webpage can be improved by installing a head plug-in, and the head plug-in is connected with the es by modifying the first configuration file of the es, namely, the "yml".
In addition, the important parameters to be configured in the first configuration file further include: 1. name, cluster name, requires that the cluster names of different servers all have to be consistent. 2. name, node name, requires that different es node words must be different. 3. Minor _ master _ nodes, which represents the minimum number of masters of a cluster, and if the minimum master data of the cluster is less than a specified number, it will not be able to start, and the recommended node master is set to the cluster number/2 + 1. 4. The master server is mainly used for managing the cluster state and is responsible for metadata processing, such as index addition deletion, fragment distribution and the like, data storage and query cannot leave the master node, pressure is low, and jvm memory can be distributed to a lower point. 5. And (4) storing index data, wherein the configuration server is true. 6. True, lock physical memory, do not use swap memory, have swap memory can open this item.
Further, Kibana is a platform for es platform analysis and visualization, and index data stored in es can be searched and displayed by using Kibana. The data can be displayed and analyzed by using the method conveniently by using charts, tables and maps. When the Kibana plug-in is installed, a visualization platform (Kibana) installation package is downloaded and decompressed and installed, and a second configuration file Kibana.
On this basis, in order to reduce the occupied resources of the es cluster and improve the execution efficiency, the following steps can be further performed:
firstly, full-text index information of a current database is checked, full-text indexes which cannot be associated with the directory are deleted as waste indexes, and then the corresponding full-text index directory is deleted, so that resources occupied by the fragments are reduced.
And secondly, acquiring a preset target capacity, and changing and setting the number of fragments and the number of copies of the index set in the search server cluster according to the target capacity. Illustratively, the target capacity is set to be 1G, and 1 slice and 1 copy are set for an index set (below 1G) with a relatively small data size, so that the resource occupied by the slices is reduced. The data of the index set (1G and above) with a large data volume are configured into 3 fragments and 1 copy.
Thirdly, the default word segmentation device adopted by the es cluster is a single word segmentation device with poor effect, so that a more practical word segmentation device needs to be installed, and an IK word segmentation device is adopted. And installing an IK word segmentation device consistent with the es cluster version, and adjusting the step length of the IK word segmentation device to a target step length so as to delete the space word segmentation in the index data. Illustratively, the IK tokenizer, which originally has a step size of 1-100, includes space tokenization, is now changed to 3-100 step size space non-tokenization, which effectively reduces the number of tokens by 22%.
And 104, acquiring database integration data, and synchronizing a target index field in the database integration data with the search server cluster.
In this embodiment, index fields such as model number, brand number, parameter and stock minimum unit code are created in the cluster of search servers, and the model number, brand number, parameter and stock minimum unit code in the database integration data are associated with the model number, brand number, parameter and stock minimum unit code in the cluster of search servers by full-text index.
When the full-quantity synchronous data synchronization mode is selected, the full-quantity synchronous plug-in is used for carrying out partition inquiry on database integrated data by using an inquiry statement and synchronously outputting an inquiry result to the search server cluster. Specifically, the database integration data is read in a loop to synchronize the database integration data to the es index. The common plug-in is logstack-input-jdbc, and logstack queries data in different partitions through sql statements and then outputs the query data to es for implementation.
When an increment synchronous data synchronization mode is selected, a rabmq message monitoring queue is created, newly added component data different from database integration data are recorded, data in es are pulled and updated according to specified time, and increment synchronous updating of the data to the es index is achieved. Specifically, a folder is newly created, for example, mysql, a jar package of the connection of the database is placed under the folder, and then a jdbc. The sql _ last _ value is to pull the data in the update es at a specified time after the id is changed, and write the result of sql execution into the stream. The incremental acquisition mode is not synchronized in a binlog mode, an incremental field is used as a condition for query, the current query position is recorded each time, and due to the incremental characteristic, all the increments in the period of time can be acquired only by querying records larger than the current record, so that incremental synchronization updating data is realized.
And 106, calling a query interface of the search server cluster, acquiring input component keywords, splicing the component keywords into component query sentences, sending the component query sentences to the search server cluster for query, and acquiring a component query result returned by the search server cluster.
And developing an external query interface for connecting the es through a golang language. When the components are queried, an external query interface of the es is called, input component keywords such as a specific model and a specific brand are obtained, the component keywords are spliced into an expression in a specified form, and the expression in the specified form is analyzed and assembled to obtain a component query statement (query statement). The specified expression format may be: field > value & (field value | field < ═ value), where | corresponds to or and &, & corresponds to and. And the server background receives and analyzes the specified expression query statement sent by the foreground, assembles the query statement of es according to the expression and sends the query statement to the search server cluster for query. When a single field is queried, the result is a dimensional query; when multiple fields are queried, the result is a multiple-dimension query. If there are multiple field queries, the queries are combined.
In this embodiment, the es index field needs to be segmented, and the rules for Chinese segmentation and English segmentation are different. The Chinese word segmentation is carried out by using an ik Chinese word segmentation rule and needs to solve the problem of semantic analysis. The English word segmentation is to customize the trigrams _ filter English word segmentation rule aiming at the analyzer, the English word segmentation rule needs to be judged by integrating 'letter', 'digit', 'punctration', 'symbol', 'whitespace', and min _ gram and max _ gram need to be defined according to the service condition. In addition, component model segmentation follows minimum granularity segmentation.
According to the component product query, the search server cluster is built, the traditional database integration data is firstly integrated into the search server cluster, and an interface is provided to realize high concurrency and quick query. The method is suitable for data query of tens of millions of levels in the component industry, and greatly improves the flexibility and accuracy of query.
In one embodiment, as shown in fig. 2, a device for component product query is provided, the device including:
a cluster building module 202, configured to build a search server cluster;
the data synchronization module 204 is used for acquiring database integration data and synchronizing a target index field in the database integration data with the search server cluster;
the query module 206 is configured to invoke a query interface of the search server cluster, obtain input component keywords, splice the component keywords into a component query statement, send the component query statement to the search server cluster for querying, and obtain a component query result returned by the search server cluster.
According to the device for inquiring the component products, the traditional database integration data is firstly integrated to the search server cluster by building the search server cluster, and an interface is provided to realize high concurrency and quick inquiry. The method is suitable for data query of tens of millions of levels in the component industry, and greatly improves the flexibility and accuracy of query.
In an embodiment, the cluster building module 202 is specifically configured to: deploying a development kit, and configuring system environment variables of the development kit; downloading a search server installation package, decompressing and installing the search server installation package, and configuring a first configuration file of a search server cluster; and downloading the visual platform installation package, decompressing and installing the visual platform installation package, and modifying the second configuration file so as to search and view the index data of the search server cluster on the visual platform.
In an embodiment, the cluster building module 202 is further specifically configured to: deleting the full-text index which cannot be associated to the directory as a waste index; and acquiring a preset target capacity, and setting the number of fragments and the number of copies of the index set in the search server cluster according to the target capacity.
In an embodiment, the cluster building module 202 is further specifically configured to: and installing a word segmentation device, and adjusting the step length of the word segmentation device to a target step length so as to delete the space word segmentation in the index data.
In an embodiment, the data synchronization module 204 is specifically configured to: the model number, brand name, parameter and stock keeping unit codes in the database consolidation data are associated with the model number, brand name, parameter and stock keeping unit codes in the search server cluster through full text indexing.
In an embodiment, the data synchronization module 204 is further specifically configured to: carrying out interval query on database integration data by using a query statement through a full-scale synchronization plug-in, and synchronously outputting a query result to a search server cluster; or, creating a message monitoring queue, recording newly added component data different from the database integration data, and synchronizing a target index field in the newly added component data with the search server cluster.
In one embodiment, the query module 206 is specifically configured to: splicing the key words of the components into expressions in a specified form, and analyzing and assembling the expressions in the specified form to obtain query sentences of the components; and sending the element query statement to the search server cluster for query.
FIG. 3 is a diagram illustrating an internal structure of a computer device in one embodiment. As shown in fig. 3, the computer device includes a processor, a memory, and a network interface connected by a system bus. Wherein the memory includes a non-volatile storage medium and an internal memory. The non-volatile storage medium of the computer device stores an operating system and also stores a computer program, and when the computer program is executed by a processor, the computer program can enable the processor to realize the component product query method. The internal memory may also have a computer program stored therein, which when executed by the processor, causes the processor to perform the component product querying method. Those skilled in the art will appreciate that the architecture shown in fig. 3 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, the processor implementing the following steps when executing the computer program: building a search server cluster; acquiring database integration data, and synchronizing a target index field in the database integration data with a search server cluster; and calling an inquiry interface of the search server cluster, acquiring input component keywords, splicing the component keywords into component inquiry sentences, sending the component inquiry sentences to the search server cluster for inquiry, and acquiring a component inquiry result returned by the search server cluster.
In one embodiment, building a cluster of search servers includes: deploying a development kit, and configuring system environment variables of the development kit; downloading a search server installation package, decompressing and installing the search server installation package, and configuring a first configuration file of a search server cluster; and downloading the visual platform installation package, decompressing and installing the visual platform installation package, and modifying the second configuration file so as to search and view the index data of the search server cluster on the visual platform.
In one embodiment, building the search server cluster further comprises: deleting the full-text index which cannot be associated to the directory as a waste index; and acquiring a preset target capacity, and setting the number of fragments and the number of copies of the index set in the search server cluster according to the target capacity.
In one embodiment, building the search server cluster further comprises: and installing a word segmentation device, and adjusting the step length of the word segmentation device to a target step length so as to delete the space word segmentation in the index data.
In one embodiment, synchronizing a target index field in database consolidation data with a cluster of search servers includes: the model number, brand name, parameter and stock keeping unit codes in the database consolidation data are associated with the model number, brand name, parameter and stock keeping unit codes in the search server cluster through full text indexing.
In one embodiment, synchronizing a target index field in database consolidation data with a cluster of search servers includes: carrying out interval query on database integration data by using a query statement through a full-scale synchronization plug-in, and synchronously outputting a query result to a search server cluster; or, creating a message monitoring queue, recording newly added component data different from the database integration data, and synchronizing a target index field in the newly added component data with the search server cluster.
In one embodiment, splicing the component keywords into a component query statement, and sending the component query statement to a search server cluster for querying, includes: splicing the key words of the components into expressions in a specified form, and analyzing and assembling the expressions in the specified form to obtain query sentences of the components; and sending the element query statement to the search server cluster for query.
A computer-readable storage medium storing a computer program which, when executed by a processor, performs the steps of: building a search server cluster; acquiring database integration data, and synchronizing a target index field in the database integration data with a search server cluster; and calling an inquiry interface of the search server cluster, acquiring input component keywords, splicing the component keywords into component inquiry sentences, sending the component inquiry sentences to the search server cluster for inquiry, and acquiring a component inquiry result returned by the search server cluster.
In one embodiment, building a cluster of search servers includes: deploying a development kit, and configuring system environment variables of the development kit; downloading a search server installation package, decompressing and installing the search server installation package, and configuring a first configuration file of a search server cluster; and downloading the visual platform installation package, decompressing and installing the visual platform installation package, and modifying the second configuration file so as to search and view the index data of the search server cluster on the visual platform.
In one embodiment, building the search server cluster further comprises: deleting the full-text index which cannot be associated to the directory as a waste index; and acquiring a preset target capacity, and setting the number of fragments and the number of copies of the index set in the search server cluster according to the target capacity.
In one embodiment, building the search server cluster further comprises: and installing a word segmentation device, and adjusting the step length of the word segmentation device to a target step length so as to delete the space word segmentation in the index data.
In one embodiment, synchronizing a target index field in database consolidation data with a cluster of search servers includes: the model number, brand name, parameter and stock keeping unit codes in the database consolidation data are associated with the model number, brand name, parameter and stock keeping unit codes in the search server cluster through full text indexing.
In one embodiment, synchronizing a target index field in database consolidation data with a cluster of search servers includes: carrying out interval query on database integration data by using a query statement through a full-scale synchronization plug-in, and synchronously outputting a query result to a search server cluster; or, creating a message monitoring queue, recording newly added component data different from the database integration data, and synchronizing a target index field in the newly added component data with the search server cluster.
In one embodiment, splicing the component keywords into a component query statement, and sending the component query statement to a search server cluster for querying, includes: splicing the key words of the components into expressions in a specified form, and analyzing and assembling the expressions in the specified form to obtain query sentences of the components; and sending the element query statement to the search server cluster for query.
It should be noted that the method, the apparatus, the device and the computer-readable storage medium for querying a component product belong to a general inventive concept, and the contents in the embodiments of the method, the apparatus, the device and the computer-readable storage medium for querying a component product are applicable to each other.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a non-volatile computer-readable storage medium, and can include the processes of the embodiments of the methods described above when the program is executed. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (esDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and bus dynamic RAM (RDRAM).
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above examples only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present application. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A method for querying a component product, the method comprising:
building a search server cluster;
acquiring database integration data, and synchronizing a target index field in the database integration data with the search server cluster;
and calling an inquiry interface of the search server cluster to obtain input component keywords, splicing the component keywords into component inquiry sentences, sending the component inquiry sentences to the search server cluster for inquiry, and obtaining a component inquiry result returned by the search server cluster.
2. The method of claim 1, wherein building a cluster of search servers comprises:
deploying a development kit, and configuring system environment variables of the development kit;
downloading a search server installation package, decompressing and installing the search server installation package, and configuring a first configuration file of the search server cluster;
downloading a visual platform installation package, decompressing and installing the visual platform installation package, and modifying the second configuration file so as to search and view the index data of the search server cluster on the visual platform.
3. The method of claim 2, wherein building a cluster of search servers further comprises:
deleting the full-text index which cannot be associated to the directory as a waste index;
and acquiring a preset target capacity, and setting the number of fragments and the number of copies of the index set in the search server cluster according to the target capacity.
4. The method of claim 2, wherein building a cluster of search servers further comprises:
and installing a word segmentation device, and adjusting the step length of the word segmentation device to a target step length so as to delete the space word segmentation in the index data.
5. The method of claim 1, wherein synchronizing the target index field in the database integration data with the cluster of search servers comprises:
associating model, brand, parameter and stock keeping unit codes in the database consolidation data with model, brand, parameter and stock keeping unit codes in the cluster of search servers for full text indexing.
6. The method of claim 1, wherein synchronizing the target index field in the database integration data with the cluster of search servers comprises:
using a query statement to perform inter-partition query on the database integration data through a full synchronization plug-in, and synchronously outputting a query result to the search server cluster; or the like, or, alternatively,
and establishing a message monitoring queue, recording newly added component data different from the database integration data, and synchronizing a target index field in the newly added component data with the search server cluster.
7. The method of claim 1, wherein the splicing the component keywords into a component query statement and sending the component query statement to the search server cluster for querying comprises:
splicing the key words of the components into expressions in a specified form, and analyzing and assembling the expressions in the specified form to obtain query sentences of the components;
and sending the component query statement to the search server cluster for query.
8. A component product query device, the device comprising:
the cluster building module is used for building a search server cluster;
the data synchronization module is used for acquiring database integration data and synchronizing a target index field in the database integration data with the search server cluster;
and the query module is used for calling a query interface of the search server cluster, acquiring input component keywords, splicing the component keywords into component query statements, sending the component query statements to the search server cluster for querying, and acquiring a component query result returned by the search server cluster.
9. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, causes the processor to carry out the steps of the method according to any one of claims 1 to 7.
10. A computer device comprising a memory and a processor, characterized in that the memory stores a computer program which, when executed by the processor, causes the processor to carry out the steps of the method according to any one of claims 1 to 7.
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| CN116431734A (en) * | 2023-06-12 | 2023-07-14 | 成都信息工程大学 | Method, system and storage medium for synchronizing es data in real time |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116431734A (en) * | 2023-06-12 | 2023-07-14 | 成都信息工程大学 | Method, system and storage medium for synchronizing es data in real time |
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