CN112948427B - Data query method, device, equipment and storage medium - Google Patents
Data query method, device, equipment and storage medium Download PDFInfo
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
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- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
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- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/22—Indexing; Data structures therefor; Storage structures
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- G06F30/00—Computer-aided design [CAD]
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Abstract
The invention relates to a data processing technology, and discloses a data query method, which comprises the following steps: the method comprises the steps of carrying out identification analysis on an engineering source file set to obtain engineering identifications, carrying out data separation on the engineering source file set by utilizing the engineering identifications to obtain attribute information and geometric information, carrying out attribute storage on the attribute information to obtain an attribute storage table, constructing a database cluster by utilizing the attribute storage table, storing the geometric information into a pre-constructed object database, packaging the object database and the database cluster by utilizing a preset service layer to obtain a query service layer, obtaining data query information, and carrying out analysis on the data query information by utilizing the query service layer to obtain a data query result. In addition, the invention also relates to a blockchain technology, and the data query result can be stored in a node of the blockchain. The invention also provides a data query device, electronic equipment and a computer readable storage medium. The invention can solve the problem of low data query efficiency.
Description
Technical Field
The present invention relates to the field of data processing technologies, and in particular, to a data query method, a data query device, an electronic device, and a computer readable storage medium.
Background
The building information model (Building Information Modeling, BIM) information base focuses on the management of the whole life cycle of a building, emphasizes that the digital technology is utilized to provide a complete building engineering information base for the building model. The information base contains not only geometric information describing the building elements, but also professional properties of the elements and spatial state information associated with the building elements. The BIM digital-analog separation system is an important technology and tool in a BIM information base, and separates and independently manages geometric information and other professional attribute data of a building model according to data characteristics.
At present, the management of BIM professional attribute data by a traditional BIM platform system has the following challenges and problems: 1. with the continuous development of building engineering, building models are more and more complex, and component properties are more and more huge. The building model of one project is now millions of components, each component has about tens of attribute data, and the BIM platform needs to store and manage massive professional attribute data, so that the storage space is greatly occupied. 2. In the traditional BIM platform, the association of the model data and the professional attribute data is only bound by means of the service Id of the component, and the association and the query based on the spatial relationship cannot be flexibly and efficiently realized, so that the data query efficiency is lower.
Disclosure of Invention
The invention provides a data query method, a data query device and a computer readable storage medium, which mainly aim to solve the problem of low data query efficiency.
In order to achieve the above object, the present invention provides a data query method, including:
acquiring an engineering source file set, and carrying out identification analysis on the engineering source file set to obtain an engineering identification;
carrying out data separation on the engineering source file set by utilizing the engineering identifier to obtain attribute information and geometric information;
performing attribute storage on the attribute information to obtain an attribute storage table, and constructing a database cluster by using the attribute storage table;
storing the geometric information into a pre-constructed object database, and packaging the object database and the database cluster by using a preset service layer to obtain a query service layer;
and acquiring data query information, and analyzing the data query information by utilizing the query service layer to obtain a data query result.
Optionally, the performing the identification parsing on the engineering source file to obtain an engineering identification includes:
sequentially analyzing each engineering source file in the engineering source file set by utilizing a pre-constructed engineering management platform to obtain a unique identifier of each engineering source file;
and taking the unique identification as an engineering identification of the corresponding engineering source file.
Optionally, the data separation is performed on the engineering source file set by using the engineering identifier to obtain attribute information and geometric information, including:
utilizing a digital-analog separation module in the engineering management platform to identify and identify the engineering identifier;
and separating data and a model from the source file with the same engineering identifier to obtain attribute information of the component and geometric information of the component.
Optionally, the storing the attribute information to obtain an attribute storage table includes:
acquiring a preset attribute extraction field;
extracting the attribute of the component with the same engineering identifier by utilizing the attribute extraction field to obtain a component attribute, wherein the component attribute comprises a component space attribute;
and carrying out sub-table storage on the constructed attributes to obtain the attribute storage table.
Optionally, the performing sub-table storage on the constructed attribute to obtain the attribute storage table includes:
performing character conversion on the engineering identifier to obtain a sub-table ID;
and based on the sub-table ID, performing sub-table storage on the constructed attribute with the same engineering identifier to obtain the attribute storage table.
Optionally, the constructing a database cluster by using the attribute storage table includes:
storing the attribute storage table in a pre-constructed cluster master node and a pre-constructed cluster standby node;
summarizing the cluster main node, the standby node and the pre-constructed arbitration node to obtain the database cluster.
Optionally, the acquiring the data query information, analyzing the data query information by using the query service layer to obtain a data query result, includes:
acquiring data query information, wherein the data query information comprises an attribute index, a spatial index and a geometric index;
calling an attribute query interface and a geometric query interface of the query service layer;
analyzing the attribute index and the spatial index by using the attribute query interface to obtain attribute information, wherein the attribute information comprises component spatial attributes, and analyzing the geometric index by using the geometric query interface to obtain geometric information;
and summarizing the geometric information and the attribute information to obtain the data query result.
In order to solve the above problems, the present invention further provides a data query device, including:
the identification analysis module is used for acquiring an engineering source file set, and carrying out identification analysis on the engineering source file set to obtain an engineering identification;
the data separation module is used for carrying out data separation on the engineering source file set by utilizing the engineering identifier to obtain attribute information and geometric information;
the attribute storage module is used for carrying out attribute storage on the attribute information to obtain an attribute storage table, and constructing a database cluster by utilizing the attribute storage table;
the data packaging module is used for storing the geometric information into a pre-constructed object database, and packaging the object database and the database cluster by utilizing a preset service layer to obtain a query service layer;
and the data query module is used for acquiring data query information, and analyzing the data query information by utilizing the query service layer to obtain a data query result.
In order to solve the above-mentioned problems, the present invention also provides an electronic apparatus including:
a memory storing at least one instruction; and
And the processor executes the instructions stored in the memory to realize the data query method.
In order to solve the above-mentioned problems, the present invention also provides a computer-readable storage medium having stored therein at least one instruction that is executed by a processor in an electronic device to implement the above-mentioned data query method.
According to the invention, the engineering identification is obtained by carrying out identification analysis on the engineering source file set, and the engineering identification is utilized to carry out data separation on the engineering source file set, so that the accuracy of data separation can be ensured due to the uniqueness of the engineering identification. And the obtained attribute information and geometric information are stored separately, so that the occupation of the storage space can be reduced. Meanwhile, the attribute information contains the spatial attribute of the component, so that the obtained attribute storage table can efficiently and rapidly inquire the spatial relationship. Therefore, the data query method, the data query device, the electronic equipment and the computer readable storage medium can solve the problem of low data query efficiency.
Drawings
FIG. 1 is a flow chart of a data query method according to an embodiment of the present invention;
FIG. 2 is a detailed flow chart of one of the steps shown in FIG. 1;
FIG. 3 is a detailed flow chart of another step of FIG. 1;
FIG. 4 is a detailed flow chart of another step of FIG. 1;
FIG. 5 is a detailed flow chart of another step of FIG. 1;
FIG. 6 is a functional block diagram of a data query device according to an embodiment of the present invention;
fig. 7 is a schematic structural diagram of an electronic device for implementing the data query method according to an embodiment of the present invention.
The achievement of the objects, functional features and advantages of the present invention will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
The embodiment of the application provides a data query method. The execution subject of the data query method includes, but is not limited to, at least one of a server, a terminal, and the like, which can be configured to execute the method provided by the embodiments of the present application. In other words, the data query method may be performed by software or hardware installed in a terminal device or a server device, and the software may be a blockchain platform. The service end includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, and the like.
Referring to fig. 1, a flow chart of a data query method according to an embodiment of the invention is shown. In this embodiment, the data query method includes:
s1, acquiring an engineering source file set, and carrying out identification analysis on the engineering source file set to obtain an engineering identification.
In the embodiment of the present invention, the engineering source file set may be a source file set of a building information model (Building Information Modeling, abbreviated as BIM), and includes files with suffixes of rvt., ifc. The building information model is a datamation tool applied to engineering design, construction and management, is shared and transmitted in the whole life cycle process of project planning, operation and maintenance through integrating datamation and informatization models of buildings, and is characterized in that a virtual building engineering three-dimensional model is established, and a complete building engineering information base consistent with actual conditions is provided for the model by utilizing a digitalization technology.
Specifically, referring to fig. 2, the performing the identification analysis on the engineering source file set to obtain an engineering identification includes:
s10, sequentially analyzing each engineering source file in the engineering source file set by utilizing a pre-constructed engineering management platform to obtain a unique identifier of each engineering source file;
s11, taking the unique identification as an engineering identification of a corresponding engineering source file.
In the embodiment of the present invention, the pre-constructed engineering management platform may be a BIM (building information model, building Information Modeling) management platform, where the BIM management platform is used to store a million-level BIM model, and store and manage massive building elements in the BIM model, professional attribute data of the building elements, space state information of the building elements, and other data.
In an optional embodiment of the present invention, the unique identifier may be a GUID identifier of an item, and since different BIM source files belong to different engineering items, each item has a globally unique GUID to identify, and the unique identifier is used as an engineering identifier of a corresponding engineering source file, so that efficiency and accuracy of data retrieval may be improved.
S2, carrying out data separation on the engineering source file set by utilizing the engineering identifier to obtain attribute information and geometric information.
In the embodiment of the present invention, the attribute information may be attribute information of building elements in a BIM source file, including: building element professional attribute information, building element space state information and the like. The geometric information may be geometric information of building elements in a BIM source file, including: building models, building component models, and the like.
Specifically, referring to fig. 3, the step of performing data separation on the engineering source file set by using the engineering identifier to obtain attribute information and geometric information includes:
s20, carrying out identification recognition on the engineering identifier by utilizing a digital-analog separation module in the engineering management platform;
s21, carrying out data and model separation on the source file with the same engineering identifier to obtain attribute information of the component and geometric information of the component.
In an alternative embodiment of the present invention, the digital-analog separation module may be a BIM digital-analog separation system, where the BIM digital-analog separation system is an important technology and tool in a BIM management platform, and may separate and independently manage geometric information of a building model and professional attribute data of other building components according to data characteristics. The components refer to building components constituting the BIM model, such as walls, doors, stairs, columns, etc.
And S3, performing attribute storage on the attribute information to obtain an attribute storage table, and constructing a database cluster by using the attribute storage table.
In the embodiment of the present invention, referring to fig. 4, the storing the attribute information to obtain an attribute storage table includes:
s30, acquiring a preset attribute extraction field;
s31, extracting the attribute of the component with the same engineering identifier by utilizing the attribute extraction field to obtain a component attribute, wherein the component attribute comprises a component space attribute;
s32, performing sub-table storage on the constructed attributes to obtain the attribute storage table.
In an alternative embodiment of the present invention, the database cluster may be a mondab cluster. The preset attribute extraction field includes: projectguide: the GUID is used for extracting the item to which the component belongs; modelGuid: extracting GUID of the model to which the component belongs; elementId: for extracting Id of the component; elementType: to extract component family types; properties: the attribute array used for extracting the component is a categoriname: category name, category id, used to extract attributes: category Id, attributes used to extract attributes: the specific attribute value list used to extract the attribute, name: to extract attribute names, value: for extracting attribute values; loc is used to extract the spatial position information of the component, and the type is extended GeoJSON, type: mongo native GeoJSON object types, coordinates: coordinate information of GeoJSON, z: the custom GeoJSON extension attribute is used for improving the spatial index of Mongo so as to support the three-dimensional spatial index.
In the embodiment of the invention, the original GeoJSON of the MongoDB only supports two-dimensional position information; extending it here increases the z-component and creates a 2 dspere type spatial index on the loc field; while an ascending index is created on the loc.z field. When searching, the range query of the space query statement and the z component is combined, and a component list and an attribute list in a specific space range can be efficiently screened.
Specifically, the step of performing sub-table storage on the constructed attribute to obtain the attribute storage table includes:
performing character conversion on the engineering identifier to obtain a sub-table ID;
and based on the sub-table ID, performing sub-table storage on the constructed attribute with the same engineering identifier to obtain the attribute storage table.
In an alternative embodiment of the present invention, the engineering identifier (i.e. projectguide) may be converted into two 64-bit integer x, y, and then a preset formula f (x, y, n) = ((x mod n) × (y mod n)) mod n, where n represents the number of preset attribute storage tables.
In detail, the constructing a database cluster by using the attribute storage table includes:
storing the attribute storage table in a pre-constructed cluster master node and a pre-constructed cluster standby node;
summarizing the cluster main node, the standby node and the pre-constructed arbitration node to obtain the database cluster.
In an optional embodiment of the present invention, the database cluster may be a mondab cluster, where the mondab cluster includes: master node (mongdb (M)), standby node (mongdb (S)) and arbitration node (mongdb (a)). The master node and the standby node store data, the arbitrating node does not store data, and the master node provides all the services of adding, deleting, checking and modifying under the default setting, and the standby node does not provide any service, but can provide query service by setting so as to reduce the pressure of the master node. An arbitration node is a special node that does not itself store data, and the main function is to decide which standby node is promoted to be the master node after the master node hangs up.
In the embodiment of the invention, the spatial information of the components is stored in the attribute storage table, so that the association and the query based on the spatial relationship of the components can be flexibly and efficiently realized.
And S4, storing the geometric information into a pre-constructed object database, and packaging the object database and the database cluster by using a preset service layer to obtain a query service layer.
In the embodiment of the invention, the pre-constructed object database can be an object storage database AWS S3, the AWS S3 can store data (geometric information) as an object, and an engineering identifier is used as a unique identifier of the object, and the engineering identifier is used for realizing object inquiry.
In an optional embodiment of the present invention, the preset service layer may be an API layer, and the API layer may provide various attributes and component query interfaces according to service requirements.
S5, acquiring data query information, and analyzing the data query information by utilizing the query service layer to obtain a data query result.
Specifically, referring to fig. 5, the obtaining the data query information, analyzing the data query information by using the query service layer, to obtain a data query result includes:
s50, acquiring data query information, wherein the data query information comprises an attribute index, a spatial index and a geometric index;
s51, calling an attribute query interface and a geometric query interface of the query service layer;
s52, analyzing the attribute index and the spatial index by using the attribute query interface to obtain attribute information, wherein the attribute information comprises component spatial attributes, and analyzing the geometric index by using the geometric query interface to obtain geometric information;
and S53, summarizing the geometric information and the attribute information to obtain the data query result.
In the embodiment of the present invention, for example, all attributes of all gates of a floor are queried, and a native $geowithin query statement and loc.z component are combined in the query statement: { $and [ { loc { $geoWithin { $geometry { type } "Polygon", cordinates [ [ [0,0], [10,10], [0,0] ] } } }, { $and [ { loc. Z "{ { $gt:0}, { loc. Z" { { $lt:3} } } } } } }, { "properties: { $eq }" Door "}, where $geoWithIn is the original query statement of MongoDB, loc. Z represents the spatial index.
In the embodiment of the invention, the spatial state information of the component is stored in the attribute storage table as one attribute (namely, the spatial attribute), and the spatial attribute is inquired through the spatial index, so that the inquiry of the spatial information of the three-dimensional data can be realized through the MongoDB two-dimensional spatial index, and the inquiry efficiency is greatly improved.
According to the invention, the engineering identification is obtained by carrying out identification analysis on the engineering source file set, and the engineering identification is utilized to carry out data separation on the engineering source file set, so that the accuracy of data separation can be ensured due to the uniqueness of the engineering identification. And the obtained attribute information and geometric information are stored separately, so that the occupation of the storage space can be reduced. Meanwhile, the attribute information contains the spatial attribute of the component, so that the obtained attribute storage table can efficiently and rapidly inquire the spatial relationship. Therefore, the embodiment of the invention can solve the problem of low data query efficiency.
Fig. 6 is a functional block diagram of a data query device according to an embodiment of the present invention.
The data query device 100 of the present invention may be installed in an electronic apparatus. Depending on the implemented functionality, the data querying device 100 may include an identification resolution module 101, a data separation module 102, an attribute storage module 103, a data encapsulation module 104, and a data querying module 105. The module of the invention, which may also be referred to as a unit, refers to a series of computer program segments, which are stored in the memory of the electronic device, capable of being executed by the processor of the electronic device and of performing a fixed function.
In the present embodiment, the functions concerning the respective modules/units are as follows:
the identification analysis module 101 is configured to obtain an engineering source file set, and perform identification analysis on the engineering source file set to obtain an engineering identification.
In the embodiment of the present invention, the engineering source file set may be a source file set of a building information model (Building Information Modeling, abbreviated as BIM), and includes files with suffixes of rvt., ifc. The building information model is a datamation tool applied to engineering design, construction and management, is shared and transmitted in the whole life cycle process of project planning, operation and maintenance through integrating datamation and informatization models of buildings, and is characterized in that a virtual building engineering three-dimensional model is established, and a complete building engineering information base consistent with actual conditions is provided for the model by utilizing a digitalization technology.
Specifically, the identifier parsing module 101 obtains the engineering identifier by:
sequentially analyzing each engineering source file in the engineering source file set by utilizing a pre-constructed engineering management platform to obtain a unique identifier of each engineering source file;
and taking the unique identification as an engineering identification of the corresponding engineering source file.
In the embodiment of the present invention, the pre-constructed engineering management platform may be a BIM (building information model, building Information Modeling) management platform, where the BIM management platform is used to store a million-level BIM model, and store and manage massive building elements in the BIM model, professional attribute data of the building elements, space state information of the building elements, and other data.
In an optional embodiment of the present invention, the unique identifier may be a GUID identifier of an item, and since different BIM source files belong to different engineering items, each item has a globally unique GUID to identify, and the unique identifier is used as an engineering identifier of a corresponding engineering source file, so that efficiency and accuracy of data retrieval may be improved.
The data separation module 102 is configured to perform data separation on the engineering source file set by using the engineering identifier to obtain attribute information and geometric information.
In the embodiment of the present invention, the attribute information may be attribute information of building elements in a BIM source file, including: building element professional attribute information, building element space state information and the like. The geometric information may be geometric information of building elements in a BIM source file, including: building models, building component models, and the like.
Specifically, the data separation module 102 obtains attribute information and geometric information by:
utilizing a digital-analog separation module in the engineering management platform to identify and identify the engineering identifier;
and separating data and a model from the source file with the same engineering identifier to obtain attribute information of the component and geometric information of the component.
In an alternative embodiment of the present invention, the digital-analog separation module may be a BIM digital-analog separation system, where the BIM digital-analog separation system is an important technology and tool in a BIM management platform, and may separate and independently manage geometric information of a building model and professional attribute data of other building components according to data characteristics. The components refer to building components constituting the BIM model, such as walls, doors, stairs, columns, etc.
The attribute storage module 103 is configured to perform attribute storage on the attribute information to obtain an attribute storage table, and construct a database cluster by using the attribute storage table.
In the embodiment of the present invention, the attribute storage module 103 obtains the attribute storage table by:
acquiring a preset attribute extraction field;
extracting the attribute of the component with the same engineering identifier by utilizing the attribute extraction field to obtain a component attribute, wherein the component attribute comprises a component space attribute;
and carrying out sub-table storage on the constructed attributes to obtain the attribute storage table.
In an alternative embodiment of the present invention, the database cluster may be a mondab cluster. The preset attribute extraction field includes: projectguide: the GUID is used for extracting the item to which the component belongs; modelGuid: extracting GUID of the model to which the component belongs; elementId: for extracting Id of the component; elementType: to extract component family types; properties: the attribute array used for extracting the component is a categoriname: category name, category id, used to extract attributes: category Id, attributes used to extract attributes: the specific attribute value list used to extract the attribute, name: to extract attribute names, value: for extracting attribute values; loc is used to extract the spatial position information of the component, and the type is extended GeoJSON, type: mongo native GeoJSON object types, coordinates: coordinate information of GeoJSON, z: the custom GeoJSON extension attribute is used for improving the spatial index of Mongo so as to support the three-dimensional spatial index.
In the embodiment of the invention, the original GeoJSON of the MongoDB only supports two-dimensional position information; extending it here increases the z-component and creates a 2 dspere type spatial index on the loc field; while an ascending index is created on the loc.z field. When searching, the range query of the space query statement and the z component is combined, and a component list and an attribute list in a specific space range can be efficiently screened.
Specifically, the attribute storage module 103 obtains the attribute storage table by:
performing character conversion on the engineering identifier to obtain a sub-table ID;
and based on the sub-table ID, performing sub-table storage on the constructed attribute with the same engineering identifier to obtain the attribute storage table.
In an alternative embodiment of the present invention, the engineering identifier (i.e. projectguide) may be converted into two 64-bit integer x, y, and then a preset formula f (x, y, n) = ((x mod n) × (y mod n)) mod n, where n represents the number of preset attribute storage tables.
Specifically, the attribute storage module 103 builds a database cluster by:
storing the attribute storage table in a pre-constructed cluster master node and a pre-constructed cluster standby node;
summarizing the cluster main node, the standby node and the pre-constructed arbitration node to obtain the database cluster.
In an optional embodiment of the present invention, the database cluster may be a mondab cluster, where the mondab cluster includes: master node (mongdb (M)), standby node (mongdb (S)) and arbitration node (mongdb (a)). The master node and the standby node store data, the arbitrating node does not store data, and the master node provides all the services of adding, deleting, checking and modifying under the default setting, and the standby node does not provide any service, but can provide query service by setting so as to reduce the pressure of the master node. An arbitration node is a special node that does not itself store data, and the main function is to decide which standby node is promoted to be the master node after the master node hangs up.
In the embodiment of the invention, the spatial information of the components is stored in the attribute storage table, so that the association and the query based on the spatial relationship of the components can be flexibly and efficiently realized.
The data packaging module 104 is configured to store the geometric information into a pre-constructed object database, and package the object database and the database cluster by using a preset service layer to obtain a query service layer.
In the embodiment of the invention, the pre-constructed object database can be an object storage database AWS S3, the AWS S3 can store data (geometric information) as an object, and an engineering identifier is used as a unique identifier of the object, and the engineering identifier is used for realizing object inquiry.
In an optional embodiment of the present invention, the preset service layer may be an API layer, and the API layer may provide various attributes and component query interfaces according to service requirements.
The data query module 105 is configured to obtain data query information, and analyze the data query information by using the query service layer to obtain a data query result.
Specifically, the data query module 105 obtains a data query result by:
acquiring data query information, wherein the data query information comprises an attribute index, a spatial index and a geometric index;
calling an attribute query interface and a geometric query interface of the query service layer;
analyzing the attribute index and the spatial index by using the attribute query interface to obtain attribute information, wherein the attribute information comprises component spatial attributes, and analyzing the geometric index by using the geometric query interface to obtain geometric information;
and summarizing the geometric information and the attribute information to obtain the data query result.
In the embodiment of the present invention, for example, all attributes of all gates of a floor are queried, and a native $geowithin query statement and loc.z component are combined in the query statement: { $and [ { loc { $geoWithin { $geometry { type } "Polygon", cordinates [ [ [0,0], [10,10], [0,0] ] } } }, { $and [ { loc. Z "{ { $gt:0}, { loc. Z" { { $lt:3} } } } } } }, { "properties: { $eq }" Door "}, where $geoWithIn is the original query statement of MongoDB, loc. Z represents the spatial index.
In the embodiment of the invention, the spatial state information of the component is stored in the attribute storage table as one attribute (namely, the spatial attribute), and the spatial attribute is inquired through the spatial index, so that the inquiry of the spatial information of the three-dimensional data can be realized through the MongoDB two-dimensional spatial index, and the inquiry efficiency is greatly improved.
Fig. 7 is a schematic structural diagram of an electronic device for implementing a data query method according to an embodiment of the present invention.
The electronic device 1 may comprise a processor 10, a memory 11 and a bus, and may further comprise a computer program, such as a data query program 12, stored in the memory 11 and executable on the processor 10.
The memory 11 includes at least one type of readable storage medium, including flash memory, a mobile hard disk, a multimedia card, a card memory (e.g., SD or DX memory, etc.), a magnetic memory, a magnetic disk, an optical disk, etc. The memory 11 may in some embodiments be an internal storage unit of the electronic device 1, such as a removable hard disk of the electronic device 1. The memory 11 may in other embodiments also be an external storage device of the electronic device 1, such as a plug-in mobile hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card) or the like, which are provided on the electronic device 1. Further, the memory 11 may also include both an internal storage unit and an external storage device of the electronic device 1. The memory 11 may be used not only for storing application software installed in the electronic device 1 and various types of data, such as codes of the data inquiry program 12, but also for temporarily storing data that has been output or is to be output.
The processor 10 may be comprised of integrated circuits in some embodiments, for example, a single packaged integrated circuit, or may be comprised of multiple integrated circuits packaged with the same or different functions, including one or more central processing units (Central Processing unit, CPU), microprocessors, digital processing chips, graphics processors, combinations of various control chips, and the like. The processor 10 is a Control Unit (Control Unit) of the electronic device, connects respective components of the entire electronic device using various interfaces and lines, and executes various functions of the electronic device 1 and processes data by running or executing programs or modules (e.g., a data query program, etc.) stored in the memory 11, and calling data stored in the memory 11.
The bus may be a peripheral component interconnect standard (peripheral component interconnect, PCI) bus or an extended industry standard architecture (extended industry standard architecture, EISA) bus, among others. The bus may be classified as an address bus, a data bus, a control bus, etc. The bus is arranged to enable a connection communication between the memory 11 and at least one processor 10 etc.
Fig. 7 shows only an electronic device with components, it being understood by a person skilled in the art that the structure shown in fig. 7 does not constitute a limitation of the electronic device 1, and may comprise fewer or more components than shown, or may combine certain components, or may be arranged in different components.
For example, although not shown, the electronic device 1 may further include a power source (such as a battery) for supplying power to each component, and preferably, the power source may be logically connected to the at least one processor 10 through a power management device, so that functions of charge management, discharge management, power consumption management, and the like are implemented through the power management device. The power supply may also include one or more of any of a direct current or alternating current power supply, recharging device, power failure detection circuit, power converter or inverter, power status indicator, etc. The electronic device 1 may further include various sensors, bluetooth modules, wi-Fi modules, etc., which will not be described herein.
Further, the electronic device 1 may also comprise a network interface, optionally the network interface may comprise a wired interface and/or a wireless interface (e.g. WI-FI interface, bluetooth interface, etc.), typically used for establishing a communication connection between the electronic device 1 and other electronic devices.
The electronic device 1 may optionally further comprise a user interface, which may be a Display, an input unit, such as a Keyboard (Keyboard), or a standard wired interface, a wireless interface. Alternatively, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch, or the like. The display may also be referred to as a display screen or display unit, as appropriate, for displaying information processed in the electronic device 1 and for displaying a visual user interface.
It should be understood that the embodiments described are for illustrative purposes only and are not limited to this configuration in the scope of the patent application.
The data query program 12 stored in the memory 11 of the electronic device 1 is a combination of instructions that, when executed in the processor 10, may implement:
acquiring an engineering source file set, and carrying out identification analysis on the engineering source file set to obtain an engineering identification;
carrying out data separation on the engineering source file set by utilizing the engineering identifier to obtain attribute information and geometric information;
performing attribute storage on the attribute information to obtain an attribute storage table, and constructing a database cluster by using the attribute storage table;
storing the geometric information into a pre-constructed object database, and packaging the object database and the database cluster by using a preset service layer to obtain a query service layer;
and acquiring data query information, and analyzing the data query information by utilizing the query service layer to obtain a data query result.
Specifically, the specific implementation method of the above instructions by the processor 10 may refer to descriptions of related steps in the corresponding embodiments of fig. 1 to 5, which are not repeated herein.
Further, the modules/units integrated in the electronic device 1 may be stored in a computer readable storage medium if implemented in the form of software functional units and sold or used as separate products. The computer readable storage medium may be volatile or nonvolatile. For example, the computer readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM).
The present invention also provides a computer readable storage medium storing a computer program which, when executed by a processor of an electronic device, can implement:
acquiring an engineering source file set, and carrying out identification analysis on the engineering source file set to obtain an engineering identification;
carrying out data separation on the engineering source file set by utilizing the engineering identifier to obtain attribute information and geometric information;
performing attribute storage on the attribute information to obtain an attribute storage table, and constructing a database cluster by using the attribute storage table;
storing the geometric information into a pre-constructed object database, and packaging the object database and the database cluster by using a preset service layer to obtain a query service layer;
and acquiring data query information, and analyzing the data query information by utilizing the query service layer to obtain a data query result.
In the several embodiments provided in the present invention, it should be understood that the disclosed apparatus, device and method may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the modules is merely a logical function division, and there may be other manners of division when actually implemented.
The modules described as separate components may or may not be physically separate, and components shown as modules may or may not be physical units, may be located in one place, or may be distributed over multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional module in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units can be realized in a form of hardware or a form of hardware and a form of software functional modules.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof.
The present embodiments are, therefore, to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference signs in the claims shall not be construed as limiting the claim concerned.
The blockchain is a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, consensus mechanism, encryption algorithm and the like. The Blockchain (Blockchain), which is essentially a decentralised database, is a string of data blocks that are generated by cryptographic means in association, each data block containing a batch of information of network transactions for verifying the validity of the information (anti-counterfeiting) and generating the next block. The blockchain may include a blockchain underlying platform, a platform product services layer, an application services layer, and the like.
Furthermore, it is evident that the word "comprising" does not exclude other elements or steps, and that the singular does not exclude a plurality. A plurality of units or means recited in the system claims can also be implemented by means of software or hardware by means of one unit or means. The terms second, etc. are used to denote a name, but not any particular order.
Finally, it should be noted that the above-mentioned embodiments are merely for illustrating the technical solution of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications and equivalents may be made to the technical solution of the present invention without departing from the spirit and scope of the technical solution of the present invention.
Claims (9)
1. A method of querying data, the method comprising:
acquiring an engineering source file set, and carrying out identification analysis on the engineering source file set to obtain engineering identifications, wherein the engineering identifications are GUID identifications of each item in the engineering source file set;
carrying out data separation on the engineering source file set by utilizing the engineering identifier to obtain attribute information and geometric information, wherein the attribute information is building component professional attribute information and building component space state information in the engineering source file set, and the geometric information is a building model and a building component model in the engineering source file set;
performing attribute storage on the attribute information to obtain an attribute storage table, and constructing a database cluster by using the attribute storage table;
storing the geometric information into a pre-constructed object database, and packaging the object database and the database cluster by using a preset service layer to obtain a query service layer;
acquiring data query information, calling an attribute query interface and a geometric query interface of the query service layer, analyzing an attribute index and a spatial index in the data query information by using the attribute query interface to obtain attribute information, analyzing a geometric index in the data query information by using the geometric query interface to obtain geometric information, and summarizing the geometric information and the attribute information to obtain the data query result.
2. The data query method of claim 1, wherein the performing the identification parsing on the engineering source file to obtain the engineering identification includes:
sequentially analyzing each engineering source file in the engineering source file set by utilizing a pre-constructed engineering management platform to obtain a unique identifier of each engineering source file;
and taking the unique identification as an engineering identification of the corresponding engineering source file.
3. The data query method as claimed in claim 2, wherein said using said engineering identifier to perform data separation on said engineering source file set to obtain attribute information and geometric information comprises:
utilizing a digital-analog separation module in the engineering management platform to identify and identify the engineering identifier;
and separating data and a model from the source file with the same engineering identifier to obtain attribute information of the component and geometric information of the component.
4. The data query method as claimed in claim 3, wherein said storing the attribute information to obtain an attribute storage table comprises:
acquiring a preset attribute extraction field;
extracting the attribute of the component with the same engineering identifier by utilizing the attribute extraction field to obtain a component attribute, wherein the component attribute comprises a component space attribute;
and carrying out sub-table storage on the component attributes to obtain the attribute storage table.
5. The data query method as claimed in claim 4, wherein said sub-table storing said constructed attributes to obtain said attribute storage table comprises:
performing character conversion on the engineering identifier to obtain a sub-table ID;
and based on the sub-table ID, performing sub-table storage on the constructed attribute with the same engineering identifier to obtain the attribute storage table.
6. The data query method of any one of claims 1 to 5, wherein said constructing a database cluster using said attribute storage table comprises:
storing the attribute storage table in a pre-constructed cluster master node and a pre-constructed cluster standby node;
summarizing the cluster main node, the standby node and the pre-constructed arbitration node to obtain the database cluster.
7. A data querying device, the device comprising:
the system comprises an identification analysis module, a storage module and a storage module, wherein the identification analysis module is used for acquiring an engineering source file set, carrying out identification analysis on the engineering source file set to obtain an engineering identification, and the engineering identification is the GUID identification of each item in the engineering source file set;
the data separation module is used for carrying out data separation on the engineering source file set by utilizing the engineering identifier to obtain attribute information and geometric information, wherein the attribute information is building component professional attribute information and building component space state information in the engineering source file set, and the geometric information is a building model and a building component model in the engineering source file set;
the attribute storage module is used for carrying out attribute storage on the attribute information to obtain an attribute storage table, and constructing a database cluster by utilizing the attribute storage table;
the data packaging module is used for storing the geometric information into a pre-constructed object database, and packaging the object database and the database cluster by utilizing a preset service layer to obtain a query service layer;
the data query module is used for acquiring data query information, calling an attribute query interface and a geometric query interface of the query service layer, analyzing an attribute index and a spatial index in the data query information by utilizing the attribute query interface to obtain attribute information, analyzing a geometric index in the data query information by utilizing the geometric query interface to obtain geometric information, and summarizing the geometric information and the attribute information to obtain the data query result.
8. 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 memory stores instructions executable by the at least one processor to enable the at least one processor to perform the data query method of any one of claims 1 to 6.
9. A computer readable storage medium storing a computer program, wherein the computer program when executed by a processor implements the data query method of any one of claims 1 to 6.
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| CN115017234A (en) * | 2022-06-29 | 2022-09-06 | 贵州财经大学 | Block chain information management system, block chain information storage and query method |
| CN115827816B (en) * | 2023-02-21 | 2023-05-02 | 山东铁路投资控股集团有限公司 | BIM component data verification and right confirmation method and device based on blockchain |
| CN116956332B (en) * | 2023-09-20 | 2024-01-05 | 深圳市智慧城市科技发展集团有限公司 | BIM data processing method, BIM data processing equipment and computer readable storage medium |
| CN117194704B (en) * | 2023-11-07 | 2024-02-06 | 航天宏图信息技术股份有限公司 | Method, device and equipment for inquiring attribute of component-level live-action three-dimensional model |
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