CN-122019530-A - Search-oriented BIM lightweight model attribute index table construction method and system

CN122019530ACN 122019530 ACN122019530 ACN 122019530ACN-122019530-A

Abstract

The invention discloses a method and a system for constructing a BIM lightweight model attribute index table for retrieval. Firstly, extracting a component attribute metadata set with a four-layer logic structure in a BIM lightweight model through a parser, then, generating an attribute index table with a flattened structure based on the set, presetting a database index on key fields of the attribute index table, and finally, converting component attribute metadata records in the component attribute metadata set into target normalized records in batches through a concurrency processing engine and writing the target normalized records into the attribute index table. Based on the filled attribute index table, the attribute query request from the lightweight terminal can be responded efficiently, and on-demand and dynamic engineering quantity statistics and report generation are realized. According to the invention, the attribute data is reconstructed into the atomized and flattened attribute index table from the complex multi-table associative memory, so that the technical bottlenecks of slow attribute retrieval and difficult engineering quantity statistics caused by a complex memory architecture of the traditional BIM lightweight model are fundamentally solved.

Inventors

LI LEI
ZHANG YUYANG
ZHANG WENDONG
WANG HAO
ZHAO YINJUN
ZHOU BINGLING
PANG KANGYU

Assignees

东慧(浙江)科技有限公司

Dates

Publication Date: 20260512
Application Date: 20251219

Claims (10)

1. The method for constructing the BIM lightweight model attribute index table for retrieval is characterized by comprising the following steps of: Extracting a component attribute metadata set in the BIM lightweight model through a parser, wherein the component attribute metadata set comprises at least one component attribute metadata record; defining and creating an attribute index table with a flattened structure based on the component attribute metadata set; And converting the component attribute metadata records in the component attribute metadata set into target normalized records through a concurrent processing engine, and writing the target normalized records into the attribute index table in batches.
2. The method of claim 1, wherein defining and creating an attribute index table having a flattened structure based on the set of component attribute metadata comprises: Creating an attribute index table, wherein the core field of the attribute index table at least comprises a global unique identifier of a component, a logic identifier of a component type, a unique identifier of a component instance, a category logic name of an attribute, a logic name of the attribute, an original value of the attribute and a unit of the attribute, and each record of the attribute index table only comprises a single attribute; A database index is created on key query fields of the attribute index table, the key query fields including at least a globally unique identifier of a component, a category logical name of an attribute, and a logical name of an attribute.
3. The method of claim 1, wherein converting, by the concurrency processing engine, component property metadata records in the component property metadata set into target normalized records and writing in batches to the property index table comprises: starting a plurality of concurrent processing threads, dividing the component attribute metadata set into subsets, and distributing the subsets to each thread for concurrent processing; extracting an original attribute value according to storage position information in a component attribute metadata record in each concurrent processing thread, combining the original attribute value with the component attribute metadata record to generate an initial normalized record, and further converting the initial normalized record into a target normalized record conforming to the attribute index table structure; And writing the generated target normalized record into the attribute index table through database batch writing operation.
4. The method of claim 1, wherein after converting, by the concurrency processing engine, the component property metadata records in the component property metadata set to target normalized records and batch writing to the property index table, further comprising: Responding to an attribute query request from the lightweight terminal based on the filled attribute index table; Or responding to the engineering quantity statistical request and generating a statistical report based on the filled attribute index table.
5. The system for constructing the BIM lightweight model attribute index table for searching is characterized by comprising the following components: The metadata analysis module is used for extracting a component attribute metadata set in the BIM lightweight model through a parser, wherein the component attribute metadata set comprises at least one component attribute metadata record; the attribute index table construction module is used for generating an attribute index table based on the component attribute metadata set; And the concurrency processing engine is used for converting the component attribute metadata records in the component attribute metadata set into target normalized records and writing the target normalized records into the attribute index table in batches.
6. The system of claim 5, further comprising: the query interface module is used for responding to the attribute query request from the lightweight terminal based on the filled attribute index table; Or a statistics report module, which is used for responding to the engineering quantity statistics request and generating a statistics report based on the filled attribute index table.
7. The system of claim 5, wherein the attribute index table construction module comprises: The table structure defining sub-module is used for creating an attribute index table with a flattened structure according to the component attribute metadata set, and the core field of the table structure defining sub-module at least comprises a global unique identifier of a component, a logic identifier of a component type, a unique identifier of a component instance, a category logic name of an attribute, a logic name of the attribute, an original value of the attribute and a unit of the attribute; and the index presetting sub-module is used for creating a database index on a key query field of the attribute index table, wherein the key query field at least comprises a global unique identifier of a component, a category logic name of an attribute and a logic name of the attribute.
8. The system of claim 5, wherein the concurrent processing engine comprises: The task scheduling sub-module is used for starting a plurality of concurrent processing threads, dividing the component attribute metadata set into subsets and distributing the subsets to each thread for concurrent processing; The data conversion sub-module is used for extracting an original attribute value according to the storage position information in the component attribute metadata record in each concurrent processing thread, combining the original attribute value with the component attribute metadata record to generate an initial normalized record, and further converting the initial normalized record into a target normalized record conforming to the attribute index table structure; and the batch writing sub-module writes the generated target normalized record into the attribute index table through database batch writing operation.
9. An electronic device, comprising: A memory for storing a computer program; a processor for executing a program stored on a memory, implementing the method steps of any one of claims 1-4.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium has stored therein a computer program which, when executed by a processor, implements the method steps of any of claims 1-4.

Description

Search-oriented BIM lightweight model attribute index table construction method and system Technical Field The invention belongs to the field of Building Information Model (BIM) and database information processing, and particularly relates to a method and a system for constructing a BIM lightweight model attribute index table for retrieval. The invention also relates to the electronic equipment and the storage medium for realizing the method. Background In the field of engineering digitization, lightweight processing of Building Information Models (BIM) is a key technology for realizing efficient application of models in lightweight terminals such as Web browsers and mobile terminals. In the prior art, a large BIM model is generally converted into a lightweight model taking a database (such as SQLite) as a carrier through a special conversion tool (such as Bimface, iTwin, etc.), and the volume of the model is obviously reduced on the premise of keeping original geometric and non-geometric information so as to meet the performance requirement of a lightweight terminal. The existing BIM lightweight model adopts a multi-level, indirectly associated heterogeneous storage architecture, which aims at providing flexibility but fundamentally sacrifices query performance. The root cause is that the architecture adopts a design paradigm that the service identification is separated from the physical storage. The meaning of the attribute value is forcibly decoupled from the storage location and connected by a complex mapping relationship. While this design supports flexible expansion of storage modes, it has the inherent cost of having to recalculate and parse this complete mapping chain at run-time, through a multi-table join operation, for each attribute query. This is a design that embeds computational complexity into the data structure, determining from an architectural level the necessity of its real-time inefficiency of querying. The main aspects are as follows: 1. The attribute retrieval performance is low, and in order to keep the flexibility of the existing BIM lightweight model, a sparse storage structure of a dynamic table and a dynamic column is often adopted to manage massive attribute data. This structure results in a search operation for specific attributes (e.g. "concrete strength grade") requiring complex associative queries and dynamic parsing across multiple data tables, which is time-complex. In the face of models containing hundreds of thousands or even millions of components, the response delay is significant and cannot meet the requirements of interactive applications for second-order responses. 2. Engineering quantity statistics functionality is limited in that accurate engineering quantity statistics (e.g., calculating the total volume of a particular type of component) are highly dependent on efficient and flexible retrieval and aggregation capabilities for attribute data. Due to the performance bottleneck of the attribute retrieval, on-demand and real-time engineering quantity statistics become extremely difficult or even impossible in a large model environment. Engineering personnel can only rely on a pre-derived fixed report, cannot flexibly carry out real-time statistics according to dynamically-changed screening conditions, and seriously influences project decision-making and management efficiency. Aiming at the problems, at present, the common optimization means in the industry are to perform query statement optimization or introduce external cache at the application layer, and the schemes belong to local optimization for treating the symptoms and the root causes: Query optimization, the fact that the underlying layer needs multi-table association cannot be changed, and mass data improvement is limited. External caching, namely, additional systems are required to be maintained, the complexity of the architecture and the maintenance cost of consistency are increased, and flexible and changeable combined query results are difficult to cache. None of these approaches address the performance issues raised by the "dynamic map-scatter store" architecture paradigm specific to the underlying BIM lightweight model. Therefore, the field is long lacking an innovative technical scheme capable of reconstructing from the data organization model level and reconstructing the efficient attribute access path on the root. The invention provides the method for realizing high-efficiency retrieval and real-time statistics of massive attribute data, and aims to fundamentally solve the long-standing technical problem in the industry. Disclosure of Invention In order to solve the two technical problems that in the existing BIM lightweight model, in lightweight terminals such as a Web terminal and a mobile terminal, the attribute retrieval speed is low and the engineering quantity cannot be counted in real time as required due to the fact that an attribute data storage structure is complex, the invention provides