CN116166661A - Information storage service system based on big data - Google Patents

Information storage service system based on big data Download PDF

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CN116166661A
CN116166661A CN202211633879.4A CN202211633879A CN116166661A CN 116166661 A CN116166661 A CN 116166661A CN 202211633879 A CN202211633879 A CN 202211633879A CN 116166661 A CN116166661 A CN 116166661A
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industrial equipment
service
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information storage
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李爱建
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • 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
    • G06F16/2228—Indexing structures
    • G06F16/2246—Trees, e.g. B+trees
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/10—File systems; File servers
    • G06F16/18—File system types
    • G06F16/182—Distributed file systems
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/21—Design, administration or maintenance of databases
    • G06F16/214—Database migration support
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/24—Querying
    • G06F16/245—Query processing
    • G06F16/2455—Query execution
    • G06F16/24552—Database cache management
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/24—Querying
    • G06F16/245—Query processing
    • G06F16/2457—Query processing with adaptation to user needs
    • G06F16/24578—Query processing with adaptation to user needs using ranking
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/27—Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/28—Databases characterised by their database models, e.g. relational or object models
    • G06F16/284—Relational databases

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Abstract

The invention discloses an information storage service method based on big data, which is applied to an information storage service system always based on big data, and comprises the following steps: the method comprises the steps of adopting a numerical control equipment industrial interconnection communication protocol to communicate with a numerical control system of industrial equipment, collecting data of the industrial equipment, and collecting the data of the industrial equipment through an open numerical control system interface; storing the data by using different data management systems according to different characteristics of the data, pushing the industrial equipment data to a message queue, writing static data and trigger data into a relational data management system database, and writing implementation operation data into the time sequence data management system database; constructing a two-level storage architecture, and using a distributed time sequence database as a cache of data; the method and the device have the characteristics of improving the use value of the data and optimizing the data storage process.

Description

Information storage service system based on big data
Technical Field
The invention relates to the technical field of numerical control equipment industrial Internet, in particular to an information storage service system based on big data.
Background
The industrial equipment can realize complex, precise, batch and multi-variety part processing, has the advantages of high precision, high efficiency, convenient operation and the like, is widely applied to the processing of parts in various fields, the numerical control system is called as the 'brain' of the industrial equipment, and digital twin is a key means for realizing the intellectualization of the industrial equipment, and the realization needs to establish complete and high-frequency industrial equipment big data. The existing industrial equipment data storage system adopts a single data management mode, can not meet the storage requirement of industrial equipment big data, ignores the relevance behind the data in the storage process, has serious problem of memory resource waste for real-time data processing, and does not support the inquiry of combined data. Therefore, it is necessary to design a big data based information storage service system that improves the data use value and optimizes the data storage process.
Disclosure of Invention
The present invention is directed to an information storage service system based on big data, so as to solve the problems set forth in the background art.
In order to solve the technical problems, the invention provides the following technical scheme: an information storage service method based on big data, the method comprising:
adopting a numerical control equipment industrial interconnection communication protocol to communicate with a numerical control system of industrial equipment, and collecting data of the industrial equipment;
storing the data by using different data management systems according to different characteristics of the data;
constructing a two-level storage architecture, and using a distributed time sequence database as a cache of data;
and carrying out semantic modeling on industrial equipment instruction big data based on the metadata, establishing an index structure and providing query service.
According to the above technical scheme, the communication between the numerical control equipment industrial interconnection communication protocol and the numerical control system of the industrial equipment is adopted, and the acquisition of the data of the industrial equipment comprises:
collecting industrial equipment data through an open numerical control system interface;
and sending the serial number of the access equipment to the registration service to perform equipment registration service.
According to the above technical solution, the storing the data by using different data management systems according to different characteristics of the data includes:
after pushing the industrial equipment data to the message queue, writing static data and trigger data into a relational data management system database, and writing execution operation data into the time sequence data management system database.
According to the above technical solution, the constructing a two-level storage architecture, using a distributed time sequence database as a cache of data includes:
carrying data of all industrial equipment jointly by using a plurality of time sequence databases;
setting a time sequence database management middleware through a consistent hash algorithm, managing data writing and inquiring of a plurality of time sequence database instances, and providing external calling through a unified borrowing port;
and recording the number of data migration, verifying the correctness of each migration, and updating the migration time.
According to the above technical solution, the semantic modeling is performed on the industrial equipment instruction big data based on metadata, an index structure is established, and providing the query service includes:
carrying out unified semantic modeling on the big data of the instruction domain by taking the state of industrial equipment as the dimension;
adopting an LSM tree as an index structure of industrial equipment processing metadata, managing the storage space of the metadata, and dividing the storage space by using three levels of indexes;
when a client initiates a request to a data query service, the query service automatically judges the position of data according to the request content and acquires the data across a plurality of databases.
According to the above technical solution, the information storage service system based on big data includes:
the data acquisition module is used for acquiring data information of industrial equipment;
the data storage module is used for storing industrial equipment data;
and the data service module is used for providing data service for the client.
According to the above technical scheme, the data acquisition module includes:
the numerical control interface acquisition module is used for acquiring industrial equipment data through the open numerical control system interface acquisition;
and the industrial equipment registration module is used for carrying out industrial equipment registration service.
According to the above technical solution, the data storage module includes:
the storage classification module is used for classifying and storing the data;
the message queue writing module is used for writing data in a message queue mode;
the data caching module is used for caching data by using the distributed time sequence database;
and the data migration module is used for automatically migrating the data to the persistent storage in the distributed file system.
According to the above technical solution, the data service module includes:
the semantic modeling unit is used for carrying out semantic modeling on the instruction domain big data by taking the industrial equipment state as a dimension;
the index building module is used for building an index structure through the LSM tree;
and the data query service module is used for providing data query service.
Compared with the prior art, the invention has the following beneficial effects: according to the invention, by arranging the data acquisition module, the data storage module and the data service module, different data management systems are used for bearing various data of industrial equipment together, and the message queue guarantees that the data is written into the time sequence database at a stable speed, so that the data loss caused by too large change of data quantity and untimely data storage of the acquired data is avoided; constructing a distributed time sequence database as a cache, carrying real-time operation data of industrial equipment, linearly expanding the read-write performance of the data according to the number of nodes, and periodically writing the data into a distributed file system according to the time sequence characteristic of the data; through the three-level index, the storage layout of the data is effectively optimized, and the relevance of the data is saved.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
FIG. 1 is a flow chart of a method for providing big data based information storage services according to an embodiment of the present invention;
fig. 2 is a schematic diagram of a module configuration of an information storage service system based on big data according to a second embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Embodiment one:
fig. 1 is a flowchart of a big data based information storage service system according to an embodiment of the present invention, where the embodiment may be applied to an environment of industrial equipment data application, and the method may be performed by the big data based information storage service system according to the embodiment of the present invention, where the system is composed of a plurality of software and hardware modules, and the method specifically includes the following steps:
s101, adopting a numerical control equipment industrial interconnection communication protocol to communicate with a numerical control system of industrial equipment, and collecting data of the industrial equipment;
in some embodiments of the invention, the industrial equipment data is collected through the open numerical control system interface collection, and the industrial equipment data is divided into three types of static data, trigger data and real-time operation data, so that the storage process is simplified. Specifically, the static data is static model data of the storage industrial control equipment, and comprises equipment basic information, system parameters, a three-dimensional geometric model and other data; the triggering data are data with extremely low change frequency, such as equipment alarm data, which are generated by the triggering of events in the numerical control system or the operation of personnel; the real-time operation data is data directly collected from production elements, such as equipment state, main shaft current and the like.
In the embodiment of the invention, the number of the industrial equipment networking is continuously increased, so that in order to realize dynamic equipment data access, equipment registration service is carried out on the premise of not interrupting the existing service, specifically, the serial number of the access equipment is sent to the registration service, after the registration service receives a request, whether the serial number is registered or not is judged first, if the serial number is registered, the registered information is returned, otherwise, the data writing service is informed to create a new data writing task, equipment data is acquired according to the existing acquisition requirement, and the data is written into a storage space according to the process.
S102, storing data by using different data management systems according to different characteristics of the data;
in some embodiments of the invention, after pushing industrial equipment data to a message queue, static data and trigger data are written into a relational data management system database through a first channel; the data management system database is written with implementation operation data through a second channel; in the step, the data and the storage space are not directly interacted, the data is written in a message queue mode and decoupled from the storage space, the data is firstly pushed into the message queue after being generated, and the writing service pulls the data from the message queue and writes the data into the storage space so as to ensure that the data is written into the time sequence database at a stable speed, and the situation that the data loss is caused due to the fact that the data quantity is too large in change and the collected data is not stored timely is avoided.
S103, constructing a two-level storage architecture, and using a distributed time sequence database as a cache of data;
in some embodiments of the present invention, the real-time data is carried by using a distributed time sequence database, after the data amount in the time sequence database reaches a threshold value, the data is obtained from the time sequence database, a new index is established according to the time sequence characteristics, the data is integrated, a new file format is generated, and then the data is automatically migrated to the distributed file system for persistent storage.
In the embodiment of the invention, the data of all industrial equipment can be guaranteed to be completely written by using a plurality of time sequence databases together to avoid the situation that the time sequence databases are interrupted to process when the number of the accessed industrial equipment is excessive or the data quantity written simultaneously is excessive due to the bottleneck of single performance, and the reliable writing of the data cannot be guaranteed, so that the completeness of the data cannot be guaranteed. Therefore, the time sequence database management middleware is further arranged through the consistent hash algorithm, the data writing and inquiring of a plurality of time sequence database instances are managed, and the time sequence database instances are provided for external calling through a unified borrowing port. Specifically, each hash ring comprises a plurality of time sequence database examples, a whole data is stored together, the hash rings are mutually backed up, the data are synchronized regularly, and the consistency of the data is ensured; the time sequence database examples of the same hash ring are mutually independent, and the time sequence database examples among different hash rings are mutually prepared; each time sequence database instance is distinguished by taking an IP address or the position of a node in a hash ring as an identifier, and taking a measurement as a minimum splitting unit. Through the step, the total throughput rate of the storage system is improved, dynamic capacity expansion and capacity reduction are realized, and the consistency and completeness of data are ensured. Specifically, when data needs to be written, a client requests an instance position after load balancing from a load balancer, the load balancer selects a middleware to forward the request, after receiving the request, each hash ring calculates a time sequence database instance according to a target database and measurement information in the request, forwards the request to the time sequence database instances, processes the request and writes the data; if the time sequence database cannot be written, the middleware writes the data into the cache file until the data is rewritten after recovery.
For example, when data is migrated each time, when the migrated data is written into the temporary file, the number of migrated data is recorded, a column of data is randomly selected, and if the total of the number of migrated data in the temporary file and the time sequence database is the same as the data sum of the corresponding column positions, the correctness of the migrated data is indicated; the migration time of the corresponding table of the sampling channel of the corresponding industrial equipment is updated every time a data migration task is completed by taking the termination time stamp of the time section of the migrated data as a value. Through the step, the characteristics of real-time operation data are fully utilized, a certain amount of data are pulled from a time sequence database through integration of data time sections, a new index about time is built for historical data in a buffer zone, then the data are generated according to a new file format and written into a distributed file system, and the problem of small files is effectively solved.
S104, carrying out semantic modeling on industrial equipment instruction big data based on metadata, establishing an index structure and providing query service;
in some embodiments of the invention, the large data of the instruction domain is subjected to unified semantic modeling by taking the state of industrial equipment as the dimension, so that the semantic expression capacity of the data is improved, and the time for acquiring the total number of historical data is reduced; adopting an LSM tree as an index structure of industrial equipment processing metadata, managing the storage space of the metadata, and dividing the storage space by using three levels of indexes; the data information of each industrial device can be visually checked through the step, meanwhile, the mechanism connection of various data of the industrial device is further embodied, the storage layout of the data is effectively optimized, and the relevance of the data is saved. When a client initiates a request to a data query service, the query service automatically judges the position of data according to the request content, and obtains the data across a plurality of databases to realize the query of the data.
Specifically, data generated in one processing process is used as a basic data storage unit, and according to metadata structure content, serial numbers of industrial equipment are used as primary indexes to search processing metadata information of corresponding industrial equipment in batches; taking the generation date of the data unit as a secondary index to determine the processing metadata information generated by the airport in one day; and taking the program number of the generated data unit as a three-level index, and only having a unique program at the same time to determine the processing metadata information corresponding to the processing program. And setting an expiration time threshold in the metadata storage space, calculating the survival time of metadata of the corresponding date of each industrial equipment, and when the survival time is greater than the threshold, sending a request to the storage space according to the information of the metadata, deleting the corresponding historical data and deleting the corresponding metadata so as to save the storage space.
Illustratively, the query for data information is specifically: acquiring a data unit list of industrial equipment; selecting a certain data unit, acquiring a start-stop time stamp of the data unit, judging the storage position of the data unit according to the start-stop time, determining the storage position of the data, initiating a request to a distributed time sequence database management middleware or a distributed file storage system according to the identifier of the data unit and the start-stop time stamp, acquiring complete data, and if the data is stored in two positions, respectively acquiring the two parts of data, merging according to time and returning to a client.
Embodiment two:
in a second embodiment of the present invention, an information storage service system based on big data is provided, and fig. 2 is a schematic diagram of module configuration of the information storage service system based on big data provided in the second embodiment, as shown in fig. 2, the system includes:
the data acquisition module is used for acquiring data information of industrial equipment;
the data storage module is used for storing industrial equipment data;
and the data service module is used for providing data service for the client.
In some embodiments of the invention, the data acquisition module comprises:
the numerical control interface acquisition module is used for acquiring industrial equipment data through the open numerical control system interface acquisition;
and the industrial equipment registration module is used for carrying out industrial equipment registration service.
In some embodiments of the invention, the data storage module comprises:
the storage classification module is used for classifying and storing the data;
the message queue writing module is used for writing data in a message queue mode;
the data caching module is used for caching data by using the distributed time sequence database;
and the data migration module is used for automatically migrating the data to the persistent storage in the distributed file system.
In some embodiments of the invention, the data service module comprises:
the semantic modeling unit is used for carrying out semantic modeling on the instruction domain big data by taking the industrial equipment state as a dimension;
the index building module is used for building an index structure through the LSM tree;
and the data query service module is used for providing data query service.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Finally, it should be noted that: the foregoing description is only a preferred embodiment of the present invention, and the present invention is not limited thereto, but it is to be understood that modifications and equivalents of some of the technical features described in the foregoing embodiments may be made by those skilled in the art, although the present invention has been described in detail with reference to the foregoing embodiments. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (9)

1. An information storage service method based on big data is characterized in that: the method comprises the following steps:
adopting a numerical control equipment industrial interconnection communication protocol to communicate with a numerical control system of industrial equipment, and collecting data of the industrial equipment;
storing the data by using different data management systems according to different characteristics of the data;
constructing a two-level storage architecture, and using a distributed time sequence database as a cache of data;
and carrying out semantic modeling on industrial equipment instruction big data based on the metadata, establishing an index structure and providing query service.
2. The big data based information storage service method according to claim 1, wherein: the method for acquiring the data of the industrial equipment comprises the following steps of:
collecting industrial equipment data through an open numerical control system interface;
and sending the serial number of the access equipment to the registration service to perform equipment registration service.
3. The big data based information storage service method according to claim 1, wherein: the storing the data by using different data management systems according to different characteristics of the data comprises:
after pushing the industrial equipment data to the message queue, writing static data and trigger data into a relational data management system database, and writing execution operation data into the time sequence data management system database.
4. The big data based information storage service method according to claim 1, wherein: the construction of the two-level storage architecture, using the distributed time sequence database as the cache of the data, comprises the following steps:
carrying data of all industrial equipment jointly by using a plurality of time sequence databases;
setting a time sequence database management middleware through a consistent hash algorithm, managing data writing and inquiring of a plurality of time sequence database instances, and providing external calling through a unified borrowing port;
and recording the number of data migration, verifying the correctness of each migration, and updating the migration time.
5. The big data based information storage service method according to claim 1, wherein: semantic modeling is carried out on industrial equipment instruction big data based on metadata, an index structure is established, and query service is provided, wherein the steps of:
carrying out unified semantic modeling on the big data of the instruction domain by taking the state of industrial equipment as the dimension;
adopting an LSM tree as an index structure of industrial equipment processing metadata, managing the storage space of the metadata, and dividing the storage space by using three levels of indexes;
when a client initiates a request to a data query service, the query service automatically judges the position of data according to the request content and acquires the data across a plurality of databases.
6. An information storage service system based on big data, characterized in that: the system comprises:
the data acquisition module is used for acquiring data information of industrial equipment;
the data storage module is used for storing industrial equipment data;
and the data service module is used for providing data service for the client.
7. The big data based information storage service system of claim 6, wherein: the data acquisition module comprises:
the numerical control interface acquisition module is used for acquiring industrial equipment data through the open numerical control system interface acquisition;
and the equipment registration module is used for carrying out industrial equipment registration service.
8. The big data based information storage service system of claim 6, wherein: the data storage module includes:
the storage classification module is used for classifying and storing the data;
the message queue writing module is used for writing data in a message queue mode;
the data caching module is used for caching data by using the distributed time sequence database;
and the data migration module is used for automatically migrating the data to the persistent storage in the distributed file system.
9. The big data based information storage service system of claim 6, wherein: the data service module comprises:
the semantic modeling unit is used for carrying out semantic modeling on the instruction domain big data by taking the industrial equipment state as a dimension;
the index building module is used for building an index structure through the LSM tree;
and the data query service module is used for providing data query service.
CN202211633879.4A 2022-12-19 2022-12-19 Information storage service system based on big data Pending CN116166661A (en)

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Application Number Priority Date Filing Date Title
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