CN114238538A - Data storage system and method based on high-precision map - Google Patents
Data storage system and method based on high-precision map Download PDFInfo
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Abstract
The invention discloses a data storage system and a method based on a high-precision map, wherein the system comprises a message cache region, a real-time storage region, a short-term storage region and a long-term storage region, wherein the short-term storage region comprises an HBase storage region for storing high-precision dynamic map data, a PostgreSQL space library for storing high-precision static map vector data and a FastDFS storage region for storing file data and space data; the long-term storage area is used for storing expired data in the short-term storage area in a file mode, establishing an index directory and storing historical data and archived data at the same time; the data storage system and the data storage method classify and store the high-precision map, and recycle and archive the high-precision map on time according to different types and different purposes, so that the utilization of hardware resources is maximized and the data resources of the high-precision map are effectively managed.
Description
Technical Field
The invention relates to a storage system and a storage method of high-precision map data.
Background
Technical iteration and commercialization of the intelligent automobile can be achieved without leaving roads, communication and other infrastructures, however, at present, due to the fact that enterprises or different departments build the infrastructures only according to requirements, a special customization system for 'chimney' forest establishment is formed, and a series of problems of resource repetition, difficulty in interconnection and intercommunication, low utilization efficiency, high construction and system maintenance cost, high management and service difficulty, low data capacity level and the like are caused.
The high-precision dynamic map comprises a quasi-dynamic map and a dynamic map, wherein the quasi-dynamic map comprises information such as signal lamps, road congestion conditions, road construction, road surface information and weather, and the dynamic map comprises high-instantaneity information such as surrounding traffic participants, traffic accident information and sudden roadblocks. The dynamic map generally acquires information through terminal sensors such as vision, laser radar and millimeter wave radar at a vehicle end and a road side end, a terminal platform performs cleaning, classification, coding, positioning, extraction and other processing on the sensed information, uploads the information to a map cloud platform or performs differential processing on the information and local basic data and static data of the terminal, dynamic map data are generated or updated, and an effective storage strategy is not established in cloud storage. The automatic driving automobile is used as an intelligent terminal and independently exists in the whole data network of the data monitoring management platform; the vehicle end is used as an acquisition end of high-precision map data and also as an application end of the high-precision map; the original data, the processed data and the result data of the dynamic high-precision map data are stored uniformly and are not distinguished effectively, so that resource management is difficult and space is wasted. Therefore, a system capable of reasonably and effectively storing static and dynamic data of high-precision maps is lacking at present.
Disclosure of Invention
The purpose of the invention is as follows: the invention aims to provide a system and a method for classifying and storing high-precision map data in blocks, which can effectively manage data resources and ensure the availability and reliability of the data.
The technical scheme is as follows: the invention relates to a data storage system based on a high-precision map, which comprises:
the message buffer area is used for accessing the high-precision map data into a message queue for buffering;
the real-time storage area is used for performing Redis subscription storage on the high-precision dynamic map data in the message cache area;
the short-term storage area comprises an HBase storage area used for storing high-precision dynamic map data, a PostgreSQL space library used for storing high-precision static map vector data and a FastDFS storage area used for storing file data and space data;
and the long-term storage area is used for storing expired data in the short-term storage area in a file mode and establishing an index directory.
Historical data with the use frequency lower than a threshold value are stored in the long-term storage area, a new data table is periodically established in the relational database for storing the historical data, and the data table stored in each period is named and stored according to time. The method comprises the steps of performing archival storage on historical data with a user access rate lower than a threshold value, wherein an archival storage module comprises a data writing area for compressing the archival data and storing the archival data in a disk, a metadata management area for storing the disk position of the archival data and the physical address of the archival data in the disk, and a data retrieval area for calling the metadata management area to inquire the archival data when a user inquires.
The message buffer area receives real-time high-precision map data through the message receiving module and stores the data into the queue, the message is pulled away from the queue through the message pulling module and sent to the consumer, and the messages in the queue are stored persistently.
The data storage method based on the high-precision map comprises the following steps:
(1) caching received real-time messages of the vehicle end and the road end through a message queue;
(2) storing the high-precision dynamic map cache data through message subscription; meanwhile, storing high-precision dynamic map data into an HBase storage area, and setting a storage period;
(3) storing the high-precision static map vector class data into a PostgreSQL space library, and storing the high-precision dynamic map file data and the space data in a FastDFS storage area; respectively setting storage periods;
(4) storing the expired data to a long-term storage area in a file mode according to time, establishing an index directory and setting a storage period;
(5) and destroying the expired data in the long-term storage area.
The step (3) further comprises the following steps: setting the high-precision map data with the use frequency smaller than the threshold value as historical data, storing the historical data in a relational database, regularly executing a database trigger to newly establish a data table, and naming and storing the stored data table in each period according to time. Setting historical data with the user access possibility lower than a threshold value as archival data, compressing and storing the archival data to a disk, sending the disk position of the archival data and the physical position of the archival data in the disk to a metadata management area for storage, and calling the metadata management area to acquire the archival data when a user inquires.
The method for caching the message in the step (1) comprises the following steps:
(11) the message receiving module receives the real-time message and forwards the real-time message to the kafka queue;
(12) the messages in the kafka queue are subjected to persistent storage;
(13) and the message pulling module pulls the message from the kafka queue to be sent to the consumer for data reading.
In the step (2), caching data is stored into a distributed message model established based on AKKA by adopting a two-level Key mode, wherein an OEM manufacturer is a first-level Key, and a unique identification number is a second-level Key; and storing in an overlay mode, and only keeping the latest data.
Has the advantages that: compared with the prior art, the invention has the advantages that: (1) the maximization of hardware resource utilization is realized, the high-precision maps are stored in a classified mode and are recovered and filed on time according to different types and different purposes, and the cost of hot data storage is saved; (2) the invention provides the required storage capacity for the dynamic high-precision data of the vehicle end, the road end and the like and the static data of the high-precision map, avoids unused or over-configured storage, better utilizes the storage resources and reduces the cost and complexity caused by unnecessary storage for management; (3) ensure the availability and reliability of data and establish good disaster recovery mechanisms, such as: the real-time storage and the short-term storage belong to hot area storage, the hot area storage possibly causes data damage due to long-term large concurrent read-write operation, the long-term storage area belongs to archival storage and is long in service life, and when the short-term storage area is damaged, the data in the long-term storage area can be activated and extracted to the short-term storage area for data recovery, so that the damage in case of disaster can be minimized, and the restorability of dynamic high-precision data is guaranteed.
Drawings
FIG. 1 is a block diagram of a data storage system of the present invention;
FIG. 2 is a diagram of a real-time message data cache architecture of the present invention;
FIG. 3 is an architecture diagram of a two-level Key implementation of the present invention for real-time data storage;
FIG. 4 is a schematic view of a directory tree of the static high-precision map data storage of the present invention;
FIG. 5 is a diagram illustrating historical representations in an embodiment of the present invention
FIG. 6 is a diagram of an archival data storage architecture of the present invention.
Detailed Description
The technical scheme of the invention is further explained by combining the attached drawings.
In the intelligent network system, vehicles, roads, environments and the like generate massive multi-domain dynamic high-precision map data (OBU source data, RSU source data and MEC fusion result data) every day, such as dynamic high-precision map data of vehicle dynamics, roadside traffic target dynamic data, environment perception, early warning and the like; file data such as point cloud, picture, video and the like; the method comprises the steps of generating about 4T of static high-precision maps such as metadata information and sensing equipment information and spatial data such as vectors, images, navigation data, laser point cloud data and 3D models every day, and adopting different storage strategies for data features with different types and different periods. As shown in fig. 1, the high-precision map-based data storage system according to the present invention includes a message buffer area, a real-time storage area, a short-term storage area, and a long-term storage area.
A message buffer area: dynamic high-precision data produced by sensing equipment such as vehicles, road sides and environments are firstly accessed into a KafKa message queue for message caching.
Real-time storage area: a set of highly-concurrent distributed response models is established based on AKKA, data in a message cache region are subscribed to Redis storage, and the data are written in an overlay mode, so that the real-time performance of the data is guaranteed.
Short-term storage area: three types of data storage are adopted, namely distributed unstructured data storage, HBase storage and distributed object storage are adopted in the embodiment, FastDFS storage and a distributed spatial database are adopted in the embodiment, and PostgreSQL storage is adopted in the embodiment.
Storing high-precision dynamic data related to vehicles and roads into distributed unstructured data storage, storing data such as point cloud, pictures, video data and slices, images and models of high-precision static maps by adopting distributed objects, and storing vector data of the high-precision static maps by adopting a space library;
the high-precision real-time dynamic data storage period is one year, and the high-precision real-time dynamic data are destroyed and stored in a long-term storage area after the high-precision real-time dynamic data storage period expires; the point cloud, video and picture data are stored for one month in a short-term storage area, and are destroyed and stored in a long-term storage area after the point cloud, video and picture data are stored for one month in a short-term storage area; and the high-precision static map data is destroyed according to real-time requirements and is stored in a long-term storage area.
Long-term storage area: the short-term storage area due data is stored in the distributed file system in a file mode according to time, and meanwhile, an index directory is established by using the elastic search according to time, cataloging, metadata and the like, so that data retrieval and extraction are facilitated. And storing the video, point cloud, picture and other file data in the long-term storage area for three years, and storing the rest data in a user-defined time as required.
The data storage method based on the high-precision map comprises the following contents:
(1) real-time message data caching
The message data cache is mainly used for receiving real-time messages of the vehicle end and real-time messages reported by the road side end in real time, most of the messages of the vehicle end and the road side end are structured data, and the messages can be stored and consumed through a message queue. As shown in fig. 2, the real-time message data caching comprises the following steps:
(11) receiving the message sent by the producer through a message receiving module, and forwarding the message to a queue; the queue is a kafka message queue, and is stored by adopting a memory, so that the main purpose is to ensure the quick reading of the message and can be consumed by consumers;
(12) the message pulling module is mainly used for pulling the message from the queue by the client and sending the message to the consumer;
(13) the message is consumed by the consumer and is stored persistently, so that the loss of the message is mainly prevented, and the expired message needs to be deleted from the persistent storage, thereby preventing the occupation of a large amount of space.
(2) Real-time data storage of high-precision dynamic map numbers
As shown in fig. 3, a secondary Key manner is adopted to store high-precision dynamic map data cache data into a high-performance distributed K-V cache system based on a memory in a coverage mode, and only the latest data is retained, which adopts a Hash storage format; the second-level Key mode takes an OEM (Original Equipment manufacturer) manufacturer as a first-level Key and takes a unique identification number as a second-level Key, so that the quick retrieval and pushing of real-time data can be met.
(3) High-precision static map data and high-precision dynamic map short-term storage
And (3.1) storing the high-precision dynamic data into a distributed unstructured data storage, wherein the storage period is one year, and the high-precision dynamic data are destroyed from a short-term storage area and stored into a long-term storage area after the storage period is expired.
(3.2) storing the high-precision static map data vector file into a distributed spatial database
Storing two-dimensional vector data of roads, lanes, road center lines, vector buildings and the like in a distributed spatial database, importing whether relevant information of field, table name and projection coordinate configuration is correct or not, performing operations such as real-time preview, editing and modification, error check and the like on the vector data, and setting a storage period as required.
(3.3) storing the static high-precision map data slices and the model files into a distributed object storage
Data directories are newly built on a server, storage directories such as slice files and model files are sequentially newly built, as shown in fig. 4, a directory tree imports three-dimensional vector building data including attribute information such as a building vector plane, a floor number or a building height, and stores the files in the server/data/dpi/tile directories, and a storage period is set as required.
And (3.4) storing the file data and the space data in a FastDFS storage area, and setting a storage period as required.
(4) Historical data storage
The data with the use frequency lower than the threshold value of the vehicle end and the road side section are set as historical data, the threshold value can be set as required, the vehicle end data and the data reported by the road side end are both structured data, and the structured data are both based on relational data, so the historical data of the high-precision map is stored in a relational database. The data of the relational database is organized according to a table structure, and for historical data, the same table structure as active data is established for storage.
The method comprises the steps that a 0 point 0 minute 0 second fixed in each month is used for executing a database trigger, an old table is renamed, then a new table which is the same as the table before renaming is established, and new incoming data are stored in the new table; the renaming rule is XX (year) XX (month) _ table name, so that the previous month data is saved on the surface of the table with the month format, and the table with the month format becomes a history table after the accumulation of time. The history representation is shown, for example, in fig. 5.
(5) Archival data storage
Setting historical data with a user access rate lower than a threshold value as archival data, setting the threshold value as required, and archiving storage of the current high-precision map, wherein the archival storage is mainly used for archiving and storing dynamic data and quasi-dynamic data, and the dynamic data is real-time data, roadside real-time data and point cloud data of vehicles.
The benefits of data archival storage are as follows:
1. the cost is saved, and the archival data is saved by adopting a low-cost storage medium.
2. The access performance of the active data is enhanced, and due to the reduction of historical data, the data retrieval is reduced, and the performance of a user for inquiring the active data is improved.
3. The knowledge storage provides considerable data support for later data mining and data analysis.
The technical points of archiving data storage are as follows:
1. and (3) retrieving: the meaning of the archived data is inquired, if the data cannot be inquired and used, the archiving has no meaning, and the data needed by the user is found from historical mass data, so that the searchable capability is provided for the user, and the time for the user to find the data is greatly saved.
2. A bottom layer: the data filing method has the advantages that the data filing quantity is large, the data filing quantity is continuously expanded, so that the consumed storage space is large, if the cost of the storage space consumption is high, a large expenditure is caused to enterprises and individuals, the data filing purpose is to create a large value, and if the cost of the data storage is too high, the data filing is meaningless.
3. And (3) expandable: the storage is mainly extensible, the archived data is continuously increased because the historical data is continuously increased, and if the data storage cannot be extended, only the data with a fixed size and within a period of time can be stored, and new and old data cannot be stored.
4. The sea volume property: the high-precision dynamic data are not only various in data types, but also large in data quantity, and larger in historical filing data, so that the high-precision map data are large in filing data.
5. Integrity: data integrity is maintained between multiple data formats.
6. Compressibility: efficient storage of file data to conserve storage capacity while facilitating fast retrieval of data.
According to the storage characteristics of the archived data analyzed above, the data format of the high-precision map data includes structured data and unstructured data, the archived data is stored in a file format, as shown in fig. 6, the storage flow is as follows:
(5.1) firstly, the archiving system reads high-precision data to be archived, and the type, format and content of the data and the data generation time can be acquired.
And (5.2) after the data is obtained, compressing the data through a compression algorithm, and storing more data in the same-capacity magnetic disk after compression.
And (5.3) sequentially writing the corresponding data into the disk according to the archiving time of the data.
And (5.4) if the storage space of the disk is insufficient, prompting the system to expand the capacity at the moment. After the new disk is added, the data is written into the new disk according to the filing time, the capacity of the disk needs to be inquired at the writing end, and the data is written into the disk with the maximum residual capacity according to the maximum residual capacity algorithm.
And 5.5, after the data is stored on the disk, submitting the data metadata information to a metadata management module for management.
(5.6) successful metadata storage is counted as successful archiving.
(5.7) the user is to retrieve the archived data, provide a retrieval interface to search,
and (5.8) when the user searches the data, inquiring the data through metadata information, wherein the metadata records the disk position of the archived data storage and the physical address placed on the disk.
Claims (10)
1. A high-precision map-based data storage system, comprising:
the message buffer area is used for accessing the high-precision map data into a message queue for buffering;
the real-time storage area is used for performing Redis subscription storage on the high-precision dynamic map data in the message cache area;
the short-term storage area comprises an HBase storage area used for storing high-precision dynamic map data, a PostgreSQL space library used for storing high-precision static map vector data and a FastDFS storage area used for storing file data and space data;
and the long-term storage area is used for storing expired data in the short-term storage area in a file mode and establishing an index directory.
2. A high-precision map-based data storage system according to claim 1, wherein historical data with the frequency of use lower than a threshold value is stored in the long-term storage area, a new data table is periodically established in the relational database for storing the historical data, and the data table stored in each period is named and stored according to time.
3. A high-precision map-based data storage system according to claim 2, wherein historical data with a user access rate lower than a threshold is archived for storage, the archive storage module comprises a data writing area for compressing and storing archive data into a disk, a metadata management area for storing disk locations where archive data are stored and physical addresses in the disk, and a data retrieval area for querying the archive data by calling the metadata management area when queried by a user.
4. A high-precision map-based data storage system according to claim 1, wherein the message buffer receives real-time high-precision map data through the message receiving module and stores the data into the queue, the message is pulled from the queue through the message pulling module and sent to the consumer, and the messages in the queue are stored persistently.
5. A data storage method based on a high-precision map is characterized by comprising the following steps:
(1) caching received real-time messages of the vehicle end and the road end through a message queue;
(2) storing the high-precision dynamic map cache data through message subscription; meanwhile, storing high-precision dynamic map data into an HBase storage area, and setting a storage period;
(3) storing the high-precision static map vector class data into a PostgreSQL space library, and storing the high-precision dynamic map file data and the space data in a FastDFS storage area; respectively setting storage periods;
(4) storing the expired data to a long-term storage area in a file mode according to time, establishing an index directory and setting a storage period;
(5) and destroying the expired data in the long-term storage area.
6. The high-precision map-based data storage method according to claim 5, wherein the step (3) further comprises: setting the high-precision map data with the use frequency smaller than the threshold value as historical data, storing the historical data in a relational database, regularly executing a database trigger to newly establish a data table, and naming and storing the stored data table in each period according to time.
7. A high-precision map-based data storage method as claimed in claim 6, wherein historical data with a user access probability lower than a threshold is set as archived data, the archived data is compressed and stored to a disk, the disk position of the archived data and the physical position of the archived data in the disk are sent to a metadata management area for storage, and the metadata management area is invoked to obtain the archived data when a user queries.
8. The high-precision map-based data storage method according to claim 5, wherein the message buffering method in step (1) is as follows:
(11) the message receiving module receives the real-time message and forwards the real-time message to the kafka queue;
(12) the messages in the kafka queue are subjected to persistent storage;
(13) and the message pulling module pulls the message from the kafka queue to be sent to the consumer for data reading.
9. The high-precision map-based data storage method according to claim 5, wherein in step (2), the cache data is stored in a distributed message model established based on AKKA by using a two-level Key method, wherein an OEM manufacturer is a first-level Key, and the unique identification number is a second-level Key.
10. A high precision map based data storage method according to claim 9, characterized in that the step (2) is performed by using an overlay mode.
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