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A highly scalable distributed indexing method for big data of new urban rail trains

An urban rail train and big data technology, applied in database indexing, structured data retrieval, digital data information retrieval, etc., can solve the problem that the key-value model database does not support auxiliary indexing, etc., to improve data retrieval efficiency and high scalability , the effect of low latency

Active Publication Date: 2022-03-15
ZHEJIANG UNIV
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Problems solved by technology

[0006] Aiming at the problem that the key-value model database does not support auxiliary indexes, the present invention provides a highly scalable distributed index method for big data of new urban rail trains, which is used to optimize and improve the auxiliary index for the key-value data storage model.

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  • A highly scalable distributed indexing method for big data of new urban rail trains
  • A highly scalable distributed indexing method for big data of new urban rail trains

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Embodiment Construction

[0040] The technical solution of the present invention will be further described in conjunction with specific implementation and examples.

[0041] like figure 1 , specific embodiments of the present invention and its implementation process are as follows:

[0042]Step 1: Use server clusters to store and build a database for the big data of new urban rail trains, connect the nodes in the server clusters to form a server cluster with a graph topology, and then divide the entire value space of the secondary key into several communities Each small interval is used as a secondary key index range, and each server is allocated a secondary key index range according to the interconnection relationship of the server cluster nodes.

[0043] Such as figure 2 In the example shown, there are 7 servers in the cluster. First, build a binary tree containing 7 nodes, and correspond the servers to the nodes of the binary tree one by one. And divide the entire index interval (0,35] of the se...

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Abstract

The invention discloses a highly scalable distributed indexing method for large data of new urban rail trains. For the big data of new urban rail trains, server clusters are used to store and build databases to form a graph topology server cluster, and each server is assigned a secondary key index range as the index interval; the key-value type data is segmented and distributed Each server builds a shard index for the local data shards; each server selects an intermediate node from the local shard index, builds an external link index and publishes it to other determined servers; uses the secondary key index to process query request. The present invention quickly locates, searches and locates the server that stores the required data blocks, and establishes an auxiliary index to support rapid and accurate data query functions, solves the problem that the key-value storage model lacks auxiliary indexes, and can improve the data capacity of the big data storage system Retrieval efficiency, high scalability and low latency.

Description

technical field [0001] The invention relates to a key-value model data storage and indexing method of a computer database, in particular to a highly scalable distributed indexing method for large data of new urban rail trains. Background technique [0002] A large amount of structured and unstructured data will be generated during the operation of new urban rail trains, including various data collected by sensors, vehicle operation and maintenance log records, and so on. Therefore, it is necessary to choose a reasonable storage model for unified storage management of various heterogeneous data. Traditional relational model databases are limited by their scalability and are not suitable for managing huge amounts of data, nor can they provide efficient data processing capabilities; while NoSQL data storage systems have good scalability and can be easily deployed in distributed The cluster can store huge amounts of data and use the parallel processing capability of the cluster...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/22G06F16/2458
CPCG06F16/2228G06F16/2458
Inventor 陈刚刘晋潘硕李辉张哲槟江大伟陈珂吴晓凡
Owner ZHEJIANG UNIV
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