Data writing and reading method and device

Abstract

The invention relates to the field of finance science and technology, and discloses a data writing and reading method and a device, and the method comprises the steps: carrying out the grammar analysis of a received copying request of first data, and determining an abstract syntax tree, wherein the abstract syntax tree comprises N first write task nodes; for each first write task node, determining a written first database and a corresponding converter; converting the first write task node into a first write task node in an execution tree of the copying request through a converter; when N first write task nodes of the execution tree are executed, sending N first write tasks to N first databases respectively; wherein the first writing task is used for writing the first data into the corresponding first database. Through the mode, the corresponding first writing task can be generated for the first data in any business scene, the dependence on the storage engine of the first database corresponding to each first writing task is reduced, and the efficiency and the flexibility of synchronous copying of different business data are improved.

Description

technical field [0001] The embodiments of the present application relate to the field of financial technology (Fintech), and in particular, to a data writing and reading method and device. Background technique [0002] With the development of computer technology, more and more technologies (such as big data, cloud computing or blockchain) are applied in the financial field, and the traditional financial industry is gradually transforming into financial technology. In the context of big data technology, it is necessary to Store massive data based on the database. [0003] In order to ensure the high availability of data, one way is to write to the primary cluster and then synchronize the data of the primary cluster to the standby cluster through asynchronous replication to achieve the final consistency of data. However, under this technical scheme of asynchronous replication of active and standby clusters, if users write frequently and have a huge amount of data, asynchronou...

AI Technical Summary

Problems solved by technology

However, under this technical scheme of asynchronous replication of active and standby clusters, if users write frequently and have a huge amount of data, asynchronous replication across clusters will cause huge synchronization costs, such as very high bandwidth requirements

When there is high latency in asynchronous replication, once the main cluster goes down, the standby cluster will not be able to provide services for a long time, which will have a great impact on the client; in addition, this technical solution has requirements for the versions of the main and standby clusters. Generally, it is mandatory that the relevant storage engine versions of the primary cluster and the standby cluster must be the same, otherwise it is likely to cause the primary cluster to copy the synchronized data, and the standby cluster cannot parse normally; further, once an exception occurs in the primary cluster, the user will switch to the standby cluster , at this time, the standby cluster provides services as the primary cluster. After the original primary cluster recovers, a manual switchback is required to initiate asynchronous data replication and synchronization from the new primary cluster (original standby cluster) to the new standby cluster (original primary cluster), resulting in Huge operation and maintenance costs

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