Mass data reconciliation method and device, medium and computer equipment

Abstract

The invention provides a mass data reconciliation method and device, a computer storage medium and computer equipment. The method comprises the steps of obtaining a to-be-reconciliated data set and areconciliated file associated with a reconciliated task execution instruction in response to the reconciliated task execution instruction; splitting the to-be-reconciliated data set into a plurality of to-be-reconciliated data subsets; performing account checking operation on the plurality of to-be-checked data subsets according to the account checking file to obtain account checking results corresponding to the to-be-checked data subsets; and according to the account checking result corresponding to each to-be-checked data subset, carrying out account balancing processing. According to the technical scheme, account checking processing is carried out on mass data, the time spent on the account checking process of the mass data can be effectively shortened, and the account checking efficiency of the mass data is remarkably improved.

Description

technical field [0001] The present invention relates to the field of payment and settlement, in particular, the present invention relates to a massive data reconciliation method, device, medium and computer equipment. Background technique [0002] Rolling accounts is one of the accounting procedures. Periodically or when the company needs it, check the general ledger and subsidiary ledger, and check whether the daily bookkeeping is consistent. Reconciliation is the core process of reconciliation, which is used to confirm whether the accounts of two or more parties are consistent, and if they are inconsistent, what are the errors. [0003] The current method of rolling accounts includes using database SQL statements to reconcile accounts and transferring the reconciliation processing logic from the database to the memory, such as using the redis memory database for processing. [0004] However, when reconciliation processing is required for massive data, the above two method...

AI Technical Summary

Problems solved by technology

[0004] However, when reconciliation processing is required for massive data, the above two methods are not suitable

Due to the large amount of data that needs to be processed, if the database is used for processing, it will cause insufficient memory, and a large number of database queries will exhaust database resources, which will affect online transactions; if the redis database is used for processing, it will cause large transaction volume The amount of data imported is large and the data warm-up is slow, so database performance can easily become a bottleneck

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