Method and device for processing data in online business processing

Abstract

The invention discloses a method for processing data in online business processing, which comprises the following steps: a data partitioning field of a target data table is confirmed according to a business characteristic; and the target data table is divided into a plurality of subtables according to the data partitioning field. The invention uses the method that the core data table in an online business processing system is divided into a plurality of subtables to enable the data amount of the subtables after division to be lower than that of the original core data table. When DDL operation is carried out to the subtables, the occupied space of the temporary table is small, and blocked talks are few, thus the pressure born by the system is greatly reduced, and the maintainability and the manageability of the core data table of the database are improved.

Description

technical field [0001] The present invention relates to the field of online transaction processing, in particular to a data processing method and device in online transaction processing, and a data query method and device in online transaction processing. Background technique [0002] On-line transaction processing (On-Line Transaction Processing, OLTP) refers to the use of computer networks to connect business processing computer equipment or networks distributed in different geographical locations with the business management center network, so that unified processing can be performed on any network node. , real-time business processing activities or customer service. OLTP is the main application of the traditional relational database. In the OLTP environment, due to the rapid development of business, in the database, some business core data tables have a huge data volume, reaching more than 100 million. Transaction processing features lead to extremely high concurrent ac...

AI Technical Summary

Problems solved by technology

However, the second method has the following disadvantages: first, when performing DDL operations on the business core data table, it will affect all sessions accessed to this data table, the blocking phenomenon is serious, and the risk is still high, and if the DDL operation counts If the data is inaccurate and the hard parsing produces an incorrect SQL execution plan, then all sessions running this SQL will be affected by this, resulting in unbearable high pressure on the system; moreover, the hash algorithm of the Oracle partition table is a black box, and all data All visits need to go through this unique path. For high-concurrency OLTP, such core tables are accessed very frequently, so performing this hash operation will also consume a considerable amount of CPU of the database server; in addition, Oracle's partition table cannot span databases. When storage becomes the bottleneck of the entire system, the horizontal scalability of data is poor

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