Database storage process migration method and system

Abstract

The embodiment of the invention provides a database storage process migration method. The migration method comprises the steps of obtaining a first storage process of a first database, a first syntaxstructure of the first database and a second syntax structure of a second database; converting the first storage process into a second storage process of a second database according to the first syntax structure and the second syntax structure; packaging the second storage process into a second database; obtaining first data stored in a first database, and synchronizing the first data to a seconddatabase to obtain second data; and according to the second storage process, performing data processing on the second data, and checking a processing result of the second data. According to the embodiment of the invention, the storage process of the traditional database can be converted into the storage process of the Hive database according to the storage process syntax structure of the Hive database; and then, the conversion accuracy of the storage process is checked according to the processing result of the data in the Hive database, so that the migration efficiency of the database storageprocess is greatly improved.

Description

technical field [0001] The embodiments of the present invention relate to the technical field of databases, and in particular, to a database storage process migration method, system, computer equipment, and computer-readable storage medium. Background technique [0002] With the widespread application of big data, more and more Internet companies are beginning to migrate the traditional data warehouse structure to the big data platform. Hive is a data warehouse tool based on Hadoop, which can map structured data files into a database table, and Hive also uses Structured Query Language (Sql), which can provide simple Sql query functions, and can also Convert Sql statements into MapReduce tasks to run, and most existing databases perform data operations based on MapReduce tasks. Therefore, for managers of traditional data warehouses, they can quickly implement simple MapReduce statistics in Hive data warehouses through Sql-like statements, without using special MapReduce, and...

AI Technical Summary

Problems solved by technology

[0003] However, the Sql-like language used by Hive is a query language (Hibernate Query Language, Hql), and there are many differences between the Sql syntax of traditional data warehouses such as Oracle and the Sql syntax of Hive. In traditional databases, Update, The Delete statement is convenient for data update and data deletion, but Hive does not support Sql language Update, delete and other statements to directly perform data update, data deletion and other operations

In addition, Hive cannot roll back after data update and data deletion

Therefore, the stored procedures of traditional data warehouses need to be manually transformed before they can be packaged into Hive, which takes a lot of time and manpower. The so-called stored procedures are a set of Sql statements to complete specific functions, which are compiled and stored in the database. The name of the stored procedure and given parameters (if the stored procedure has parameters) to call to execute it

[0004] The present invention aims to solve the problem that the storage procedure of the traditional database cannot be directly migrated to the Sql database due to the differences in the grammatical structure of the Sql database

Images