Data backflow method and system and data access method and system in relational database

Abstract

The invention discloses a data backflow method and system and a data access method and system in a relational database. The data backflow method comprises the steps: creating a first data table in the relational database, wherein the first data table comprises a name field and a data content field; determining a second data table where data backflow needs to be carried out in a distributed system, and the format and the name of the second data table; reading all original data in the second data table according to the format of the second data table, converting all the original data into a character string, and in the character string, utilizing preset separators for conducting separation according to different rows and columns where the original data are located in the second data table, wherein the separators comprise row separators and column separators; using the character string as the data content of one record, writing the data content of the record into the data content field of the first data table, using the name of the second data table as the name of the record, and writing the name of the record into the name field of the first data table.

Description

technical field [0001] The present application relates to the technical field of data processing, in particular to data reflow and data access methods and systems in relational databases. Background technique [0002] The amount of data generated by the Internet industry is very large, and the amount of calculation generally needs to be completed in large-scale distributed systems such as Hadoop. For example, relevant log data, browsing data, user data, transaction data, commodity data, etc. will all be passed through Hadoop completes related calculations. [0003] Hadoop makes full use of the power of the cluster for high-speed computing and storage, so it is very advantageous for computing large amounts of data. However, since the available data processed by Hadoop is often scattered and stored on different servers, and generally only provides command-line reading, it is not very friendly in terms of user access and data acquisition. Therefore, the available data after p...

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Problems solved by technology

[0005] However, in this traditional method, because every time a Hadoop table is generated, the same table must be created in the relational database, and the process of creating a table in the database needs to be followed every time, which is relatively cumbersome and lengthy, and the relational database Every time a new table is created in the database, corresponding code needs to be written to access the data in the table, and the workload is relatively large

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