Method for Generating Massive Data
At present,there is not exist a flexible data generation framework which is generally accepted.This paper extended existing data generation methods to create a framework for generating massive data.The work presented user-defined functions and expressions to execute iteration operations based on data sequences,established connection between data sequences and RDBMS.A mechanism was added to control the inconsistency degree of data.The work analysed the cases that several iteration nodes had simple references and complex references for establishing an iteration mode,which resolved the problem that several iteration nodes had multi-references.The mode produced an additional overload,but it avoided buffering.A data generation language was presented to transfer iterations to SQL for generating different data schemas and multiple-grain inconsistent data.The experiments refer to data schemas of benchmarks,the results show that the approach is efficient.