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There is no unified definition of Data anomalies, which refers to thespecific data operation mode that may violate the consistency of the database.Known data anomalies include Dirty Write, Dirty Read, Non-repeatable Read,Phantom, Read Skew and Write Skew, etc. In order to improve the efficiency ofconcurrency control algorithms, data anomalies are also used to define theisolation levels, because the weak isolation level can improve the efficiencyof transaction processing systems. This paper systematically studies the dataanomalies and the corresponding isolation levels. We report twenty-two new dataanomalies that other papers have not reported, and all data anomalies areclassified miraculously. Based on the classification of data anomalies, two newisolation levels systems with different granularity are proposed, which revealsthe rule of defining isolation levels based on data anomalies and makes thecognition of data anomalies and isolation levels more concise.

Systematic definition and classification of data anomalies in DBMS (English Version)