Differential logging: a commutative and associative logging scheme for highly parallel main memory database

Abstract

With a GByte of memory priced at less than $2000, main-memory DBMSs (MMDBMSs) are emerging as an economically viable alternative to disk-resident DBMSs (DRDBMSs) in many problem domains. The MMDBMS can show significantly higher performance than the DRDBMS by reducing disk accesses to the sequential form of log writing and occasional checkpointing. Upon a system crash, the recovery process begins by accessing the disk-resident log and checkpoint data to restore a consistent state. With increasing CPU speed, however, such disk access is still the dominant bottleneck in MMDBMSs. To overcome this bottleneck, this paper explores alternatives of parallel logging and recovery. The major contribution of this paper is the so-called differential logging scheme that permits unrestricted parallelism in logging and recovery. Using the bit-wise XOR operation both to compute the differential log between the before and after images and to recover the consistent database state, this scheme offers the room for significant performance improvement in the MMDBMS. First, with logging done on the difference, the log volume is reduced to almost half compared with the conventional physical logging. Second, the commutativity and associativity of XOR enables processing of log records in an arbitrary order. This means that we can freely distribute log records to multiple disks to improve the logging performance. During the recovery time, we can do a parallel restart independently for each log disk. This paper shows the superior performance of the differential logging compared to the physical logging in a shared-memory multiprocessor environment.