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TRAID: Exploiting Temporal Redundancy and Spatial Redundancy to Boost Transaction Processing Systems Performance

机译:TRAID:利用时间冗余和空间冗余来提高事务处理系统的性能

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In the past few years, more storage system applications have employed transaction processing techniques to ensure data integrity and consistency. Logging is one of the key requirements to ensure transaction Atomicity, Consistency, Isolation, Durability (ACID) properties and data recoverability in transaction processing systems (TPS). Recently, emerging complex I/O bound transactions have resulted in substantially more log content and higher log flushing latency. The latency will delay transaction commit and decrease the overall throughput of the TPS. On the other hand, RAID is widely used as the underlying storage system for Databases to guarantee system reliability and availability with high I/O performance. In this paper, we observe the overlap between the redundancies in the underlying RAID storage system and database logging system, and propose a novel reliable storage architecture called Transactional RAID (TRAID). TRAID deduplicates this overlap by only logging one compact version (XOR results) of recovery references for the updating data. It minimizes the amount of log content and thereby boosts the overall transaction processing performance. At the same time, TRAID guarantees the same RAID reliability, as well as recovery correctness and ACID semantics as current TPS setups. We experiment on two open-source database systems: Berkeley DB and PostgreSQL, with three different workloads: standard OLTP benchmark TPC-C, customized TPC-C with strong access locality, and customized TPC-C with write-intensive property. Then we test TRAID performance with "Group CommitȁD; enabled. Finally, we evaluate the recovery efficiency of TRAID. Our extensive results demonstrate that for throughput, TRAID outperforms RAID by 43.24-69.5 percent for various workloads; it also saves on log space by 28.57-35.48 percent, and outperforms RAID by about 20 percent in throughput with "Group CommitȁD; enabled. At last, we show that TRAID outperforms RAID from 28.7 to 35.7 p-nrcent during the recovery.
机译:在过去的几年中,更多的存储系统应用程序采用事务处理技术来确保数据的完整性和一致性。日志记录是确保事务处理系统(TPS)中的事务原子性,一致性,隔离性,持久性(ACID)属性和数据可恢复性的关键要求之一。最近,新出现的复杂的受I / O约束的事务导致大量的日志内容和更高的日志刷新延迟。延迟将延迟事务提交并降低TPS的整体吞吐量。另一方面,RAID被广泛用作数据库的基础存储系统,以确保系统的可靠性和高I / O性能的可用性。在本文中,我们观察了底层RAID存储系统和数据库记录系统中的冗余之间的重叠,并提出了一种新颖的可靠存储架构,称为事务RAID(TRAID)。 TRAID通过仅记录恢复数据的一个精简版本(XOR结果)来更新数据,从而消除了这种重叠。它最大程度地减少了日志内容的数量,从而提高了整体事务处理性能。同时,TRAID保证与当前TPS设置相同的RAID可靠性以及恢复正确性和ACID语义。我们在两个开源数据库系统上进行了实验:Berkeley DB和PostgreSQL,它们具有三种不同的工作负载:标准OLTP基准TPC-C,具有强大访问局部性的定制TPC-C和具有写密集型属性的定制TPC-C。然后,使用“启用组提交”来测试TRAID性能。最后,我们评估TRAID的恢复效率。我们的广泛结果表明,对于吞吐量,TRAID在各种工作负载下的性能比RAID高43.24-69.5%;它还节省了28.57的日志空间-35.48%,“ GroupCommitȁD”在吞吐量方面比RAID高出约20%。已启用。最后,我们显示在恢复过程中,TRAID的性能从RAID的28.7提高到35.7 p-nrcent。

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