Abstract
Log replication is a key component in highly available database systems. In order to guarantee data consistency and reliability, it is common for modern database systems to utilize Paxos protocol, which is responsible for replicating transactional logs from one primary node to multiple backups. However, the Paxos replication needs to store and synchronize some additional metadata, such as committed log sequence number (commit point), to guarantee the consistency of the database. This increases the overhead of storage and network, which would have a negative impact on the throughput in the update intensive work load. In this paper, we present an implementation of log replication and database recovery methods, which adopts the idea of piggybacking, i.e., commit point can be embedded in the commit logs. This practice not only retains virtues of Paxos replication, but also reduces disk and network IO effectively. We implemented and evaluated our approach in a main memory database system. Our experiments show that the piggybacking method can offer 1.3× higher throughput than typical log replication with synchronization mechanism.
Highlights
Through the smart phone, we can submit transaction processing requests to the databases at any time
We present an implementation of log replication and database recovery methods, which adopts the idea of piggybacking, i.e., commit point can be embedded in the commit logs
We evaluate the performance of several different implementations of the synchronization of the commit point, i.e., piggybacking method, synchronization method and asynchronous method, which are implemented in the open source database system OceanBase 0.4.2:
Summary
We can submit transaction processing requests to the databases at any time. In Chinese ‘‘Single Day’’ (i.e., Double 11 shopping carnival), the total transactions may hit the level of hundreds of millions in the first minute. To resolve this challenge, many NoSQL and NewSQL systems were designed and implemented [7]. Compared to the relational DBMS’s, NoSQL systems have some excellent characteristics, such as without needing to predefine the data schema, high scalability, share-nothing architecture and asynchronous replication. These features provide strong support for the Internet applications in the Web 2.0. NoSQL systems have got extensive attentions, and main industry players including Google, Amazon and Facebook have developed their NoSQL database products which have played a key role in their services
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
