One of the significant problem in peer-to-peer databases is collision problem. These databases do not rely on a central leader that is a reason to increase scalability and fault tolerance. Utilizing these systems in high throughput computing cause more flexibility in computing system and meanwhile solve the problems in most of the computing systems which are depend on a central nodes. There are limited researches in this scope and they seem are not suitable for using in a large scale. In this paper, we used Cassandra which is a distributed database based on peer-to-peer network as a high throughput computing system. Cassandra uses Paxos to elect central leader by default that causes collision problem. Among existent consensus algorithms Raft separates the key elements of consensus, such as leader election, so enforces a stronger degree of coherency to reduce the number of states that must be considered, such as collision.
翻译:同侪数据库中的一个重大问题是碰撞问题。 这些数据库并不依赖于一个中央领导,而中央领导是增加可缩放性和过失容忍度的原因。 在高载量计算中使用这些系统在计算系统方面带来更大的灵活性,同时解决大多数依赖中心节点的计算系统的问题。在这个范围内,研究范围有限,似乎不适合大规模使用。在本文件中,我们使用基于同侪网络的分布式数据库卡桑德拉作为高载量计算系统。卡桑德拉利用和平协会(Cassandra)以默认方式选择造成碰撞问题的中央领导。在现有的协商一致算法中,拉夫特分离了共识的关键要素,如领导人选举,因此,为了减少必须考虑的诸如碰撞等国家的数目,我们加强了一致性。