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Partial Rollback-based Scheduling on In-memory Transactional Data Grids
Big Data Research ( IF 3.5 ) Pub Date : 2017-08-24 , DOI: 10.1016/j.bdr.2017.06.004
Junwhan Kim

In-memory transactional data girds, often referred to as NoSQL data grids demand high concurrency for scalability and high performance in data-intensive applications. As an alternative concurrency control model, distributed transactional memory (DTM) promises to alleviate the difficulties of lock-based distributed synchronization. However, if a transaction aborts, DTM suffers from additional communication delays to remotely request and retrieve all its objects again, resulting in degraded performance. To avoid unnecessary aborts, the multi-versioning (MV) model of using multiple object versions in DTM can be considered. MV transactional memory inherently guarantees commits of read-only transactions, but limits concurrency of write transactions. We present a new transactional scheduler, called partial rollback-based transactional scheduler (or PTS), for a multi-versioned DTM model. The model supports multiple object versions to exploit concurrency of read-only transactions, and detects conflicts of write transactions at an object level. Instead of aborting a transaction, PTS assigns backoff times for conflicting transactions, and the transaction is rolled-back partially. We implemented PTS on Infinispan, and conducted comprehensive experimental studies on no and partial replication models. Our implementation reveals that PTS improves transactional throughput over MV-Transactional Forwarding Algorithm without PTS and a scalable one-copy serializable partial replication protocol (SCORe) by as much as 2.4× and 1.3×, respectively.



中文翻译:

内存事务数据网格上基于部分回滚的调度

内存中的事务数据网格(通常称为NoSQL数据网格)要求高并发性,以便在数据密集型应用程序中实现可伸缩性和高性能。作为一种可选的并发控制模型,分布式事务内存(DTM)有望减轻基于锁的分布式同步的困难。但是,如果事务中止,DTM会遭受额外的通信延迟,从而无法远程请求并再次检索其所有对象,从而导致性能下降。为了避免不必要的中止,可以考虑在DTM中使用多个对象版本的多版本(MV)模型。MV事务内存从本质上保证了提交只读事务,但限制了写事务的并发性。我们提出了一种新的事务调度程序,称为基于部分回滚的事务调度程序(或PTS),用于多版本DTM模型。该模型支持多个对象版本,以利用只读事务的并发性,并在对象级别检测写事务的冲突。PTS不会中止事务,而是为冲突的事务分配退避时间,并且事务会部分回滚。我们在Infinispan上实施了PTS,并对无复制和部分复制模型进行了全面的实验研究。我们的实现表明,与不带PTS的MV事务转发算法和可伸缩的一副本可序列化部分复制协议(SCORe)相比,PTS的事务吞吐量分别提高了2.4倍和1.3倍。并在对象级别检测写事务冲突。PTS不会中止事务,而是为冲突的事务分配退避时间,并且事务会部分回滚。我们在Infinispan上实施了PTS,并针对无复制和部分复制模型进行了全面的实验研究。我们的实现表明,与不带PTS的MV事务转发算法和可伸缩的单副本可序列化部分复制协议(SCORe)相比,PTS的事务吞吐量分别提高了2.4倍和1.3倍。并在对象级别检测写事务冲突。PTS不会中止事务,而是为冲突的事务分配退避时间,并且事务会部分回滚。我们在Infinispan上实施了PTS,并针对无复制和部分复制模型进行了全面的实验研究。我们的实现表明,与不带PTS的MV事务转发算法和可伸缩的单副本可序列化部分复制协议(SCORe)相比,PTS的事务吞吐量分别提高了2.4倍和1.3倍。

更新日期:2017-08-24
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