Over the past decade, in-memory database systems have become prevalent in academia and industry. Evaluation results demonstrate that compared with state-of-the-art schemes, continuity hashing achieves high throughput (i.e., 1.45X - 2.43X improvement), low latency (about 1.7X speedup) and the smallest number of PM writes with various workloads, while has acceptable load factors of about 70%. Continuity hashing further leverages indicators that can be atomically modified to support log-free PM consistency for all the write operations. In the continuity hashing, remote read only needs a single RDMA read to directly fetch the home bucket and the neighbouring SBuckets, which contain all the positions of maintaining a key-value item, thus alleviating RDMA access amplification. The continuity hashing leverages a fine-grained contiguous shared region, called SBuckets, to provide standby positions for the neighbouring two buckets in case of hash collisions. In order to address these problems, we propose a continuity hashing, which is a "one-stone-two-birds" design to optimize both RDMA and PM. In general, existing hashing schemes separately optimize RDMA and PM, thus partially addressing the problems of RDMA Access Amplification and High-Overhead PM Consistency. Such numbers outperform a state-of-the-art single-node system (i.e., Silo) and a distributed transaction system (i.e., Calvin) by at least 1.9X and 29.6X for TPC-C.Ĭoalescing RDMA and Persistent Memory (PM) delivers high end-to-end performance for networked storage systems, which requires rethinking the design of efficient hash structures. Evaluation using typical OLTP workloads including TPC-C and SmallBank shows that DrTM has better single-node efficiency and scales well on a six-node cluster it achieves greater than 1.51, 34 and 5.24, 138 million transactions per second for TPC-C and SmallBank on a single node and the cluster, respectively. We describe how DrTM supports common database features like read-only transactions and logging for durability. We further build an efficient hash table for DrTM by leveraging HTM and RDMA to simplify the design and notably improve the performance. To mitigate the high probability of HTM aborts for large transactions, we design and implement an optimized transaction chopping algorithm to decompose a set of large transactions into smaller pieces such that HTM is only required to protect each piece. To achieve high efficiency, it mostly offloads concurrency control such as tracking read/write accesses and conflict detection into HTM in a local machine and leverages the strong consistency between RDMA and HTM to ensure serializability among concurrent transactions across machines. OLTP uses a fully normalized schema for database consistency.DrTM is a fast in-memory transaction processing system that exploits advanced hardware features such as remote direct memory access (RDMA) and hardware transactional memory (HTM).Databases are directly accessible to end-users.
#Fast transaction processing system password#
Online transaction process (OLTP) is secure and password protected.
Online transaction is a payment method in which the transfer of fund or money happens online over electronic fund transfer. Online analytical processing ( OLAP) uses complex queries to analyze aggregated historical data from OLTP systems. Online transaction processing ( OLTP) captures, stores, and processes data from transactions in real time.
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