Comparing two-phase locking and optimistic concurrency control protocols in multiprocessor real-time databases

Previous studies (Haritsa et al., 1990) have shown that optimistic concurrency control (OCC) generally performs better than lock-based protocols in disk-based real-time database systems (RTDBS). We compare the two concurrency control protocols in both disk-based and memory-resident multiprocessor RTDBS. Based on their performance characteristics, a new lock-based protocol, called two phase locking-lock write all (2PL-LW), is proposed. The results of our performance evaluation experiments show that different characteristics of the two environments indeed have great impact on the protocols' performance. We identify such system characteristics and show that our new lock-based protocols, 2PL-LW, is better than OCC in meeting transaction deadlines in both disk-based and memory-resident RTDBS.published_or_final_versio

Research issues in real-time database systems

Cataloged from PDF version of article.Today's real-time systems are characterized by managing large volumes of data. Efficient database management algorithms for accessing and manipulating data are required to satisfy timing constraints of supported applications. Real-time database systems involve a new research area investigating possible ways of applying database systems technology to real-time systems. Management of real-time information through a database system requires the integration of concepts from both real-time systems and database systems. Some new criteria need to be developed to involve timing constraints of real-time applications in many database systems design issues, such as transaction/query processing, data buffering, CPU, and IO scheduling. In this paper, a basic understanding of the issues in real-time database systems is provided and the research efforts in this area are introduced. Different approaches to various problems of real-time database systems are briefly described, and possible future research directions are discussed

LogBase: A Scalable Log-structured Database System in the Cloud

Numerous applications such as financial transactions (e.g., stock trading) are write-heavy in nature. The shift from reads to writes in web applications has also been accelerating in recent years. Write-ahead-logging is a common approach for providing recovery capability while improving performance in most storage systems. However, the separation of log and application data incurs write overheads observed in write-heavy environments and hence adversely affects the write throughput and recovery time in the system. In this paper, we introduce LogBase - a scalable log-structured database system that adopts log-only storage for removing the write bottleneck and supporting fast system recovery. LogBase is designed to be dynamically deployed on commodity clusters to take advantage of elastic scaling property of cloud environments. LogBase provides in-memory multiversion indexes for supporting efficient access to data maintained in the log. LogBase also supports transactions that bundle read and write operations spanning across multiple records. We implemented the proposed system and compared it with HBase and a disk-based log-structured record-oriented system modeled after RAMCloud. The experimental results show that LogBase is able to provide sustained write throughput, efficient data access out of the cache, and effective system recovery.Comment: VLDB201

Implementing Performance Competitive Logical Recovery

New hardware platforms, e.g. cloud, multi-core, etc., have led to a reconsideration of database system architecture. Our Deuteronomy project separates transactional functionality from data management functionality, enabling a flexible response to exploiting new platforms. This separation requires, however, that recovery is described logically. In this paper, we extend current recovery methods to work in this logical setting. While this is straightforward in principle, performance is an issue. We show how ARIES style recovery optimizations can work for logical recovery where page information is not captured on the log. In side-by-side performance experiments using a common log, we compare logical recovery with a state-of-the art ARIES style recovery implementation and show that logical redo performance can be competitive.Comment: VLDB201

Practical cross-engine transactions in dual-engine database systems

With the growing DRAM capacity and core count in modern servers, database systems are becoming increasingly multi-engine to feature a heterogeneous set of engines. In particular, a memory-optimized engine and a conventional storage-centric engine may coexist to satisfy various application needs. However, handling cross-engine transactions that access more than one engine remains challenging in terms of correctness, performance and programmability. This thesis describes Skeena, an approach to cross-engine transactions with proper isolation guarantees and low overhead. Skeena adapts and integrates past concurrency control theory to provide a complete solution to supporting various isolation levels in dual-engine systems, and proposes a lightweight transaction tracking structure that captures the necessary information to guarantee correctness with low overhead. Evaluation on a 40-core server shows that Skeena only incurs minuscule overhead for cross-engine transactions, without penalizing single-engine transactions