Performance analysis of a real-time database with optimistic concurrency control

For a real-time shared-memory database with Optimistic Concurrency Control (OCC), an approximation for the transaction response-time distribution and thus for the deadline miss probability is obtained. Transactions arrive at the database according to a Poisson process. There is a limited number of CPUs that can handle transactions in parallel. TransactIons have soft deadlines, and the probability of data conflicts is equal for all transactions. The response time of a transaction consists of possible waiting time (if at arrival all CPUs are occupied) plus a number of execution runs (due to the occurrence of conflicts). In this study, we analyze the case where the execution time of all transactions is constant. Although in practice execution times are never really constant, it is important to analyze this simplifying constant case first, before trying to analyze more general execution-time distributions. We model the real-time database (RTDB) with OCC by a multi-server queueing system with a very special kind of feedback. The probability that a transaction is fed back for a rerun depends on the number of transactions that has committed during its execution. Numerical experiments, which compare the approximative analysis with simulation, show that the analysis provides a good and very fast approximation for the response-time distribution and thus for the percentage of transactions that meets its deadline. We also discuss how the model and the analysis can be extended such that more realistic assumptions, e.g. non-uniform data access, several transaction types, and general execution-time distributions, can be handled

Executing Multidatabase Transactions

In a multidatabase environment, the traditional transaction model has been found to be too restrictive. Therefore, several extended transaction models have been proposed in which some of the requirements of transaction, such as isolation or atomicity, are optional. The authors describe one of such extensions, the flexible transaction model and discuss the scheduling of transactions involving multiple autonomous database systems managed by heterogeneous DBMS. The scheduling algorithm for flexible transactions is implemented using L.0, a logically parallel language which provides a framework for concisely specifying the multidatabase transactions and for scheduling them. The key aspects of a flexible transaction specification, such as subtransaction execution dependencies and transaction success criteria, can be naturally represented in L.0. Furthermore, scheduling in L.0 achieves maximal parallelism allowed by the specifications of transactions, which results in the improvement of their response times. To provide access to multiple heterogeneous hardware and software systems, they use the Distributed Operation Language (DOL). DOL approach is based on providing a common communication and data exchange protocol and uses local access managers to protect the autonomy of member software systems. When L.0 determines that a subtransaction is ready to execute, it hands it through an interface to the DOL system for execution. The interface between L.0 and DOL provides the former with the execution status of subtransactions

On Predictive Modeling for Optimizing Transaction Execution in Parallel OLTP Systems

A new emerging class of parallel database management systems (DBMS) is designed to take advantage of the partitionable workloads of on-line transaction processing (OLTP) applications. Transactions in these systems are optimized to execute to completion on a single node in a shared-nothing cluster without needing to coordinate with other nodes or use expensive concurrency control measures. But some OLTP applications cannot be partitioned such that all of their transactions execute within a single-partition in this manner. These distributed transactions access data not stored within their local partitions and subsequently require more heavy-weight concurrency control protocols. Further difficulties arise when the transaction's execution properties, such as the number of partitions it may need to access or whether it will abort, are not known beforehand. The DBMS could mitigate these performance issues if it is provided with additional information about transactions. Thus, in this paper we present a Markov model-based approach for automatically selecting which optimizations a DBMS could use, namely (1) more efficient concurrency control schemes, (2) intelligent scheduling, (3) reduced undo logging, and (4) speculative execution. To evaluate our techniques, we implemented our models and integrated them into a parallel, main-memory OLTP DBMS to show that we can improve the performance of applications with diverse workloads.Comment: VLDB201

Implementation of parallel nested transactions for nested rule execution in active databases

Ankara : Department of Computer Engineering and Information Science and the Institute of Engineering and Science of Bilkent University, 1996.Thesis (Master's) -- Bilkent University, 1996.Includes bibliographical references leaves 53-56.(Jonventional, passive datal)ases, ex('cute transcictions or queries in response to the requests from a user or an application program. In contrcist, an Active Database Management System (ADI3MS) allows users to specify actions to be executed when some specific evcMits are signaled. ADBMSs ¿ichieve tliis feciture by mecins of rules. Execution of ruh's is an important part of an ADBMS which may affect the overall performanc'e of the system. Nested transactions are proposed as a rule execution model for ADBMSs. The nested trcinsciction model, in contrast to flat transactions, allows transactions to be started inside some other trcinsactions forming a transaction hierarchy. In this thesis, implementation issues of pcirallel nested transactions, wluM’e all the transactions in the hierarchy may run in pcirallel, aix' discussed for parallel rule execution in ADBMSs. Implementation of nested transactions ha.s I^een performed by extending the flat trcuisaction semantics of OpenOODB using Solaris threads. A formal specification of the proposed (xxec.ution model using ACTA framework is also provided.Saygın, YücelM.S

Parallel Deferred Update Replication

Deferred update replication (DUR) is an established approach to implementing highly efficient and available storage. While the throughput of read-only transactions scales linearly with the number of deployed replicas in DUR, the throughput of update transactions experiences limited improvements as replicas are added. This paper presents Parallel Deferred Update Replication (P-DUR), a variation of classical DUR that scales both read-only and update transactions with the number of cores available in a replica. In addition to introducing the new approach, we describe its full implementation and compare its performance to classical DUR and to Berkeley DB, a well-known standalone database