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30
Postgres-r(si): Combining replica control with concurrency control based on snapshot isolation
- In International Conference on Data Engineering
, 2005
"... Replicating data over a cluster of workstations is a powerful tool to increase performance, and provide fault-tolerance for demanding database applications. The big challenge in such systems is to combine replica control (keeping the copies consistent) with concurrency control. Most of the research ..."
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Cited by 93 (10 self)
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Replicating data over a cluster of workstations is a powerful tool to increase performance, and provide fault-tolerance for demanding database applications. The big challenge in such systems is to combine replica control (keeping the copies consistent) with concurrency control. Most of the research so far has focused on providing the tra-ditional correctness criteria serializability. However, more and more database systems, e.g., Oracle and PostgreSQL, use multi-version concurrency control providing the iso-lation level snapshot isolation. In this paper, we present Postgres-R(SI), an extension of PostgreSQL offering trans-parent replication. Our replication tool is designed to work smoothly with PostgreSQL’s concurrency control provid-ing snapshot isolation for the entire replicated system. We present a detailed description of the replica control algo-rithm, and how it is combined with PostgreSQL’s concur-rency control component. Furthermore, we discuss some challenges we encountered when implementing the proto-col. Our performance analysis based on the TPC-W bench-mark shows that this approach exhibits excellent perfor-mance for real-life applications even if they are update in-tensive. 1.
Tashkent+: Memory-aware load balancing and update filtering in replicated databases
- In EuroSys 2007: Proceedings of the 2nd European Conference on Computer Systems
, 2007
"... We present a memory-aware load balancing (MALB) technique to dispatch transactions to replicas in a replicated database. Our MALB algorithm exploits knowledge of the working sets of transactions to assign them to replicas in such a way that they execute in main memory, thereby reducing disk I/O. In ..."
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Cited by 37 (7 self)
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We present a memory-aware load balancing (MALB) technique to dispatch transactions to replicas in a replicated database. Our MALB algorithm exploits knowledge of the working sets of transactions to assign them to replicas in such a way that they execute in main memory, thereby reducing disk I/O. In support of MALB, we introduce a method to estimate the size and the contents of transaction working sets. We also present an optimization called update filtering that reduces the overhead of update propagation between replicas. We show that MALB greatly improves performance over other load balancing techniques – such as round robin, least connections, and locality-aware request distribution (LARD) – that do not use explicit information on how transactions use memory. In particular, LARD demonstrates good performance for read-only static content Web workloads, but it gives performance inferior to MALB for database workloads as it does not efficiently handle large requests. MALB combined with update filtering further boosts performance over LARD. We build a prototype replicated system, called Tashkent+, with which we demonstrate that MALB and update filtering techniques improve performance of the TPC-W and RUBiS benchmarks. In particular, in a 16-replica cluster and using the ordering mix of TPC-W, MALB doubles the throughput over least connections and improves throughput 52 % over LARD. MALB with update filtering further improves throughput to triple that of least connections and more than double that of LARD. Our techniques exhibit super-linear speedup; the throughput of the 16-replica cluster is 37 times the peak throughput of a standalone database due to better use of the cluster’s memory.
Exploiting distributed version concurrency in a transactional memory cluster
- In PPOPP
, 2006
"... We investigate a transactional memory runtime system providing scaling and strong consistency for generic C++ and SQL applications on commodity clusters. We introduce a novel page-level distributed concurrency control algorithm, called Distributed Multiversioning (DMV). DMV automatically detects and ..."
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Cited by 32 (3 self)
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We investigate a transactional memory runtime system providing scaling and strong consistency for generic C++ and SQL applications on commodity clusters. We introduce a novel page-level distributed concurrency control algorithm, called Distributed Multiversioning (DMV). DMV automatically detects and resolves conflicts caused by data races for distributed transactions accessing shared in-memory data structures. DMV’s key novelty is in exploiting the distributed data versions that naturally occur in a replicated cluster in order to avoid read-write conflicts. Specifically, DMV runs conflicting transactions in parallel on different replicas, instead of using different physical data copies within a single node as in classic multiversioning. In its most general update-anywhere configuration, DMV can be used to implement a software transactional memory abstraction for classic distributed shared memory applications. DMV supports scaling for highly multithreaded database applications as well by centralizing updates on a master replica and creating the required page versions for read-only transactions on a set of slaves. In this DMV configuration, a version-aware scheduling technique distributes the read-only transactions across the slaves in such a way to minimize version conflicts. In our evaluation, we use DMV as a lightweight approach to scaling a hash table microbenchmark workload and the industrystandard e-commerce workload of the TPC-W benchmark on a commodity cluster. Our measurements show scaling for both benchmarks. In particular, we show near-linear scaling up to 8 transactional nodes for the most common e-commerce workload, the TPC-W shopping mix. We further show that our scaling for the TPC-W e-commerce benchmark compares favorably with that of an existing coarse-grained asynchronous replication technique.
Dbfarm: A scalable cluster for multiple databases
- In Middleware
, 2006
"... Abstract. In many enterprise application integration scenarios, middleware has been instrumental in taking advantage of the flexibility and cost efficiency of clusters of computers. Web servers, application servers, platforms such as CORBA, J2EE or.NET, message brokers, and TP-Monitors, just to ment ..."
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Cited by 16 (1 self)
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Abstract. In many enterprise application integration scenarios, middleware has been instrumental in taking advantage of the flexibility and cost efficiency of clusters of computers. Web servers, application servers, platforms such as CORBA, J2EE or.NET, message brokers, and TP-Monitors, just to mention a few examples, are all forms of middleware that exploit and are built for distributed deployment. The one piece in the puzzle that largely remains a centralized solution is the database. There is, of course, much work done on scaling and parallelizing databases. In fact, several products support deployment on clusters. Clustered databases, however, place the emphasis on single applications and target very large databases. By contrast, the middleware platforms just mentioned use clustered deployment not only for scalability but also for efficiently supporting multiple concurrent applications. In this paper we tackle the problem of clustered deployment of a database engine for supporting multiple applications. In the database case, multiple applications imply multiple and different database instances being used concurrently. In the paper we show how to build such a system and demonstrate its ability to support up to 300 different databases without loss of performance.
Fine-Grained Replication and Scheduling with Freshness and Correctness Guarantees
- in Proceedings of the 31st International Conference on Very Large Data Bases (VLDB’05
, 2005
"... Lazy replication protocols provide good scalabil-ity properties by decoupling transaction execution from the propagation of new values to replica sites while guaranteeing a correct and more efficient transaction processing and replica maintenance. However, they impose several restrictions that are o ..."
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Cited by 16 (2 self)
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Lazy replication protocols provide good scalabil-ity properties by decoupling transaction execution from the propagation of new values to replica sites while guaranteeing a correct and more efficient transaction processing and replica maintenance. However, they impose several restrictions that are often not valid in practical database settings, e.g., they require that each transaction executes at its initiation site and/or are restricted to full replica-tion schemes. Also, the protocols cannot guaran-tee that the transactions will always see the fresh-est available replicas. This paper presents a new lazy replication protocol called PDBREP that is free of these restrictions while ensuring one-copy-serializable executions. The protocol exploits the distinction between read-only and update transac-tions and works with arbitrary physical data orga-nizations such as partitioning and striping as well as different replica granularities. It does not re-quire that each read-only transaction executes en-tirely at its initiation site. Hence, each read-only site need not contain a fully replicated database. PDBREP moreover generalizes the notion of fresh-ness to finer data granules than entire databases. 1
Highly available transactions: Virtues and limitations
, 2014
"... To minimize network latency and remain online during server failures and network partitions, many modern distributed data storage systems eschew transactional functionality, which provides strong semantic guarantees for groups of multiple operations over multiple data items. In this work, we conside ..."
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Cited by 13 (5 self)
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To minimize network latency and remain online during server failures and network partitions, many modern distributed data storage systems eschew transactional functionality, which provides strong semantic guarantees for groups of multiple operations over multiple data items. In this work, we consider the problem of providing Highly Available Transactions (HATs): transactional guarantees that do not suffer unavailability during system partitions or incur high network latency. We introduce a taxonomy of highly available systems and analyze existing ACID isolation and distributed data consistency guarantees to identify which can and cannot be achieved in HAT systems. This unifies the literature on weak transactional isolation, replica consistency, and highly available systems. We analytically and experimentally quantify the availability and performance benefits of HATs—often two to three orders of magnitude over wide-area networks—and discuss their necessary semantic compromises. 1
Scalable atomic visibility with RAMP transactions
- In ACM SIGMOD Conference
, 2014
"... Databases can provide scalability by partitioning data across several servers. However, multi-partition, multi-operation transactional ac-cess is often expensive, employing coordination-intensive locking, validation, or scheduling mechanisms. Accordingly, many real-world systems avoid mechanisms tha ..."
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Cited by 13 (1 self)
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Databases can provide scalability by partitioning data across several servers. However, multi-partition, multi-operation transactional ac-cess is often expensive, employing coordination-intensive locking, validation, or scheduling mechanisms. Accordingly, many real-world systems avoid mechanisms that provide useful semantics for multi-partition operations. This leads to incorrect behavior for a large class of applications including secondary indexing, foreign key enforcement, and materialized view maintenance. In this work, we identify a new isolation model—Read Atomic (RA) isolation—that matches the requirements of these use cases by ensuring atomic vis-ibility: either all or none of each transaction’s updates are observed by other transactions. We present algorithms for Read Atomic Multi-Partition (RAMP) transactions that enforce atomic visibility while offering excellent scalability, guaranteed commit despite partial failures (via synchronization independence), and minimized com-munication between servers (via partition independence). These RAMP transactions correctly mediate atomic visibility of updates and provide readers with snapshot access to database state by using limited multi-versioning and by allowing clients to independently resolve non-atomic reads. We demonstrate that, in contrast with ex-isting algorithms, RAMP transactions incur limited overhead—even under high contention—and scale linearly to 100 servers. 1.
Online recovery in cluster databases
- In EDBT ’08: Proceedings of the 11th international conference on Extending database technology
, 2008
"... Cluster based replication solutions are an attractive mechanism to provide both high-availability and scalability for the database backend within the multi-tier information systems of service-oriented businesses. An important issue that has not yet received sufficient attention is how database repli ..."
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Cited by 8 (0 self)
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Cluster based replication solutions are an attractive mechanism to provide both high-availability and scalability for the database backend within the multi-tier information systems of service-oriented businesses. An important issue that has not yet received sufficient attention is how database replicas that have failed can be reintegrated into the system or how completely new replicas can be added in order to increase the capacity of the system. Ideally, recovery takes place online, i.e, while transaction processing continues at the replicas that are already running. In this paper we present a complete online recovery solution for database clusters. One important issue is to find an efficient way to transfer the data the joining replica needs. In this paper, we present two data transfer strategies. The first transfers the latest copy of each data item, the second transfers the updates a rejoining replica has missed during its downtime. A second challenge is to coordinate this transfer with ongoing transaction processing such that the joining node does not miss any updates. We present a coordination protocol that can be used with Postgres-R, a replication tool which uses a group communication system for replica control. We have implemented and compared our transfer solutions against a set of parameters, and present heuristics which allow an automatic selection of the optimal strategy for a given configuration. 1.
Strongly consistent replication for a bargain
- In Data Engineering (ICDE), 2010 IEEE 26th International Conference on
, 2010
"... Abstract — Strong consistency is an important correctness property for replicated databases. It ensures that each transaction accesses the latest committed database state as provided in centralized databases. Achieving strong consistency in replicated databases is a major performance challenge and i ..."
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Cited by 7 (1 self)
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Abstract — Strong consistency is an important correctness property for replicated databases. It ensures that each transaction accesses the latest committed database state as provided in centralized databases. Achieving strong consistency in replicated databases is a major performance challenge and is typically not provided, exposing inconsistent data to client applications. We propose two scalable techniques that exploit lazy update propagation and workload information to guarantee strong consistency by delaying transaction start. We implement a prototype replicated database system and incorporate the proposed techniques for providing strong consistency. Extensive experiments using both a micro-benchmark and the TPC-W benchmark demonstrate that our proposals are viable and achieve considerable scalability while maintaining strong consistency. I.
Jiménez-Peris – Enhancing Edge Computing With Database Replication
- IEEE Int. Symp. on Reliable Distributed Systems (SRDS
, 2007
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