Implementing atomicity in two systems: techniques, tradeoffs, and experience

Cabrera, Luis-Felipe; McPherson, John; Schwarz, Peter; Wyllie, Jim

doi:10.1109/32.245737

Cited by 10 publications

(7 citation statements)

References 20 publications

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“…Write-ahead logging provides update-in-place changes: a redo and/or undo log entry is written to the log before the update-in-place so that it can be redone or undone in case of a crash. Write-ahead logging is generally considered superior to shadow pages [4].…”

Section: Write-ahead Loggingmentioning

confidence: 99%

Segment-based recovery

Sears

Brewer

2009

Proc. VLDB Endow.

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Although existing write-ahead logging algorithms scale to conventional database workloads, their communication and synchronization overheads limit their usefulness for modern applications and distributed systems. We revisit write-ahead logging with an eye toward finer-grained concurrency and an increased range of workloads, then remove two core assumptions: that pages are the unit of recovery and that timestamps (LSNs) should be stored on each page. Recovering individual application-level objects (rather than pages) simplifies the handing of systems with object sizes that differ from the page size. We show how to remove the need for LSNs on the page, which in turn enables DMA or zero-copy I/O for large objects, increases concurrency, and reduces communication between the application, buffer manager and log manager. Our experiments show that the looser coupling significantly reduces the impact of latency among the components. This makes the approach particularly applicable to large scale distributed systems, and enables a "cross pollination" of ideas from distributed systems and transactional storage. However, these advantages come at a cost; segments are incompatible with physiological redo, preventing a number of important optimizations. We show how allocation enables (or prevents) mixing of ARIES pages (and physiological redo) with segments. We present an allocation policy that avoids undesirable interactions that complicate other combinations of ARIES and LSN-free pages, and then present a proof that both approaches and our combination are correct. Many optimizations presented here were proposed in the past. However, we believe this is the first unified approach.

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Section: Write-ahead Loggingmentioning

confidence: 99%

Segment-based recovery

Sears

Brewer

2009

Proc. VLDB Endow.

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“…In the above steps, the realiT.ation algorithm of step (2) and (5) is uniformly described as follows.…”

Section: Partitioned Crash Recovery Strategymentioning

confidence: 99%

A dynamic crash recovery scheme for distributed real-time database systems

Xiao

Liu

et al. 2006

J. of Shanghai Univ.

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Recovery performance in the event of failures is very important for distributed real-time database systems. This paper presents a time-cognizant logging-based crash recovery scheme (TCLCRS) that aims at distributed real-time databases, which adopts a main memory database as its ground support. In our scheme, each site maintains a real-time log for local transactions and the subtransactions, which execute at the site, and execute local checkpointing independently. Log records are stored in non-volatile highspeed store, which is divided into four different partitions based on transaction classes. During restart recovery after a site crash, partitioned crash recovery strategy is adopted to ensure that the site can be brought up before the entire local secondary database is reloaded in main memory. The partitioned crash recovery strategy not only guarantees the internal consistency to be recovered, but also guarantee the temporal consistency and recovery of the sates of physical world influenced by uncommitted transactions. Combined with twophase commit protocol, TCLCRS can guarantee failure atomicity of distributed real-time transactions.

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“…We call this type of transaction as large update transaction. Updating large objects is one typical example of the large update transaction, and shadow paging was shown to be more appropriate for it [6].…”

Section: Problemmentioning

confidence: 99%

“…Meanwhile, Cabrera et al [6] showed that no single recovery method provides the best performance to all transaction types. To minimize logging overhead, they proposed to choose an appropriate recovery method according to the property of each transaction"s workload.…”

Section: Introductionmentioning

confidence: 99%

Adaptive logging for mobile device

2010

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Nowadays, due to the increased user requirements of the fast and reliable data management operation for mobile applications, major device vendors use embedded DBMS for their mobile devices such as MP3 players, mobile phones, digital cameras and PDAs. However, database logging is the major bottleneck against the fast response time. There has been a lot of work minimizing logging overhead but no single recovery method provides the best performance to a variety of database workloads. In this paper, we present a novel recovery method called adaptive logging which can switch the logging method from ARIES to shadow paging adaptively at a page level according to the update state of each page on run time. Also, we propose a log compaction method called deferred logging which removes redundant logs by deferring to create log records until the updated data page is flushed or until the transaction commits. Deferred logging is coupled with adaptive logging seamlessly so that it boosts the performance of adaptive logging by reducing the typical overhead of hybrid methods. We have implemented the proposed approaches to our embedded DBMS which was deployed to more than 10 million mobile devices and evaluated them through a real world application on a mobile device. The result shows that our approaches can reduce logging overhead significantly and consequently can improve the response time of both small update transaction and large update transaction effectively.

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Implementing atomicity in two systems: techniques, tradeoffs, and experience

Cited by 10 publications

References 20 publications

Segment-based recovery

Segment-based recovery

A dynamic crash recovery scheme for distributed real-time database systems

Adaptive logging for mobile device

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