Asset Details
MbrlCatalogueTitleDetail
Do you wish to reserve the book?
Falkirk Wheel: Rollback Recovery for Dataflow Systems
by
Isard, Michael
, Abadi, Martín
in
Algorithms
/ Batch processing
/ Checkpointing
/ Domains
/ Iterative methods
/ Microprocessors
/ Processors
/ Recovery
2015
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
You are currently in the queue to collect this book. You will be notified once it is your turn to collect the book.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
Oops! Something went wrong.
While trying to remove the title from your shelf something went wrong :( Kindly try again later!
Do you wish to request the book?
Falkirk Wheel: Rollback Recovery for Dataflow Systems
by
Isard, Michael
, Abadi, Martín
in
Algorithms
/ Batch processing
/ Checkpointing
/ Domains
/ Iterative methods
/ Microprocessors
/ Processors
/ Recovery
2015
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Paper
Falkirk Wheel: Rollback Recovery for Dataflow Systems
2015
Request Book From Autostore
and Choose the Collection Method
Overview
We present a new model for rollback recovery in distributed dataflow systems. We explain existing rollback schemes by assigning a logical time to each event such as a message delivery. If some processors fail during an execution, the system rolls back by selecting a set of logical times for each processor. The effect of events at times within the set is retained or restored from saved state, while the effect of other events is undone and re-executed. We show that, by adopting different logical time \"domains\" at different processors, an application can adopt appropriate checkpointing schemes for different parts of its computation. We illustrate with an example of an application that combines batch processing with low-latency streaming updates. We show rules, and an algorithm, to determine a globally consistent state for rollback in a system that uses multiple logical time domains. We also introduce selective rollback at a processor, which can selectively preserve the effect of events at some logical times and not others, independent of the original order of execution of those events. Selective rollback permits new checkpointing policies that are particularly well suited to iterative streaming algorithms. We report on an implementation of our new framework in the context of the Naiad system.
Publisher
Cornell University Library, arXiv.org
Subject
This website uses cookies to ensure you get the best experience on our website.