Editing Application checkpointing (section)

== Checkpointing in distributed systems ==

In the [[distributed computing]] environment, checkpointing is a technique that helps tolerate failures that would otherwise force a long-running application to restart from the beginning. The most basic way to implement checkpointing is to stop the application, copy all the required data from the memory to reliable storage (e.g., [[parallel file system]]), then continue with execution.<ref>Plank, J. S., Beck, M., Kingsley, G., & Li, K. (1994). Libckpt: Transparent checkpointing under unix. Computer Science Department.</ref> In the case of failure, when the application restarts, it does not need to start from scratch. Rather, it will read the latest state ("the checkpoint") from the stable storage and execute from that point. While there is ongoing debate on whether checkpointing is the dominant I/O workload on distributed computing systems, the general consensus is that checkpointing is one of the major I/O workloads.<ref>{{cite book|chapter=IOMiner: Large-Scale Analytics Framework for Gaining Knowledge from I/O Logs|publisher=IEEE|date=Sep 2018|doi=10.1109/CLUSTER.2018.00062|title=2018 IEEE International Conference on Cluster Computing (CLUSTER)|pages=466–476|last1=Wang|first1=Teng|last2=Snyder|first2=Shane|last3=Lockwood|first3=Glenn|last4=Carns|first4=Philip|last5=Wright|first5=Nicholas|last6=Byna|first6=Suren|isbn=978-1-5386-8319-4|s2cid=53235850}}</ref><ref>{{cite web|title=Comparative I/O workload characterization of two leadership class storage clusters Logs|url=https://dl.acm.org/citation.cfm?id=2834985/|publisher=ACM|format=PDF|date=Nov 2015}}</ref>

There are two main approaches for checkpointing in the distributed computing systems: coordinated checkpointing and uncoordinated checkpointing. In the coordinated checkpointing approach, processes must ensure that their checkpoints are consistent. This is usually achieved by some kind of [[two-phase commit protocol]] algorithm. In the uncoordinated checkpointing, each process checkpoints its own state independently. It must be stressed that simply forcing processes to checkpoint their state at fixed time intervals is not sufficient to ensure global consistency. The need for establishing a consistent state (i.e., no missing messages or duplicated messages) may force other processes to roll back to their checkpoints, which in turn may cause other processes to roll back to even earlier checkpoints, which in the most extreme case may mean that the only consistent state found is the initial state (the so-called ''[[domino effect]]'').<ref>Bouteiller, B., Lemarinier, P., Krawezik, K., & Capello, F. (2003, December). Coordinated checkpoint versus message log for fault tolerant MPI. In Cluster Computing, 2003. Proceedings. 2003 IEEE International Conference on (pp. 242-250). IEEE.</ref><ref>Elnozahy, E. N., Alvisi, L., Wang, Y. M., & Johnson, D. B. (2002). A survey of rollback-recovery protocols in message-passing systems. ACM Computing Surveys, 34(3), 375-408.</ref>