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| Content Provider | ACM Digital Library |
|---|---|
| Author | Kejriwal, Ankita Lee, Collin Matsushita, Satoshi Park, Seo Jin Ousterhout, John |
| Abstract | Linearizability is the strongest form of consistency for concurrent systems, but most large-scale storage systems settle for weaker forms of consistency. RIFL provides a general-purpose mechanism for converting at-least-once RPC semantics to exactly-once semantics, thereby making it easy to turn non-linearizable operations into linearizable ones. RIFL is designed for large-scale systems and is lightweight enough to be used in low-latency environments. RIFL handles data migration by associating linearizability metadata with objects in the underlying store and migrating metadata with the corresponding objects. It uses a lease mechanism to implement garbage collection for metadata. We have implemented RIFL in the RAMCloud storage system and used it to make basic operations such as writes and atomic increments linearizable; RIFL adds only 530 ns to the 13.5 μs base latency for durable writes. We also used RIFL to construct a new multi-object transaction mechanism in RAMCloud; RIFL's facilities significantly simplified the transaction implementation. The transaction mechanism can commit simple distributed transactions in about 20 μs and it outperforms the H-Store main-memory database system for the TPC-C benchmark. |
| Starting Page | 71 |
| Ending Page | 86 |
| Page Count | 16 |
| File Format | PDF MP4 |
| ISBN | 9781450338349 |
| DOI | 10.1145/2815400.2815416 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2015-10-04 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Content Type | Audio Text |
| Resource Type | Article |
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