More Like this

1. Strong and Efficient Consistency with Consistency-Aware Durability

   Ganesan, Aishwarya; Alagappan, Ramnatthan; Arpaci-Dusseau, Andrea; Arpaci-Dusseau, Remzi (January 2020, 18th USENIX Conference on File and Storage Technologies (FAST '20))

   We introduce consistency-aware durability or CAD, a new approach to durability in distributed storage that enables strong consistency while delivering high performance. We demonstrate the efficacy of this approach by designing cross-client monotonic reads, a novel and strong consistency property that provides monotonic reads across failures and sessions in leader-based systems. We build ORCA, a modified version of ZooKeeper that implements CAD and cross-client monotonic reads. We experimentally show that ORCA provides strong consistency while closely matching the performance of weakly consistent ZooKeeper. Compared to strongly consistent ZooKeeper, ORCA provides significantly higher throughput (1.8 – 3.3×), and notably reduces latency, sometimes by an order of magnitude in geo-distributed settings. 

   more » « less
2. Strong and Efficient Consistency with Consistency-Aware Durability

   Ganesan, A; Alagappan, R.; Arpaci-Dusseau, A.; Arpaci-Dusseau, R. (April 2020, USENIX FAST)

   We introduce consistency-aware durability or CAD, a new approach to durability in distributed storage that enables strong consistency while delivering high performance. We demonstrate the efficacy of this approach by designing cross-client monotonic reads, a novel and strong consistency property that provides monotonic reads across failures and sessions in leader-based systems. We build ORCA, a modified version of ZooKeeper that implements CAD and cross-client mono- tonic reads. We experimentally show that ORCA provides strong consistency while closely matching the performance of weakly consistent ZooKeeper. Compared to strongly consistent ZooKeeper, ORCA provides significantly higher through- put (1.8 – 3.3x), and notably reduces latency, sometimes by an order of magnitude in geo-distributed settings. 

   more » « less
3. CoPPar Tree: Fast and Composable Consistency at Global Scale

   Yang, Xincheng; Hale, Kyle C (July 2025, IEEE)

   Many distributed applications rely on the strong guarantees of sequential consistency to ensure program correctness. Replication systems or frameworks that support such applications typically implement sequential consistency by em- ploying voting schemes among replicas. However, such schemes suffer dramatic performance loss when deployed globally due to increased long-haul message latency between replicas in separate data centers. One approach to overcome this challenge involves deploying distinct instances of a service in each geographic cluster, then loosely coupling those services. Unfortunately, the consistency guarantees of the individual replication system in- stances do not compose when coupled this way, sacrificing overall sequential consistency. We propose an alternative approach, the consistent, propagatable partition tree (CoPPar Tree), a data structure that spans multiple data centers and data partitions, and that realizes sequential consistency using divide-and-conquer. By leveraging the geospatial affinity of data used in global services, CoPPar Tree can localize reads and writes in a sequentially consistent manner, improving the overall performance of a sequentially consistent service deployed at global scale. Our work allows clients to access local data and fully run SMR protocols locally without additional overhead. We implemented CoPPar Tree by enhancing ZooKeeper with an extension called ZooTree, which can be deployed without changing existing ZooKeeper clusters, and which achieves a speedup of 100×for reads and up to 10× for writes over prior work. 

   more » « less
4. The FuzzyLog: A Partially Ordered Shared Log

   Lockerman, Joshua; Faleiro, Jose M.; Kim, Juno; Sankaram, Soham; Abadi, Daniel J.; Aspnes, James; Siddhartha, Sen; Balakrishnan, Mahesh (October 2018, OSDI 2018)

   The FuzzyLog is a partially ordered shared log abstraction. Distributed applications can concurrently append to the partial order and play it back. FuzzyLog applications obtain the benefits of an underlying shared log --- extracting strong consistency, durability, and failure atomicity in simple ways --- without suffering from its drawbacks. By exposing a partial order, the FuzzyLog enables three key capabilities for applications: linear scaling for throughput and capacity (without sacrificing atomicity), weaker consistency guarantees, and tolerance to network partitions. We present Dapple, a distributed implementation of the FuzzyLog abstraction that stores the partial order compactly and supports efficient appends / playback via a new ordering protocol. We implement several data structures and applications over the FuzzyLog, including several map variants as well as a ZooKeeper implementation. Our evaluation shows that these applications are compact, fast, and flexible: they retain the simplicity (100s of lines of code) and strong semantics (durability and failure atomicity) of a shared log design while exploiting the partial order of the FuzzyLog for linear scalability, flexible consistency guarantees (e.g., causal+ consistency), and network partition tolerance. On a 6-node Dapple deployment, our FuzzyLogbased ZooKeeper supports 3M/sec single-key writes, and 150K/sec atomic cross-shard renames. 

   more » « less
5. The fuzzylog: a partially ordered shared log

   Lockerman, Joshua; Faleiro, Jose M.; Kim, Juno; Sankaran, Soham; Abadi, Daniel J.; Aspnes, James; Sen, Siddhartha; Balakrishnan, Mahesh (January 2018, Proceedings of the 12th USENIX Conference on Operating Systems Design and Implementation)

   The FuzzyLog is a partially ordered shared log abstraction. Distributed applications can concurrently append to the partial order and play it back. FuzzyLog applications obtain the benefits of an underlying shared log - extracting strong consistency, durability, and failure atomicity in simple ways - without suffering from its drawbacks. By exposing a partial order, the FuzzyLog enables three key capabilities for applications: linear scaling for throughput and capacity (without sacrificing atomicity), weaker consistency guarantees, and tolerance to network partitions. We present Dapple, a distributed implementation of the FuzzyLog abstraction that stores the partial order compactly and supports efficient appends / playback via a new ordering protocol. We implement several data structures and applications over the FuzzyLog, including several map variants as well as a ZooKeeper implementation. Our evaluation shows that these applications are compact, fast, and flexible: they retain the simplicity (100s of lines of code) and strong semantics (durability and failure atomicity) of a shared log design while exploiting the partial order of the FuzzyLog for linear scalability, flexible consistency guarantees (e.g., causal+ consistency), and network partition tolerance. On a 6-node Dapple deployment, our FuzzyLog-based ZooKeeper supports 3M/sec single-key writes, and 150K/sec atomic cross-shard renames. 

   more » « less