The Chubby lock service for loosely-coupled distributed systems
By Brett D. Fleisch. 2006
1,050 citations recorded by the source corpus.
Subfields: ML Systems & Hardware
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In ML Systems & Hardware
- John K. Ousterhout
- Diego Ongaro
- D. Andersen
- Michael Kaminsky
- Ion Stoica
- Xin Jin
- Yonggang Wen
- Robbert van Renesse
Citations in the corpus
- TensorFlow: A system for large-scale machine learning (2016, neutral): “Although we do not use strong consistency for the training state, we rely on a system like Chubby [8] or ZooKeeper [31] to map task IDs to IP addresses.”
- Borg, Omega, and Kubernetes (2016, background): “This has many benefits: (1) it relieves application developers and operations teams from worrying about specific details of machines and operating systems; (2) it provides the infrastructure team flexibility to roll out new hardware and upgrade operating systems with minimal impact on running applic”
- Large-scale cluster management at Google with Borg (2015, methodology): “Borg writes the task’s hostname and port into a consistent, highly-available file in Chubby [14] with this name, which is used by our RPC system to find the task endpoint.”
- Split/Merge: System Support for Elastic Execution in Virtual Middleboxes (2013, neutral): “In the rare case that strong consistency is required, the application does not specify a combiner, and library instead interacts with a distributed locking service [3,11].”
- Trends in big data analytics (2014, methodology): “systems use Chubby [18] locking service to synchronize accesses to”
- ZooKeeper: Wait-free Coordination for Internet-scale Systems (2010, methodology): “For example, Chubby [6] is a locking service with strong synchronization guarantees.”
- In Search of an Understandable Consensus Algorithm (2014, methodology): “• Systems that implement consensus algorithms, such as Chubby [2, 4], ZooKeeper [10, 11], and Span-ner [5].”
- Kineograph: taking the pulse of a fast-changing and connected world (2012, methodology): “The Chubby lock service for loosely-coupled distributed systems.”
- Tendermint: Byzantine Fault Tolerance in the Age of Blockchains (2016, background): “Paxos has been the staple consensus algorithm for industry, upon which the likes of Amazon [26], Google [10], and others have built out highly available global Internet services.”
- Site Reliability Engineering: How Google Runs Production Systems (2016, methodology): “These files can be stored in Chubby, Bigtable, or our source-based filesystem [Kem11].”
- There is more consensus in Egalitarian parliaments (2013, methodology): “Today’s clusters use faulttolerant coordination engines such as Chubby [4], Boxwood [22], or ZooKeeper [12] for activities including operation sequencing, coordination, leader election, and resource discovery.”
- Megastore: Providing Scalable, Highly Available Storage for Interactive Services (2011, methodology): “We use Google’s Chubby lock service [13]: coordinators obtain specific Chubby locks in remote datacenters at startup.”
- Big data related technologies, challenges and future prospects (2015, background): “In recent years, WSNs have received considerable interest and have been applied to many applications, such as environmental research [11, 12], water quality monitoring [13], civil engineering [14, 15], and wildlife habit monitoring [16].”
- Sinfonia: a new paradigm for building scalable distributed systems (2007, background): “The Chubby lock service for loosely-coupled distributed systems.”
- Toward Scalable Systems for Big Data Analytics: A Technology Tutorial (2014, background): “Bigtable depends on a number of technologies in Google’s infrastructure, including GFS [31], a cluster management system, an SSTable file format and Chubby [147].”
- Bigtable: a distributed storage system for structured data (2006, background): “Bigtable relies on a highly-available and persistent distributed lock service called Chubby [8].”
- NetChain: Scale-Free Sub-RTT Coordination (2018, methodology): “(ii) How much does NetChain need? As shown in [1], a Chubby instance at Google that serves tens of thousands of clients store 22k files in total, among which ∼90% are 0-1 KB and only ∼0.”
- Mencius: Building Efficient Replicated State Machine for WANs (2008, neutral): “Recent examples of services that use replicated state machines include Chubby [6, 8], ZooKeeper [37] and Boxwood [28].”