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fix-deadlink-dynamo (#27)
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goungoun authored and rxin committed Apr 10, 2018
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Expand Up @@ -50,7 +50,7 @@ If you are reading this and taking the effort to understand these papers, we wou

* [The Google File System](http://research.google.com/archive/gfs.html) (2003) and [Bigtable: A Distributed Storage System for Structured Data](http://research.google.com/archive/bigtable.html) (2006): Two core components of Google's data infrastructure. GFS is an append-only distributed file system for large sequential reads (data-intensive applications). BigTable is high-performance distributed data store that builds on GFS. One way to think about it is that GFS is optimized for high throughput, and BigTable explains how to build a low-latency data store on top of GFS. Some of these might have been replaced by newer proprietary technologies internal to Google, but the ideas stand.

* [Chord: A Scalable Peer-to-peer Lookup Service for Internet Applications](http://www.cs.berkeley.edu/~rxin/db-papers/Chord-DHT.pdf) (2001) and [Dynamo: Amazon’s Highly Available Key-value Store](http://www.cs.berkeley.edu/~rxin/db-papers/Dynamo.pdf) (2007): Chord was born in the days when distributed hash tables was a hot research. It does one thing, and does it really well: how to look up the location of a key in a completely distributed setting (peer-to-peer) using consistent hashing. The Dynamo paper explains how to build a distributed key-value store using Chord. Note some design decisions change from Chord to Dynamo, e.g. finger table O(logN) vs O(N), because in Dynamo's case, Amazon has more control over nodes in a data center, while Chord assumes peer-to-peer nodes in wide area networks.
* [Chord: A Scalable Peer-to-peer Lookup Service for Internet Applications](http://www.cs.berkeley.edu/~rxin/db-papers/Chord-DHT.pdf) (2001) and [Dynamo: Amazon’s Highly Available Key-value Store](https://courses.cs.washington.edu/courses/csep552/18wi/papers/decandia-dynamo.pdf) (2007): Chord was born in the days when distributed hash tables was a hot research. It does one thing, and does it really well: how to look up the location of a key in a completely distributed setting (peer-to-peer) using consistent hashing. The Dynamo paper explains how to build a distributed key-value store using Chord. Note some design decisions change from Chord to Dynamo, e.g. finger table O(logN) vs O(N), because in Dynamo's case, Amazon has more control over nodes in a data center, while Chord assumes peer-to-peer nodes in wide area networks.



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