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DistributedSystemNotes

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Notes on Lindsey Kuper's lectures on Distributed Systems

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# Distributed Systems

Lecture notes for course [CSE138, Spring 2020](http://composition.al/CSE138-2020-03/index.html) given by [Prof Lindsey Kuper](https://users.soe.ucsc.edu/~lkuper/), Assistant Professor of Computing at UCSC

Due to the Covid-19 lockdown being enforced at the time, these lectures had to be delivered online and are available on [YouTube](https://www.youtube.com/user/lindseykuper/videos) and [Twitch](https://www.twitch.tv/lindseykuper/videos)

This series of lectures also includes a discussion panel with recent grad students and two guest lecturers.
Notes have not been created for these events; however, you can watch the videos here:

* ["Grad Student Discussion Panel"](https://www.youtube.com/watch?v=ArKapXZkJvM) Lindsey Kuper talks with Emma Gomish, Pete Wilcox and Lawrence Lawson.
 May 15th, 2020
* ["Blockchain Consensus"](https://www.youtube.com/watch?v=m6qZY7_ingY) by Chris Colohan, May 27th, 2020
* ["Building Peer-to-Peer Applications"](https://www.twitch.tv/videos/640120840) by Karissa McKelvey, June 3rd, 2020

| Date | Description | Subjects Recapped |
|---|---|---|
| Lecture 1 | There are no notes for this lecture as it was concerned with course administration and logistics |
| [Lecture 2](./Lecture%2002.md) April&nbsp;1st,&nbsp;2020 | Distributed Systems: What and why? Time and clocks |
| [Lecture 3](./Lecture%2003.md) April&nbsp;3rd,&nbsp;2020| Lamport diagrams Causality and the "happens before" relation Network models State and events Partial orders
| [Lecture 4](./Lecture%2004.md) April&nbsp;6th,&nbsp;2020 | Total orders and Lamport clocks | Partial orders Happens before relation
| [Lecture 5](./Lecture%2005.md) April&nbsp;8th,&nbsp;2020 | Vector clocks Protocol runs and anomalies Message Delivery vs. Message Receipt FIFO delivery | Lamport Clocks
| [Lecture 6](./Lecture%2006.md) April&nbsp;10th,&nbsp;2020 | Causal delivery Totally-ordered delivery Implementing FIFO delivery Preview of implementing causal broadcast | Delivery vs. Receipt FIFO delivery
| [Lecture 7](./Lecture%2007.md) April&nbsp;13th,&nbsp;2020 | Implementing causal broadcast Uses of causality in distributed systems Consistent snapshots Preview of the Chandy-Lamport snapshot algorithm | Causal anomalies and vector clocks
| [Lecture 8](./Lecture%2008.md) April&nbsp;15th,&nbsp;2020 | Chandy-Lamport Snapshot Algorithm |
| [Lecture 9](./Lecture%2009.md) April&nbsp;17th,&nbsp;2020 | Chandy-Lamport wrap-up: limitations, assumptions and properties Uses of snapshots Centralized vs. decentralized algorithms Safety and liveness | Delivery guarantees and protocols
| [Lecture 10](./Lecture%2010.md) April&nbsp;20th,&nbsp;2020 | Reliable delivery Fault classification and fault models The Two Generals problem | Safety and liveness
| [Lecture 11](./Lecture%2011.md) April&nbsp;22nd,&nbsp;2020 | Implementing reliable delivery Idempotence At-least-once/at-most-once/exactly-once delivery Unicast/Broadcast/Multicast Reliable broadcast Implementing reliable broadcast Preview of replication
| [Lecture 12](./Lecture%2012.md) April&nbsp;24th,&nbsp;2020 | Replication Total order vs. determinism Consistency models: FIFO, causal and strong Primary-backup replication Chain replication Latency and throughput
| [Lecture 13](./Lecture%2013.md) April&nbsp;27th,&nbsp;2020 | **Pause for breath!** Wrapping up replication techniques
| [Lecture 14](./Lecture%2014.md) May&nbsp;1st,&nbsp;2020 | Handling node failure in replication protocols Introduction to consensus Problems equivalent to consensus The FLP result Introduction to Paxos | Strongly consistent replication protocols
| [Lecture 15](./Lecture%2015.md) May&nbsp;4th,&nbsp;2020 | Paxos: the interesting parts
| [Lecture 16](./Lecture%2016.md) May&nbsp;6th,&nbsp;2020 | Paxos wrap-up: Non-termination, Multi-Paxos, Fault tolerance Other consensus protocols: Viewstamped Replication, Zab, Raft Passive vs. Active (state machine) replication
| [Lecture 17](./Lecture%2017.md) May&nbsp;8th,&nbsp;2020 | Eventual consistency Strong convergence and strong eventual consistency Introduction to application-specific conflict resolution Network partitions Availability The consistency/availability trade-off
| [Lecture 18](./Lecture%2018.md) May&nbsp;11th,&nbsp;2020 | Dynamo: A review of old ideas<ul><li>Availability</li><li>Network partitions</li><li>Eventual consistency</li><li>Vector clocks</li><li>Application-specific conflict resolution</li></ul>Introduction to:<ul><li>Anti-entropy with Merkle trees</li><li>Gossip</li><li>Quorum consistency</li></ul>
| [Lecture 19](./Lecture%2019.md) May&nbsp;13th,&nbsp;2020 | More about Quorum Consistency Introduction to sharding Consistent hashing
| [Lecture 20](./Lecture%2020.md) May&nbsp;18th,&nbsp;2020 | Online systems vs. Offline systems Raw data vs. Derived data Introduction to Google's MapReduce framework MapReduce example: transform a forward index into an inverted index
| [Lecture 21](./Lecture%2021.md) May&nbsp;20th,&nbsp;2020 | MapReduce<ul><li>Types</li><li>Approach to fault tolerance</li><li>Combine functions</li><li>More examples</li></ul> | MapReduce phases
| [Lecture 22](./Lecture%2022.md) May&nbsp;29th,&nbsp;2020 | The math behind replica conflict resolution<ul><li>Upper bounds</li><li>Least upper bounds</li><li>Join-semilattices</li></ul> | Strong convergence Partial orders
| [Lecture 23](./Lecture%2023.md) June&nbsp;1st,&nbsp;2020 | Filling in the gaps: Overviews of 2-phase commit and Practical Byzantine Fault Tolerance (PBFT) Quick overview of the history of:<ul><li>Lamport and Vector Clocks</li><li>Replication Strategies</li><li>Consensus</li><li>Replication Needs Consensus</li></ul>

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