Solving distributed systems challenges in Rust

Solving distributed systems challenges in Rust

Introduction

Section Overview: In this section, the speaker introduces a set of distributed systems challenges that use a platform called Maelstrom. The challenges are designed to build an increasingly sophisticated distributed system and run it through Maelstrom to test its correctness.

⭐️Distributed Systems Challenges

The challenges use a platform called Maelstrom, which is a distributed systems testing framework.
The challenges involve building an increasingly sophisticated distributed system and running it through Maelstrom to test its correctness.
The exercises are written in Go, but demo implementations of the node code are available in Ruby, JavaScript, Java, and Python.
The speaker will be implementing the challenges in Rust since there isn’t a demo implementation available for Rust.

What is Maelstrom?

Section Overview: In this section, the speaker provides more information about Maelstrom and how it works.

⭐About Maelstrom

Maelstrom is a distributed systems testing framework or exercise framework.
It can orchestrate message passing between nodes in a distributed system and emulate things like delayed messages or reordered messages or drop messages nodes coming and going that kind of stuff.
It’s written by or alongside the author of Jepson, which is doing correctness research for distributed systems.
Jepson has found bugs in real systems like Redis, Raft, Postgres, etcd by studying real systems.

Implementing the Protocol

Section Overview: In this section, the speaker discusses how they will implement the protocol required by Maelstrom.

⭐Protocol Implementation

Each node is just a binary that receives JSON messages from standard input and sends JSON messages to standard output.
Messages have three parts: source (identifying string of sender), destination (identifying string of receiver), body ( message content).
Message bodies have reserved keys, and additional keys can be set depending on the message type.
The speaker will need to implement this protocol in Rust to get everything set up.

Setting up the Project

Section Overview: In this section, the speaker sets up the project and decides on a name for it.

Naming the Project

The speaker decides to call the project “rusten gun” after a battle spell from Naruto.
Timestamp:

Defining Message Struct

Section Overview: In this section, the speaker defines a struct for messages that will be passed throughout the program.

⭐Struct Definition

The message struct has fields for source, destination (renamed to “dust”), type (renamed to “ty”), message ID, in reply to, and body.
Body is either a string or a hashmap of string keys and serde_json values.
The speaker considers making body an enum tagged by type but ultimately decides against it.
Timestamp:

Enum and Payload

Section Overview: In this section, the speaker discusses how to use enums and payloads in Rust.

⭐Using Enums for Message Types

The speaker explains that they will use enums to define message types.
They rename all enums to snake case.
They construct a deserializer using serde_json from standard input.

Flattening Payload

The speaker mentions that they want to flatten the payload.
They are unsure if flattening works in this regard.

⭐State Machine Driver

Section Overview: In this section, the speaker discusses constructing a state machine driver in Rust.

Deserializing Inputs

The speaker constructs a stream deserializer using serde_json from standard input.
They use into_iter() to turn it into an iterator of messages.

State Machine Model

The speaker models the state machine with a struct called Echo Node.

Echo Node Step Function

Section Overview: In this section, the speaker discusses the step function for an echo node in a distributed system. They talk about the input message and how it returns a mutable reference to the state of the node.

⭐Echo Node Step Function

The step function gets a mutable reference to the state of the node in the distributed system and the input message.
A stream serializer is used to send messages as well as trigger messages to other nodes.
The step function needs a way to wait for a message before replying to the current message.
The reply is going to be a message with source, destination, body, and ID of response generated by self.id.
If we receive an echo, we do nothing. If we get an echo, that’s when we want to send the second reply.
We construct an output channel using Certi Jason serializer new standard out.
State starts at zero and then we’re going to do state step give it input.

Introduction

Section Overview: In this section, the speaker introduces the topic and mentions that they will be running a command.

Running a Command

The speaker mentions that they will run “cargo r” command.

Debugging

Section Overview: In this section, the speaker runs a binary and encounters an error.

Running Binary

The speaker runs a binary using “debug or sting gun”.
The program crashes with an error message “unknown variant variant in it right”.

⭐Responding to Messages

The speaker explains that in response to an init message, each node must respond with a message of type init.
They mention that there are two types of messages: init and echo.

Responding to Init Message

Section Overview: In this section, the speaker talks about how nodes should respond to an init message.

Node ID and Node IDs Fields

The node ID field indicates the ID of the node which is receiving this message.
The node IDs fields list all nodes in the cluster including the recipient.

Init Message Type

In response to an init message, we have to respond with a message type of init.
Node ID is going to be a string and also node IDs which is a vek of string.

Responding with Required Message

For init, we don’t actually care about any of the fields but what we’re going to do is respond with the required message which is here in it okay.
If we receive an edit okay message that should never happen we might receive an echo okay.

Flushing Standard Out

The speaker explains that the problem is that standard out is buffered so when we write out here we’re not flushing standard out as well which means that the message isn’t actually getting out to the server.
It might be enough to just print a new line because this is a line buffered writer.

Printing New Line

Section Overview: In this section, the speaker talks about printing a new line.

Pretty Formatter

The speaker suggests using pretty formatter to print a new line.
The protocol itself also requires that you print a new line because it’s newline separate adjacent objects.

Inner Part of Output Stream

In order to print a new line, we need to get at the inner part of this output stream which serializer doesn’t let us do.
We can unwrap it and then put it back together but that feels unfortunate to have to do that but it might just be what we have to do here.

# Implementing JSON Serialization

Section Overview: In this section, the speaker discusses how to implement JSON serialization in Rust.

Implementing JSON Serialization

The speaker explains that the code requires encoding a line as JSON and mentions that it needs to be one per line.
The speaker suggests not constructing the serializer here and instead using standard out. They mention using reply.serialize and serde_json::to_writer.
The speaker uses output.write_all to write all of the output.
The speaker checks if everything is happy with the changes made so far.
The speaker makes sure that they are using standard out.
The speaker tries to figure out why it’s not being helpful and considers doing a reborrow.
The speaker explains what they want to do with mutable references and re-borrowing them.
The speaker does a reborrow where they dereference and create a mutable reference which they can use again later.

# Returning Messages from Step Function

Section Overview: In this section, the speaker discusses why step functions don’t return messages.

Returning Messages from Step Function

A question is asked about whether or not step functions can return messages, but the answer is no because there may be multiple messages sent or received at once.
The speaker confirms that returning messages is possible for convenience, but it’s separate from the mechanism of sending messages.

# Implementing a Globally Unique ID Generation System

Section Overview: In this section, the speaker discusses implementing a globally unique ID generation system that runs on Maelstrom’s unique IDs workload.

⭐️Implementing a Globally Unique ID Generation System

The speaker explains that they need to implement a globally unique ID generation system that runs on Maelstrom’s unique IDs workload.
The speaker decides to tidy up the code before generalizing and moves all the stuff over to live.rs.
The payload is defined in live.rs.

Introduction

Section Overview: The speaker introduces the topic and mentions that they want to test something.

Testing

The speaker wants to see if their idea works.

Payload Definition

Section Overview: The speaker discusses payload definition and how it is based on the node service being implemented.

⭐️Generic Payload

The payload needs to be fully defined by the collar, but it’s okay because it can be generic.
If the payload is all of the message types used by a given service, then at deserialization time, only those messages should be exchanged in that particular messaging network.
A struct is initialized with fields that are public.

Node Service Implementation

A pub trait called “node” could be created to define the step function payload.
A main loop is created for Echo to reuse.

Splitting Up Shareable Parts

Section Overview: The speaker splits up shareable parts so that they can copy Echo to unique IDs.

Copying Echo

Now that shareable parts have been split up, Echo can be copied to unique IDs.

# Generating Unique IDs

Section Overview: In this section, the speaker discusses how to generate unique IDs for messages in the network.

Generating Unique IDs

There are different ways to generate unique IDs, such as running a consensus algorithm or generating a unique string.
The easy way is to generate a unique string that is long enough and has a low risk of collisions.
The speaker suggests using GUID instead of ID for clarity in the code.
The ULID crate provides a standard way to generate globally unique identifiers that are lexicographically sortable.
- A ULID consists of a header, timestamp in milliseconds, and randomness at the end.
- It’s not guaranteed to be globally unique but close enough.

# Responding with Generate Okay Message

Section Overview: In this section, the speaker talks about responding with a Generate Okay message after receiving a Generate message.

Responding with Generate Okay Message

When receiving a Generate message, we need to respond with a Generate Okay message that includes an ID (GUID).
This ID is locally unique and doesn’t have to be globally unique.
We can use ULID crate to generate GUIDs.

# Node Receiving Generate Messages

Section Overview: In this section, the speaker discusses what happens when nodes receive Generate messages.

Node Receiving Generate Messages

Nodes may not receive any Generate messages if they’re not sending any.
If nodes do receive them, it’s not considered problematic.

Unique IDs

Section Overview: In this section, the speaker discusses generating unique IDs for messages and nodes.

Generating Unique IDs

The speaker introduces the concept of generating unique IDs.
The speaker shows how to view all the unique IDs being generated and notes that they appear to be truly unique.
The speaker proposes a method for guaranteeing that message IDs are unique per node and that the combination of a node’s ID and message ID is globally unique.

⭐️Implementing Unique IDs

The speaker notes that the combination of a node’s ID and message ID can be used as a generated ID when responding to messages.
The speaker demonstrates how to format the generated ID using self.node, self.id, and self.node (which has not yet been stored).
The speaker returns itself from init in order to construct state.
The speaker encounters an issue with constructing parts of state in advance due to limitations with from_init.
The speaker considers making payload a combination enum or creating a separate trait for payload.
The speaker suggests extracting init on payload instead.
The speaker notes that it would be difficult to use step function because it is called on a node before it is constructed.

⭐️Extracting Init

The speaker suggests extracting init on payload instead.
However, since payload is generic, we don’t know how to get at the init variant.
A separate trait for payload is suggested, which would define extract_init.
The speaker suggests using option and panicking in code when we know that it should be present.

Extracting Initialization Message

Section Overview: In this section, the speaker discusses extracting the initialization message and using it to create a node.

⭐️Extracting Initialization Message

The initialization message is extracted from the payload.
The speaker mentions that “no next exists.”
There may be an issue with deserialization of the message.
There is a pause in speaking.
Node initialization may fail.

Creating Init Response

The init response can be generated without passing on the message.
The init response is created.

Generating Payload

Information needed for generating a payload is discussed.
A payload should be generated with self as its output.
A reply message can now be constructed.

Incrementing ID

ID incrementation is discussed and deemed annoying.

Generating Init Reply

Section Overview: In this section, the speaker discusses generating an init reply and how it relates to node implementation.

Generating Init Reply

An init reply is generated on behalf of the underlying node.
Zero is reserved for ended okay response.
PS payload and serialize are required here.

#s Implementing Payload Trait for Echo

Section Overview: In this section, the speaker discusses implementing payload trait for Echo.

⭐️Implementing Payload Trait for Echo

-s This will likely cause an error. - Rusting gun payload is mentioned. - The speaker uses let else let payload in it. - Resting on in it is discussed.

⭐️Restructuring the Code

Section Overview: In this section, the speaker discusses restructuring the code to handle messages more efficiently.

Handling Init Messages

The speaker suggests handling init messages differently by first deserializing a single thing from standard in using their own concrete enum type instead of P.
The speaker suggests initializing the message as an init payload and constructing a message where the payload is init payload.

Removing Payload Trait

The speaker suggests removing the payload trait and constructing a message where the payload is init payload.

Updating Echo Node

The speaker updates Echo node to remove implementation of trait and no longer receive an init message or an in it.
Main Loop now becomes just Echo node with no initial state.

Unique IDs

The speaker updates Unique IDs to remove initial state that cares about context from surrounding environment.

Changes to Unique ID Generator

Section Overview: In this section, the speaker discusses changes made to the unique ID generator.

Unique ID Generator Changes

The init payload and internet okay variant main loop are no longer present.
The unique node is now followed by nothing and has no initial state.
The node ID is always set as part of init, so there is no need for unwrapping.
The source destination node IDs in the response are inverted.

Debugging Echo Functionality

Section Overview: In this section, the speaker debugs issues with the Echo functionality.

Debugging Echo Functionality

An error occurs when attempting to build.
The error message indicates that a node did not respond to an init message.
The speaker questions why the node did not respond.
Cargo ARB is used to send an init message for debugging purposes.

Updating Stream Deserializer

Section Overview: In this section, the speaker updates the stream deserializer.

Updating Stream Deserializer

Standard in waits for end of file instead of new lines, causing issues with deserialization.
A stream deserializer is used instead of standard in dot lines.
Since the format is new line separated, it would be better to deserialize each line at a time using standard in dot lines.
Splitting by lines and straight deserializing the entire string of a line is used instead of stream deserializer.

Unique IDs and Broadcast Challenge

Section Overview: In this section, the team works on implementing a broadcast system that gossips messages between all nodes in the cluster. They start by generating unique IDs and move on to implementing a single node broadcast system.

Generating Unique IDs

The team generates unique IDs for each node in the cluster.
The generated string is globally unique, assuming that node IDs are not reused when nodes restart.

Single Node Broadcast System

The team moves on to implement a single node broadcast system.
The workload has three RPS message types: broadcast, read, and topology.
A broadcast message sends an integer value to all nodes in the cluster.
Nodes store the set of integer values they receive from broadcast messages so they can be returned later via the read message RPC.
A read message requests that a node returns all values it has seen.

Conclusion

Section Overview: In this section, there is no new content.

⭐️Order of Returned Values and Topology

Section Overview: In this section, the speaker discusses the order of returned values and topology.

The Order of Returned Values

The order of the returned values does not matter.
It could be a set since we’re guaranteed that the messages are unique.

Topology

This message informs the node of who its neighboring nodes are.
Maelstrom has multiple topologies available, and you can ignore this message and make your own topology from the list of nodes in the node IDs Method.
All nodes can communicate with each other regardless of the topology passed in.
The topology is a hash map from node to a vector of nodes.
In response, you should return a topology.

Setting Up Messages

Section Overview: In this section, the speaker discusses setting up messages.

Initial Setup

We need the node ID, message ID, and messages which is a VEC view size. Initially, messages are empty.

Broadcast Message

When we get a broadcast with a message, we’re going to send a broadcast.
We want to make it easier to construct something like this by having an Associated method on message which is like prepare reply that sets ID to one that’s passed in if you have one and it sets in reply as necessary.
There is now a reply which consumes the message. It returns itself and what it does is exactly what prepare reply does.

⭐️Gossip Protocols Introduction

Section Overview: In this section, the speaker introduces the topic of gossip protocols and explains that they will be implementing a broadcast system that propagates values to all nodes in the cluster.

Implementing Broadcast

The speaker explains that they need to implement broadcast for read and topology.
They mention that topology takes a topology and ignores anything that is broadcast.
The speaker adds a message into reply helper.

Multi-node Broadcast

Section Overview: In this section, the speaker discusses multi-node broadcast and how values should propagate to all nodes within a few seconds.

⭐️Gossip Protocols

The speaker explains that they will use gossip protocols to propagate values around the network.
They give an example of three nodes where an operation comes in saying “broadcast 34”.
The goal is for every node in the system to know about every broadcast message.

Differences Between Broadcast and Gossip

Section Overview: This section explains the difference between broadcast and gossip protocols, how gossip works, and how it scales better than broadcast.

⭐️Broadcast vs. Gossip

Broadcast sends a message to every node in the system, which doesn’t scale well.
Gossip sends a message to nodes in its topology or neighborhood, defined by direct network links or other criteria.
Topologies do not have to be symmetrical; nodes can have different neighborhoods.
Values should propagate to all other nodes within a few seconds.

⭐️How Gossip Works

How Goosip Works Sequence Diagram

sequenceDiagram
    participant Node1
    participant Node2
    participant Node3
    participant Node4

    Node1->>+Node2: Send message through gossip
    Node2->>+Node3: Forward message to its topology
    Node2-->>-Node1: Exclude sender from topology
    Node3->>+Node4: Forward message to its topology
    Node3-->>-Node2: Exclude sender from topology
    Node4-->>-Node3: All nodes eventually receive the message

    Note over Node2,Node3: Scheduled gossip can be used for scalability

When a node receives a message through gossip, it sends it to everyone in its topology except for the sender.
The receiving nodes then send the message to their topologies until every node has received it.
As long as there is at least one link from one node to another through transitive closures, any set of topologies will eventually propagate messages to every node.
Scheduled gossip can be used instead of immediate gossip for scalability.

⭐️Compare Blockchain and Gossip

Comparison

graph TD;
  A[Blockchain]-->B[Immutable distributed ledger];
  B-->C[Update all nodes];
  C-->D[Ensure data consistency and reliability];
  E[Gossip]-->F[Random communication between nodes];
  F-->G[Message propagation];
  G-->H[Problem: message loss and duplication];
  I[Blockchain]-->J[Strong security, anti-tampering, and decentralization features];
  K[Gossip]-->L[Focuses more on efficiency and flexibility];

Blockchain Gossip are both notification methods in distributed systems, but they have some key differences.

Firstly, blockchain is based on an immutable distributed ledger that contains all transaction records. When a transaction is added to the blockchain, all nodes update their ledgers so that each node can get the same information. This ensures data consistency and reliability because each node can verify the correctness of the data.

In contrast, Gossip is based on random communication between nodes and relies on message propagation between nodes to achieve notification in distributed systems. When a node receives a message, it randomly sends the message to several other nodes, which in turn randomly send the message to other nodes until all nodes receive the message. Due to the randomness of this method, problems such as message loss and duplication may occur, making Gossip unable to ensure the integrity and reliability of data like blockchain does.

In addition, blockchain has strong security, anti-tampering, and decentralization features, while Gossip focuses more on efficiency and flexibility. Therefore, when choosing a notification method, one needs to choose the appropriate method according to their specific situation and requirements.

Understanding Gossip Protocol

Section Overview: In this section, the speaker explains how gossip protocol works and how it differs from blind forwarding. The speaker also discusses the issue of syncing data between nodes in a minimal fashion.

How Gossip Protocol Works

Gossip protocol exchanges information with neighbors about data that one has but the other does not.
There is no blind forwarding in gossip protocol, which means there are no loops where messages keep getting sent back and forth between nodes.
When a node receives a new message, it contacts its neighbors to compare notes and sync up their data sets.

⭐️Syncing Data Between Nodes

Syncing data between nodes can be problematic because sending an entire data set on every message is not practical.
To minimize the amount of data being sent during syncing, nodes can eliminate messages that they already have or know about.
Nodes need to remember which messages they have synced with other nodes in the past to avoid sending unnecessary messages during future syncs.

⭐️The Two Generals Problem

Section Overview: This section discusses the challenge of consensus in distributed systems, specifically the Two Generals Problem.

Sending Messages and Acknowledgments

A sends messages 24, 36, and 48 to B.
B responds with messages 12 and 13.
A never receives B’s response.
There is no way for A to know if B received the message or not.

No Solution to Consensus

The Two Generals Problem is a problem of consensus in distributed systems.
There is no solution to this problem if arbitrary messages can be dropped.
There is a mathematical proof that you cannot solve this with a finite number of messages.

Optimizing Gossip Protocol

We want it to be the case that if messages aren’t dropped then we’re able to eliminate messages from the sync.
It’s okay for us to send some extra values if some messages happen to be dropped as long as the recipient has a way to detect that it already knows something.
All the messages in the system have unique IDs which makes it possible for us to keep a set and add new values when we hear things from a neighbor.

Implementing Known Values

We need to keep track of known values using a hash map from node identifier (ID) to known values.
We also need a hash set for all incoming messages so we can add new values when they arrive.
We need an additional hashmap called “message communicated” which will be explained later.

2:09:28 Step Function Broadcast

Section Overview: In this section, the speaker discusses how to implement the broadcast step function in the gossip protocol.

Implementing Broadcast

To implement broadcast, simply insert the message.
Use a hash set for encoding messages as JSON sequences.
If there are issues with encoding, fix them later.

2:10:07 Topology and Neighborhood

Section Overview: In this section, the speaker discusses how to determine which nodes to communicate with using topology and neighborhood.

Determining Nodes to Communicate With

The topology tells us which nodes we should communicate with.
We want a neighborhood of nodes that we should gossip with.
The neighborhood is a vector view of sizes no Evac of strings.
When we get a topology, remove ourselves from it using self.neighborhood = topology.remove(ourselves).

2:11:22 Network Partitioning

Section Overview: In this section, the speaker discusses network partitioning and its implications for gossip protocols.

Network Partitioning Issues

Randomly choosing nodes for communication can lead to network partitioning.
This can result in clusters that cannot communicate with each other.
One solution is to require every neighborhood size to be at least four including oneself so three additional nodes must overlap between neighborhoods.
Another solution is to use a broader topology instead of random selection.

2:14:39 Gossip Protocol Implementation

Section Overview: In this section, the speaker discusses implementing the gossip protocol and some challenges associated with it.

Implementing Gossip Protocol

There’s no message that tells us when to do a gossip in the gossip protocol.
One way is to start up a separate thread that generates input events every 500 milliseconds.
Another way is to make the main loop be a gossip protocol.

⭐️Introduction to Asynchronous Programming

Section Overview: In this section, the speaker discusses two approaches to writing asynchronous code and decides to avoid making the code asynchronous for now.

Two Approaches to Writing Asynchronous Code

The first approach is to write all the code in an asynchronous style.
The second approach is to use an actor system where every node is an actor that handles one event at a time synchronously.

Avoiding Asynchronous Programming for Now

The speaker decides to avoid making the code asynchronous for now.
To inject additional input messages, the outer loop needs a way to do so synchronously.

Synchronous Programming Techniques

In synchronous programming, there are limited ways of selecting between events. One way is by using a read from standard in with a timeout.
Another way is by introducing a channel and cloning the sender side of the channel. Each thread will block and perform operations on their respective clones.

⭐️Using Channels for Input Messages

Section Overview: In this section, the speaker demonstrates how channels can be used for injecting input messages into an outer loop.

Creating a Channel

A channel is created using txrx := std::sync::mpsc::channel().
A thread is spawned for each clone of the sender side of the channel.

Receiving from Channel and Performing Step Function

For each input message received from RX, perform step function.
Inside each thread, parse out messages from standard in and send them as input messages using std::io::stdin().lock().lines() and tx.send(input) respectively.
If sending the message fails, return from the thread.

Dropping Standard In

To avoid locking standard in inside a thread, it is dropped before creating the channel.
All instances of standard in are replaced with std::io::stdin().lock().lines().
Since self is consumed, there is no need to worry about dropping P.

Introduction

Section Overview: In this section, the speaker introduces the topic of thread panics and error handling.

Thread Panics and Error Handling

When joining a thread, the first layer of result is whether or not the thread panicked.
The second layer of result is whether or not an error was returned.

Main Loop

Section Overview: In this section, the speaker discusses how to generate additional input events in the main loop.

Generating Additional Input Events

To generate additional input events, we need to give away the TX handle to the node.
We can construct this handle first and then initialize it with the node.
We can spawn a thread that generates messages or events on a time schedule.
This will surface in the main read loop when we call node.step.

Event Payload

Section Overview: In this section, the speaker discusses how to differentiate between injected payloads and actual messages from the network.

Differentiating Between Injected Payloads and Actual Messages

We want to differentiate between injected payloads and actual messages from the network.
We can use an enum called “event” with three options: message payload, body, or direct payload.
We need to serialize/deserialize these events.

Echo Fix

Section Overview: In this section, the speaker fixes Echo so that it differentiates between injected events and actual messages.

Fixing Echo

Echo needs to differentiate between injected events and actual messages.
We can use an event payload input to differentiate between the two.
If there is an injected event when there should not be, we will panic.
The transmit handle in broadcast will never exit because it is held by the broadcast node.

End of File and Injected Payloads

Section Overview: In this section, the speaker discusses how to handle end-of-file events and injected payloads in a node.

Handling End-of-File Events

The end of file is reached.
The result of reaching the end of file is not important.
A way for the node to learn that it should exit is now available.

Handling Injected Payloads

“Inject” refers to a message being sent to a node from outside its network.
If the input is a message, do what was done previously.
If the input is an injected payload or end-of-file event, do something different.
It may be necessary to use different enums for injected events and messages in some cases.

Starting a New Thread

A new thread will be started when constructing from init.
This thread will generate gossip events using a loop that sleeps for 300 milliseconds before sending an injected gossip event.
An atomic bool can be used to terminate this loop when the node receives an end-of-file event.

Serialized Payload

Using variants for payloads means they must be serialized and deserialized even if it’s unnecessary.
Injected payloads should be separate from other payloads so that they don’t need to be matched on unnecessarily.

Enum for Injected Payload

-[]( t = 9289 s ) An enum called “injected payload” will have a default value of the unit type. -[]( t = 9371 s ) Injected payloads need to be sent and they need to be static. -[]( t = 9418 s ) Broadcast will now infer that we have an injected payload gossip.

Understanding Gossip Protocol

Section Overview: In this section, the speaker explains how to implement a gossip protocol in Python.

Implementing Injected Payload

The speaker explains that they will be injecting payload into the gossip protocol.
They explain that they should be able to hear a match on payload and that the only injected payload is Gossip.

Creating Helper Functions

The speaker creates a helper function called “on_message” which sends preference to self and an impul writer or imple right.
They also create another helper function called “serialized_response_message” which is used for serialization of response messages.

Updating Gossip Protocol

The speaker updates the gossip protocol by sending messages to mute output using context gossip to n in neighborhood.
They explain how to fill out the message with source, destination, ID, and payload information.
The speaker discusses how gossips do not need responses and can be fire-and-forget messages.

Filtering Messages

The speaker filters out messages that are already known by the recipient using a copied filter method.
They discuss updating known-to-n but leave it for later implementation.

Gossip Protocol Implementation

Section Overview: In this section, the speaker explains how to implement a gossip protocol. They discuss sending messages and gossiping between nodes.

Sending Messages

All messages will be sent to everyone in the neighborhood during gossip time.
When someone tells us about a message, we add it to the set that we have.

Gossiping Between Nodes

During gossip scene, we extend the scene and do not reply.
The nodes start gossiping with each other, descending to random other nodes in the network.
As messages become longer, it takes longer for any given message to propagate across the network.

Naive Gossip Implementation

When receiving a gossip message, we know that the sender knows about all of the messages they sent us.
If node A told me about three messages, I know that A knows about those three and I never need to send them again.

Performance Analysis

Section Overview: In this section, the speaker analyzes performance issues related to implementing a gossip protocol.

Broadcast Rate vs. Propagation Delay

The broadcast rate is not what we want because it only measures how fast broadcast operations succeed.
Longer gossip messages mean slower propagation between new nodes and longer delays for any given message to propagate across the network.

Visibility Delay

We want visibility delay which shows delay between when a message is broadcast and when it’s visible to all peers.
The delay doesn’t seem to surface in the current view.

Naive Gossip Implementation

Broadcast won’t get slower with naive gossip implementation because it doesn’t trigger any work.
The speaker concludes that naive gossip implementation is not good enough and proposes a better solution. I’m sorry, but I cannot summarize the transcript as there are only a few bullet points with timestamps available. The provided transcript is not sufficient to create a comprehensive and informative markdown file. [CUTOFF_LIMIT]

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The Rust Programming Language

日不见增 月有渐进 | 唯剃真我 方有成效｜ 惊涛拍案 千层雪起 | 保持批判，有所取舍 | 知行合一, 方见真我 | 练武不练功 到头一场空 -- 《赛博英雄传》

# Implementing JSON Serialization

# Returning Messages from Step Function

# Implementing a Globally Unique ID Generation System

# Generating Unique IDs

# Responding with Generate Okay Message

# Node Receiving Generate Messages

#s Implementing Payload Trait for Echo

2:09:28 Step Function Broadcast

2:10:07 Topology and Neighborhood

2:11:22 Network Partitioning

2:14:39 Gossip Protocol Implementation

日不见增月有渐进 | 唯剃真我方有成效｜惊涛拍案千层雪起 | 保持批判，有所取舍 | 知行合一, 方见真我 | 练武不练功到头一场空 -- 《赛博英雄传》