raft | : rowboat : Raft implementation in Go | Architecture library
kandi X-RAY | raft Summary
kandi X-RAY | raft Summary
This is an instructional implementation of the Raft distributed consensus algorithm in Go. It's accompanied by a series of blog posts:. Each of the partN directories in this repository is the complete source code for Part N of the blog post series (except Part 0, which is introductory and has no code). There is a lot of duplicated code between the different partN directories - this is a conscious design decision. Rather than abstracting and reusing parts of the implementation, I opted for keeping the code as simple as possible. Each directory is completely self contained and can be read and undestood in isolation. Using a graphical diff tool to see the deltas between the parts can be instructional.
Support
Quality
Security
License
Reuse
Top functions reviewed by kandi - BETA
Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of raft
raft Key Features
raft Examples and Code Snippets
Community Discussions
Trending Discussions on raft
QUESTION
The Raft paper says:
Raft uses the voting process to prevent a candidate from winning an election unless its log contains all committed entries. A candidate must contact a majority of the cluster in order to be elected, which means that every committed entry must be present in at least one of those servers. If the candidate’s log is at least as up-to-date as any other log in that majority, then it will hold all the committed entries. The RequestVote RPC implements this restriction: the RPC includes information about the candidate’s log, and the voter denies its vote if its own log is more up-to-date than that of the candidate
How does it guarantee, however, that there will always even be an electable leader (i.e. one that's as up-to-date as a majority of cluster)?
For example, let's say we have a cluster of three servers A, B, C with A as the leader. First log entry is stored in A and B, second log entry is stored in A and C. Then A crashes, and B and C try to elect a leader. But at this point there is no majority (i.e. 2 out of 3) servers that have both first and second entries. So it seems like leader election can't ever happen (unless A restarts, but Raft's supposed to be resilient to a failure of 1 out of 3 servers..)
...ANSWER
Answered 2022-Apr-08 at 20:25The paper defines a "Log Matching Property" that is relevant to this scenario:
• [..]
• If two entries in different logs have the same index and term, then the logs are identical in all preceding entries.
Since A and C both contain the same second entry, C must also contain the first entry. This is ensured because:
The second property is guaranteed by a simple consistency check performed by AppendEntries. When sending an AppendEntries RPC, the leader includes the index and term of the entry in its log that immediately precedes the new entries. If the follower does not find an entry in its log with the same index and term, then it refuses the new entries.
Until C has the entry that B has, it will reject further appends. So at some point in your scenario, C must have received that entry to finally accept the newer entry from A.
Therefore, C is the most up to date between B and C. (It would reject a leadership vote from B.)
QUESTION
I am running docker in a Raspberry Pi 3 Model B Plus Rev 1.3, running Raspberry pi OS with all packages up to date.
TL;DR
The healthchecks on a given container works fine for some time (around 30 min, some times less some times more), but at some point they get "stuck" and so the container remains healthy, even though it is not the case. Is there a way to debug what's going on with the healthchecks and so try to figure out what is happening?
the healthcheck is not configured in the Dockerfile, but instead in the yml file I use to deploy the stack as follows
...ANSWER
Answered 2022-Mar-15 at 17:16This issue appears to no longer be happening. I upgraded to Raspbian bullseye, and healthchecks have been running for a week straight, without issues.
QUESTION
I'm running Hyperledger Fabric network in Azure Kubernetes Cluster. I'm using single Azure Files volume (1000 GB) as my persistent volume.
However, my Orderer POD keeps restarting over and over again.
Orderer POD is logging following error:
...ANSWER
Answered 2022-Feb-18 at 05:48Turns out my WAL logs directory was deleted. Anyone landing on this question, please set following (if not already set) ENV variables on your Orderer deployments:
QUESTION
I'm doing a project in react native and my ImageBackgroud component does not want to render. The odd thing is I am already using ImageBackground in another component and it works there. I tried resizing the image but that didn't help.
Here is my component that renders child component with ImageBackground:
...ANSWER
Answered 2022-Feb-09 at 01:01image: {
flex: 1,
overflow:'hidden',
justifyContent:'center',
padding:30
},
QUESTION
I have 3 nodes etcd cluster i.e. one master and two slaves. I need to bring down the master node for some maintenance activity. So, I tried conducting elections to elect a new master but it didn't work.
Below is the current state of the etcd cluster
...ANSWER
Answered 2022-Feb-04 at 12:31QUESTION
I have a fresh Spring Boot 2.6.3 Java 11 application with a Spring Kafka Dependency (generated with start.spring.io).
By default Kafka 3.0.0 is is used. I want to change the Kafka version to 3.1.0 and added
...ANSWER
Answered 2022-Jan-28 at 20:46According to the docs section on overriding dependencies
You could manually add the one it's looking for
QUESTION
etcd is use to consensus metadata in Kubernetes. I can see Dgraph BadgerDB and other key value stores are using etcd, but I don't know quite how they are using it. Update: It looks like they are using a raft subset of etcd.
My question:etcd is for storing metadata and not data as such - is it possible/recommended to combine etcd with another key value store to handle large data?
I have also looked at hashicorp raft
...ANSWER
Answered 2022-Jan-27 at 09:08The etcd service was conceived to handle metadata: retrieve one key, get some data wich usually in the kilobytes range. Not megabytes.
You cannot "offlad" etcd to another database / datastore. Etcd need to have its data with low latency on the majority of nodes.
The biggest criticism about etcd are hardware requirements: 8GB RAM x 3 machines might be too much for some use cases.
Is it etcd good for you? It depends a lot on:
- Your workload (mostly read-oriented than write-oriented)
- How many requests you need from etcd in a short time period: do not 'fire' too many requests at once to etcd or you might trigger a leader election.
- And your data size: use
--auto-compactionenabled to keep disk usage as low as possible removing old data versions.
QUESTION
For a University assignment, I have to implement a simulation of the Raft protocol in Akka (I am using Akka typed, using Behaviors).
In the Raft protocol, interactions between actors have a 1:1 mapping between a request and a response; responses must be delivered in a timely manner.
Therefore, it makes sense to use the ask pattern as demonstrated by the documentation in the Request-Response with ask between two actors example.
In my implementation, requests and responses must be context-aware: this means that, when an actor that performed a query receives a response, it must know what query the response was for. The example in the documentation suggests to include a query ID in the message.
What I need to solve can be described with the following example:
- Actor A sends a query with ID=1 to actor B (it includes the query ID in the message).
- B does not reply in time (the network, or B itself, may be slow), thus A re-issues a query with ID=2 to B.
- Actor B receives the query with ID=1, and replies to actor A (including the query ID in the message).
- Actor A receives B's reply with ID=1. A knows that the last query it sent had ID=2, thus must NOT process the reply but wait for the one with ID=2.
I think that, to "filter" replies that do not have a correct query ID, I can put a BehaviorInterceptor in actor A that checks that the ID in the reply matches the expected query ID.
To summarize:
- Actor A writes in a hashmap the query ID to be expected from actor B's next reply,
- The interceptor uses this hashmap to check the ID in the reply. Is this a good design?
Moreover, I don't understand whether ask is blocking or not.
Ideally, I would like to use ask in a non-blocking way: actor A asks actor B, and, while waiting for B's reply, A can do other operations.
While waiting for B's reply, actor A can also change its behavior if needed (also a Behavior that does not handle B's replies).
Thank you for any insight!
...ANSWER
Answered 2022-Jan-24 at 18:23An ask between two actors (using the ActorContext) is non-blocking.
Since the high watermark of the requests to a given target is an important part of protocol state for the actor, I would just store it in the asking actor's state (e.g. in Scala a Map[ActorRef[Request], Int]). The adapted response contains the target and the id it's in response to (you define how this is incorporated when performing the ask); when receiving the adapted response, the first thing is comparing the id in the response to the high watermark for the target.
In Scala, for example:
QUESTION
I have a question that is more of a design one rather than a coding one.
I'm currently using Akka (we're transitioning from Classic to Typed) to implement a Raft cluster, using the Java version. Our assignment requires the cluster - like the paper implementation - to operate on harsh network conditions, and as such I would like to implement Akka-side a way to systematically delay messages. Timings and selectivity do not matter - e.g., assume we want to delay ALL messages going through the system by 200ms.u
My idea was to use Routers - https://doc.akka.io/docs/akka/current/typed/routers.html - but I would like to know what's the best approach to write something that is both scalable and does not add unpredictable bugs (like using Thread.sleep() does, which delays message queue handling)
EDIT: The raft cluster is hosted on a single machine, so transmission is basically instantaneous now, and any interaction is handled by Akka itself. No network stack is ever involed.
...ANSWER
Answered 2022-Jan-15 at 17:23Based on understanding your question, since you are looking at network level, you should be taking a look at chaos testing tools.
You can check for bunch of these tools here: https://github.com/dastergon/awesome-chaos-engineering
QUESTION
I have a problem in Nodejs but I dont't know why this error happening
in config folder I have a file with name generateToken.js and this file have this code:
ANSWER
Answered 2022-Jan-15 at 13:07First of all, generateActiveToken is a async function so put an await before function call.
The proper way to export a module is like below:
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install raft
Support
Reuse Trending Solutions
Find, review, and download reusable Libraries, Code Snippets, Cloud APIs from over 650 million Knowledge Items
Find more librariesStay Updated
Subscribe to our newsletter for trending solutions and developer bootcamps
Share this Page
