proposal
redpanda
Our great sponsors
proposal | redpanda | |
---|---|---|
46 | 69 | |
3,276 | 8,647 | |
0.5% | 3.4% | |
4.4 | 10.0 | |
14 days ago | 4 days ago | |
Go | C++ | |
BSD 3-clause "New" or "Revised" License | - |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
proposal
-
Does Go Have Subtyping?
The conclusion is pretty weird to me.
Go does rely on monomorphization for generics, just like C++ and Rust. The only difference is that this is an implementation detail, so Go can group multiple monomorphizations without worrying about anything else [1]. This form of hybrid monomorphization is being increasingly common, GHC does that and Rust is also trying to do so [2], so nothing special for Go here.
On the other hand, explaining variance as a lifted polymorphism is---while not incorrect per se---also weird in part because a lack of variance is at worst just an annoyance. You can always make an adopter to unify heterogeneous types. Rust calls it `Box`, Go happens to call it an interface type instead. Both languages even do not allow heterogeneous concrete (or runtime) types in a single slice! So variance has no use in both languages because no concrete types are eligible for variance anyway.
I think the conclusion got weird because the term "subtyping" is being misused. Subtyping, in the broadest sense, is just a non-trivial type relation. Many languages thus have a multiple notion of subtyping, often (almost) identical to each other but sometimes not. Go in particular has a lot of them, and even some relation like "T implements U" is a straightforward record subtyping. It is no surprise that the non-uniform value representation has the largest influence, and only monomorphization schemes and hetero-to-homogeneous adapters vary in this particular group.
[1] https://github.com/golang/proposal/blob/master/design/generi...
[2] https://rust-lang.github.io/compiler-team/working-groups/pol...
-
Backward Compatibility, Go 1.21, and Go 2
> I wonder: why not go further and say "there will never be a Go 2" in order to eliminate ambiguity about this?
They did, five years ago. Albeit with an “if”.
https://github.com/golang/proposal/blob/d661ed19a203000b7c54...
> If the above process works as planned, then in an important sense there never will be a Go 2. Or, to put it a different way, we will slowly transition to new language and library features. We could at any point during the transition decide that now we are Go 2, which might be good marketing. Or we could just skip it (there has never been a C 2.0, why have a Go 2.0?).
> Popular languages like C, C++, and Java never have a version 2. In effect, they are always at version 1.N, although they use different names for that state. I believe that we should emulate them. In truth, a Go 2 in the full sense of the word, in the sense of an incompatible new version of the language or core libraries, would not be a good option for our users. A real Go 2 would, perhaps unsurprisingly, be harmful.
-
Why Turborepo is migrating from Go to Rust – Vercel
Go Team wanted generics since the start. It was always a problem implementing them without severely hurting compile time and creating compilation bloat. Rust chose to ignore this problem, by relying on LLVM backend for optimizations and dead code elimination.
-
Major standard library changes in Go 1.20
As far as I can tell, the consensus for generics was "it will happen, but we really want to get this right, and it's taking time."
I know some people did the knee-jerk attacks like "Go sucks, it should have had generics long ago" or "Go is fine, it doesn't need generics". I don't think we ever needed to take those attitudes seriously.
> Will error handling be overhauled or not?
Error handling is a thorny issue. It's the biggest complaint people have about Go, but I don't think that exceptions are obviously better, and the discriminated unions that power errors in Rust and some other languages are conspicuously absent from Go. So you end up with a bunch of different proposals for Go error handling that are either too radical or little more than syntactic sugar. The syntactic sugar proposals leave much to be desired. It looks like people are slowly grinding through these proposals until one is found with the right balance to it.
I honestly don't know what kind of changes to error handling would appear in Go 2 if/when it lands, and I think the only reasonable answer right now is "wait and find out". You can see a more reasonable proposal here:
https://github.com/golang/proposal/blob/master/design/go2dra...
Characterizing it as a "lack of vision" does not seem fair here--I started using Rust back in the days when boxed pointers had ~ on them, and it seemed like it took Rust a lot of iterations to get to the current design. Which is fine. I am also never quite sure what is going to get added to future versions of C#.
I am also not quite sure why Go gets so much hate on Hacker News--as far as I can tell, people have more or less given up on criticizing Java and C# (it's not like they've ossified), and C++ is enough of a dumpster fire that it seems gauche to point it out.
-
What's the status of the various "Go 2" proposals?
As it says on that page - those were not proposals. They were draft ideas to get feedback on. You can see the list of proposals in this repository: https://github.com/golang/proposal
-
An alternative memory limiter for Go based on GC tuning and request throttling
Approximately a year ago we faced with a necessity of limiting Go runtime memory consumption and started work on our own memory limiter. At the same time, Michael Knyszek published his well-known proposal. Now we have our own implementation quite similar to what has been released in 1.18, but there are two key differences:
- Shaving 40% off Google’s B-Tree Implementation with Go Generics
-
I did something evil
They actually didn't.
-
On a potential "Partial Monomorphization"
Also take a look at https://github.com/golang/proposal/blob/master/design/generics-implementation-gcshape.md. This is a hybrid approach (like the one you're talking about) the Go compiler takes for its generics implementation. It uses GC allocation size classes ("shapes") to figure out how to group types that need to be monomorphized.
redpanda
-
Choosing Between a Streaming Database and a Stream Processing Framework in Python
Stream-processing platforms such as Apache Kafka, Apache Pulsar, or Redpanda are specifically engineered to foster event-driven communication in a distributed system and they can be a great choice for developing loosely coupled applications. Stream processing platforms analyze data in motion, offering near-zero latency advantages. For example, consider an alert system for monitoring factory equipment. If a machine's temperature exceeds a certain threshold, a streaming platform can instantly trigger an alert and engineers do timely maintenance.
-
The best WebAssembly runtime may be no runtime at all
Yeah it’s just the stack switching itself that is a handful of cycles, but there is not much more overhead for the full VM switch if you structure your embedding the right way. Code the code is source available if you want to peek at it!
https://github.com/redpanda-data/redpanda/blob/dev/src/v/was...
-
redpanda VS quix-streams - a user suggested alternative
2 projects | 7 Dec 2023
-
Kafka Is Dead, Long Live Kafka
I've heard good things about Red Panda[1], but I haven't tried it.
that's a littlebit of a stretch. when you say "no shortage" - outside of redpanda what product exists that actually compete in all deployment modes?
it's a misconception that redpanda is simply a better kafka. the way to think about it is that is a new storage engine, from scratch, that speaks the kafka protocol. similar to all of the pgsql companies in a different space, i.e.: big table pgsql support is not a better postgres, fundamentally different tech. you can read the src and design here: https://github.com/redpanda-data/redpanda. or an electric car is not the same as a combustion engine, but only similar in that they are cars that take you from point a to point b.
-
Real-time Data Processing Pipeline With MongoDB, Kafka, Debezium And RisingWave
Redpanda with the MongoDB Debezium Connector installed. We use Redpanda as a Kafka broker.
-
Flink CDC / alternatives
And Kafka + Kafka Connect has https://www.confluent.io/ https://aiven.io/ https://upstash.com/ (and not quite Kafka, but protocol-compatible, https://redpanda.com/)
-
Kafka alternatives
Redpanda
-
Real-time data analytics with Apache Superset, Redpanda, and RisingWave
In today's fast-paced data-driven world, organizations must analyze data in real-time to make timely and informed decisions. Real-time data analytics enables businesses to gain valuable insights, respond to real-time events, and stay ahead of the competition. Also, the analytics engine must be capable of running analytical queries and returning results in real-time. In this article, we will explore how you can build a real-time data analytics solution using the open-source tools Redpanda a distributed streaming platform, Apache Superset, a data visualization, and a business intelligence platform, combined with RisingWave a streaming database.
What are some alternatives?
Apache Kafka - Mirror of Apache Kafka
Apache Pulsar - Apache Pulsar - distributed pub-sub messaging system
NATS - High-Performance server for NATS.io, the cloud and edge native messaging system.
jetstream - JetStream Utilities
RabbitMQ - Open source RabbitMQ: core server and tier 1 (built-in) plugins
kafkacat - Generic command line non-JVM Apache Kafka producer and consumer [Moved to: https://github.com/edenhill/kcat]
Seastar - High performance server-side application framework
Jocko - Kafka implemented in Golang with built-in coordination (No ZK dep, single binary install, Cloud Native)
Gotify - A simple server for sending and receiving messages in real-time per WebSocket. (Includes a sleek web-ui)
prometheus - The Prometheus monitoring system and time series database.
java-pubsublite-kafka
VictoriaMetrics - VictoriaMetrics: fast, cost-effective monitoring solution and time series database