Protocol Buffers VS Apache Pig

Flyxc messages are based on protocol buffers ("protobuf" if you want to sound cool). They are not human readable but much more compact and faster for computers to work with:. - Source: dev.to / 9 days ago

> Aren’t a standard You mean like an IETF standard? That is true, although the specification is quite simple to implement. It is certainly a de-facto standard, even if it hasn’t been standardized by the IETF or IEEE or ANSI or ECMA. > inherently limits anything built on top of them to not be a standard either I’m not sure that strictly follows. https://datatracker.ietf.org/doc/html/rfc9232 for example directly... - Source: Hacker News / 4 months ago

The MQTT protocol is widely used in IoT applications because of its simplicity and ability to connect different data sources to applications using a publish/subscribe model. While many MQTT brokers support persistent sessions and can store message history as long as an MQTT client is not available, there may be cases where data needs to be stored for a longer period. In such cases, it is recommended to use a time... - Source: dev.to / 5 months ago

Generate a mock from an API definition Skyramp simplifies the process of mocking by allowing you to generate mocks directly from your API definitions, such as OpenAPI or Protobuf. This means you can easily create realistic mocks that mimic the behavior of your actual microservices. With the Skyramp CLI, it's as easy as running skyramp mocker generate ... With the relevant inputs. See the Skyramp Docs for which... - Source: dev.to / 5 months ago

Tsavo also touched upon how consistency is also crucial at the SDK level and the data layer. A fun fact about our company is that a majority of our client-side SDKs are generated off of protobuf specs or HTTP open API specs. This means that when a new endpoint with a certain capability is released, we can quickly have it available in Kotlin, TypeScript, Dart, Rust, Go, and some other languages. This rapid... - Source: dev.to / 6 months ago

Pig, a platform/programming language for authoring parallelizable jobs. - Source: dev.to / over 1 year ago

In the early days of the Big Data era when K8s hasn't even been born yet, the common open source go-to solution was the Hadoop stack. We have written several old-fashioned Map-Reduce jobs, scripts using Pig until we came across Spark. Since then Spark has became one of the most popular data processing engines. It is very easy to start using Lighter on YARN deployments. Just run a docker with proper configuration... - Source: dev.to / over 2 years ago