As for the actual process of building the contract, what works well for me is using API Blueprint-style Markdown in a compatible tool like Apiary, which renders your content into Swagger-like documentation as you type. This way, I and others can mutually "live-scribe" the API contract as we discuss, and seeing it on-screen helps to get people on the same page (and sometimes highlight potential issues that would... Source: about 1 year ago

I’m not sure a JS library qualifies as a PL. Or automation software (SoftStack). Or an API description language. Or a build system. Source: over 1 year ago

Create a Proper API Documentation The following open-source projects can help you with creating documentation for your APIs: APIBluePrint Swagger. - Source: dev.to / over 1 year ago

A common complaint about OpenAPI is that it’s difficult to learn and to read. Consequently, over the years we’ve seen many alternatives to OpenAPI, such as RAML, WADL, API Blueprint, and others. The problem with many of these alternatives is that in most cases they aren’t really more readable or easier to learn. Simpler description languages also tend to support less capabilities for documenting API features.... - Source: dev.to / almost 2 years ago

For the context of this post, only the first task is essential. In it, the team works together to define the API contract. They discuss data format, whether the API will be Rest or RPC, authentication, data compression, and other vital issues. The delivery of this task is the documentation, preferably in a standard like OpenAPI or API Blueprint (my preferred format). - Source: dev.to / almost 2 years ago

Restate is built as a sharded replicated state machine similar to how TiKV (https://tikv.org/), Kudu (https://kudu.apache.org/kudu.pdf) or CockroachDB (https://github.com/cockroachdb/cockroach) since it makes it possible to tune the system more easily for different deployment scenarios (on-prem, cloud, cost-effective blob storage). Moreover, it allows for some other cool things like seamlessly moving from one log... - Source: Hacker News / 16 days ago

I’ve recently started my journey with Apache Flink. As I learn certain concepts, I’d like to share them. One such "learning" is the expansion of array type columns in Flink SQL. Having used ksqlDB in a previous life, I was looking for functionality similar to the EXPLODE function to "flatten" a collection type column into a row per element of the collection. Because Flink SQL is ANSI compliant, it’s no surprise... - Source: dev.to / about 1 month ago

You should let the Apache Flink team know, they mention exactly-once processing on their home page (under "correctness guarantees") and in their list of features. [0] https://flink.apache.org/ [1] https://flink.apache.org/what-is-flink/flink-applications/#building-blocks-for-streaming-applications. - Source: Hacker News / about 2 months ago

Data scientists often prefer Python for its simplicity and powerful libraries like Pandas or SciPy. However, many real-time data processing tools are Java-based. Take the example of Kafka, Flink, or Spark streaming. While these tools have their Python API/wrapper libraries, they introduce increased latency, and data scientists need to manage dependencies for both Python and JVM environments. For example,... - Source: dev.to / 3 months ago

Other stream processing engines (such as Flink and Spark Streaming) provide SQL interfaces too, but the key difference is a streaming database has its storage. Stream processing engines require a dedicated database to store input and output data. On the other hand, streaming databases utilize cloud-native storage to maintain materialized views and states, allowing data replication and independent storage scaling. - Source: dev.to / 5 months ago