Based on our record, Observable seems to be a lot more popular than Google Cloud Dataproc. While we know about 287 links to Observable, we've tracked only 3 mentions of Google Cloud Dataproc. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Curious to see whether more recent dithering approaches would produce better results. They don't even have to be more resource hungry than the classic Bayer or Floyd-Steinberg dithers! Interleaved Gradient Noise[0][1][2] comes to mind as an alternative to Bayer, and it can even be approximated quite well with just 8-bit operations! Basically, use the following function to determine your threshold based on pixel... - Source: Hacker News / 6 days ago
Could this be implemented in Rust? Does that project (sqlite-loadable-rs) support WASM? https://observablehq.com/@asg017/introducing-sqlite-loadable-rs. - Source: Hacker News / 24 days ago
Have you tried out a tangled-tree visualization? [1] I've found it to be super useful when visualizing these sorts of relationships in a compact way. [1] https://observablehq.com/@nitaku/tangled-tree-visualization-ii. - Source: Hacker News / 24 days ago
Maybe I'm easy to impress, but I always stop and play around with the nested tree example when I come across Sortable. It works so flawlessly, and feels very tuned to mobile dnd. It even works to arrange (and reflow) inline spans in a paragraph! I have yet to come across this functionality in a text editor.. [0]: https://observablehq.com/@dleeftink/sortable-playground. - Source: Hacker News / about 1 month ago
Arrow JS is just ArrayBuffers underneath. You do want to amortize some operations to avoid unnecessary conversions. I.e. Arrow JS stores strings as UTF-8, but native JS strings are UTF-16 I believe. Arrow is especially powerful across the WASM <--> JS boundary! In fact, I wrote a library to interpret Arrow from Wasm memory into JS without any copies [0]. (Motivating blog post [1]) [0]:... - Source: Hacker News / about 1 month ago
I have also a spark cluster created with google cloud dataproc. Source: about 1 year ago
Specifically, we heavily rely on managed services from our cloud provider, Google Cloud Platform (GCP), for hosting our data in managed databases like BigTable and Spanner. For data transformations, we initially heavily relied on DataProc - a managed service from Google to manage a Spark cluster. - Source: dev.to / about 2 years ago
With that, the best way to maximize processing and minimize time is to use Dataflow or Dataproc depending on your needs. These systems are highly parallel and clustered, which allows for much larger processing pipelines that execute quickly. Source: over 2 years ago
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