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Apache ParquetNo Apache Parquet videos yet. You could help us improve this page by suggesting one.
Apache Parquet might be a bit more popular than Drupal. We know about 31 links to it since March 2021 and only 28 links to Drupal. 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.
I would be interested in some good migration tools, paid ones are also ok. I found a post about this on drupal.org, but it didn't seem like an easy process. It is a multilanguage site with many content types, and a totally custom theme. Source: over 3 years ago
You got already good advice, but wanted to point the guide of drupal.org where you can see some tools listed with instructions and channels https://www.drupal.org/community/contributor-guide/reference-information/talk/tools. Source: almost 4 years ago
There is a service call GitPod that provides a temporary container Drupal environment. If you are familiar with what is going on around the future of how Drupal modules will eventually be offered up, you will likely have seen the "Project Browser" module as a contrib demo of the approach. It is used for people to give feedback to the developers. So they set up the typical 'SimplyTestMe' but also a GitPod... Source: almost 4 years ago
For reviews, it depends entirely on what you mean by "review". I believe core has a simple comment module, although it may have been deprecated for D9? There are likely many review-style modules on drupal.org that might work, or if you just want to link out to third-party reviews then it could just be a repeating-value link field on the Product content type. Source: almost 4 years ago
They should also use standards tools like Github. The drupal.org platform was certainly impressive 10 years ago, today it's a pain to use it. They ducktape it with gitlab, but really it sucks to have to read documentation to simply do a pull request. Source: almost 4 years ago
Apache Iceberg fits these requirements well. Iceberg stores data as immutable Apache Parquet files and adds them through atomic commits, so readers always see a consistent snapshot. A separate metadata layer prunes files by their statistics before the data itself is ever read, and those statistics can be extended to match an observability filtering profile. - Source: dev.to / 26 days ago
Depends on the domain. There's a bunch of sciences using large datasets served up efficiently using static file formats, e.g., https://zarr.dev/ and https://parquet.apache.org/. - Source: Hacker News / about 2 months ago
The data files themselves are still standard Parquet or ORC. The table format adds a metadata layer on top that gives those files the properties of a database table. - Source: dev.to / 3 months ago
The dataset is huge - in parquet conversion - it is total 9gb. And in raw PNG image nested folders - it is 67 gigabytes. Huge... - Source: dev.to / 4 months ago
The solution is to standardize on columnar formats like Apache Parquet. Parquet stores data in columns, not rows, which immediately enables column pruning. If a query is SELECT avg(price) FROM sales, the engine reads only the price column and ignores all others. This can reduce storage footprints by up to 75% compared to raw formats and is a cornerstone of modern analytics performance. - Source: dev.to / 9 months ago
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