+1 Hyukjin Kwon <gurwls...@apache.org> 于2024年8月12日周一 16:18写道：
> +1 > > On Tue, Aug 13, 2024 at 7:04 AM Nicholas Chammas < > nicholas.cham...@gmail.com> wrote: > >> And just for the record, the stats that I screenshotted >> <https://lists.apache.org/api/email.lua?attachment=true&id=jd1hyq6c9v1qg0ym5qlct8lgcxk9yd6z&file=7a28ae0d6eb4c25e047ff90601a941f7acfc3214f837604b545b4f926b8eb628> >> in >> that thread I linked to showed the following page views for each >> sub-section under `docs/latest/api/`: >> >> - python: 758K >> - java: 66K >> - sql: 39K >> - scala: 35K >> - r: <1K >> >> I don’t recall over what time period those stats were collected for, and >> there are certainly some factors of how the stats are gathered and how the >> various language API docs are accessed that impact those numbers. So it’s >> by no means a solid, objective measure. But I thought it was an interesting >> signal nonetheless. >> >> >> On Aug 12, 2024, at 5:50 PM, Nicholas Chammas <nicholas.cham...@gmail.com> >> wrote: >> >> Not an R user myself, but +1. >> >> I first wondered about the future of SparkR after noticing >> <https://lists.apache.org/thread/jd1hyq6c9v1qg0ym5qlct8lgcxk9yd6z> how >> low the visit stats were for the R API docs as compared to Python and >> Scala. (I can’t seem to find those visit stats >> <https://analytics.apache.org/index.php?module=CoreHome&action=index&date=today&period=month&idSite=40#?period=month&date=2024-07-02&idSite=40&category=General_Actions&subcategory=General_Pages> >> for >> the API docs anymore.) >> >> >> On Aug 12, 2024, at 11:47 AM, Shivaram Venkataraman < >> shivaram.venkatara...@gmail.com> wrote: >> >> Hi >> >> About ten years ago, I created the original SparkR package as part of my >> research at UC Berkeley [SPARK-5654 >> <https://issues.apache.org/jira/browse/SPARK-5654>]. After my PhD I >> started as a professor at UW-Madison and my contributions to SparkR have >> been in the background given my availability. I continue to be involved in >> the community and teach a popular course at UW-Madison which uses Apache >> Spark for programming assignments. >> >> As the original contributor and author of a research paper on SparkR, I >> also continue to get private emails from users. A common question I get is >> whether one should use SparkR in Apache Spark or the sparklyr package >> (built on top of Apache Spark). You can also see this in StackOverflow >> questions and other blog posts online: >> https://www.google.com/search?q=sparkr+vs+sparklyr . While, I have >> encouraged users to choose the SparkR package as it is maintained by the >> Apache project, the more I looked into sparklyr, the more I was convinced >> that it is a better choice for R users that want to leverage the power of >> Spark: >> >> (1) sparklyr is developed by a community of developers who understand the >> R programming language deeply, and as a result is more idiomatic. In >> hindsight, sparklyr’s more idiomatic approach would have been a better >> choice than the Scala-like API we have in SparkR. >> >> (2) Contributions to SparkR have decreased slowly. Over the last two >> years, there have been 65 commits on the Spark R codebase (compared to >> ~2200 on the Spark Python code base). In contrast Sparklyr has over 300 >> commits in the same period.. >> >> (3) Previously, using and deploying sparklyr had been cumbersome as it >> needed careful alignment of versions between Apache Spark and sparklyr. >> However, the sparklyr community has implemented a new Spark Connect based >> architecture which eliminates this issue. >> >> (4) The sparklyr community has maintained their package on CRAN – it >> takes some effort to do this as the CRAN release process requires passing a >> number of tests. While SparkR was on CRAN initially, we could not maintain >> that given our release process and cadence. This makes sparklyr much more >> accessible to the R community. >> >> So it is with a bittersweet feeling that I’m writing this email to >> propose that we deprecate SparkR, and recommend sparklyr as the R language >> binding for Spark. This will reduce complexity of our own codebase, and >> more importantly reduce confusion for users. As the sparklyr package is >> distributed using the same permissive license as Apache Spark, there should >> be no downside for existing SparkR users in adopting it. >> >> My proposal is to mark SparkR as deprecated in the upcoming Spark 4 >> release, and remove it from Apache Spark with the following major release, >> Spark 5. >> >> I’m looking forward to hearing your thoughts and feedback on this >> proposal and I’m happy to create the SPIP ticket for a vote on this >> proposal using this email thread as the justification. >> >> Thanks >> Shivaram >> >> >> >>
