+1 Are the sparklyr folks on this list?
Twitter: https://twitter.com/holdenkarau Books (Learning Spark, High Performance Spark, etc.): https://amzn.to/2MaRAG9 <https://amzn.to/2MaRAG9> YouTube Live Streams: https://www.youtube.com/user/holdenkarau Pronouns: she/her On Mon, Aug 12, 2024 at 5:22 PM Xiao Li <gatorsm...@gmail.com> wrote: > +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 >>> >>> >>> >>>
