I don't think the crux of the problem is about users who download the source -- Spark's source distribution is clearly marked as something that needs to be built and they can run `mvn -DskipTests -Psparkr package` based on instructions in the Spark docs.
The crux of the problem is that with a source or binary R package, the client side the SparkR code needs the Spark JARs to be available. So we can't just connect to a remote Spark cluster using just the R scripts as we need the Scala classes around to create a Spark context etc. But this is a use case that I've heard from a lot of users -- my take is that this should be a separate package / layer on top of SparkR. Dan Putler (cc'd) had a proposal on a client package for this and maybe able to add more. Thanks Shivaram On Thu, Sep 24, 2015 at 11:36 AM, Hossein <fal...@gmail.com> wrote: > Requiring users to download entire Spark distribution to connect to a remote > cluster (which is already running Spark) seems an over kill. Even for most > spark users who download Spark source, it is very unintuitive that they need > to run a script named "install-dev.sh" before they can run SparkR. > > --Hossein > > On Wed, Sep 23, 2015 at 7:28 PM, Sun, Rui <rui....@intel.com> wrote: >> >> SparkR package is not a standalone R package, as it is actually R API of >> Spark and needs to co-operate with a matching version of Spark, so exposing >> it in CRAN does not ease use of R users as they need to download matching >> Spark distribution, unless we expose a bundled SparkR package to CRAN >> (packageing with Spark), is this desirable? Actually, for normal users who >> are not developers, they are not required to download Spark source, build >> and install SparkR package. They just need to download a Spark distribution, >> and then use SparkR. >> >> >> >> For using SparkR in Rstudio, there is a documentation at >> https://github.com/apache/spark/tree/master/R >> >> >> >> >> >> >> >> From: Hossein [mailto:fal...@gmail.com] >> Sent: Thursday, September 24, 2015 1:42 AM >> To: shiva...@eecs.berkeley.edu >> Cc: Sun, Rui; dev@spark.apache.org >> Subject: Re: SparkR package path >> >> >> >> Yes, I think exposing SparkR in CRAN can significantly expand the reach of >> both SparkR and Spark itself to a larger community of data scientists (and >> statisticians). >> >> >> >> I have been getting questions on how to use SparkR in RStudio. Most of >> these folks have a Spark Cluster and wish to talk to it from RStudio. While >> that is a bigger task, for now, first step could be not requiring them to >> download Spark source and run a script that is named install-dev.sh. I filed >> SPARK-10776 to track this. >> >> >> >> >> --Hossein >> >> >> >> On Tue, Sep 22, 2015 at 7:21 PM, Shivaram Venkataraman >> <shiva...@eecs.berkeley.edu> wrote: >> >> As Rui says it would be good to understand the use case we want to >> support (supporting CRAN installs could be one for example). I don't >> think it should be very hard to do as the RBackend itself doesn't use >> the R source files. The RRDD does use it and the value comes from >> >> https://github.com/apache/spark/blob/master/core/src/main/scala/org/apache/spark/api/r/RUtils.scala#L29 >> AFAIK -- So we could introduce a new config flag that can be used for >> this new mode. >> >> Thanks >> Shivaram >> >> >> On Mon, Sep 21, 2015 at 8:15 PM, Sun, Rui <rui....@intel.com> wrote: >> > Hossein, >> > >> > >> > >> > Any strong reason to download and install SparkR source package >> > separately >> > from the Spark distribution? >> > >> > An R user can simply download the spark distribution, which contains >> > SparkR >> > source and binary package, and directly use sparkR. No need to install >> > SparkR package at all. >> > >> > >> > >> > From: Hossein [mailto:fal...@gmail.com] >> > Sent: Tuesday, September 22, 2015 9:19 AM >> > To: dev@spark.apache.org >> > Subject: SparkR package path >> > >> > >> > >> > Hi dev list, >> > >> > >> > >> > SparkR backend assumes SparkR source files are located under >> > "SPARK_HOME/R/lib/." This directory is created by running >> > R/install-dev.sh. >> > This setting makes sense for Spark developers, but if an R user >> > downloads >> > and installs SparkR source package, the source files are going to be in >> > placed different locations. >> > >> > >> > >> > In the R runtime it is easy to find location of package files using >> > path.package("SparkR"). But we need to make some changes to R backend >> > and/or >> > spark-submit so that, JVM process learns the location of worker.R and >> > daemon.R and shell.R from the R runtime. >> > >> > >> > >> > Do you think this change is feasible? >> > >> > >> > >> > Thanks, >> > >> > --Hossein >> >> > > --------------------------------------------------------------------- To unsubscribe, e-mail: dev-unsubscr...@spark.apache.org For additional commands, e-mail: dev-h...@spark.apache.org
