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new 908efa3 [ZEPPELIN-4529]. Update R interpreter document
908efa3 is described below
commit 908efa3fc71c23ae3ec94f868fa835f208ca05d3
Author: Jeff Zhang <zjf...@apache.org>
AuthorDate: Thu Jan 16 16:10:56 2020 +0800
[ZEPPELIN-4529]. Update R interpreter document
### What is this PR for?
This PR update the R interpreter document. In this document, I highlight
how to use `%r.r`, `%r.ir` and how to create shiny app in R Interpreter.
### What type of PR is it?
[ Documentation ]
### Todos
* [ ] - Task
### What is the Jira issue?
* https://issues.apache.org/jira/browse/ZEPPELIN-4529
### How should this be tested?
* No test needed
### Screenshots (if appropriate)
### Questions:
* Does the licenses files need update? No
* Is there breaking changes for older versions? No
* Does this needs documentation? No
Author: Jeff Zhang <zjf...@apache.org>
Closes #3629 from zjffdu/ZEPPELIN-4529 and squashes the following commits:
ce5767712 [Jeff Zhang] [ZEPPELIN-4529]. Update R interpreter document
---
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15 files changed, 165 insertions(+), 46 deletions(-)
diff --git a/docs/_includes/themes/zeppelin/_navigation.html
b/docs/_includes/themes/zeppelin/_navigation.html
index a1796e7..f19dc30 100644
--- a/docs/_includes/themes/zeppelin/_navigation.html
+++ b/docs/_includes/themes/zeppelin/_navigation.html
@@ -127,6 +127,7 @@
<li><a
href="{{BASE_PATH}}/interpreter/spark.html">Spark</a></li>
<li><a href="{{BASE_PATH}}/interpreter/jdbc.html">JDBC</a></li>
<li><a
href="{{BASE_PATH}}/interpreter/python.html">Python</a></li>
+ <li><a href="{{BASE_PATH}}/interpreter/r.html">R</a></li>
<li role="separator" class="divider"></li>
<li><a
href="{{BASE_PATH}}/interpreter/alluxio.html">Alluxio</a></li>
<li><a href="{{BASE_PATH}}/interpreter/beam.html">Beam</a></li>
@@ -151,7 +152,6 @@
<li><a
href="{{BASE_PATH}}/interpreter/neo4j.html">Neo4j</a></li>
<li><a href="{{BASE_PATH}}/interpreter/pig.html">Pig</a></li>
<li><a
href="{{BASE_PATH}}/interpreter/postgresql.html">Postgresql, HAWQ</a></li>
- <li><a href="{{BASE_PATH}}/interpreter/r.html">R</a></li>
<li><a
href="{{BASE_PATH}}/interpreter/scalding.html">Scalding</a></li>
<li><a href="{{BASE_PATH}}/interpreter/scio.html">Scio</a></li>
<li><a
href="{{BASE_PATH}}/interpreter/shell.html">Shell</a></li>
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diff --git a/docs/interpreter/r.md b/docs/interpreter/r.md
index 966dc1e..15bbe2c 100644
--- a/docs/interpreter/r.md
+++ b/docs/interpreter/r.md
@@ -74,79 +74,198 @@ We recommend you to also install the following optional R
libraries for happy da
+ sqldf
+ wordcloud
-## Configuration
-
-To run Zeppelin with the R Interpreter, the `SPARK_HOME` environment variable
must be set. The best way to do this is by editing `conf/zeppelin-env.sh`.
-If it is not set, the R Interpreter will not be able to interface with Spark.
-
-You should also copy `conf/zeppelin-site.xml.template` to
`conf/zeppelin-site.xml`. That will ensure that Zeppelin sees the R Interpreter
the first time it starts up.
-
-## Using the R Interpreter
+## Supported Interpreters
+
+Zeppelin supports R language in 3 interpreters
+
+<table class="table-configuration">
+ <tr>
+ <th>Name</th>
+ <th>Class</th>
+ <th>Description</th>
+ </tr>
+ <tr>
+ <td>%r.r</td>
+ <td>RInterpreter</td>
+ <td>Vanilla r interpreter, with least dependencies, only R environment
installed is required.
+ It is always recommended to use the fully qualified interpreter name
<code>%r.r</code>code>, because <code>%r</code> is ambiguous,
+ it could mean both <code>%spark.r</code> and <code>%r.r</code></td>
+ </tr>
+ <tr>
+ <td>%r.ir</td>
+ <td>IRInterpreter</td>
+ <td>Provide more fancy R runtime via
[IRKernel](https://github.com/IRkernel/IRkernel), almost the same experience
like using R in Jupyter. It requires more things, but is the recommended
interpreter for using R in Zeppelin.</td>
+ </tr>
+ <tr>
+ <td>%r.shiny</td>
+ <td>ShinyInterpreter</td>
+ <td>Run Shiny app in Zeppelin</td>
+ </tr>
+</table>
+
+If you want to use R with Spark, it is almost the same via `%spark.r`,
`%spark.ir` & `%spark.shiny` . You can refer Spark Interpreter docs for more
details.
-By default, the R Interpreter appears as two Zeppelin Interpreters, `%r` and
`%knitr`.
-
-`%r` will behave like an ordinary REPL. You can execute commands as in the
CLI.
+## Configuration
-<img class="img-responsive"
src="{{BASE_PATH}}/assets/themes/zeppelin/img/docs-img/repl2plus2.png"
width="700px"/>
+<table class="table-configuration">
+ <tr>
+ <th>Property</th>
+ <th>Default</th>
+ <th>Description</th>
+ </tr>
+ <tr>
+ <td>zeppelin.R.cmd</td>
+ <td>R</td>
+ <td>Path of the installed R binary. You should set this property
explicitly if R is not in your <code>$PATH</code>(example: /usr/bin/R).
+ </td>
+ </tr>
+ <tr>
+ <td>zeppelin.R.knitr</td>
+ <td>true</td>
+ <td>Whether to use knitr or not. It is recommended to install
[knitr](https://yihui.org/knitr/)</td>
+ </tr>
+ <tr>
+ <td>zeppelin.R.image.width</td>
+ <td>100%</td>
+ <td>Image width of R plotting</td>
+ </tr>
+ <tr>
+ <td>zeppelin.R.shiny.iframe_width</td>
+ <td>100%</td>
+ <td>IFrame width of Shiny App</td>
+ </tr>
+ <tr>
+ <td>zeppelin.R.shiny.iframe_height</td>
+ <td>500px</td>
+ <td>IFrame height of Shiny App</td>
+ </tr>
+</table>
+
+## Using the R Interpreter(`%r.r` & `%r.ir`)
+
+By default, the R Interpreter appears as two Zeppelin Interpreters, `%r.r` and
`%r.ir`.
+
+`%r.r` behaves like an ordinary REPL and use SparkR to communicate between R
process and JVM process.
+`%r.ir` use IRKernel underneath, it behaves like using IRKernel in Jupyter
notebook.
+
+R basic expression
+
+<img class="img-responsive"
src="{{BASE_PATH}}/assets/themes/zeppelin/img/docs-img/r_basic.png"
width="800px"/>
R base plotting is fully supported
-<img class="img-responsive"
src="{{BASE_PATH}}/assets/themes/zeppelin/img/docs-img/replhist.png"
width="550px"/>
-
-If you return a data.frame, Zeppelin will attempt to display it using
Zeppelin's built-in visualizations.
+<img class="img-responsive"
src="{{BASE_PATH}}/assets/themes/zeppelin/img/docs-img/r_plotting.png"
width="800px"/>
-<img class="img-responsive"
src="{{BASE_PATH}}/assets/themes/zeppelin/img/docs-img/replhead.png"
width="550px"/>
+Besides R base plotting, you can use other visualization library, e.g.
`ggplot` and `googlevis`
-`%knitr` interfaces directly against `knitr`, with chunk options on the first
line:
+<img class="img-responsive"
src="{{BASE_PATH}}/assets/themes/zeppelin/img/docs-img/r_ggplot.png"
width="800px"/>
-<img class="img-responsive"
src="{{BASE_PATH}}/assets/themes/zeppelin/img/docs-img/knitgeo.png"
width="550px"/>
+<img class="img-responsive"
src="{{BASE_PATH}}/assets/themes/zeppelin/img/docs-img/r_googlevis.png"
width="800px"/>
-<img class="img-responsive"
src="{{BASE_PATH}}/assets/themes/zeppelin/img/docs-img/knitstock.png"
width="550px"/>
-<img class="img-responsive"
src="{{BASE_PATH}}/assets/themes/zeppelin/img/docs-img/knitmotion.png"
width="550px"/>
+## Make Shiny App in Zeppelin
-The two interpreters share the same environment. If you define a variable
from `%r`, it will be within-scope if you then make a call using `knitr`.
+[Shiny](https://shiny.rstudio.com/tutorial/) is an R package that makes it
easy to build interactive web applications (apps) straight from R.
+For developing one Shiny App in Zeppelin, you need to at least 3 paragraphs
(server paragraph, ui paragraph and run type paragraph)
-## Using SparkR & Moving Between Languages
+* Server type R shiny paragraph
-If `SPARK_HOME` is set, the `SparkR` package will be loaded automatically:
+```r
-<img class="img-responsive"
src="{{BASE_PATH}}/assets/themes/zeppelin/img/docs-img/sparkrfaithful.png"
width="550px"/>
+%r.shiny(type=server)
-The Spark Context and SQL Context are created and injected into the local
environment automatically as `sc` and `sql`.
+# Define server logic to summarize and view selected dataset ----
+server <- function(input, output) {
-The same context are shared with the `%spark`, `%sql` and `%pyspark`
interpreters:
+ # Return the requested dataset ----
+ datasetInput <- reactive({
+ switch(input$dataset,
+ "rock" = rock,
+ "pressure" = pressure,
+ "cars" = cars)
+ })
-<img class="img-responsive"
src="{{BASE_PATH}}/assets/themes/zeppelin/img/docs-img/backtoscala.png"
width="700px"/>
+ # Generate a summary of the dataset ----
+ output$summary <- renderPrint({
+ dataset <- datasetInput()
+ summary(dataset)
+ })
-You can also make an ordinary R variable accessible in scala and Python:
-
-<img class="img-responsive"
src="{{BASE_PATH}}/assets/themes/zeppelin/img/docs-img/varr1.png"
width="550px"/>
-
-And vice versa:
+ # Show the first "n" observations ----
+ output$view <- renderTable({
+ head(datasetInput(), n = input$obs)
+ })
+}
+```
-<img class="img-responsive"
src="{{BASE_PATH}}/assets/themes/zeppelin/img/docs-img/varscala.png"
width="550px"/>
+* UI type R shiny paragraph
+
+```r
+%r.shiny(type=ui)
+
+# Define UI for dataset viewer app ----
+ui <- fluidPage(
+
+ # App title ----
+ titlePanel("Shiny Text"),
+
+ # Sidebar layout with a input and output definitions ----
+ sidebarLayout(
+
+ # Sidebar panel for inputs ----
+ sidebarPanel(
+
+ # Input: Selector for choosing dataset ----
+ selectInput(inputId = "dataset",
+ label = "Choose a dataset:",
+ choices = c("rock", "pressure", "cars")),
+
+ # Input: Numeric entry for number of obs to view ----
+ numericInput(inputId = "obs",
+ label = "Number of observations to view:",
+ value = 10)
+ ),
+
+ # Main panel for displaying outputs ----
+ mainPanel(
+
+ # Output: Verbatim text for data summary ----
+ verbatimTextOutput("summary"),
+
+ # Output: HTML table with requested number of observations ----
+ tableOutput("view")
+
+ )
+ )
+)
+```
-<img class="img-responsive"
src="{{BASE_PATH}}/assets/themes/zeppelin/img/docs-img/varr2.png"
width="550px"/>
+* Run type R shiny paragraph
-## Caveats & Troubleshooting
+```r
-* Almost all issues with the R interpreter turned out to be caused by an
incorrectly set `SPARK_HOME`. The R interpreter must load a version of the
`SparkR` package that matches the running version of Spark, and it does this by
searching `SPARK_HOME`. If Zeppelin isn't configured to interface with Spark in
`SPARK_HOME`, the R interpreter will not be able to connect to Spark.
+%r.shiny(type=run)
-* The `knitr` environment is persistent. If you run a chunk from Zeppelin that
changes a variable, then run the same chunk again, the variable has already
been changed. Use immutable variables.
+```
-* (Note that `%spark.r` and `%r` are two different ways of calling the same
interpreter, as are `%spark.knitr` and `%knitr`. By default, Zeppelin puts the
R interpreters in the `%spark.` Interpreter Group.
+After executing the run type R shiny paragraph, the shiny app will be launched
and embedded as Iframe in paragraph.
-* Using the `%r` interpreter, if you return a data.frame, HTML, or an image,
it will dominate the result. So if you execute three commands, and one is
`hist()`, all you will see is the histogram, not the results of the other
commands. This is a Zeppelin limitation.
+<img class="img-responsive"
src="{{BASE_PATH}}/assets/themes/zeppelin/img/docs-img/r_shiny.png"
width="800px"/>
-* If you return a data.frame (for instance, from calling `head()`) from the
`%spark.r` interpreter, it will be parsed by Zeppelin's built-in data
visualization system.
+### Run multiple shiny app
-* Why `knitr` Instead of `rmarkdown`? Why no `htmlwidgets`? In order to
support `htmlwidgets`, which has indirect dependencies, `rmarkdown` uses
`pandoc`, which requires writing to and reading from disc. This makes it many
times slower than `knitr`, which can operate entirely in RAM.
+If you want to run multiple shiny app, you can specify `app` in paragraph
local property to differentiate shiny app.
-* Why no `ggvis` or `shiny`? Supporting `shiny` would require integrating a
reverse-proxy into Zeppelin, which is a task.
+e.g.
-* Max OS X & case-insensitive filesystem. If you try to install on a
case-insensitive filesystem, which is the Mac OS X default, maven can
unintentionally delete the install directory because `r` and `R` become the
same subdirectory.
+```r
+%r.shiny(type=ui, app=app_1)
+```
-* Error `unable to start device X11` with the repl interpreter. Check your
shell login scripts to see if they are adjusting the `DISPLAY` environment
variable. This is common on some operating systems as a workaround for ssh
issues, but can interfere with R plotting.
+```r
+%r.shiny(type=server, app=app_1)
+```
-* akka Library Version or `TTransport` errors. This can happen if you try to
run Zeppelin with a SPARK_HOME that has a version of Spark other than the one
specified with `-Pspark-1.x` when Zeppelin was compiled.
+```r
+%r.shiny(type=run, app=app_1)
+```
\ No newline at end of file
