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The following commit(s) were added to refs/heads/master by this push:
new d9021efff8 [ZEPPELIN-6430] Clean up removed R interpreter docs
d9021efff8 is described below
commit d9021efff83e8145bf9d398e73b68ba30e1d3050
Author: Jongyoul Lee <[email protected]>
AuthorDate: Wed Jul 8 11:38:01 2026 +0900
[ZEPPELIN-6430] Clean up removed R interpreter docs
## What changed
This cleans up documentation references left behind after the R
interpreter, SparkR, and rlang code removal in ZEPPELIN-6430.
- Removed R build/runtime requirements from docs where they are no longer
Zeppelin requirements.
- Removed `%spark.r` and R example blocks, and updated the generic
interpreter example to use `%spark.sql`.
- Updated stale `env_python_3_with_R.yml` links to the current Python
environment file.
- Removed R example links and support-list entries from interpreter,
quickstart, Livy, VM, ZeppelinContext, and SDK docs.
## Why
The code removal left docs that still implied R interpreter or SparkR
support. These updates avoid sending users toward removed functionality while
keeping supported Python, Spark, SQL, and Mahout docs intact.
## Validation
- `git diff --check`
- `rg -n "SparkR|R interpreter|r-base|r-cran|IRkernel|R
Tutorial|%spark\\.r|%r\\b|env_python_3_with_R" docs --glob "*.md"`
- Additional strict search for actual R feature remnants returned no
matches; the broad search only leaves false positives such as
`interpreter-base` / `interpreter-based`.
Closes #5282 from jongyoul/codex/cleanup-r-docs.
Signed-off-by: Jongyoul Lee <[email protected]>
---
docs/interpreter/livy.md | 4 +--
docs/interpreter/mahout.md | 38 +--------------------------
docs/interpreter/python.md | 2 +-
docs/interpreter/spark.md | 10 +++----
docs/quickstart/install.md | 4 +--
docs/setup/basics/how_to_build.md | 2 --
docs/setup/deployment/virtual_machine.md | 1 -
docs/usage/interpreter/overview.md | 2 +-
docs/usage/other_features/zeppelin_context.md | 21 +--------------
docs/usage/zeppelin_sdk/session_api.md | 2 --
10 files changed, 12 insertions(+), 74 deletions(-)
diff --git a/docs/interpreter/livy.md b/docs/interpreter/livy.md
index d6ba00864d..b48ad0472b 100644
--- a/docs/interpreter/livy.md
+++ b/docs/interpreter/livy.md
@@ -26,7 +26,7 @@ limitations under the License.
## Overview
[Livy](http://livy.io/) is an open source REST interface for interacting with
Spark from anywhere. It supports executing snippets of code or programs in a
Spark context that runs locally or in YARN.
-* Interactive Scala, Python and R shells
+* Interactive Scala and Python shells
* Batch submissions in Scala, Java, Python
* Multi users can share the same server (impersonation support)
* Can be used for submitting jobs from anywhere with REST
@@ -237,7 +237,7 @@ select * from products where ${product_id=1}
And creating dynamic format programmatically is not feasible in livy
interpreter, because ZeppelinContext is not available in livy interpreter.
## Shared SparkContext
-Starting from livy 0.5 which is supported by Zeppelin 0.8.0, SparkContext is
shared between scala, python, r and sql.
+Starting from livy 0.5 which is supported by Zeppelin 0.8.0, SparkContext is
shared between scala, python and sql.
That means you can query the table via `%livy.sql` when this table is
registered in `%livy.spark`, `%livy.pyspark`.
## FAQ
diff --git a/docs/interpreter/mahout.md b/docs/interpreter/mahout.md
index c07edc6899..ecab15668c 100644
--- a/docs/interpreter/mahout.md
+++ b/docs/interpreter/mahout.md
@@ -159,7 +159,7 @@ val Xty = drmXty.collect(::, 0)
val beta = solve(XtX, Xty)
```
-## Leveraging Resource Pools and R for Visualization
+## Leveraging Resource Pools for Visualization
Resource Pools are a powerful Zeppelin feature that lets us share information
between interpreters. A fun trick is to take the output of our work in Mahout
and analyze it in other languages.
@@ -184,39 +184,3 @@ val z = InterpreterContext.get().getResourcePool()
```
Now we can access the resource pool in a consistent manner from the
`%flinkMahout` interpreter.
-
-
-### Passing a variable from Mahout to R and Plotting
-
-In this simple example, we use Mahout (on Flink or Spark, the code is the
same) to create a random matrix and then take the Sin of each element. We then
randomly sample the matrix and create a tab separated string. Finally we pass
that string to R where it is read as a .tsv file, and a DataFrame is created
and plotted using native R plotting libraries.
-
-```scala
-val mxRnd = Matrices.symmetricUniformView(5000, 2, 1234)
-val drmRand = drmParallelize(mxRnd)
-
-
-val drmSin = drmRand.mapBlock() {case (keys, block) =>
- val blockB = block.like()
- for (i <- 0 until block.nrow) {
- blockB(i, 0) = block(i, 0)
- blockB(i, 1) = Math.sin((block(i, 0) * 8))
- }
- keys -> blockB
-}
-
-z.put("sinDrm", org.apache.mahout.math.drm.drmSampleToTSV(drmSin, 0.85))
-```
-
-And then in an R paragraph...
-
-```r
-%spark.r {"imageWidth": "400px"}
-
-library("ggplot2")
-
-sinStr = z.get("flinkSinDrm")
-
-data <- read.table(text= sinStr, sep="\t", header=FALSE)
-
-plot(data, col="red")
-```
diff --git a/docs/interpreter/python.md b/docs/interpreter/python.md
index 93567dc211..8600975c1d 100644
--- a/docs/interpreter/python.md
+++ b/docs/interpreter/python.md
@@ -79,7 +79,7 @@ Zeppelin supports python language which is very popular in
data analytics and ma
For beginner, we would suggest you to play Python in Zeppelin docker first.
In the Zeppelin docker image, we have already installed
-miniconda and lots of [useful python
libraries](https://github.com/apache/zeppelin/blob/branch-0.10/scripts/docker/zeppelin/bin/env_python_3_with_R.yml)
+miniconda and lots of [useful python
libraries](https://github.com/apache/zeppelin/blob/master/scripts/docker/zeppelin/bin/env_python_3.yml)
including IPython's prerequisites, so `%python` would use IPython.
Without any extra configuration, you can run most of tutorial notes under
folder `Python Tutorial` directly.
diff --git a/docs/interpreter/spark.md b/docs/interpreter/spark.md
index 2b31a055cc..f7311a2133 100644
--- a/docs/interpreter/spark.md
+++ b/docs/interpreter/spark.md
@@ -1,7 +1,7 @@
---
layout: page
title: "Apache Spark Interpreter for Apache Zeppelin"
-description: "Apache Spark is a fast and general-purpose cluster computing
system. It provides high-level APIs in Java, Scala, Python and R, and an
optimized engine that supports general execution engine."
+description: "Apache Spark is a fast and general-purpose cluster computing
system. It provides high-level APIs including Java, Scala and Python, and an
optimized engine that supports general execution engine."
group: interpreter
---
<!--
@@ -25,7 +25,7 @@ limitations under the License.
## Overview
[Apache Spark](http://spark.apache.org) is a fast and general-purpose cluster
computing system.
-It provides high-level APIs in Java, Scala, Python and R, and an optimized
engine that supports general execution graphs.
+It provides high-level APIs including Java, Scala and Python, and an optimized
engine that supports general execution graphs.
Apache Spark is supported in Zeppelin with Spark interpreter group which
consists of following interpreters.
<table class="table-configuration">
@@ -73,7 +73,7 @@ Apache Spark is supported in Zeppelin with Spark interpreter
group which consist
</tr>
<tr>
<td>Support multiple languages</td>
- <td>Scala, SQL, Python, R are supported, besides that you can also
collaborate across languages, e.g. you can write Scala UDF and use it in
PySpark</td>
+ <td>Scala, SQL and Python are supported, besides that you can also
collaborate across languages, e.g. you can write Scala UDF and use it in
PySpark</td>
</tr>
<tr>
<td>Support multiple execution modes</td>
@@ -104,7 +104,7 @@ Apache Spark is supported in Zeppelin with Spark
interpreter group which consist
For beginner, we would suggest you to play Spark in Zeppelin docker.
In the Zeppelin docker image, we have already installed
-miniconda and lots of [useful python
libraries](https://github.com/apache/zeppelin/blob/branch-0.10/scripts/docker/zeppelin/bin/env_python_3_with_R.yml)
+miniconda and lots of [useful python
libraries](https://github.com/apache/zeppelin/blob/master/scripts/docker/zeppelin/bin/env_python_3.yml)
including IPython prerequisites, so `%spark.pyspark` would use IPython.
Without any extra configuration, you can run most of tutorial notes under
folder `Spark Tutorial` directly.
@@ -365,7 +365,7 @@ You can also choose `scoped` mode. For `scoped` per note
mode, Zeppelin creates
## SparkContext, SQLContext, SparkSession, ZeppelinContext
-SparkContext, SparkSession and ZeppelinContext are automatically created and
exposed as variable names `sc`, `spark` and `z` respectively, in Scala, Python
and R environments.
+SparkContext, SparkSession and ZeppelinContext are automatically created and
exposed as variable names `sc`, `spark` and `z` respectively, in Scala and
Python environments.
> Note that Scala/Python environment shares the same SparkContext, SQLContext,
> SparkSession and ZeppelinContext instance.
diff --git a/docs/quickstart/install.md b/docs/quickstart/install.md
index 0dbd4870e4..b252ec5265 100644
--- a/docs/quickstart/install.md
+++ b/docs/quickstart/install.md
@@ -165,7 +165,7 @@ Congratulations, you have successfully installed Apache
Zeppelin! Here are a few
* And then, try run Tutorial Notebooks shipped with your Zeppelin
distribution.
* And see how to change
[configurations](../setup/operation/configuration.html) like port number, etc.
-#### Spark, Flink, SQL, Python, R and more
+#### Spark, Flink, SQL, Python and more
* [Spark support in Zeppelin](./spark_with_zeppelin.html), to know more about
deep integration with [Apache Spark](http://spark.apache.org/).
* [Flink support in Zeppelin](./flink_with_zeppelin.html), to know more about
deep integration with [Apache Flink](http://flink.apache.org/).
* [SQL support in Zeppelin](./sql_with_zeppelin.html) for SQL support
@@ -174,5 +174,3 @@ Congratulations, you have successfully installed Apache
Zeppelin! Here are a few
#### Multi-user support ...
* Check [Multi-user support](../setup/basics/multi_user_support.html)
-
-
diff --git a/docs/setup/basics/how_to_build.md
b/docs/setup/basics/how_to_build.md
index 0175fa96e0..176d7a9146 100644
--- a/docs/setup/basics/how_to_build.md
+++ b/docs/setup/basics/how_to_build.md
@@ -195,8 +195,6 @@ sudo apt-get install git
sudo apt-get install openjdk-11-jdk
sudo apt-get install npm
sudo apt-get install libfontconfig
-sudo apt-get install r-base-dev
-sudo apt-get install r-cran-evaluate
```
_Notes:_
diff --git a/docs/setup/deployment/virtual_machine.md
b/docs/setup/deployment/virtual_machine.md
index 915ce89c79..44afeaeed6 100644
--- a/docs/setup/deployment/virtual_machine.md
+++ b/docs/setup/deployment/virtual_machine.md
@@ -98,7 +98,6 @@ The virtual machine consists of:
- libfontconfig to avoid phatomJs missing dependency issues
- openjdk-7-jdk
- Python addons: pip, matplotlib, scipy, numpy, pandas
- - [R](https://www.r-project.org/) and R Packages required to run the R
Interpreter and the related R tutorial notebook, including: Knitr, devtools,
repr, rCharts, ggplot2, googleVis, mplot, htmltools, base64enc, data.table
## How to build & run Zeppelin
diff --git a/docs/usage/interpreter/overview.md
b/docs/usage/interpreter/overview.md
index 271103c414..5186b9ed5f 100644
--- a/docs/usage/interpreter/overview.md
+++ b/docs/usage/interpreter/overview.md
@@ -38,7 +38,7 @@ When you click the ```+Create``` button on the interpreter
page, the interpreter
You can create multiple interpreters for the same engine with different
interpreter setting. e.g. You can create `spark2` for Spark 2.x and create
`spark1` for Spark 1.x.
-For each paragraph you write in Zeppelin, you need to specify its interpreter
first via `%interpreter_group.interpreter_name`. e.g. `%spark.pyspark`,
`%spark.r`.
+For each paragraph you write in Zeppelin, you need to specify its interpreter
first via `%interpreter_group.interpreter_name`. e.g. `%spark.pyspark`,
`%spark.sql`.
If you specify interpreter, you can also pass local properties to it (if it
needs them). This is done by providing a set of key/value pairs, separated by
comma, inside the round brackets right after the interpreter name. If key or
value contain characters like `=`, or `,`, then you can either escape them with
`\` character, or wrap the whole value inside the double quotes For example:
diff --git a/docs/usage/other_features/zeppelin_context.md
b/docs/usage/other_features/zeppelin_context.md
index 9cd9167fe2..efb72b01ab 100644
--- a/docs/usage/other_features/zeppelin_context.md
+++ b/docs/usage/other_features/zeppelin_context.md
@@ -35,7 +35,7 @@ environments is described below.
## Usage in Programming Language Cells
-In many programming-language interpreters (e.g. Apache Spark, Python, R) the
zeppelin-context is available
+In many programming-language interpreters (e.g. Apache Spark and Python) the
zeppelin-context is available
as a predefined variable `z` that can be used by directly invoking its methods.
The methods available on the `z` object are described below.
Other interpreters based on programming languages. also provide the predefined
variable `z`.
@@ -86,24 +86,6 @@ df = z.getAsDataFrame("table_name")
{% endhighlight %}
</div>
-
-<div data-lang="R" markdown="1">
-
-{% highlight python %}
-# Get/Put object from R
-%spark.r
-
-z.put("objName", myObject)
-myObject <- z.get("objName")
-
-# df is R DataFrame
-# "table_name" must be table type. Currently only sql interpreter (%spark.sql
or %jdbc) result is supported.
-df <- z.getAsDataFrame("table_name")
-
-{% endhighlight %}
-
- </div>
-
</div>
Currently, there're two types of data could be shared across interpreters:
@@ -305,4 +287,3 @@ Some interpreters use a subclass of `BaseZepplinContext`
augmented with interpre
Such interpreter-specific functions are described within each interpreter's
documentation.
-
diff --git a/docs/usage/zeppelin_sdk/session_api.md
b/docs/usage/zeppelin_sdk/session_api.md
index c32d3af412..63fbe9afb2 100644
--- a/docs/usage/zeppelin_sdk/session_api.md
+++ b/docs/usage/zeppelin_sdk/session_api.md
@@ -154,5 +154,3 @@ For more detailed usage of session api, you can check the
examples in module `ze
*
[FlinkAdvancedExample2](https://github.com/apache/zeppelin/blob/master/zeppelin-client-examples/src/main/java/org/apache/zeppelin/client/examples/FlinkAdvancedExample2.java)
*
[HiveExample](https://github.com/apache/zeppelin/blob/master/zeppelin-client-examples/src/main/java/org/apache/zeppelin/client/examples/HiveExample.java)
*
[PythonExample](https://github.com/apache/zeppelin/blob/master/zeppelin-client-examples/src/main/java/org/apache/zeppelin/client/examples/PythonExample.java)
-*
[RExample](https://github.com/apache/zeppelin/blob/master/zeppelin-client-examples/src/main/java/org/apache/zeppelin/client/examples/RExample.java)
-
