b62e2536db
### What changes were proposed in this pull request? Spark 3.0 accidentally dropped R < 3.5. It is built by R 3.6.3 which not support R < 3.5: ``` Error in readRDS(pfile) : cannot read workspace version 3 written by R 3.6.3; need R 3.5.0 or newer version. ``` In fact, with SPARK-31918, we will have to drop R < 3.5 entirely to support R 4.0.0. This is inevitable to release on CRAN because they require to make the tests pass with the latest R. ### Why are the changes needed? To show the supported versions correctly, and support R 4.0.0 to unblock the releases. ### Does this PR introduce _any_ user-facing change? In fact, no because Spark 3.0.0 already does not work with R < 3.5. Compared to Spark 2.4, yes. R < 3.5 would not work. ### How was this patch tested? Jenkins should test it out. Closes #28908 from HyukjinKwon/SPARK-32073. Authored-by: HyukjinKwon <gurwls223@apache.org> Signed-off-by: HyukjinKwon <gurwls223@apache.org>
64 lines
3.4 KiB
Markdown
64 lines
3.4 KiB
Markdown
---
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license: |
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Licensed to the Apache Software Foundation (ASF) under one or more
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contributor license agreements. See the NOTICE file distributed with
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this work for additional information regarding copyright ownership.
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The ASF licenses this file to You under the Apache License, Version 2.0
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(the "License"); you may not use this file except in compliance with
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the License. You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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---
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## Building SparkR on Windows
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To build SparkR on Windows, the following steps are required
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1. Make sure `bash` is available and in `PATH` if you already have a built-in `bash` on Windows. If you do not have, install [Cygwin](https://www.cygwin.com/).
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2. Install R (>= 3.5) and [Rtools](https://cloud.r-project.org/bin/windows/Rtools/). Make sure to
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include Rtools and R in `PATH`.
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3. Install JDK that SparkR supports (see `R/pkg/DESCRIPTION`), and set `JAVA_HOME` in the system environment variables.
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4. Download and install [Maven](https://maven.apache.org/download.html). Also include the `bin`
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directory in Maven in `PATH`.
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5. Set `MAVEN_OPTS` as described in [Building Spark](https://spark.apache.org/docs/latest/building-spark.html).
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6. Open a command shell (`cmd`) in the Spark directory and build Spark with [Maven](https://spark.apache.org/docs/latest/building-spark.html#buildmvn) and include the `-Psparkr` profile to build the R package. For example to use the default Hadoop versions you can run
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```bash
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mvn.cmd -DskipTests -Psparkr package
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```
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Note that `.\build\mvn` is a shell script so `mvn.cmd` on the system should be used directly on Windows.
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Make sure your Maven version is matched to `maven.version` in `./pom.xml`.
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Note that it is a workaround for SparkR developers on Windows. Apache Spark does not officially support to _build_ on Windows yet whereas it supports to _run_ on Windows.
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## Unit tests
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To run the SparkR unit tests on Windows, the following steps are required —assuming you are in the Spark root directory and do not have Apache Hadoop installed already:
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1. Create a folder to download Hadoop related files for Windows. For example, `cd ..` and `mkdir hadoop`.
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2. Download the relevant Hadoop bin package from [steveloughran/winutils](https://github.com/steveloughran/winutils). While these are not official ASF artifacts, they are built from the ASF release git hashes by a Hadoop PMC member on a dedicated Windows VM. For further reading, consult [Windows Problems on the Hadoop wiki](https://wiki.apache.org/hadoop/WindowsProblems).
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3. Install the files into `hadoop\bin`; make sure that `winutils.exe` and `hadoop.dll` are present.
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4. Set the environment variable `HADOOP_HOME` to the full path to the newly created `hadoop` directory.
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5. Run unit tests for SparkR by running the command below. You need to install the needed packages following the instructions under [Running R Tests](https://spark.apache.org/docs/latest/building-spark.html#running-r-tests) first:
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```
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.\bin\spark-submit2.cmd --conf spark.hadoop.fs.defaultFS="file:///" R\pkg\tests\run-all.R
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```
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