[MINOR][DOCS] Tighten up some key links to the project and download pages to use HTTPS

## What changes were proposed in this pull request?

Tighten up some key links to the project and download pages to use HTTPS

## How was this patch tested?

N/A

Closes #24665 from srowen/HTTPSURLs.

Authored-by: Sean Owen <[email protected]>
Signed-off-by: Dongjoon Hyun <[email protected]>

Author: srowen

.github/PULL_REQUEST_TEMPLATE

@@ -7,4 +7,4 @@
 (Please explain how this patch was tested. E.g. unit tests, integration tests, manual tests)
 (If this patch involves UI changes, please attach a screenshot; otherwise, remove this)
 
-Please review http://spark.apache.org/contributing.html before opening a pull request.
+Please review https://spark.apache.org/contributing.html before opening a pull request.

CONTRIBUTING.md

@@ -1,12 +1,12 @@
 ## Contributing to Spark
 
 *Before opening a pull request*, review the 
-[Contributing to Spark guide](http://spark.apache.org/contributing.html). 
+[Contributing to Spark guide](https://spark.apache.org/contributing.html). 
 It lists steps that are required before creating a PR. In particular, consider:
 
 - Is the change important and ready enough to ask the community to spend time reviewing?
 - Have you searched for existing, related JIRAs and pull requests?
-- Is this a new feature that can stand alone as a [third party project](http://spark.apache.org/third-party-projects.html) ?
+- Is this a new feature that can stand alone as a [third party project](https://spark.apache.org/third-party-projects.html) ?
 - Is the change being proposed clearly explained and motivated?
 
 When you contribute code, you affirm that the contribution is your original work and that you 

R/README.md

@@ -17,7 +17,7 @@ export R_HOME=/home/username/R
 
 #### Build Spark
 
-Build Spark with [Maven](http://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
+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
 
 ```bash
 build/mvn -DskipTests -Psparkr package
@@ -35,15 +35,15 @@ SparkContext, you can run
 
     ./bin/sparkR --master "local[2]"
 
-To set other options like driver memory, executor memory etc. you can pass in the [spark-submit](http://spark.apache.org/docs/latest/submitting-applications.html) arguments to `./bin/sparkR`
+To set other options like driver memory, executor memory etc. you can pass in the [spark-submit](https://spark.apache.org/docs/latest/submitting-applications.html) arguments to `./bin/sparkR`
 
 #### Using SparkR from RStudio
 
 If you wish to use SparkR from RStudio, please refer [SparkR documentation](https://spark.apache.org/docs/latest/sparkr.html#starting-up-from-rstudio).
 
 #### Making changes to SparkR
 
-The [instructions](http://spark.apache.org/contributing.html) for making contributions to Spark also apply to SparkR.
+The [instructions](https://spark.apache.org/contributing.html) for making contributions to Spark also apply to SparkR.
 If you only make R file changes (i.e. no Scala changes) then you can just re-install the R package using `R/install-dev.sh` and test your changes.
 Once you have made your changes, please include unit tests for them and run existing unit tests using the `R/run-tests.sh` script as described below.
 
@@ -58,7 +58,7 @@ To run one of them, use `./bin/spark-submit <filename> <args>`. For example:
 ```bash
 ./bin/spark-submit examples/src/main/r/dataframe.R
 ```
-You can run R unit tests by following the instructions under [Running R Tests](http://spark.apache.org/docs/latest/building-spark.html#running-r-tests).
+You can run R unit tests by following the instructions under [Running R Tests](https://spark.apache.org/docs/latest/building-spark.html#running-r-tests).
 
 ### Running on YARN
 

R/WINDOWS.md

@@ -20,19 +20,19 @@ license: |
 
 To build SparkR on Windows, the following steps are required
 
-1. Install R (>= 3.1) and [Rtools](http://cran.r-project.org/bin/windows/Rtools/). Make sure to
+1. Install R (>= 3.1) and [Rtools](https://cloud.r-project.org/bin/windows/Rtools/). Make sure to
 include Rtools and R in `PATH`. Note that support for R prior to version 3.4 is deprecated as of Spark 3.0.0.
 
 2. Install
-[JDK8](http://www.oracle.com/technetwork/java/javase/downloads/jdk8-downloads-2133151.html) and set
+[JDK8](https://www.oracle.com/technetwork/java/javase/downloads/jdk8-downloads-2133151.html) and set
 `JAVA_HOME` in the system environment variables.
 
-3. Download and install [Maven](http://maven.apache.org/download.html). Also include the `bin`
+3. Download and install [Maven](https://maven.apache.org/download.html). Also include the `bin`
 directory in Maven in `PATH`.
 
-4. Set `MAVEN_OPTS` as described in [Building Spark](http://spark.apache.org/docs/latest/building-spark.html).
+4. Set `MAVEN_OPTS` as described in [Building Spark](https://spark.apache.org/docs/latest/building-spark.html).
 
-5. Open a command shell (`cmd`) in the Spark directory and build Spark with [Maven](http://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
+5. 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
 
     ```bash
     mvn.cmd -DskipTests -Psparkr package
@@ -52,7 +52,7 @@ To run the SparkR unit tests on Windows, the following steps are required —ass
 
 4. Set the environment variable `HADOOP_HOME` to the full path to the newly created `hadoop` directory.
 
-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](http://spark.apache.org/docs/latest/building-spark.html#running-r-tests) first:
+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:
 
     ```
     .\bin\spark-submit2.cmd --conf spark.hadoop.fs.defaultFS="file:///" R\pkg\tests\run-all.R

README.md

@@ -7,7 +7,7 @@ rich set of higher-level tools including Spark SQL for SQL and DataFrames,
 MLlib for machine learning, GraphX for graph processing,
 and Structured Streaming for stream processing.
 
-<http://spark.apache.org/>
+<https://spark.apache.org/>
 
 [![Jenkins Build](https://amplab.cs.berkeley.edu/jenkins/job/spark-master-test-sbt-hadoop-2.7/badge/icon)](https://amplab.cs.berkeley.edu/jenkins/job/spark-master-test-sbt-hadoop-2.7)
 [![AppVeyor Build](https://img.shields.io/appveyor/ci/ApacheSoftwareFoundation/spark/master.svg?style=plastic&logo=appveyor)](https://ci.appveyor.com/project/ApacheSoftwareFoundation/spark)
@@ -17,12 +17,12 @@ and Structured Streaming for stream processing.
 ## Online Documentation
 
 You can find the latest Spark documentation, including a programming
-guide, on the [project web page](http://spark.apache.org/documentation.html).
+guide, on the [project web page](https://spark.apache.org/documentation.html).
 This README file only contains basic setup instructions.
 
 ## Building Spark
 
-Spark is built using [Apache Maven](http://maven.apache.org/).
+Spark is built using [Apache Maven](https://maven.apache.org/).
 To build Spark and its example programs, run:
 
     build/mvn -DskipTests clean package
@@ -31,9 +31,9 @@ To build Spark and its example programs, run:
 
 You can build Spark using more than one thread by using the -T option with Maven, see ["Parallel builds in Maven 3"](https://cwiki.apache.org/confluence/display/MAVEN/Parallel+builds+in+Maven+3).
 More detailed documentation is available from the project site, at
-["Building Spark"](http://spark.apache.org/docs/latest/building-spark.html).
+["Building Spark"](https://spark.apache.org/docs/latest/building-spark.html).
 
-For general development tips, including info on developing Spark using an IDE, see ["Useful Developer Tools"](http://spark.apache.org/developer-tools.html).
+For general development tips, including info on developing Spark using an IDE, see ["Useful Developer Tools"](https://spark.apache.org/developer-tools.html).
 
 ## Interactive Scala Shell
 
@@ -83,7 +83,7 @@ can be run using:
     ./dev/run-tests
 
 Please see the guidance on how to
-[run tests for a module, or individual tests](http://spark.apache.org/developer-tools.html#individual-tests).
+[run tests for a module, or individual tests](https://spark.apache.org/developer-tools.html#individual-tests).
 
 There is also a Kubernetes integration test, see resource-managers/kubernetes/integration-tests/README.md
 
@@ -94,16 +94,16 @@ storage systems. Because the protocols have changed in different versions of
 Hadoop, you must build Spark against the same version that your cluster runs.
 
 Please refer to the build documentation at
-["Specifying the Hadoop Version and Enabling YARN"](http://spark.apache.org/docs/latest/building-spark.html#specifying-the-hadoop-version-and-enabling-yarn)
+["Specifying the Hadoop Version and Enabling YARN"](https://spark.apache.org/docs/latest/building-spark.html#specifying-the-hadoop-version-and-enabling-yarn)
 for detailed guidance on building for a particular distribution of Hadoop, including
 building for particular Hive and Hive Thriftserver distributions.
 
 ## Configuration
 
-Please refer to the [Configuration Guide](http://spark.apache.org/docs/latest/configuration.html)
+Please refer to the [Configuration Guide](https://spark.apache.org/docs/latest/configuration.html)
 in the online documentation for an overview on how to configure Spark.
 
 ## Contributing
 
-Please review the [Contribution to Spark guide](http://spark.apache.org/contributing.html)
+Please review the [Contribution to Spark guide](https://spark.apache.org/contributing.html)
 for information on how to get started contributing to the project.

build/sbt-launch-lib.bash

@@ -56,13 +56,13 @@ acquire_sbt_jar () {
       wget --quiet ${URL1} -O "${JAR_DL}" &&\
         mv "${JAR_DL}" "${JAR}"
     else
-      printf "You do not have curl or wget installed, please install sbt manually from http://www.scala-sbt.org/\n"
+      printf "You do not have curl or wget installed, please install sbt manually from https://www.scala-sbt.org/\n"
       exit -1
     fi
     fi
     if [ ! -f "${JAR}" ]; then
     # We failed to download
-    printf "Our attempt to download sbt locally to ${JAR} failed. Please install sbt manually from http://www.scala-sbt.org/\n"
+    printf "Our attempt to download sbt locally to ${JAR} failed. Please install sbt manually from https://www.scala-sbt.org/\n"
     exit -1
     fi
     printf "Launching sbt from ${JAR}\n"

dev/create-release/vote.tmpl

@@ -6,7 +6,7 @@ a minimum of 3 +1 votes.
 [ ] +1 Release this package as Apache Spark {version}
 [ ] -1 Do not release this package because ...
 
-To learn more about Apache Spark, please see http://spark.apache.org/
+To learn more about Apache Spark, please see https://spark.apache.org/
 
 The tag to be voted on is {tag} (commit {tag_commit}):
 https://github.com/apache/spark/tree/{tag}

docs/building-spark.md

@@ -51,7 +51,7 @@ You can fix these problems by setting the `MAVEN_OPTS` variable as discussed bef
 
 ### build/mvn
 
-Spark now comes packaged with a self-contained Maven installation to ease building and deployment of Spark from source located under the `build/` directory. This script will automatically download and setup all necessary build requirements ([Maven](https://maven.apache.org/), [Scala](http://www.scala-lang.org/), and [Zinc](https://github.com/typesafehub/zinc)) locally within the `build/` directory itself. It honors any `mvn` binary if present already, however, will pull down its own copy of Scala and Zinc regardless to ensure proper version requirements are met. `build/mvn` execution acts as a pass through to the `mvn` call allowing easy transition from previous build methods. As an example, one can build a version of Spark as follows:
+Spark now comes packaged with a self-contained Maven installation to ease building and deployment of Spark from source located under the `build/` directory. This script will automatically download and setup all necessary build requirements ([Maven](https://maven.apache.org/), [Scala](https://www.scala-lang.org/), and [Zinc](https://github.com/typesafehub/zinc)) locally within the `build/` directory itself. It honors any `mvn` binary if present already, however, will pull down its own copy of Scala and Zinc regardless to ensure proper version requirements are met. `build/mvn` execution acts as a pass through to the `mvn` call allowing easy transition from previous build methods. As an example, one can build a version of Spark as follows:
 
     ./build/mvn -DskipTests clean package
 
@@ -125,7 +125,7 @@ should run continuous compilation (i.e. wait for changes). However, this has not
 extensively. A couple of gotchas to note:
 
 * it only scans the paths `src/main` and `src/test` (see
-[docs](http://davidb.github.io/scala-maven-plugin/example_cc.html)), so it will only work
+[docs](https://davidb.github.io/scala-maven-plugin/example_cc.html)), so it will only work
 from within certain submodules that have that structure.
 
 * you'll typically need to run `mvn install` from the project root for compilation within
@@ -159,7 +159,7 @@ Configure the JVM options for SBT in `.jvmopts` at the project root, for example
     -Xmx2g
     -XX:ReservedCodeCacheSize=512m
 
-For the meanings of these two options, please carefully read the [Setting up Maven's Memory Usage section](http://spark.apache.org/docs/latest/building-spark.html#setting-up-mavens-memory-usage).
+For the meanings of these two options, please carefully read the [Setting up Maven's Memory Usage section](https://spark.apache.org/docs/latest/building-spark.html#setting-up-mavens-memory-usage).
 
 ## Speeding up Compilation
 
@@ -238,8 +238,8 @@ The run-tests script also can be limited to a specific Python version or a speci
 
 To run the SparkR tests you will need to install the [knitr](https://cran.r-project.org/package=knitr), [rmarkdown](https://cran.r-project.org/package=rmarkdown), [testthat](https://cran.r-project.org/package=testthat), [e1071](https://cran.r-project.org/package=e1071) and [survival](https://cran.r-project.org/package=survival) packages first:
 
-    R -e "install.packages(c('knitr', 'rmarkdown', 'devtools', 'e1071', 'survival'), repos='http://cran.us.r-project.org')"
-    R -e "devtools::install_version('testthat', version = '1.0.2', repos='http://cran.us.r-project.org')"
+    R -e "install.packages(c('knitr', 'rmarkdown', 'devtools', 'e1071', 'survival'), repos='https://cloud.r-project.org/')"
+    R -e "devtools::install_version('testthat', version = '1.0.2', repos='https://cloud.r-project.org/')"
 
 You can run just the SparkR tests using the command:
 

python/README.md

@@ -7,22 +7,22 @@ rich set of higher-level tools including Spark SQL for SQL and DataFrames,
 MLlib for machine learning, GraphX for graph processing,
 and Structured Streaming for stream processing.
 
-<http://spark.apache.org/>
+<https://spark.apache.org/>
 
 ## Online Documentation
 
 You can find the latest Spark documentation, including a programming
-guide, on the [project web page](http://spark.apache.org/documentation.html)
+guide, on the [project web page](https://spark.apache.org/documentation.html)
 
 
 ## Python Packaging
 
 This README file only contains basic information related to pip installed PySpark.
 This packaging is currently experimental and may change in future versions (although we will do our best to keep compatibility).
 Using PySpark requires the Spark JARs, and if you are building this from source please see the builder instructions at
-["Building Spark"](http://spark.apache.org/docs/latest/building-spark.html).
+["Building Spark"](https://spark.apache.org/docs/latest/building-spark.html).
 
-The Python packaging for Spark is not intended to replace all of the other use cases. This Python packaged version of Spark is suitable for interacting with an existing cluster (be it Spark standalone, YARN, or Mesos) - but does not contain the tools required to set up your own standalone Spark cluster. You can download the full version of Spark from the [Apache Spark downloads page](http://spark.apache.org/downloads.html).
+The Python packaging for Spark is not intended to replace all of the other use cases. This Python packaged version of Spark is suitable for interacting with an existing cluster (be it Spark standalone, YARN, or Mesos) - but does not contain the tools required to set up your own standalone Spark cluster. You can download the full version of Spark from the [Apache Spark downloads page](https://spark.apache.org/downloads.html).
 
 
 **NOTE:** If you are using this with a Spark standalone cluster you must ensure that the version (including minor version) matches or you may experience odd errors.