SPARK-3069 [DOCS] Build instructions in README are outdated

Here's my crack at Bertrand's suggestion. The Github `README.md` contains build info that's outdated. It should just point to the current online docs, and reflect that Maven is the primary build now.

(Incidentally, the stanza at the end about contributions of original work should go in https://cwiki.apache.org/confluence/display/SPARK/Contributing+to+Spark too. It won't hurt to be crystal clear about the agreement to license, given that ICLAs are not required of anyone here.)

Author: Sean Owen <sowen@cloudera.com>

Closes #2014 from srowen/SPARK-3069 and squashes the following commits:

501507e [Sean Owen] Note that Zinc is for Maven builds too
db2bd97 [Sean Owen] sbt -> sbt/sbt and add note about zinc
be82027 [Sean Owen] Fix additional occurrences of building-with-maven -> building-spark
91c921f [Sean Owen] Move building-with-maven to building-spark and create a redirect. Update doc links to building-spark.html Add jekyll-redirect-from plugin and make associated config changes (including fixing pygments deprecation). Add example of SBT to README.md
999544e [Sean Owen] Change "Building Spark with Maven" title to "Building Spark"; reinstate tl;dr info about dev/run-tests in README.md; add brief note about building with SBT
c18d140 [Sean Owen] Optionally, remove the copy of contributing text from main README.md
8e83934 [Sean Owen] Add CONTRIBUTING.md to trigger notice on new pull request page
b1c04a1 [Sean Owen] Refer to current online documentation for building, and remove slightly outdated copy in README.md

CONTRIBUTING.md

+## Contributing to Spark
+
+Contributions via GitHub pull requests are gladly accepted from their original
+author. Along with any pull requests, please state that the contribution is
+your original work and that you license the work to the project under the
+project's open source license. Whether or not you state this explicitly, by
+submitting any copyrighted material via pull request, email, or other means
+you agree to license the material under the project's open source license and
+warrant that you have the legal authority to do so.
+
+Please see [Contributing to Spark wiki page](https://cwiki.apache.org/SPARK/Contributing+to+Spark)
+for more information.

README.md

@@ -13,16 +13,19 @@ and Spark Streaming for stream processing.
 ## Online Documentation
 
 You can find the latest Spark documentation, including a programming
-guide, on the project webpage at <http://spark.apache.org/documentation.html>.
+guide, on the [project web page](http://spark.apache.org/documentation.html).
 This README file only contains basic setup instructions.
 
 ## Building Spark
 
-Spark is built on Scala 2.10. To build Spark and its example programs, run:
+Spark is built using [Apache Maven](http://maven.apache.org/).
+To build Spark and its example programs, run:
 
-    ./sbt/sbt assembly
+    mvn -DskipTests clean package
 
 (You do not need to do this if you downloaded a pre-built package.)
+More detailed documentation is available from the project site, at
+["Building Spark"](http://spark.apache.org/docs/latest/building-spark.html).
 
 ## Interactive Scala Shell
 
@@ -71,73 +74,24 @@ can be run using:
 
     ./dev/run-tests
 
+Please see the guidance on how to 
+[run all automated tests](https://cwiki.apache.org/confluence/display/SPARK/Contributing+to+Spark#ContributingtoSpark-AutomatedTesting)
+
 ## A Note About Hadoop Versions
 
 Spark uses the Hadoop core library to talk to HDFS and other Hadoop-supported
 storage systems. Because the protocols have changed in different versions of
 Hadoop, you must build Spark against the same version that your cluster runs.
-You can change the version by setting `-Dhadoop.version` when building Spark.
-
-For Apache Hadoop versions 1.x, Cloudera CDH MRv1, and other Hadoop
-versions without YARN, use:
-
-    # Apache Hadoop 1.2.1
-    $ sbt/sbt -Dhadoop.version=1.2.1 assembly
-
-    # Cloudera CDH 4.2.0 with MapReduce v1
-    $ sbt/sbt -Dhadoop.version=2.0.0-mr1-cdh4.2.0 assembly
-
-For Apache Hadoop 2.2.X, 2.1.X, 2.0.X, 0.23.x, Cloudera CDH MRv2, and other Hadoop versions
-with YARN, also set `-Pyarn`:
-
-    # Apache Hadoop 2.0.5-alpha
-    $ sbt/sbt -Dhadoop.version=2.0.5-alpha -Pyarn assembly
-
-    # Cloudera CDH 4.2.0 with MapReduce v2
-    $ sbt/sbt -Dhadoop.version=2.0.0-cdh4.2.0 -Pyarn assembly
-
-    # Apache Hadoop 2.2.X and newer
-    $ sbt/sbt -Dhadoop.version=2.2.0 -Pyarn assembly
-
-When developing a Spark application, specify the Hadoop version by adding the
-"hadoop-client" artifact to your project's dependencies. For example, if you're
-using Hadoop 1.2.1 and build your application using SBT, add this entry to
-`libraryDependencies`:
-
-    "org.apache.hadoop" % "hadoop-client" % "1.2.1"
 
-If your project is built with Maven, add this to your POM file's `<dependencies>` section:
-
-    <dependency>
-      <groupId>org.apache.hadoop</groupId>
-      <artifactId>hadoop-client</artifactId>
-      <version>1.2.1</version>
-    </dependency>
-
-
-## A Note About Thrift JDBC server and CLI for Spark SQL
-
-Spark SQL supports Thrift JDBC server and CLI.
-See sql-programming-guide.md for more information about using the JDBC server and CLI.
-You can use those features by setting `-Phive` when building Spark as follows.
-
-    $ sbt/sbt -Phive  assembly
+Please refer to the build documentation at
+["Specifying the Hadoop Version"](http://spark.apache.org/docs/latest/building-spark.html#specifying-the-hadoop-version)
+for detailed guidance on building for a particular distribution of Hadoop, including
+building for particular Hive and Hive Thriftserver distributions. See also
+["Third Party Hadoop Distributions"](http://spark.apache.org/docs/latest/hadoop-third-party-distributions.html)
+for guidance on building a Spark application that works with a particular
+distribution.
 
 ## Configuration
 
 Please refer to the [Configuration guide](http://spark.apache.org/docs/latest/configuration.html)
 in the online documentation for an overview on how to configure Spark.
-
-
-## Contributing to Spark
-
-Contributions via GitHub pull requests are gladly accepted from their original
-author. Along with any pull requests, please state that the contribution is
-your original work and that you license the work to the project under the
-project's open source license. Whether or not you state this explicitly, by
-submitting any copyrighted material via pull request, email, or other means
-you agree to license the material under the project's open source license and
-warrant that you have the legal authority to do so.
-
-Please see [Contributing to Spark wiki page](https://cwiki.apache.org/SPARK/Contributing+to+Spark)
-for more information.

docs/README.md

@@ -23,8 +23,9 @@ The markdown code can be compiled to HTML using the [Jekyll tool](http://jekyllr
 To use the `jekyll` command, you will need to have Jekyll installed. 
 The easiest way to do this is via a Ruby Gem, see the 
 [jekyll installation instructions](http://jekyllrb.com/docs/installation).
-If not already installed, you need to install `kramdown` with `sudo gem install kramdown`.
-Execute `jekyll` from the `docs/` directory. Compiling the site with Jekyll will create a directory
+If not already installed, you need to install `kramdown` and `jekyll-redirect-from` Gems
+with `sudo gem install kramdown jekyll-redirect-from`.
+Execute `jekyll build` from the `docs/` directory. Compiling the site with Jekyll will create a directory
 called `_site` containing index.html as well as the rest of the compiled files.
 
 You can modify the default Jekyll build as follows:

docs/_config.yml

-pygments: true
+highlighter: pygments
 markdown: kramdown
+gems:
+  - jekyll-redirect-from
 
 # These allow the documentation to be updated with nerw releases
 # of Spark, Scala, and Mesos.

docs/_layouts/global.html

@@ -109,7 +109,7 @@
                                 <li><a href="hardware-provisioning.html">Hardware Provisioning</a></li>
                                 <li><a href="hadoop-third-party-distributions.html">3<sup>rd</sup>-Party Hadoop Distros</a></li>
                                 <li class="divider"></li>
-                                <li><a href="building-with-maven.html">Building Spark with Maven</a></li>
+                                <li><a href="building-spark.html">Building Spark</a></li>
                                 <li><a href="https://cwiki.apache.org/confluence/display/SPARK/Contributing+to+Spark">Contributing to Spark</a></li>
                             </ul>
                         </li>

docs/building-with-maven.md → docs/building-spark.md

 ---
 layout: global
-title: Building Spark with Maven
+title: Building Spark
+redirect_from: "building-with-maven.html"
 ---
 
 * This will become a table of contents (this text will be scraped).
@@ -159,4 +160,21 @@ then ship it over to the cluster. We are investigating the exact cause for this.
 
 The assembly jar produced by `mvn package` will, by default, include all of Spark's dependencies, including Hadoop and some of its ecosystem projects. On YARN deployments, this causes multiple versions of these to appear on executor classpaths: the version packaged in the Spark assembly and the version on each node, included with yarn.application.classpath.  The `hadoop-provided` profile builds the assembly without including Hadoop-ecosystem projects, like ZooKeeper and Hadoop itself. 
 
+# Building with SBT
 
+Maven is the official recommendation for packaging Spark, and is the "build of reference".
+But SBT is supported for day-to-day development since it can provide much faster iterative
+compilation. More advanced developers may wish to use SBT.
+
+The SBT build is derived from the Maven POM files, and so the same Maven profiles and variables
+can be set to control the SBT build. For example:
+
+    sbt/sbt -Pyarn -Phadoop-2.3 compile
+
+# Speeding up Compilation with Zinc
+
+[Zinc](https://github.com/typesafehub/zinc) is a long-running server version of SBT's incremental
+compiler. When run locally as a background process, it speeds up builds of Scala-based projects
+like Spark. Developers who regularly recompile Spark with Maven will be the most interested in
+Zinc. The project site gives instructions for building and running `zinc`; OS X users can
+install it using `brew install zinc`.
\ No newline at end of file

docs/hadoop-third-party-distributions.md

@@ -11,7 +11,7 @@ with these distributions:
 
 When compiling Spark, you'll need to specify the Hadoop version by defining the `hadoop.version`
 property. For certain versions, you will need to specify additional profiles. For more detail,
-see the guide on [building with maven](building-with-maven.html#specifying-the-hadoop-version):
+see the guide on [building with maven](building-spark.html#specifying-the-hadoop-version):
 
     mvn -Dhadoop.version=1.0.4 -DskipTests clean package
     mvn -Phadoop-2.2 -Dhadoop.version=2.2.0 -DskipTests clean package

docs/index.md

@@ -12,7 +12,7 @@ It also supports a rich set of higher-level tools including [Spark SQL](sql-prog
 
 Get Spark from the [downloads page](http://spark.apache.org/downloads.html) of the project website. This documentation is for Spark version {{site.SPARK_VERSION}}. The downloads page 
 contains Spark packages for many popular HDFS versions. If you'd like to build Spark from 
-scratch, visit [building Spark with Maven](building-with-maven.html).
+scratch, visit [Building Spark](building-spark.html).
 
 Spark runs on both Windows and UNIX-like systems (e.g. Linux, Mac OS). It's easy to run
 locally on one machine --- all you need is to have `java` installed on your system `PATH`,
@@ -105,7 +105,7 @@ options for deployment:
 * [3<sup>rd</sup> Party Hadoop Distributions](hadoop-third-party-distributions.html): using common Hadoop distributions
 * Integration with other storage systems:
   * [OpenStack Swift](storage-openstack-swift.html)
-* [Building Spark with Maven](building-with-maven.html): build Spark using the Maven system
+* [Building Spark](building-spark.html): build Spark using the Maven system
 * [Contributing to Spark](https://cwiki.apache.org/confluence/display/SPARK/Contributing+to+Spark)
 
 **External Resources:**

docs/running-on-yarn.md

@@ -11,7 +11,7 @@ was added to Spark in version 0.6.0, and improved in subsequent releases.
 
 Running Spark-on-YARN requires a binary distribution of Spark which is built with YARN support.
 Binary distributions can be downloaded from the Spark project website. 
-To build Spark yourself, refer to the [building with Maven guide](building-with-maven.html).
+To build Spark yourself, refer to [Building Spark](building-spark.html).
 
 # Configuration
 

docs/streaming-kinesis-integration.md

@@ -108,7 +108,7 @@ A Kinesis stream can be set up at one of the valid Kinesis endpoints with 1 or m
 #### Running the Example
 To run the example,
 
-- Download Spark source and follow the [instructions](building-with-maven.html) to build Spark with profile *-Pkinesis-asl*.
+- Download Spark source and follow the [instructions](building-spark.html) to build Spark with profile *-Pkinesis-asl*.
 
         mvn -Pkinesis-asl -DskipTests clean package
 

make-distribution.sh

@@ -40,7 +40,7 @@ function exit_with_usage {
   echo ""
   echo "usage:"
   echo "./make-distribution.sh [--name] [--tgz] [--with-tachyon] <maven build options>"
-  echo "See Spark's \"Building with Maven\" doc for correct Maven options."
+  echo "See Spark's \"Building Spark\" doc for correct Maven options."
   echo ""
   exit 1
 }