From 61e21fe7f478e7b06b72851f26b87d99cbbdf117 Mon Sep 17 00:00:00 2001 From: Sean Owen Date: Tue, 16 Sep 2014 09:18:03 -0700 Subject: SPARK-3069 [DOCS] Build instructions in README are outdated Here's my crack at Bertrand's suggestion. The Github `README.md` contains build info that's outdated.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 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on new pull request page b1c04a1 [Sean Owen] Refer to current online documentation for building, and remove slightly outdated copy in README.md --- CONTRIBUTING.md | 12 +++ README.md | 78 +++----------- docs/README.md | 5 +- docs/_config.yml | 4 +- docs/_layouts/global.html | 2 +- docs/building-spark.md | 180 +++++++++++++++++++++++++++++++ docs/building-with-maven.md | 162 ---------------------------- docs/hadoop-third-party-distributions.md | 2 +- docs/index.md | 4 +- docs/running-on-yarn.md | 2 +- docs/streaming-kinesis-integration.md | 2 +- make-distribution.sh | 2 +- 12 files changed, 221 insertions(+), 234 deletions(-) create mode 100644 CONTRIBUTING.md create mode 100644 docs/building-spark.md delete mode 100644 docs/building-with-maven.md diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md new file mode 100644 index 0000000000..c6b4aa5344 --- /dev/null +++ b/CONTRIBUTING.md @@ -0,0 +1,12 @@ +## 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. diff --git a/README.md b/README.md index 5b09ad8684..b05bbfb5a5 100644 --- a/README.md +++ b/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 . +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 `` section: - - - org.apache.hadoop - hadoop-client - 1.2.1 - - - -## 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. diff --git a/docs/README.md b/docs/README.md index 0a0126c574..fdc89d2eb7 100644 --- a/docs/README.md +++ b/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: diff --git a/docs/_config.yml b/docs/_config.yml index 45b78fe724..d3ea2625c7 100644 --- a/docs/_config.yml +++ b/docs/_config.yml @@ -1,5 +1,7 @@ -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. diff --git a/docs/_layouts/global.html b/docs/_layouts/global.html index b30ab1e521..a53e8a775b 100755 --- a/docs/_layouts/global.html +++ b/docs/_layouts/global.html @@ -109,7 +109,7 @@
  • Hardware Provisioning
  • 3rd-Party Hadoop Distros
  • -
  • Building Spark with Maven
    • +
  • Building Spark
  • Contributing to Spark
    • diff --git a/docs/building-spark.md b/docs/building-spark.md new file mode 100644 index 0000000000..2378092d4a --- /dev/null +++ b/docs/building-spark.md @@ -0,0 +1,180 @@ +--- +layout: global +title: Building Spark +redirect_from: "building-with-maven.html" +--- + +* This will become a table of contents (this text will be scraped). +{:toc} + +Building Spark using Maven requires Maven 3.0.4 or newer and Java 6+. + + +# Setting up Maven's Memory Usage + +You'll need to configure Maven to use more memory than usual by setting `MAVEN_OPTS`. We recommend the following settings: + +{% highlight bash %} +export MAVEN_OPTS="-Xmx2g -XX:MaxPermSize=512M -XX:ReservedCodeCacheSize=512m" +{% endhighlight %} + +If you don't run this, you may see errors like the following: + + [INFO] Compiling 203 Scala sources and 9 Java sources to /Users/me/Development/spark/core/target/scala-{{site.SCALA_BINARY_VERSION}}/classes... + [ERROR] PermGen space -> [Help 1] + + [INFO] Compiling 203 Scala sources and 9 Java sources to /Users/me/Development/spark/core/target/scala-{{site.SCALA_BINARY_VERSION}}/classes... + [ERROR] Java heap space -> [Help 1] + +You can fix this by setting the `MAVEN_OPTS` variable as discussed before. + +**Note:** *For Java 8 and above this step is not required.* + +# Specifying the Hadoop Version + +Because HDFS is not protocol-compatible across versions, if you want to read from HDFS, you'll need to build Spark against the specific HDFS version in your environment. You can do this through the "hadoop.version" property. If unset, Spark will build against Hadoop 1.0.4 by default. Note that certain build profiles are required for particular Hadoop versions: + + + + + + + + + + + + +
    Hadoop versionProfile required
    0.23.xhadoop-0.23
    1.x to 2.1.x(none)
    2.2.xhadoop-2.2
    2.3.xhadoop-2.3
    2.4.xhadoop-2.4
    + +For Apache Hadoop versions 1.x, Cloudera CDH "mr1" distributions, and other Hadoop versions without YARN, use: + +{% highlight bash %} +# Apache Hadoop 1.2.1 +mvn -Dhadoop.version=1.2.1 -DskipTests clean package + +# Cloudera CDH 4.2.0 with MapReduce v1 +mvn -Dhadoop.version=2.0.0-mr1-cdh4.2.0 -DskipTests clean package + +# Apache Hadoop 0.23.x +mvn -Phadoop-0.23 -Dhadoop.version=0.23.7 -DskipTests clean package +{% endhighlight %} + +For Apache Hadoop 2.x, 0.23.x, Cloudera CDH, and other Hadoop versions with YARN, you can enable the "yarn-alpha" or "yarn" profile and optionally set the "yarn.version" property if it is different from "hadoop.version". The additional build profile required depends on the YARN version: + + + + + + + + + +
    YARN versionProfile required
    0.23.x to 2.1.xyarn-alpha
    2.2.x and lateryarn
    + +Examples: + +{% highlight bash %} +# Apache Hadoop 2.0.5-alpha +mvn -Pyarn-alpha -Dhadoop.version=2.0.5-alpha -DskipTests clean package + +# Cloudera CDH 4.2.0 +mvn -Pyarn-alpha -Dhadoop.version=2.0.0-cdh4.2.0 -DskipTests clean package + +# Apache Hadoop 0.23.x +mvn -Pyarn-alpha -Phadoop-0.23 -Dhadoop.version=0.23.7 -DskipTests clean package + +# Apache Hadoop 2.2.X +mvn -Pyarn -Phadoop-2.2 -Dhadoop.version=2.2.0 -DskipTests clean package + +# Apache Hadoop 2.3.X +mvn -Pyarn -Phadoop-2.3 -Dhadoop.version=2.3.0 -DskipTests clean package + +# Apache Hadoop 2.4.X +mvn -Pyarn -Phadoop-2.4 -Dhadoop.version=2.4.0 -DskipTests clean package + +# Different versions of HDFS and YARN. +mvn -Pyarn-alpha -Phadoop-2.3 -Dhadoop.version=2.3.0 -Dyarn.version=0.23.7 -DskipTests clean package +{% endhighlight %} + +# Building With Hive and JDBC Support +To enable Hive integration for Spark SQL along with its JDBC server and CLI, +add the `-Phive` profile to your existing build options. +{% highlight bash %} +# Apache Hadoop 2.4.X with Hive support +mvn -Pyarn -Phadoop-2.4 -Dhadoop.version=2.4.0 -Phive -DskipTests clean package +{% endhighlight %} + +# Spark Tests in Maven + +Tests are run by default via the [ScalaTest Maven plugin](http://www.scalatest.org/user_guide/using_the_scalatest_maven_plugin). + +Some of the tests require Spark to be packaged first, so always run `mvn package` with `-DskipTests` the first time. The following is an example of a correct (build, test) sequence: + + mvn -Pyarn -Phadoop-2.3 -DskipTests -Phive clean package + mvn -Pyarn -Phadoop-2.3 -Phive test + +The ScalaTest plugin also supports running only a specific test suite as follows: + + mvn -Dhadoop.version=... -DwildcardSuites=org.apache.spark.repl.ReplSuite test + + +# Continuous Compilation + +We use the scala-maven-plugin which supports incremental and continuous compilation. E.g. + + mvn scala:cc + +should run continuous compilation (i.e. wait for changes). However, this has not been tested extensively. + +# Using With IntelliJ IDEA + +This setup works fine in IntelliJ IDEA 11.1.4. After opening the project via the pom.xml file in the project root folder, you only need to activate either the hadoop1 or hadoop2 profile in the "Maven Properties" popout. We have not tried Eclipse/Scala IDE with this. + +# Building Spark Debian Packages + +The Maven build includes support for building a Debian package containing the assembly 'fat-jar', PySpark, and the necessary scripts and configuration files. This can be created by specifying the following: + + mvn -Pdeb -DskipTests clean package + +The debian package can then be found under assembly/target. We added the short commit hash to the file name so that we can distinguish individual packages built for SNAPSHOT versions. + +# Running Java 8 Test Suites + +Running only Java 8 tests and nothing else. + + mvn install -DskipTests -Pjava8-tests + +Java 8 tests are run when `-Pjava8-tests` profile is enabled, they will run in spite of `-DskipTests`. +For these tests to run your system must have a JDK 8 installation. +If you have JDK 8 installed but it is not the system default, you can set JAVA_HOME to point to JDK 8 before running the tests. + +# Building for PySpark on YARN + +PySpark on YARN is only supported if the jar is built with Maven. Further, there is a known problem +with building this assembly jar on Red Hat based operating systems (see [SPARK-1753](https://issues.apache.org/jira/browse/SPARK-1753)). If you wish to +run PySpark on a YARN cluster with Red Hat installed, we recommend that you build the jar elsewhere, +then ship it over to the cluster. We are investigating the exact cause for this. + +# Packaging without Hadoop Dependencies for YARN + +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 diff --git a/docs/building-with-maven.md b/docs/building-with-maven.md deleted file mode 100644 index bce7412c7d..0000000000 --- a/docs/building-with-maven.md +++ /dev/null @@ -1,162 +0,0 @@ ---- -layout: global -title: Building Spark with Maven ---- - -* This will become a table of contents (this text will be scraped). -{:toc} - -Building Spark using Maven requires Maven 3.0.4 or newer and Java 6+. - - -# Setting up Maven's Memory Usage - -You'll need to configure Maven to use more memory than usual by setting `MAVEN_OPTS`. We recommend the following settings: - -{% highlight bash %} -export MAVEN_OPTS="-Xmx2g -XX:MaxPermSize=512M -XX:ReservedCodeCacheSize=512m" -{% endhighlight %} - -If you don't run this, you may see errors like the following: - - [INFO] Compiling 203 Scala sources and 9 Java sources to /Users/me/Development/spark/core/target/scala-{{site.SCALA_BINARY_VERSION}}/classes... - [ERROR] PermGen space -> [Help 1] - - [INFO] Compiling 203 Scala sources and 9 Java sources to /Users/me/Development/spark/core/target/scala-{{site.SCALA_BINARY_VERSION}}/classes... - [ERROR] Java heap space -> [Help 1] - -You can fix this by setting the `MAVEN_OPTS` variable as discussed before. - -**Note:** *For Java 8 and above this step is not required.* - -# Specifying the Hadoop Version - -Because HDFS is not protocol-compatible across versions, if you want to read from HDFS, you'll need to build Spark against the specific HDFS version in your environment. You can do this through the "hadoop.version" property. If unset, Spark will build against Hadoop 1.0.4 by default. Note that certain build profiles are required for particular Hadoop versions: - - - - - - - - - - - - -
    Hadoop versionProfile required
    0.23.xhadoop-0.23
    1.x to 2.1.x(none)
    2.2.xhadoop-2.2
    2.3.xhadoop-2.3
    2.4.xhadoop-2.4
    - -For Apache Hadoop versions 1.x, Cloudera CDH "mr1" distributions, and other Hadoop versions without YARN, use: - -{% highlight bash %} -# Apache Hadoop 1.2.1 -mvn -Dhadoop.version=1.2.1 -DskipTests clean package - -# Cloudera CDH 4.2.0 with MapReduce v1 -mvn -Dhadoop.version=2.0.0-mr1-cdh4.2.0 -DskipTests clean package - -# Apache Hadoop 0.23.x -mvn -Phadoop-0.23 -Dhadoop.version=0.23.7 -DskipTests clean package -{% endhighlight %} - -For Apache Hadoop 2.x, 0.23.x, Cloudera CDH, and other Hadoop versions with YARN, you can enable the "yarn-alpha" or "yarn" profile and optionally set the "yarn.version" property if it is different from "hadoop.version". The additional build profile required depends on the YARN version: - - - - - - - - - -
    YARN versionProfile required
    0.23.x to 2.1.xyarn-alpha
    2.2.x and lateryarn
    - -Examples: - -{% highlight bash %} -# Apache Hadoop 2.0.5-alpha -mvn -Pyarn-alpha -Dhadoop.version=2.0.5-alpha -DskipTests clean package - -# Cloudera CDH 4.2.0 -mvn -Pyarn-alpha -Dhadoop.version=2.0.0-cdh4.2.0 -DskipTests clean package - -# Apache Hadoop 0.23.x -mvn -Pyarn-alpha -Phadoop-0.23 -Dhadoop.version=0.23.7 -DskipTests clean package - -# Apache Hadoop 2.2.X -mvn -Pyarn -Phadoop-2.2 -Dhadoop.version=2.2.0 -DskipTests clean package - -# Apache Hadoop 2.3.X -mvn -Pyarn -Phadoop-2.3 -Dhadoop.version=2.3.0 -DskipTests clean package - -# Apache Hadoop 2.4.X -mvn -Pyarn -Phadoop-2.4 -Dhadoop.version=2.4.0 -DskipTests clean package - -# Different versions of HDFS and YARN. -mvn -Pyarn-alpha -Phadoop-2.3 -Dhadoop.version=2.3.0 -Dyarn.version=0.23.7 -DskipTests clean package -{% endhighlight %} - -# Building With Hive and JDBC Support -To enable Hive integration for Spark SQL along with its JDBC server and CLI, -add the `-Phive` profile to your existing build options. -{% highlight bash %} -# Apache Hadoop 2.4.X with Hive support -mvn -Pyarn -Phadoop-2.4 -Dhadoop.version=2.4.0 -Phive -DskipTests clean package -{% endhighlight %} - -# Spark Tests in Maven - -Tests are run by default via the [ScalaTest Maven plugin](http://www.scalatest.org/user_guide/using_the_scalatest_maven_plugin). - -Some of the tests require Spark to be packaged first, so always run `mvn package` with `-DskipTests` the first time. The following is an example of a correct (build, test) sequence: - - mvn -Pyarn -Phadoop-2.3 -DskipTests -Phive clean package - mvn -Pyarn -Phadoop-2.3 -Phive test - -The ScalaTest plugin also supports running only a specific test suite as follows: - - mvn -Dhadoop.version=... -DwildcardSuites=org.apache.spark.repl.ReplSuite test - - -# Continuous Compilation - -We use the scala-maven-plugin which supports incremental and continuous compilation. E.g. - - mvn scala:cc - -should run continuous compilation (i.e. wait for changes). However, this has not been tested extensively. - -# Using With IntelliJ IDEA - -This setup works fine in IntelliJ IDEA 11.1.4. After opening the project via the pom.xml file in the project root folder, you only need to activate either the hadoop1 or hadoop2 profile in the "Maven Properties" popout. We have not tried Eclipse/Scala IDE with this. - -# Building Spark Debian Packages - -The Maven build includes support for building a Debian package containing the assembly 'fat-jar', PySpark, and the necessary scripts and configuration files. This can be created by specifying the following: - - mvn -Pdeb -DskipTests clean package - -The debian package can then be found under assembly/target. We added the short commit hash to the file name so that we can distinguish individual packages built for SNAPSHOT versions. - -# Running Java 8 Test Suites - -Running only Java 8 tests and nothing else. - - mvn install -DskipTests -Pjava8-tests - -Java 8 tests are run when `-Pjava8-tests` profile is enabled, they will run in spite of `-DskipTests`. -For these tests to run your system must have a JDK 8 installation. -If you have JDK 8 installed but it is not the system default, you can set JAVA_HOME to point to JDK 8 before running the tests. - -# Building for PySpark on YARN - -PySpark on YARN is only supported if the jar is built with Maven. Further, there is a known problem -with building this assembly jar on Red Hat based operating systems (see [SPARK-1753](https://issues.apache.org/jira/browse/SPARK-1753)). If you wish to -run PySpark on a YARN cluster with Red Hat installed, we recommend that you build the jar elsewhere, -then ship it over to the cluster. We are investigating the exact cause for this. - -# Packaging without Hadoop Dependencies for YARN - -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. - - diff --git a/docs/hadoop-third-party-distributions.md b/docs/hadoop-third-party-distributions.md index ab1023b8f1..dd73e9dc54 100644 --- a/docs/hadoop-third-party-distributions.md +++ b/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 diff --git a/docs/index.md b/docs/index.md index 7fe6b43d32..e8ebadbd4e 100644 --- a/docs/index.md +++ b/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: * [3rd 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:** diff --git a/docs/running-on-yarn.md b/docs/running-on-yarn.md index 212248bcce..74bcc2eeb6 100644 --- a/docs/running-on-yarn.md +++ b/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 diff --git a/docs/streaming-kinesis-integration.md b/docs/streaming-kinesis-integration.md index c6090d9ec3..379eb513d5 100644 --- a/docs/streaming-kinesis-integration.md +++ b/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 diff --git a/make-distribution.sh b/make-distribution.sh index 9b012b9222..884659954a 100755 --- a/make-distribution.sh +++ b/make-distribution.sh @@ -40,7 +40,7 @@ function exit_with_usage { echo "" echo "usage:" echo "./make-distribution.sh [--name] [--tgz] [--with-tachyon] " - 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 } -- cgit v1.2.3