Repository: spark Updated Branches: refs/heads/master 4134ff0c6 -> 932d80029
[SPARK-15333][DOCS] Reorganize building-spark.md; rationalize vs wiki ## What changes were proposed in this pull request? See JIRA for the motivation. The changes are almost entirely movement of text and edits to sections. Minor changes to text include: - Copying in / merging text from the "Useful Developer Tools" wiki, in areas of - Docker - R - Running one test - standardizing on ./build/mvn not mvn, and likewise for ./build/sbt - correcting some typos - standardizing code block formatting No text has been removed from this doc; text has been imported from the https://cwiki.apache.org/confluence/display/SPARK/Useful+Developer+Tools wiki ## How was this patch tested? Jekyll doc build and inspection of resulting HTML in browser. Author: Sean Owen <so...@cloudera.com> Closes #13124 from srowen/SPARK-15333. Project: http://git-wip-us.apache.org/repos/asf/spark/repo Commit: http://git-wip-us.apache.org/repos/asf/spark/commit/932d8002 Tree: http://git-wip-us.apache.org/repos/asf/spark/tree/932d8002 Diff: http://git-wip-us.apache.org/repos/asf/spark/diff/932d8002 Branch: refs/heads/master Commit: 932d8002931d352dd2ec87184e6c84ec5fa859cd Parents: 4134ff0 Author: Sean Owen <so...@cloudera.com> Authored: Tue May 17 16:40:38 2016 +0100 Committer: Sean Owen <so...@cloudera.com> Committed: Tue May 17 16:40:38 2016 +0100 ---------------------------------------------------------------------- docs/building-spark.md | 295 +++++++++++++++++++++++--------------------- 1 file changed, 156 insertions(+), 139 deletions(-) ---------------------------------------------------------------------- http://git-wip-us.apache.org/repos/asf/spark/blob/932d8002/docs/building-spark.md ---------------------------------------------------------------------- diff --git a/docs/building-spark.md b/docs/building-spark.md index 63532c7..2c987cf 100644 --- a/docs/building-spark.md +++ b/docs/building-spark.md @@ -7,48 +7,18 @@ 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 3.3.9 or newer and Java 7+. -The Spark build can supply a suitable Maven binary; see below. - -# Building with `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: - -{% highlight bash %} -build/mvn -Pyarn -Phadoop-2.4 -Dhadoop.version=2.4.0 -DskipTests clean package -{% endhighlight %} - -Other build examples can be found below. - -**Note:** When building on an encrypted filesystem (if your home directory is encrypted, for example), then the Spark build might fail with a "Filename too long" error. As a workaround, add the following in the configuration args of the `scala-maven-plugin` in the project `pom.xml`: - - <arg>-Xmax-classfile-name</arg> - <arg>128</arg> - -and in `project/SparkBuild.scala` add: - - scalacOptions in Compile ++= Seq("-Xmax-classfile-name", "128"), - -to the `sharedSettings` val. See also [this PR](https://github.com/apache/spark/pull/2883/files) if you are unsure of where to add these lines. - -# Building a Runnable Distribution +# Building Apache Spark -To create a Spark distribution like those distributed by the -[Spark Downloads](http://spark.apache.org/downloads.html) page, and that is laid out so as -to be runnable, use `./dev/make-distribution.sh` in the project root directory. It can be configured -with Maven profile settings and so on like the direct Maven build. Example: +## Apache Maven - ./dev/make-distribution.sh --name custom-spark --tgz -Psparkr -Phadoop-2.4 -Phive -Phive-thriftserver -Pyarn - -For more information on usage, run `./dev/make-distribution.sh --help` +The Maven-based build is the build of reference for Apache Spark. +Building Spark using Maven requires Maven 3.3.9 or newer and Java 7+. -# Setting up Maven's Memory Usage +### 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 %} + export MAVEN_OPTS="-Xmx2g -XX:MaxPermSize=512M -XX:ReservedCodeCacheSize=512m" If you don't run this, you may see errors like the following: @@ -65,7 +35,26 @@ You can fix this by setting the `MAVEN_OPTS` variable as discussed before. * For Java 8 and above this step is not required. * If using `build/mvn` with no `MAVEN_OPTS` set, the script will automate this for you. -# Specifying the Hadoop Version +### 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: + + ./build/mvn -Pyarn -Phadoop-2.4 -Dhadoop.version=2.4.0 -DskipTests clean package + +Other build examples can be found below. + +## Building a Runnable Distribution + +To create a Spark distribution like those distributed by the +[Spark Downloads](http://spark.apache.org/downloads.html) page, and that is laid out so as +to be runnable, use `./dev/make-distribution.sh` in the project root directory. It can be configured +with Maven profile settings and so on like the direct Maven build. Example: + + ./dev/make-distribution.sh --name custom-spark --tgz -Psparkr -Phadoop-2.4 -Phive -Phive-thriftserver -Pyarn + +For more information on usage, run `./dev/make-distribution.sh --help` + +## 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 2.2.0 by default. Note that certain build profiles are required for particular Hadoop versions: @@ -87,87 +76,63 @@ You can enable the `yarn` profile and optionally set the `yarn.version` property Examples: -{% highlight bash %} + # Apache Hadoop 2.2.X + ./build/mvn -Pyarn -Phadoop-2.2 -DskipTests clean package -# Apache Hadoop 2.2.X -mvn -Pyarn -Phadoop-2.2 -DskipTests clean package + # Apache Hadoop 2.3.X + ./build/mvn -Pyarn -Phadoop-2.3 -Dhadoop.version=2.3.0 -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 or 2.5.X + ./build/mvn -Pyarn -Phadoop-2.4 -Dhadoop.version=VERSION -DskipTests clean package -# Apache Hadoop 2.4.X or 2.5.X -mvn -Pyarn -Phadoop-2.4 -Dhadoop.version=VERSION -DskipTests clean package + # Apache Hadoop 2.6.X + ./build/mvn -Pyarn -Phadoop-2.6 -Dhadoop.version=2.6.0 -DskipTests clean package -# Apache Hadoop 2.6.X -mvn -Pyarn -Phadoop-2.6 -Dhadoop.version=2.6.0 -DskipTests clean package + # Apache Hadoop 2.7.X and later + ./build/mvn -Pyarn -Phadoop-2.7 -Dhadoop.version=VERSION -DskipTests clean package -# Apache Hadoop 2.7.X and later -mvn -Pyarn -Phadoop-2.7 -Dhadoop.version=VERSION -DskipTests clean package + # Different versions of HDFS and YARN. + ./build/mvn -Pyarn -Phadoop-2.3 -Dhadoop.version=2.3.0 -Dyarn.version=2.2.0 -DskipTests clean package -# Different versions of HDFS and YARN. -mvn -Pyarn -Phadoop-2.3 -Dhadoop.version=2.3.0 -Dyarn.version=2.2.0 -DskipTests clean package -{% endhighlight %} +## Building With Hive and JDBC Support -# Building With Hive and JDBC Support To enable Hive integration for Spark SQL along with its JDBC server and CLI, add the `-Phive` and `Phive-thriftserver` profiles to your existing build options. By default Spark will build with Hive 1.2.1 bindings. -{% highlight bash %} -# Apache Hadoop 2.4.X with Hive 1.2.1 support -mvn -Pyarn -Phadoop-2.4 -Dhadoop.version=2.4.0 -Phive -Phive-thriftserver -DskipTests clean package -{% endhighlight %} - -# Building for Scala 2.10 -To produce a Spark package compiled with Scala 2.10, use the `-Dscala-2.10` property: - - ./dev/change-scala-version.sh 2.10 - mvn -Pyarn -Phadoop-2.4 -Dscala-2.10 -DskipTests clean package - -# PySpark Tests with Maven -If you are building PySpark and wish to run the PySpark tests you will need to build Spark with hive support. + # Apache Hadoop 2.4.X with Hive 1.2.1 support + ./build/mvn -Pyarn -Phadoop-2.4 -Dhadoop.version=2.4.0 -Phive -Phive-thriftserver -DskipTests clean package -{% highlight bash %} -build/mvn -DskipTests clean package -Phive -./python/run-tests -{% endhighlight %} +## Packaging without Hadoop Dependencies for YARN -The run-tests script also can be limited to a specific Python version or a specific module - - ./python/run-tests --python-executables=python --modules=pyspark-sql - -**Note:** You can also run Python tests with an sbt build, provided you build Spark with hive support. - -# 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). +The assembly directory 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. -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 -Phive-thriftserver clean package - mvn -Pyarn -Phadoop-2.3 -Phive -Phive-thriftserver test - -The ScalaTest plugin also supports running only a specific test suite as follows: +## Building for Scala 2.10 +To produce a Spark package compiled with Scala 2.10, use the `-Dscala-2.10` property: - mvn -Dhadoop.version=... -DwildcardSuites=org.apache.spark.repl.ReplSuite test + ./dev/change-scala-version.sh 2.10 + ./build/mvn -Pyarn -Phadoop-2.4 -Dscala-2.10 -DskipTests clean package -# Building submodules individually +## Building submodules individually It's possible to build Spark sub-modules using the `mvn -pl` option. For instance, you can build the Spark Streaming module using: -{% highlight bash %} -mvn -pl :spark-streaming_2.11 clean install -{% endhighlight %} + ./build/mvn -pl :spark-streaming_2.11 clean install where `spark-streaming_2.11` is the `artifactId` as defined in `streaming/pom.xml` file. -# Continuous Compilation +## Continuous Compilation We use the scala-maven-plugin which supports incremental and continuous compilation. E.g. - mvn scala:cc + ./build/mvn scala:cc should run continuous compilation (i.e. wait for changes). However, this has not been tested extensively. A couple of gotchas to note: @@ -182,86 +147,138 @@ the `spark-parent` module). Thus, the full flow for running continuous-compilation of the `core` submodule may look more like: - $ mvn install + $ ./build/mvn install $ cd core - $ mvn scala:cc + $ ../build/mvn scala:cc -# Building Spark with IntelliJ IDEA or Eclipse +## Speeding up Compilation with Zinc -For help in setting up IntelliJ IDEA or Eclipse for Spark development, and troubleshooting, refer to the -[wiki page for IDE setup](https://cwiki.apache.org/confluence/display/SPARK/Useful+Developer+Tools#UsefulDeveloperTools-IDESetup). +[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`. -# Running Java 8 Test Suites +If using the `build/mvn` package `zinc` will automatically be downloaded and leveraged for all +builds. This process will auto-start after the first time `build/mvn` is called and bind to port +3030 unless the `ZINC_PORT` environment variable is set. The `zinc` process can subsequently be +shut down at any time by running `build/zinc-<version>/bin/zinc -shutdown` and will automatically +restart whenever `build/mvn` is called. -Running only Java 8 tests and nothing else. +## Building with SBT - mvn install -DskipTests - mvn -pl :java8-tests_2.11 test +Maven is the official build tool recommended 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. -or +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 java8-tests/test + ./build/sbt -Pyarn -Phadoop-2.3 package -Java 8 tests are automatically enabled when a Java 8 JDK is detected. -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. +To avoid the overhead of launching sbt each time you need to re-compile, you can launch sbt +in interactive mode by running `build/sbt`, and then run all build commands at the command +prompt. For more recommendations on reducing build time, refer to the +[wiki page](https://cwiki.apache.org/confluence/display/SPARK/Useful+Developer+Tools#UsefulDeveloperTools-ReducingBuildTimes). -# Running Docker based Integration Test Suites +##Â Encrypted Filesystems -Running only docker based integration tests and nothing else. +When building on an encrypted filesystem (if your home directory is encrypted, for example), then the Spark build might fail with a "Filename too long" error. As a workaround, add the following in the configuration args of the `scala-maven-plugin` in the project `pom.xml`: - mvn install -DskipTests - mvn -Pdocker-integration-tests -pl :spark-docker-integration-tests_2.11 + <arg>-Xmax-classfile-name</arg> + <arg>128</arg> -or +and in `project/SparkBuild.scala` add: - sbt docker-integration-tests/test + scalacOptions in Compile ++= Seq("-Xmax-classfile-name", "128"), +to the `sharedSettings` val. See also [this PR](https://github.com/apache/spark/pull/2883/files) if you are unsure of where to add these lines. -# Packaging without Hadoop Dependencies for YARN +## IntelliJ IDEA or Eclipse -The assembly directory 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. +For help in setting up IntelliJ IDEA or Eclipse for Spark development, and troubleshooting, refer to the +[wiki page for IDE setup](https://cwiki.apache.org/confluence/display/SPARK/Useful+Developer+Tools#UsefulDeveloperTools-IDESetup). -# Building with SBT -Maven is the official build tool recommended 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. +# Running Tests -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: +Tests are run by default via the [ScalaTest Maven plugin](http://www.scalatest.org/user_guide/using_the_scalatest_maven_plugin). - build/sbt -Pyarn -Phadoop-2.3 package +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: -To avoid the overhead of launching sbt each time you need to re-compile, you can launch sbt -in interactive mode by running `build/sbt`, and then run all build commands at the command -prompt. For more recommendations on reducing build time, refer to the -[wiki page](https://cwiki.apache.org/confluence/display/SPARK/Useful+Developer+Tools#UsefulDeveloperTools-ReducingBuildTimes). + ./build/mvn -Pyarn -Phadoop-2.3 -DskipTests -Phive -Phive-thriftserver clean package + ./build/mvn -Pyarn -Phadoop-2.3 -Phive -Phive-thriftserver test + +The ScalaTest plugin also supports running only a specific Scala test suite as follows: + + ./build/mvn -P... -Dtest=none -DwildcardSuites=org.apache.spark.repl.ReplSuite test + ./build/mvn -P... -Dtest=none -DwildcardSuites=org.apache.spark.repl.* test + +or a Java test: -# Testing with SBT + ./build/mvn test -P... -DwildcardSuites=none -Dtest=org.apache.spark.streaming.JavaAPISuite + +## Testing with SBT Some of the tests require Spark to be packaged first, so always run `build/sbt package` the first time. The following is an example of a correct (build, test) sequence: - build/sbt -Pyarn -Phadoop-2.3 -Phive -Phive-thriftserver package - build/sbt -Pyarn -Phadoop-2.3 -Phive -Phive-thriftserver test + ./build/sbt -Pyarn -Phadoop-2.3 -Phive -Phive-thriftserver package + ./build/sbt -Pyarn -Phadoop-2.3 -Phive -Phive-thriftserver test To run only a specific test suite as follows: - build/sbt -Pyarn -Phadoop-2.3 -Phive -Phive-thriftserver "test-only org.apache.spark.repl.ReplSuite" + ./build/sbt -Pyarn -Phadoop-2.3 -Phive -Phive-thriftserver "test-only org.apache.spark.repl.ReplSuite" + ./build/sbt -Pyarn -Phadoop-2.3 -Phive -Phive-thriftserver "test-only org.apache.spark.repl.*" To run test suites of a specific sub project as follows: - build/sbt -Pyarn -Phadoop-2.3 -Phive -Phive-thriftserver core/test + ./build/sbt -Pyarn -Phadoop-2.3 -Phive -Phive-thriftserver core/test -# Speeding up Compilation with Zinc +## Running Java 8 Test Suites -[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`. +Running only Java 8 tests and nothing else. -If using the `build/mvn` package `zinc` will automatically be downloaded and leveraged for all -builds. This process will auto-start after the first time `build/mvn` is called and bind to port -3030 unless the `ZINC_PORT` environment variable is set. The `zinc` process can subsequently be -shut down at any time by running `build/zinc-<version>/bin/zinc -shutdown` and will automatically -restart whenever `build/mvn` is called. + ./build/mvn install -DskipTests + ./build/mvn -pl :java8-tests_2.11 test + +or + + ./build/sbt java8-tests/test + +Java 8 tests are automatically enabled when a Java 8 JDK is detected. +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. + +## PySpark Tests with Maven + +If you are building PySpark and wish to run the PySpark tests you will need to build Spark with Hive support. + + ./build/mvn -DskipTests clean package -Phive + ./python/run-tests + +The run-tests script also can be limited to a specific Python version or a specific module + + ./python/run-tests --python-executables=python --modules=pyspark-sql + +**Note:** You can also run Python tests with an sbt build, provided you build Spark with Hive support. + +## Running R Tests + +To run the SparkR tests you will need to install the R package `testthat` +(run `install.packages(testthat)` from R shell). You can run just the SparkR tests using +the command: + + ./R/run-tests.sh + +## Running Docker-based Integration Test Suites + +In order to run Docker integration tests, you have to install the `docker` engine on your box. +The instructions for installation can be found at [the Docker site](https://docs.docker.com/engine/installation/). +Once installed, the `docker` service needs to be started, if not already running. +On Linux, this can be done by `sudo service docker start`. + + ./build/mvn install -DskipTests + ./build/mvn -Pdocker-integration-tests -pl :spark-docker-integration-tests_2.11 + +or + + ./build/sbt docker-integration-tests/test --------------------------------------------------------------------- To unsubscribe, e-mail: commits-unsubscr...@spark.apache.org For additional commands, e-mail: commits-h...@spark.apache.org