bigtop

Bigtop is an Apache Foundation project for Infrastructure Engineers and Data Scientists looking for comprehensive packaging, testing, and configuration of the leading open source big data components.

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(the “License”); you may not use this file except in compliance with
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Apache Bigtop

…is a project for the development of packaging and tests of the Apache Hadoop ecosystem.

The primary goal of Apache Bigtop is to build a community around the packaging and interoperability testing of Apache Hadoop-related projects. This includes testing at various levels (packaging, platform, runtime, upgrade, etc…) developed by a community with a focus on the system as a whole, rather than individual projects.

Immediately Get Started with Deployment and Smoke Testing of BigTop

The simplest way to get a feel for how bigtop works, is to just cd into provisioner and try out the docker recipes. It rapidly spins up, and runs the bigtop smoke tests on, a local bigtop based big data distribution. Once you get the gist, you can hack around with the recipes to learn how the puppet/rpm/smoke-tests all work together, going deeper into the components you are interested in as described below.

Quick overview of source code directories

bigtop-deploy : deployment scripts and puppet stuff for Apache Bigtop.
bigtop-packages : RPM/DEB specifications for Apache Bigtop subcomponents.
bigtop-test-framework : The source code for the iTest utilities (framework used by smoke tests).
bigtop-tests :
test-artifacts : source for tests.
test-execution : maven pom drivers for running the integration tests found in test-artifacts.
bigtop-toolchain : puppet scripts for setting up an instance which can build Apache Bigtop, sets up utils like jdk/maven/protobufs/…
provisioner : Docker Provisioner that automatically spin up Hadoop environment with one click.
docker : Dockerfiles and Docker Sandbox build scripts.

Also, there is a new project underway, Apache Bigtop blueprints, which aims to create templates/examples that demonstrate/compare various Apache Hadoop ecosystem components with one another.

Contributing

There are lots of ways to contribute. People with different expertise can help with various subprojects:

puppet : Much of the Apache Bigtop deploy and packaging tools use puppet to bootstrap and set up a cluster. But recipes for other tools are also welcome (ie. Chef, Ansible, etc.)
groovy : Primary language used to write the Apache Bigtop smokes and itest framework.
maven : Used to build Apache Bigtop smokes and also to define the high level Apache Bigtop project.
RPM/DEB : Used to package Apache Hadoop ecosystem related projects into GNU/Linux installable packages for most popular GNU/Linux distributions. So one could add a new project or improve existing packages.
hadoop : Apache Hadoop users can also contribute by using the Apache Bigtop smokes, improving them, and evaluating their breadth.
contributing your workloads : Contributing your workloads enable us to tests projects against real use cases and enable you to have people verifying the use cases you care about are always working.
documentation : We are always in need of a better documentation!
giving feedback : Tell us how you use Apache Bigtop, what was great and what was not so great. Also, what are you expecting from it and what would you like to see in the future?

Also, opening JIRA’s and getting started by posting on the mailing list is helpful.

What do people use Apache Bigtop for?

You can go to the Apache Bigtop website for notes on how to do “common” tasks like:

Apache Hadoop App developers: Download an Apache Bigtop built Apache Hadoop 2.0 VM from the website, so you can have a running psuedodistributed Apache Hadoop cluster to test your code on.
Cluster administers or deployment gurus: Run the Apache Bigtop smoke tests to ensure that your cluster is working.
Vendors: Build your own Apache Hadoop distribution, customized from Apache Bigtop bits.

Getting Started

Below are some recipes for getting started with using Apache Bigtop. As Apache Bigtop has different subprojects, these recipes will continue to evolve.
For specific questions it’s always a good idea to ping the mailing list at [email protected] to get some immediate feedback, or open a JIRA.

For Users: Running the smoke tests

The simplest way to test bigtop is described in bigtop-tests/smoke-tests/README file

For integration (API level) testing with maven, read on.

For Users: Running the integration tests

WARNING: since testing packages requires installing them on a live system it is highly recommended to use VMs for that. Testing Apache Bigtop is done using iTest framework. The tests are organized in maven submodules, with one submodule per Apache Bigtop component. The bigtop-tests/test-execution/smokes/pom.xml defines all submodules to be tested, and each submodule is in its own directory under smokes/, for example:

smokes/hadoop/pom.xml
smokes/hive/pom.xml
… and so on.

New way (with Gradle build in place)
- Step 1: install smoke tests for one or more components
  - Example 1:
    
    gradle installTestArtifacts
  - Example 2: Installing just Hadoop-specific smoke tests
    
    gradle install-hadoop
- Step 2: Run the the smoke tests on your cluster (see Step 3 and/or Step 4 below)
We are on the route of migrating subprojects under top-level gradle build. Currently
converted projects could be listed by running
```
  gradle projects
```
To see the list of tasks in a subproject, ie itest-common, you can run
```
  gradle itest-common:tasks
```
Old Way
- Step 1: Build the smokes with snapshots. This ensures that all transitive dependencies etc… are in your repo
```
mvn clean install -DskipTests -DskipITs -DperformRelease -f ./bigtop-test-framework/pom.xml
mvn clean install -DskipTests -DskipITs -DperformRelease -f ./test-artifacts/pom.xml
```
- Step 2: Now, rebuild in “offline” mode. This will make sure that your local changes to bigtop are embeded in the changes.
```
mvn clean install -DskipTests -DskipITs -DperformRelease -o -nsu -f ./bigtop-test-framework/pom.xml
mvn clean install -DskipTests -DskipITs -DperformRelease -o -nsu -f ./bigtop-tests/test-artifacts/pom.xml
```
- Step 3: Now, you can run the smoke tests on your cluster.
  - Example 1: Running all the smoke tests with TRACE level logging (shows std out from each mr job).
```
  mvn clean verify -Dorg.apache.bigtop.itest.log4j.level=TRACE -f ./bigtop/bigtop-tests/test-execution/smokes/pom.xml
```
  - Just running hadoop examples, nothing else.
```
  mvn clean verify -D'org.apache.maven-failsafe-plugin.testInclude=**/*TestHadoopExamples*' -f bigtop-tests/test-execution/smokes/hadoop/pom.xml
```
  Note: A minor bug/issue: you need the “testInclude” regular expression above, even if you don’t want to customize the tests,
  since existing test names don’t follow the maven integration test naming convention of IT*, but instead, follow the surefire (unit test) convention of Test*.

For Users: Creating Your Own Apache Hadoop Environment

Another common use case for Apache Bigtop is creating / setting up your own Apache Hadoop distribution.
For details on this, check out the bigtop-deploy/README.md file, which describes how to use the puppet repos
to create and setup your VMs.
You can also try out provisioner to quickly get the idea how it works.

For Developers: Building the entire distribution from scratch

Packages have been built for CentOS, Fedora, OpenSUSE, Ubuntu, and Debian. They can probably be built for other platforms as well. Some of the binary artifacts might be compatible with other closely related distributions.

On all systems, Building Apache Bigtop requires certain set of tools

To bootstrap the development environment from scratch execute

./gradlew toolchain

This build task expected Puppet to be installed; user has to have sudo permissions. The task will pull down and install
all development dependencies, frameworks and SDKs, required to build the stack on your platform.

Before executing the above command, user can use the following script to install Puppet:

sudo bigtop_toolchain/bin/puppetize.sh

Note for CentOS (and RHEL, which is not supported officially but on a best effort basis) 8 users: on these distros,
puppetize.sh installs the puppet command into /opt/puppetlabs/bin, which is not included usually in secure_path defined in /etc/sudoers.
So users may have to add that path to secure_path manually.
Also, RHEL 8 users may have to enable their subscriptions themselves for using EPEL.
cf. https://fedoraproject.org/wiki/EPEL#How_can_I_use_these_extra_packages.3F

To immediately set environment after running toolchain, run

. /etc/profile.d/bigtop.sh

Building packages : gradle [component-name]-pkg

If -Dbuildwithdeps=true is set, the Gradle will follow the order of the build specified in
the “dependencies” section of bigtop.bom file. Otherwise just a single component will get build (original behavior).

To use an alternative definition of a stack composition (aka BOM), specify its
name with -Dbomfile=<filename> system property in the build time.

You can visualize all tasks dependencies by running gradle tasks --all
Customize build packages(BIGTOP-3784)

By default, the installation path of components will follow Filesystem Hierarchy Standard, but you can use -PparentDir=/path to add prefix to the path, in this example, prefix /path/${bigtop_version} will be added

To avoid download wrong version of components when you have multiple repositories configured on your machine, you can use -PpkgSuffix to add bigtop version to package suffix, for example, package name zookeeper will be changed to zookeeper_3_2_0 when using Bigtop-3.2.0
Enabling Parallel Build for packages(BIGTOP-4044)

Apache Bigtop defaults to non-parallel builds. Use -PbuildThreads with a number or a combination of numbers followed by ‘C’, such as ‘-PbuildThreads=2’ or ‘-PbuildThreads=2C’, to specify the number of CPU cores for Maven’s parallel build feature, which can speed up the compilation process for compatible components.

Consult the bigtop.bom file to verify component compatibility with parallel builds; those marked with maven_parallel_build = true support this option.
Building local YUM/APT repositories : gradle [yum|apt]
Recommended build environments

Bigtop provides “development in the can” environments, using Docker containers.
These have the build tools set by the toolchain, as well as the user and build
environment configured and cached. All currently supported OSes could be pulled
from official Bigtop repository at https://hub.docker.com/r/bigtop/slaves/tags/

To build a component (bigtop-groovy) for a particular OS (ubuntu-22.04) you can
run the following from a clone of Bigtop workspace (assuming your system has
Docker engine setup and working)
docker run --rm -u jenkins:jenkins -v `pwd`:/ws --workdir /ws bigtop/slaves:trunk-ubuntu-22.04 bash -l -c './gradlew allclean ; ./gradlew bigtop-groovy-pkg'

For Developers: Building and modifying the web site

The website can be built by running mvn site:site from the root directory of the
project. The main page can be accessed from “project_root/target/site/index.html”.

The source for the website is located in “project_root/src/site/”.

For Developers: Building a component from Git repository

Prerequisites

You will need git installed.
You will need java 8 installed.
You will need to use gradlew which is included in the source code. (Right in the root of the project folder)
This project’s gradlew has more documentation here
Use git to download BigTop :

git clone https://github.com/apache/bigtop.git

move into the root project folder:

cd bigtop

To fetch source from a Git repository, there’re two ways to achieve this:
a). modify ./bigtop.bom and add JSON snippets to your component/package, or
b). specify properties at command line

bigtop.bom

Add following JSON snippets to the desired component/package:

git     { repo = ""; ref = ""; dir = ""; commit_hash = "" }

repo - SSH, HTTP or local path to Git repo.
ref - branch, tag or commit hash to check out.
dir - [OPTIONAL] directory name to write source into.
commit_hash - [OPTIONAL] a commit hash to reset to.

Some packages have different names for source directory and source tarball
(hbase-0.98.5-src.tar.gz contains hbase-0.98.5 directory).
By default source will be fetched in a directory named by tarball { source = TARBALL_SRC }
without .t* extension.
To explicitly set directory name use the dir option.

When commit_hash specified, the repo to build the package will be reset to the commit hash.

Example for HBase:

      name    = 'hbase'
      version { base = '1.3.2'; pkg = base; release = 1 }
      git     { repo = "https://github.com/apache/hbase.git"
                ref  = "branch-1.3"
                dir  = "${name}-${version.base}"
                commit_hash = "1bedb5bfbb5a99067e7bc54718c3124f632b6e17"
              }

command line

./gradlew [component]-pkg-ind -Pgit_repo="" -Pgit_ref="" -Pgit_dir="" -Pgit_commit_hash="" -Pbase_version=""

Where git_repo, git_ref, git_dir, and git_commit_hash are exactly the same with what we set in JSON.
And base_version is to overwrite:

      version { base = ''}

Example for Kafka:

./gradlew kafka-pkg-ind -Pgit_repo=https://github.com/apache/kafka.git -Pgit_ref=trunk -Pgit_commit_hash=dc0601a1c604bea3f426ed25b6c20176ff444079 -Pbase_version=2.2.0

You can mix both ways to build from Git, but command line always overwrites bigtop.bom.

Contact us

You can get in touch with us on the Apache Bigtop mailing lists.