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Hadoop Testing

This serves as a testing sandbox for Hadoop, equipped with fundamental components of the Hadoop ecosystem to facilitate the rapid establishment of test environments.

We try to deploy a big data ecosystem in multiple Docker containers to simulate the production environment. Generally speaking, it contains two types of deployment modes(standalone and mixed deployed). Standalone mode is just like a SaaS service provided by cloud vendors, while the mixed deployed mode is just like the semi-managed EMR service of cloud vendors. The whole deployment architecture is shown below:

deployment_architecture

Draw by excalidraw

Features

  • Realistic simulation of production environment;
  • Kerberos ready, and optional;
  • Lightweight, highly scalable and tailored Hadoop ecosystem;
  • Multi-purpose, multi-scenario, suitable for:
    • Component developer: unit and integration testing;
    • DevOps engineer: parameter adjustment verification, compatibility testing of component upgrades;
    • Solution architect: Sandbox simulation of migration work, work shop demonstration;
    • Data ETL engineer: a test environment that is easy to build and destroy;

Components

The supported components are listed below:

Name Version Kerberos Ready Optional Default Enabled Variables
JDK 8 8.0.392 Not Applicable No Yes
JDK 17 17.0.9 Not Applicable No Yes
JDK 21 21.0.1 Not Applicable Yes No jdk21_enabled
KDC latest Yes Yes No kerberos_enabled
MySQL 8.0 No No Yes
ZooKeeper 3.8.4 Not Yet No Yes
Hadoop HDFS 3.3.6 Yes No Yes
Hadoop YARN 3.3.6 Yes No Yes
Hive Metastore 2.3.9 Yes No Yes
HiveServer2 2.3.9 Yes No Yes
Kyuubi 1.10.0 Yes No Yes
Spark 3.5.2 Yes Yes Yes spark_enabled
Flink 1.20.0 Yes Yes No flink_enabled
Trino 436 Not Yet Yes No trino_enabled
Ranger 2.4.0 Not Yet Yes No ranger_enabled
Zeppelin 0.11.0 Not Yet Yes Yes zeppelin_enabled, zeppelin_custom_name
Kafka 2.8.1 Not Yet Yes No kafka_enabled
Grafana 11.1.3 Not Applicable Yes No grafana_enabled
Prometheus 2.53.1 Not Applicable Yes No promeheus_enabled
Loki 3.1.0 Not Applicable Yes No loki_enabled
Iceberg 1.7.0 Yes Yes Yes iceberg_enabled
Hudi 0.14.1 Yes Yes No hudi_enabled

Note :

  • Most components respect JAVA_HOME, which is configured as JDK 8
  • Spark is configured to use JDK 17
  • Trino is configured to use JDK 21

Prepare

This project uses Ansible to render the Dockerfile, shell scripts, and configuration files from the templates. Please make sure you have installed it before building.

(Optional, Recommended) Install pyenv

Considering, ansible strongly depends on the Python environment. To make the Python environment independent and easy to manage, it is recommended to use pyenv-virtualenv to manage Python environment.

Here we provide guides for macOS and CentOS users.

macOS

Install from Homebrew

brew install pyenv pyenv-virtualenv

Append to ~/.zshrc, and perform source ~/.zshrc or open a new terminal to take effect.

eval "$(pyenv init -)"
eval "$(pyenv virtualenv-init -)"

CentOS

Before installing, we need to install some required packages.

yum install gcc make patch zlib-devel bzip2 bzip2-devel readline-devel sqlite sqlite-devel openssl-devel tk-devel libffi-devel xz-devel

Then, install pyenv:

curl https://pyenv.run | bash

If you use bash, add it into ~/.bash_profile or ~/.bashrc:

export PYENV_ROOT="$HOME/.pyenv"
[[ -d $PYENV_ROOT/bin ]] && export PATH="$PYENV_ROOT/bin:$PATH"
eval "$(pyenv init -)"

Add it into ~/.bashrc:

eval "$(pyenv virtualenv-init -)"

After all, source ~/.bash_profile and ~/.bashrc.

(Optional) Configure SSH

This step allows you to ssh all the hadoop-* containers from your host, then can use ansible to control all the hadoop-* containers.

The macOS should have pre-installed nc, and you can manually install nc on CentOS using the following command:

yum install epel-release && yum install -y nc

Then configure the ~/.ssh/config file in your host:

Host hadoop-*
    Hostname %h.orb.local
    User root
    Port 22
    ForwardAgent yes
    IdentityFile ~/.ssh/id_rsa_hadoop_testing
    StrictHostKeyChecking no
    ProxyCommand nc -x 127.0.0.1:18070 %h %p

Note : DO NOT forget to reduce access permission by invoking this command:

chmod 600 ~/.ssh/id_rsa_hadoop_testing

After all the containers have been launched, test the controllability via this command:

ansible-playbook test-ssh.yaml

It should print all nodes' OS information (include host and hadoop related containers).

If not, use -vvv config option to debug it.

Use pyenv

Create virtualenv

pyenv install 3.11
pyenv virtualenv 3.11 hadoop-testing

Localize virtualenv

pyenv local hadoop-testing

Install packages to the isolated virtualenv

pip install -r requirements.txt

How to use

Firstly, use ansible to render some templates files, including download.sh, .env, compose.yaml, Dockerfile, configuration files, etc.

ansible-playbook build.yaml

By default, all services disable authN, you can enable Kerberos by passing the kerberos_enabled variable:

ansible-playbook build.yaml -e "{kerberos_enabled: true}"

And some components are disabled by default, you can enable them by passing the <component>_enabled variable:

ansible-playbook build.yaml -e "{jdk21_enabled: true, trino_enabled: true}"

Note: the whole variable list are defined in host_vars/local.yaml.

If something goes wrong, consider adding -vvv arg to debug the playbook:

ansible-playbook build.yaml -vvv

Download all required artifacts, which will be used for building Docker images.

This script will download a large amount of artifacts, depending on your network bandwidth, it may take a few minutes or even hours to complete. You can also download them manually and put them into the download directory, the scripts won't download them again if they already exist.

./download.sh

Build docker images

./build-image.sh

Run the testing playground

docker compose up

Note: depending on the performance of your hardware, some components may take dozens of seconds after container launching to complete the initial work, generally, the slowest one is creating folders on HDFS, the progress can be observed by monitoring container logs.

Access services

Networks

Option 1: OrbStack (macOS only)

For macOS users, it's recommended to use OrbStack as the container runtime. OrbStack provides an out-of-box container domain name resolving feature to allow accessing each container via <container-name>.orb.local.

Option 2: Socks5 Proxy

For other platforms, or you start the containers on a remote server, we provide a socks5 proxy server in a container named socks5, which listens 18070 port and is exposed to the dockerd host by default, you can forward traffic to this socks server to access services run in other containers.

For example, to access service in Browser, use SwitchyOmega to forward traffic of *.orb.local to <dockerd-hostname>:18070.

img img img

Service endponits

Once the testing environment is fully operational, the following services will be accessible:

img

Roadmap

  1. Add more components, such as LDAP, HBase, Superset etc.
  2. Fully templatized. Leverage Ansible and Jinja2 to templatize the Dockerfiles, shell scripts, and configuration files, so that users can easily customize the testing environment by modifying the configurations, e.g. only enabling a subset of components, and changing the version of the components.
  3. Provide user-friendly docs, with some basic tutorials and examples, e.g. how to create a customized testing environment, how to run some basic examples, how to add a new component, etc.