Configure Spark cluster using Ansible

From info319

Ansible

On your local host, install Ansible, for example: 

sudo apt install ansible

Configure Ansible

To prepare: 

sudo cp /etc/ansible/hosts /etc/ansible/hosts.original
sudo chmod 666 /etc/ansible/hosts

Ansible needs to know the names of your cluster machines. Change info319-cluster.tf so it also writes a file like this to /etc/ansible/hosts: 

terraform-driver
terraform-worker-0
...
terraform-worker-5

Finally, Ansible must be installed on all the hosts too. Add the line 

- ansible

to the packages: section of user-data.cfg, and re-run terraform apply.

Test run Ansible

Make sure you can log into your cluster machines without a password. Test your Ansible setup from your local machine: 

ansible all -m ping

On your local machine, create the file info319-cluster.yaml with a simple task that backs up ~/.bashrc: 

- name: Prepare .bashrc
  hosts: all
  tasks:

    - name: Save original .bashrc
      ansible.builtin.copy:
        src: /home/ubuntu/.bashrc
        dest: /home/ubuntu/.bashrc.original
        remote_src: yes

Run Ansible: 

ansible-playbook info319-cluster.yaml

Ansible playbook

Extend the playbook file info319-cluster.yaml to re-create the setup from Exercise 4 on the new Terraform cluster. You have some freedom with respect to the order of things.

Preparing .bashrc

In Exercise 4 we made a lot of modifications to ~/.bashrc. In some cases it is more practical to have the cluster configuration in a separate file, for example ~/.info319.

  • Add a task that uses the ansible.builtin.file module to create ("touch") /home/ubuntu/.info319 on all the hosts.
  • Add a task that uses the ansible.builtin.lineinfile module to add this line to /home/ubuntu/.info319 on all the hosts:
source .info319

See the documentation here: https://docs.ansible.com/ansible/latest/collections/index.html, for example https://docs.ansible.com/ansible/latest/collections/ansible/builtin/lineinfile_module.html.

Configure SSH

You can use the blockinfile module to add your local ipv4-hosts to /etc/hosts on each node: 

   - name: Copy IPv4 addresses to /etc/hosts
     ansible.builtin.blockinfile:
       path: /etc/hosts
       block: "{{ lookup('file', 'ipv4-hosts') } }"
     become: yes

Note: There should not be a space between the two curly braces at the end of the key: line. But without the space, WikiText misinterprets them as a template marker.

On your local machine, create the file config in your exercise-5 folder: 

Host terraform-* localhost
     User ubuntu
     IdentityFile ~/.ssh/info319-spark-cluster
     StrictHostKeyChecking no
     UserKnownHostsFile /dev/null

Include ~/.ssh/config.terraform-hosts

(This is the config.stub file from Exercise 4, with the Include line added. Also, localhost has been added to the first line to allow nodes to ssh themselves...)

Use the copy module to upload this file, along with ~/.ssh/config.terraform-hosts and ~/.ssh/info319-spark-cluster to all hosts.

In addition to uploading the config and private key files, you must also authorise the public info319-spark-cluster.pub key, like this: 

    - name: Authorise public cluster key
      ansible.posix.authorized_key:
        key: "{{ lookup('file', '/home/YOUR_USERNAME/.ssh/info319-spark-cluster.pub') } }"
        user: ubuntu

Tip: ansible-playbook has a --start-at-task "Task name" option to avoid repeating all earlier blocks and stages. You can also use --step to have Ansible ask before each step whether to execute, skip, or finish.

Install Java

Use Ansible's ansible.builtin.apt module and install an old and stable Java version, for example openjdk-8-jdk-headless.

Mount volumes

Using the community.general.parted, community.general.filesystem and ansible.posix.mount modules from your local machine may require installation: 

ansible-galaxy collection install community.general
ansible-galaxy collection install ansible.posix

Install HDFS and YARN

To install HDFS and YARN you need the master_node and num_workers available as Ansible variables (facts). You can use the ansible.builtin.shell and .set_fact modules to do this, for example at the start of a new Ansible play: 

- name: Install HDFS and YARN
  hosts: all
  tasks:

    - name: Register master_node expression
      shell: grep tf-driver /etc/hosts | cut -d' ' -f1
      register: master_node_expr

    - name: Set master_node fact
      set_fact:
        master_node: "{{ master_node_expr.stdout } }"

Write two corresponding tasks for num_workers.

Use the ansible.builtin.get_url module to download the Hadoop and later Spark archives directly to each cluster host. But if you re-run your script many times, it takes time and can trigger rate limitations in the download hosts. If so, it is better to let Ansible download each archive once to your local machine and then copy it onto the hosts as needed.

Use the ansible.builtin.unarchive module to unpack the archives. Use the apt module to install gzip if you need it. Use ansible.builtin.file to create symbolic links as in Exercise 4.

Use ansible.builtin.lineinfile to define environment variables by adding them to ~/.info319 (instead of ~/.bashrc).

Change the variable syntax in the files {core,hdfs,mapred,yarn}-site.xml from Exercise 4 from Linux to Ansible. For example

  • from core-site.xml:
<configuration>
    <property>
        <name>fs.defaultFS</name>
        <value>hdfs://${HADOOP_NAMENODE}:9000</value>
    </property>
</configuration>
  • to core-site.xml.j2:
<configuration>
    <property>
        <name>fs.defaultFS</name>
        <value>hdfs://{{ hadoop_namenode } }:9000</value>
    </property>
</configuration>

You can now use the ansible.builtin.template module instead of Linux' envsubst command to configure the files. Note that the files use the {{ hadoop_namenode } } variable. It is not defined yet, but should have the same value as {{ master_node } }.

Use ansible.builtin.shell to create Hadoop's worker and master files as in Execise 4, and to format the HDFS namenode and create the HDFS root folder on the terraform-driver host.

Note that hdfs namenode -format has got a -nonInteractive option that does not re-format an already formatted namenode. Use failed_when to make Ansible ignore Exit code 1 from hdfs in such cases: 

    - name: Format HDFS namenode
      ansible.builtin.shell:
        argv: ["/home/ubuntu/volume/hadoop/bin/hdfs", "namenode", "-format", "-nonInteractive"]
      register: result
      failed_when: result.rc not in [0, 1]

Now you can log into terraform-driver and test run HDFS on the cluster as in Exercise 4.

Finally, you can start HDFS and YARN from terraform-driver. Note that the ansible.builtin.copy and ansible.builtin.shell modules will normally not run ~/.bashrc. The reason is that ~/.bashrc is intended for interactive shells running, for example, in a terminal window. ~/.bashrc is not needed for many simpler commands, but more complex programs and scripts like Hadoop's start-all.sh need many environment variables. Therefore, you must start your own /usr/bin/bash, initialise it with ~/.info319, and then run start-all.sh inside it: 

    - name: Start HDFS and YARN
      ansible.builtin.shell:
        argv: ["/usr/bin/bash", "--rcfile", "/home/ubuntu/.info319", "-c", "start-all.sh"]

Install Spark on the cluster

Proceed as in Exercise 4. You already know the Ansible modules that are needed. Afterwards you can log into terraform-driver and test run Spark on the cluster as in Exercise 4.

Install Zookeeper on the cluster

There are two challenges with Zookeeper:

  1. it may not run on all the machines in the cluster (it must be an odd number)
  2. each zookeeper needs to know its myid number

As for the first point, an easy solution is to run Zookeeper on all hosts if the number is odd, but only on the workers if the total number is even.

As for the second point, Exercise 4 suggested shell commands you can use to manage zookeeper ids. But Ansible also has powerful loop constructs you can use.

This task will start Zookeeper on the selected nodes: 

   - name: Start Zookeper
     ansible.builtin.shell: 
       argv: ["/usr/bin/bash", "--rcfile", "/home/ubuntu/.info319", "-c", "zkServer.sh start ${ZOOKEEPER_HOME}/conf/zookeeper.properties"]

Install Kafka on the cluster

Again, you already know the Ansible modules that are needed to proceed as in Exercise 4. Each Kafka node needs to know its local_ip, which you can set like this: 

    - name: Register local_ip expression
      shell: ip -4 address | grep -o "^ *inet \(.\+\)\/.\+global.*$" | grep -o "[0-9]\+\.[0-9]\+\.[0-9]\+\.[0-9]\+" | head -1
      register: local_ip_expr

    - name: Set local_ip fact
      set_fact:
        local_ip: "{{ local_ip_expr.stdout } }"

It also needs to know its id, which was written to the file /home/ubuntu/volume/zookeeper/data/myid before (better than /tmp/zookeeper/myid which was suggested before).

Finally, you can log into terraform-driver and test run Spark on top of Kafka as in Exercise 4. Congratulations!

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