5.2. Using Elastic MapReduce on AWS

This topic provides an overview of the components and services that you set up and configure in a deployment that uses Amazon EMR. Work to prepare complete installation procedures for edX Insights is in progress.

For more information about AWS, including detailed procedures, see the AWS Documentation.

Important

The tasks described by this topic rely on the use of third-party services and software. Because the services and software are subject to change by their owners, the information provided here is intended as a guideline and not as exact procedures.

5.2.1. Virtual Private Cloud

Create a Virtual Private Cloud (VPC) with at least one public subnet. A limitation of EMR running in a VPC is that clusters must be deployed into public subnets of VPCs. An existing VPC can be used if one is already available for use.

EdX recommends that you configure the VPC to have at least one private subnet in addition to the required public subnet. A private subnet is not required. For more information, see the example configuration scenario in the Amazon Virtual Private Cloud User Guide published by AWS.

An example configuration that includes only a single public subnet can also be found in the Amazon Virtual Private Cloud User Guide.

5.2.1.1. Other Considerations

  • To take advantage of price fluctuations in the spot pricing market , you can also deploy several public subnets in different availability zones.
  • Consider that the clusters deployed using EMR will need network connectivity to a read replica of the LMS database. EdX recommends that you use the same VPC as the LMS if possible.
  • While it is possible to run all of these services outside of a VPC, edX does not recommend doing so.

5.2.2. Identity and Access Management

For Amazon Identity and Access Management (IAM), create an IAM role for use by the EMR cluster. Assign all of the Elastic Compute Cloud (EC2) nodes in the cluster to this role. An option is to consider copying the contents of the default EC2 role for Amazon EMR used by AWS.

Make sure that an IAM user with administrative privileges is available for use.

5.2.3. SSH Credentials

Generate a secure SSH key that you use to access all AWS resources. For example, run the following command.

ssh-keygen -t rsa -C "your_email@example.com"

Upload the public key from the SSH key pair to AWS and assign a key pair name to it.

5.2.4. Elastic Compute Cloud

Ensure that at least one Amazon Elastic Compute Cloud (EC2) instance is available to host the various services. Depending on the scale of your deployment, additional instances might be necessary.

Make sure to use the secure key pair name to deploy all of the EC2 instances.

5.2.5. Relational Database Service

Deploy a MySQL 5.6 Relational Database Service (RDS) instance. This RDS instance is the result store.

5.2.5.1. Connectivity

Ensure that there is connectivity between the EC2 instance that hosts the edX Analytics API and your RDS instance.

Also, ensure that instances deployed into the public subnet of the VPC can connect to your RDS instance.

5.2.5.2. Users

Create at least the following two users on the RDS instance.

  • The “pipeline” user must have permission to create databases, tables, and indexes, and issue arbitrary Data Manipulation Language (DML) commands.
  • The “api” user must have read-only access.

Configure passwords for both of these users.

5.2.5.3. Other Considerations

Configure the RDS instance to use “utf8_bin” collation by default for columns in all databases and tables.

5.2.6. Scheduler Service

Establish an SSH connection to the EC2 instance within the VPC that will run the scheduler service. Then, issue the following commands from a shell running on that instance.

  1. Check out the sources files from edx-analytics-configuration.

    git clone https://github.com/edx/edx-analytics-configuration.git
    
  2. Configure the shell to use the AWS credentials of the administrative AWS user.

    export AWS_ACCESS_KEY_ID=<access key ID goes here>
    export AWS_SECRET_ACCESS_KEY=<secret access key goes here>
    
  3. Install the AWS Command Line Interface.

    pip install awscli
    

5.2.7. Simple Storage Solution Buckets

Create a Simple Storage Solution (S3) bucket to hold all Hadoop logs from the EMR cluster.

aws s3 mb s3://<your logging bucket name here>

Then, create an S3 bucket to hold secure configuration files and initialization scripts.

aws s3 mb s3://<your configuration bucket name here>

5.2.8. MySQL Connector Library

Download the MySQL connector library from Oracle. After the download is complete, you then upload it to S3.

aws s3 cp /tmp/mysql-connector-java-5.1.*.tar.gz s3://<your configuration bucket name here>/

The edx-analytics-configuration/batch/bootstrap/install-sqoop script references a specific version of the MySQL connector library. Update this install-sqoop script to point to the correct version of the library in the S3 bucket. You must update the script before you continue.

Then, upload the contents of the edx-analytics-configuration/batch/bootstrap/ directory into your configuration bucket.

aws s3 sync edx-analytics-configuration/batch/bootstrap/ s3://<your configuration bucket name here>/

5.2.9. Cluster Configuration File

Create a cluster configuration file to specify the parameters for the EMR cluster. Review the parameters that follow, and change them to specify your desired configuration. For example, review the core and task mappings and change the values for bidprice and type to meet your needs.

Then, save this file to a temporary location such as /tmp/cluster.yml.

{
    name: <your cluster name here>,
    keypair_name: <your keypair name here>,
    vpc_subnet_id: <your VPC public subnet ID here>,
    log_uri: "s3://<your logging bucket name here>",
    instance_groups: {
        master: {
            num_instances: 1,
            type: m3.xlarge,
            market: ON_DEMAND,
        },
        core: {
            num_instances: 2,
            type: m3.xlarge,
            market: SPOT,
            bidprice: 0.8
        },
        task: {
            num_instances: 1,
            type: m3.xlarge,
            market: SPOT,
            bidprice: 0.8
        }
    },
    release_label: emr-4.7.2,
    applications: [ {name: Hadoop}, {name: Hive}, {name: Sqoop-Sandbox}, {name: Ganglia} ],
    steps: [
      {
        type: script,
        name: Install MySQL connector for Sqoop,
        step_args: [ "s3://<your-analytics-packages-bucket>/install-sqoop", "s3://<your-analytics-packages-bucket>" ],
        # You might want to set this to CANCEL_AND_WAIT while debugging step failures.
        action_on_failure: TERMINATE_JOB_FLOW
      }
    ],
    configurations: [
      {
        classification: mapred-site,
        properties:
        {
          mapreduce.framework.name: 'yarn',
          mapreduce.jobtracker.retiredjobs.cache.size: '50',
          mapreduce.reduce.shuffle.input.buffer.percent: '0.20',
        }
      },
      {
        classification: yarn-site,
        properties:
        {
          yarn.resourcemanager.max-completed-applications: '5'
        }
      }
    ],
    user_info: []
}

You might find you need to update Hadoop instance types and container sizes. In particular, if you encounter jobs that are running out of physical memory, you might want to choose a larger instance. If your instance is a good size but being underutilized, you might want to explicitly define larger values in the “mapred-site” configuration than would be provided by default in the instance size you are using. Here is an example of settings we use with an m3.2xlarge instance type.

{
  classification: mapred-site,
  properties:
  {
    mapreduce.framework.name: 'yarn',
    mapreduce.jobtracker.retiredjobs.cache.size: '50',
    mapreduce.reduce.shuffle.input.buffer.percent: '0.20',
    mapreduce.map.java.opts: '-Xmx2458m',
    mapreduce.reduce.java.opts: '-Xmx4916m',
    mapreduce.map.memory.mb: '3072',
    mapreduce.reduce.memory.mb: '6144'
  }
}

5.2.10. EMR Cluster

Deploy the EMR cluster.

EXTRA_VARS="@/tmp/cluster.yml" make provision.emr

5.2.10.1. Example Output

pip install -q -r requirements.txt

ansible-playbook --connection local -i 'localhost,' batch/provision.yml -e "$EXTRA_VARS"

PLAY [Provision cluster] ******************************************************

TASK: [provision EMR cluster] *************************************************
changed: [localhost]

TASK: [add master to group] ***************************************************
ok: [localhost]

TASK: [display master IP address] *********************************************
ok: [localhost] => {
    "msg": "10.0.1.236"
}

TASK: [display job flow ID] ***************************************************
ok: [localhost] => {
    "msg": "j-29UUJVM8P1NPY"
}

PLAY [Configure SSH access to cluster] ****************************************

TASK: [user | debug var=user_info] ********************************************
ok: [10.0.1.236] => {
    "item": "",
    "user_info": []
}

TASK: [user | create the edxadmin group] **************************************
changed: [10.0.1.236]

TASK: [user | ensure sudoers.d is read] ***************************************
changed: [10.0.1.236]

TASK: [user | grant full sudo access to the edxadmin group] *******************
changed: [10.0.1.236]

TASK: [user | create the users] ***********************************************
skipping: [10.0.1.236]

TASK: [user | create .ssh directory] ******************************************
skipping: [10.0.1.236]

TASK: [user | assign admin role to admin users] *******************************
skipping: [10.0.1.236]

TASK: [user | copy github key[s] to .ssh/authorized_keys] ********************
skipping: [10.0.1.236]

TASK: [user | create bashrc file for normal users] ****************************
skipping: [10.0.1.236]

TASK: [user | create .profile for all users] **********************************
skipping: [10.0.1.236]

TASK: [user | modify shell for restricted users] ******************************
skipping: [10.0.1.236]

TASK: [user | create bashrc file for restricted users] ************************
skipping: [10.0.1.236]

TASK: [user | create sudoers file from template] ******************************
changed: [10.0.1.236]

TASK: [user | change home directory ownership to root for restricted users] ***
skipping: [10.0.1.236]

TASK: [user | create ~/bin directory] *****************************************
skipping: [10.0.1.236]

TASK: [user | create allowed command links] ***********************************
skipping: [10.0.1.236]

PLAY RECAP ********************************************************************
10.0.1.236                 : ok=0    changed=4    unreachable=0    failed=0
localhost                  : ok=4    changed=1    unreachable=0    failed=0

5.2.10.1.1. Additional Tasks

To complete the EMR configuration, additional configuration and automation procedures are required, including scheduling jobs and automating log duplication. For more information, see the edX Analytics Installation wiki page.