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Mounting Yandex Object Storage buckets to the file system of Yandex Data Processing hosts

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Updated at July 16, 2026
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In Yandex Data Processing, you can use initialization actions to configure hosts.

With these actions, you can automate the installation and setup of GeeseFS, the software enabling Yandex Data Processing cluster hosts to mount Yandex Object Storage buckets via FUSE.

To set up GeeseFS:

  1. Set up your infrastructure.
  2. Prepare the initialization action.
  3. Create a cluster that uses the initialization action.
  4. Check bucket availability.

If you no longer need the resources you created, delete them.

Getting started

Sign up for Yandex Cloud and create a billing account:

  1. Navigate to the management console and log in to Yandex Cloud or create a new account.
  2. On the Yandex Cloud Billing page, make sure you have a billing account linked and it has the ACTIVE or TRIAL_ACTIVE status. If you do not have a billing account, create one and link a cloud to it.

If you have an active billing account, you can create or select a folder for your infrastructure on the cloud page.

Learn more about clouds and folders here.

Set up your infrastructure

  1. Create a service account with the dataproc.agent and dataproc.provisioner roles.

  2. Create an Object Storage bucket.

  3. Grant the service account read access to the bucket by using one of the following methods:

    • Set up the bucket ACL and grant READ permission to the service account.

      The service account will get read access only to the specified bucket.

    • Assign the service account the storage.viewer role.

      The service account will get read access to all buckets in the folder.

  4. Create a NAT gateway for the subnet you want to create your Yandex Data Processing cluster in.

  1. If you do not have Terraform yet, install it.

  2. Get the authentication credentials. You can add them to environment variables or specify them later in the provider configuration file.

  3. Configure and initialize a provider. There is no need to create a provider configuration file manually, you can download it.

  4. Place the configuration file in a separate working directory and specify the parameter values. If you did not add the authentication credentials to environment variables, specify them in the configuration file.

  5. Download the data-processing-init-actions-geesefs.tf configuration file to the same working directory.

    This file describes:

  6. In the data-processing-init-actions-geesefs.tf file, specify the following settings:

    • dp_network_name: Name of the network for your Yandex Data Processing cluster.
    • dp_subnet_name: Name of the subnet for your Yandex Data Processing cluster.
    • dp_sg_name: Name of the security group for your Yandex Data Processing cluster.
    • dp_sa_folder_id: ID of the folder to create your infrastructure and Yandex Data Processing cluster in.
    • dp_sa_name: Name of the service account for your Yandex Data Processing cluster and Object Storage bucket.
    • dp_bucket_name: Object Storage bucket name.
    • dataproc_name: Yandex Data Processing cluster name.
    • ssh-path: Path to the public SSH key file for your Yandex Data Processing cluster.

  7. Make sure the Terraform configuration files are correct using this command:

    terraform validate

    Terraform will display any configuration errors detected in your files.

  8. Create the required infrastructure:

    1. Run this command to view the planned changes:

      terraform plan

      If you described the configuration correctly, the terminal will display a list of the resources to update and their parameters. This is a verification step that does not apply changes to your resources.

    2. If everything looks correct, apply the changes:

      1. Run this command:

        terraform apply

      2. Confirm updating the resources.

      3. Wait for the operation to complete.

    All the required resources will be created in the specified folder. You can check resource availability and their settings in the management console.

Prepare the initialization action

  1. Create an initialization action file named geesefs_mount.sh taking two positional arguments: the name of the Object Storage bucket and the host's file system directory where you are going to mount it.

    #!/bin/bash

set -e

BUCKET=$1
MOUNT_POINT=$2

# Downloading GeeseFS
wget https://github.com/yandex-cloud/geesefs/releases/latest/download/geesefs-linux-amd64 -O /opt/geesefs
chmod a+rwx /opt/geesefs
mkdir -p "${MOUNT_POINT}"

# Preparing a script to run on every boot
BOOT_SCRIPT="/var/lib/cloud/scripts/per-boot/80-geesefs-mount.sh"
echo "#!/bin/bash" >> ${BOOT_SCRIPT}
echo "/opt/geesefs -o allow_other --iam ${BUCKET} ${MOUNT_POINT}" >> ${BOOT_SCRIPT}
chmod 755 ${BOOT_SCRIPT}

# Running the script
${BOOT_SCRIPT}

  2. Upload the geesefs_mount.sh file to the Object Storage bucket you created earlier.

Create a cluster that will use the initialization action

Create a Yandex Data Processing cluster with the following settings:

  • In the Version field, select 2.0.

  • In the Service account field, select the service account you previously created.

  • In the Custom scripts field, click Add and set the action parameters:

    • In the URI field, specify the path to the action file in the bucket, such as:

      s3a://<bucket_name>/geesefs_mount.sh

    • In the Arguments field, specify the name of the previously created bucket and /mnt/test as your mount point. Specify arguments on separate lines:

      <bucket_name>
/mnt/test

  • In the Bucket name field, select the previously created bucket.

  • In the Subclusters menu, enable Public access in the settings

    Note

    Public access to cluster hosts is required if you plan to connect to the cluster via the internet. This connection option is simpler and is recommended for the purposes of this guide. You can connect to non-public hosts as well but only from Yandex Cloud virtual machines located in the same cloud network as the cluster.

  1. In the data-processing-init-actions-geesefs.tf file, set the variable value as follows: create_cluster = 1.

  2. Make sure the Terraform configuration files are correct using this command:

    terraform validate

    Terraform will display any configuration errors detected in your files.

  3. Create the required infrastructure:

    1. Run this command to view the planned changes:

      terraform plan

      If you described the configuration correctly, the terminal will display a list of the resources to update and their parameters. This is a verification step that does not apply changes to your resources.

    2. If everything looks correct, apply the changes:

      1. Run this command:

        terraform apply

      2. Confirm updating the resources.

      3. Wait for the operation to complete.

    All the required resources will be created in the specified folder. You can check resource availability and their settings in the management console.

Check bucket availability

  1. After the cluster status changes to Alive, connect over SSH to any of its hosts as the ubuntu user.

  2. To make sure the bucket has been mounted successfully, run this command:

    ls /mnt/test

    It will output the list of objects stored in the bucket’s root folder. In this case, the name of the geesefs_mount.sh file.

Delete the resources you created

Tip

Before deleting the infrastructure, manually delete all objects from the bucket.

Some resources are not free of charge. Delete the resources you no longer need to avoid paying for them:

  1. Delete the Yandex Data Processing cluster.
  2. If you used static public IP addresses to access the cluster hosts, release and delete them.
  3. Delete the Object Storage bucket.
  4. Delete the service account.

  1. In the terminal, navigate to the working directory with the data-processing-init-actions-geesefs.tf configuration file.

  2. Delete the resources using this command:

    terraform destroy

  3. Type yes and press Enter.

    This will delete all resources described in the data-processing-init-actions-geesefs.tf configuration file.

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