Running Alluxio on Google Cloud Dataproc

Slack Docker Pulls GitHub edit source

This guide describes how to configure Alluxio to run on Google Cloud Dataproc.


Google Cloud Dataproc is a managed on-demand service to run Presto, Spark and Hadoop compute workloads. It manages the deployment of various Hadoop Services and allows for hooks into these services for customizations. Aside from the added performance benefits of caching, Alluxio also enables users to run compute workloads against on-premise storage, or even a different cloud provider’s storage such as AWS S3 and Azure Blob Store.


  • A project with Cloud Dataproc API and Compute Engine API enabled.
  • A GCS Bucket.
  • Make sure that the gcloud CLI is set up with necessary GCS interoperable storage access keys.

    Note: GCS interoperability should be enabled in the Interoperability tab in GCS setting.

A GCS bucket is required if mounted to the root of the Alluxio namespace. Alternatively, the root UFS can be reconfigured to HDFS or any other supported under store.

Basic Setup

When creating a Dataproc cluster, Alluxio can be installed using an initialization action.

Create a cluster

There are several properties set as metadata labels which control the Alluxio Deployment.

  • A required argument is the root UFS address configured using alluxio_root_ufs_uri. If value LOCAL is provided, hdfs launched by the current dataproc cluster will be used as Alluxio root UFS.
  • Properties must be specified using the metadata key alluxio_site_properties delimited using a semicolon (;).

Example 1: use google cloud storage bucket as Alluxio root UFS

$ gcloud dataproc clusters create <cluster_name> \
--initialization-actions gs://alluxio-public/dataproc/2.3.0/ \
--metadata \

Example 2: use Dataproc internal HDFS as Alluxio root UFS

$ gcloud dataproc clusters create <cluster_name> \
--initialization-actions gs://alluxio-public/dataproc/2.3.0/ \
--metadata \


The Alluxio deployment on Google Dataproc can customized for more complex scenarios by passing additional metadata labels to the gcloud clusters create command.

Active Sync can be enabled on paths in Alluxio for a root HDFS mount point using the metadata key alluxio_sync_list. Specify a list of paths in Alluxio delimited using ;.

--metadata \

Additional files can be downloaded into the Alluxio installation directory at /opt/alluxio/conf using the metadata key alluxio_download_files_list. Specify http(s) or gs uris delimited using ;.

--metadata \

The default Alluxio Worker memory is set to 1/3 of the physical memory on the instance. If a specific value is desired, set alluxio.worker.memory.size in the provided

Alternatively, when volumes such as Dataproc Local SSDs are mounted, specify the metadata label alluxio_ssd_capacity_usage to configure the percentage of all available SSDs on the virtual machine provisioned as Alluxio worker storage. Memory is not configured as the primary Alluxio storage tier in this case.

Pass additional arguments to the gcloud clusters create command.

--num-worker-local-ssds=1 \
--metadata \

Next steps

The status of the cluster deployment can be monitored using the CLI.

$ gcloud dataproc clusters list

Identify the instance name and SSH into this instance to test the deployment.

$ gcloud compute ssh <cluster_name>-m

Test that Alluxio is running as expected

$ sudo runuser -l alluxio -c "alluxio runTests"

Alluxio is installed and configured in /opt/alluxio/. Alluxio services are started as alluxio user.

Compute Applications

Spark, Hive and Presto on Dataproc are pre-configured to connect to Alluxio.