Single node clusters are Dataproc clusters with only one node. This singlenode acts as the master and worker for yourDataproc cluster. While singlenode clusters only have one node, most Dataproc concepts and featuresstill apply, except thoselisted below.

There are a number of situations where single node Dataproc clusters canbe useful, including:

• Trying out new versions of Spark and Hadoop or other open source components
• Building proof-of-concept (PoC) demonstrations
• Lightweight data science
• Small-scale non-critical data processing
• Education related to the Spark and Hadoop ecosystem

Single node cluster semantics

The following semantics apply to single node Dataproc clusters:

• Single node clusters are configured the same as multi node Dataprocclusters, and include services such as HDFS and YARN.
• Single node clusters report as master nodes forinitialization actions.
• Single node clusters show 0 workers since the single node acts asboth master and worker.
• Single node clusters are given hostnames that follow the patternclustername-m.You can use this hostname to SSH into or connect to aweb UI on the node.
• Single node clusters cannot be upgraded to multi node clusters. Once created,single node clusters are restricted to one node. Similarly, multi nodeclusters cannot be scaled down to single node clusters.

Limitations

• Single node clusters are not recommended for large-scale parallel dataprocessing. If you exceed the resources on a single node cluster, a multi nodeDataproc cluster is recommended.

• Single node clusters are not available withhigh-availabilitysince there is only one node in the cluster.

• Single node clusters cannot usepreemptible VMs.

Create a single node cluster

gcloud dataproc clusters createcluster-name \    --region=region \    --single-node \    ... other args