Single node clusters

Single node clusters are Dataproc clusters with only one node. This single node acts as the master and worker for your Dataproc cluster. While single node clusters only have one node, most Dataproc concepts and features still apply, except those listed below .

There are a number of situations where single node Dataproc clusters can be 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 Dataproc clusters, and include services such as HDFS and YARN.
• Single node clusters report as master nodes for initialization actions .
• Single node clusters show 0 workers since the single node acts as both master and worker.
• Single node clusters are given hostnames that follow the pattern clustername-m . You can use this hostname to SSH into or connect to a web 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 node clusters cannot be scaled down to single node clusters.

Limitations

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

• Single node clusters are not available with high-availability since there is only one node in the cluster.

• Single node clusters cannot use preemptible VMs .

Create a single node cluster

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