Configuring the Gremlin console for Gremlin Server in the remote.yaml file

How to configure the Gremlin console for connection to the Gremlin Server.

dse.yaml

The location of the dse.yaml file depends on the type of installation:

Package installations
Installer-Services installations

/etc/dse/dse.yaml

Tarball installations
Installer-No Services installations

installation_location/resources/dse/conf/dse.yaml

remote.yaml

The location of the remote.yaml file depends on the type of installation:

Package installations
Installer-Services installations

/etc/dse/graph/gremlin-console/conf/remote.yaml

Tarball installations
Installer-No Services installations

installation_location/resources/graph/gremlin-console/conf/remote.yaml
The Gremlin console can be used to connect to the Gremlin Server running in DSE Graph. An Apache TinkerPop YAML file, remote.yaml, is configured with Gremlin Server information. The settings for the Gremlin Server itself are set in the dse.yaml file.
hosts: [localhost]
port: 8182
serializer: { className: org.apache.tinkerpop.gremlin.driver.ser.GryoMessageSerializerV1d0,
              config: { ioRegistries: [org.apache.tinkerpop.gremlin.tinkergraph.structure.TinkerIoRegistry] }}
connectionPool: {
  maxContentLength: 65536000
}

A host and port are specified that identify a DataStax Enterprise node that is running the Gremlin Server. By default, the host is a local node and the port is 8182. The port value needs to match the port value specified for gremlin_server in the dse.yaml file. The serializer value specifies the class and configuration for the serializer used to pass information between the Gremlin console and the Gremlin Server. The connectionPool setting specifies the maximum length of a content block that will be passed between the Gremlin console and the Gremlin Server.

Security considerations for authentication between the Gremlin console and the Gremlin server require additional options in the remote.yaml file. You can also connect to the Spark Master node for the datacenter by either running the console from the Spark Master or specifying the Spark Master in the hosts field in the the remote.yaml file.