Apache Beam Google DataFlow Pipeline Engine

Project ID

The project ID for your Google Cloud Project. This is required if you want to run your pipeline using the Dataflow managed service.

Service Account

With this option you can run the pipeline dataflow job with a specific service account, instead of the default GCE robot. The default is to leave this blank.

Application name

The name of the Dataflow job being executed as it appears in Dataflow’s jobs list and job details. Also used when updating an existing pipeline.

Staging location

Cloud Storage path for staging local files. Must be a valid Cloud Storage URL, beginning with gs://.

Initial number of workers

The initial number of Google Compute Engine instances to use when executing your pipeline. This option determines how many workers the Dataflow service starts up when your job begins.

Maximum number of workers

The maximum number of Compute Engine instances to be made available to your pipeline during execution. Note that this can be higher than the initial number of workers (specified by numWorkers to allow your job to scale up, automatically or otherwise.

Auto-scaling algorithm

Worker machine type

The Compute Engine machine type that Dataflow uses when starting worker VMs. You can use any of the available Compute Engine machine type families as well as custom machine types.

For best results, use n1 machine types. Shared core machine types, such as f1 and g1 series workers, are not supported under the Dataflow Service Level Agreement.

Note that Dataflow bills by the number of vCPUs and GB of memory in workers. Billing is independent of the machine type family. Check the list of machine types for reference.

Worker disk type

The type of persistent disk to use, specified by a full URL of the disk type resource.

For example, use compute.googleapis.com/projects//zones//diskTypes/pd-ssd to specify a SSD persistent disk.

more.

Disk size in GB

The disk size, in gigabytes, to use on each remote Compute Engine worker instance. If set, specify at least 30 GB to account for the worker boot image and local logs.

Region

Specifies a Compute Engine region for launching worker instances to run your pipeline. This option is used to run workers in a different location than the region used to deploy, manage, and monitor jobs. The zone for workerRegion is automatically assigned.

Note: This option cannot be combined with workerZone or zone.

(regions list).

Zone

Specifies a Compute Engine zone for launching worker instances to run your pipeline. This option is used to run workers in a different location than the region used to deploy, manage, and monitor jobs.

Note: This option cannot be combined with workerRegion or zone.

Network

This is the GCE network for launching workers. For more information, see the reference documentation https://cloud.google.com/compute/docs/networking. The default is up to the Dataflow service.

Subnetwork

This is the GCE subnetwork for launching workers. For more information, see the reference documentation https://cloud.google.com/compute/docs/networking. The default is up to the Dataflow service.

Use public IPs?

Specifies whether worker pools should be started with public IP addresses. WARNING: This feature is experimental. You must be allowlisted to use it.

Dataflow Service Options

This is a comma separated list of options in the format option=value,option2=value2,…​. It serves as a catch-all option for the Dataflow service. This helps if Beam is missing some service related options and if new options are added in the future older Beam versions could still use them through these catch-all options.

User agent

A user agent string as per RFC2616, describing the pipeline to external services.

Temp location

Cloud Storage path for temporary files. Must be a valid Cloud Storage URL, beginning with gs://.

Plugins to stage (, delimited)

Comma separated list of plugins.

Transform plugin classes

List of transform plugin classes.

XP plugin classes

List of extensions point plugins.

Streaming Hop transforms flush interval (ms)

The amount of time after which the internal buffer is sent completely over the network and emptied.

Hop streaming transforms buffer size

The internal buffer size to use.

Fat jar file location

Fat jar location. Generate a fat jar using Tools → Generate a Hop fat jar. The generated fat jar file name will be copied to the clipboard.