Cluster

User friendly container for Google Cloud Bigtable Cluster.

class google.cloud.bigtable.cluster.Cluster(cluster_id, instance, location_id=None, serve_nodes=None, default_storage_type=None, kms_key_name=None, _state=None, min_serve_nodes=None, max_serve_nodes=None, cpu_utilization_percent=None)

Bases: object

Representation of a Google Cloud Bigtable Cluster.

We can use a Cluster to:

  • reload() itself

  • create() itself

  • update() itself

  • delete() itself

  • disable_autoscaling() itself

  • Parameters

    • cluster_id (str) – The ID of the cluster.

    • instance (Instance) – The instance where the cluster resides.

    • location_id (str) – (Creation Only) The location where this cluster’s nodes and storage reside . For best performance, clients should be located as close as possible to this cluster. For list of supported locations refer to https://cloud.google.com/bigtable/docs/locations

    • serve_nodes (int) – (Optional) The number of nodes in the cluster for manual scaling. If any of the autoscaling configuration are specified, then the autoscaling configuration will take precedent.

    • default_storage_type (int) – (Optional) The type of storage Possible values are represented by the following constants: google.cloud.bigtable.enums.StorageType.SSD. google.cloud.bigtable.enums.StorageType.HDD, Defaults to google.cloud.bigtable.enums.StorageType.UNSPECIFIED.

    • kms_key_name (str) – (Optional, Creation Only) The name of the KMS customer managed encryption key (CMEK) to use for at-rest encryption of data in this cluster. If omitted, Google’s default encryption will be used. If specified, the requirements for this key are:

    1. The Cloud Bigtable service account associated with the
project that contains the cluster must be granted the
`cloudkms.cryptoKeyEncrypterDecrypter` role on the CMEK.


    2. Only regional keys can be used and the region of the CMEK
key must match the region of the cluster.


    3. All clusters within an instance must use the same CMEK key.



* **_state** ([*int*](https://python.readthedocs.io/en/latest/library/functions.html#int)) – (OutputOnly)
The current state of the cluster.
Possible values are represented by the following constants:
`google.cloud.bigtable.enums.Cluster.State.NOT_KNOWN`.
`google.cloud.bigtable.enums.Cluster.State.READY`.
`google.cloud.bigtable.enums.Cluster.State.CREATING`.
`google.cloud.bigtable.enums.Cluster.State.RESIZING`.
`google.cloud.bigtable.enums.Cluster.State.DISABLED`.


* **min_serve_nodes** ([*int*](https://python.readthedocs.io/en/latest/library/functions.html#int)) – (Optional) The minimum number of nodes to be set in the cluster for autoscaling.
Must be 1 or greater.
If specified, this configuration takes precedence over
`serve_nodes`.
If specified, then
`max_serve_nodes` and `cpu_utilization_percent` must be
specified too.


* **max_serve_nodes** ([*int*](https://python.readthedocs.io/en/latest/library/functions.html#int)) – (Optional) The maximum number of nodes to be set in the cluster for autoscaling.
If specified, this configuration
takes precedence over `serve_nodes`. If specified, then
`min_serve_nodes` and `cpu_utilization_percent` must be
specified too.


* **cpu_utilization_percent** – (Optional) The CPU utilization target for the cluster’s workload for autoscaling.
If specified, this configuration takes precedence over `serve_nodes`. If specified, then
`min_serve_nodes` and `max_serve_nodes` must be
specified too.

create()

Create this cluster.

For example:

from google.cloud.bigtable import Client
from google.cloud.bigtable import enums

# Assuming that there is an existing instance with `INSTANCE_ID`
# on the server already.
# to create an instance see
# 'https://cloud.google.com/bigtable/docs/creating-instance'

client = Client(admin=True)
instance = client.instance(INSTANCE_ID)

cluster_id = "clus-my-" + UNIQUE_SUFFIX
location_id = "us-central1-a"
serve_nodes = 1
storage_type = enums.StorageType.SSD

cluster = instance.cluster(
    cluster_id,
    location_id=location_id,
    serve_nodes=serve_nodes,
    default_storage_type=storage_type,
)
operation = cluster.create()
# We want to make sure the operation completes.
operation.result(timeout=100)

NOTE: Uses the project, instance and cluster_id on the current Cluster in addition to the serve_nodes. To change them before creating, reset the values via

cluster.serve_nodes = 8
cluster.cluster_id = 'i-changed-my-mind'

before calling create().

  • Return type

    Operation

  • Returns

    The long-running operation corresponding to the create operation.

  • Raises

    ValueError if the both serve_nodes and autoscaling configurations are set at the same time or if none of the serve_nodes or autoscaling configurations are set or if the autoscaling configurations are only partially set.

delete()

Delete this cluster.

For example:

from google.cloud.bigtable import Client

client = Client(admin=True)
instance = client.instance(INSTANCE_ID)
cluster_to_delete = instance.cluster(cluster_id)

cluster_to_delete.delete()

Marks a cluster and all of its tables for permanent deletion in 7 days.

Immediately upon completion of the request:

  • Billing will cease for all of the cluster’s reserved resources.

  • The cluster’s delete_time field will be set 7 days in the future.

Soon afterward:

  • All tables within the cluster will become unavailable.

At the cluster’s delete_time:

  • The cluster and all of its tables will immediately and irrevocably disappear from the API, and their data will be permanently deleted.

disable_autoscaling(serve_nodes)

Disable autoscaling by specifying the number of nodes.

For example:

from google.cloud.bigtable import Client

client = Client(admin=True)
instance = client.instance(INSTANCE_ID)
# Create a cluster with autoscaling enabled
cluster = instance.cluster(
    CLUSTER_ID, min_serve_nodes=1, max_serve_nodes=2, cpu_utilization_percent=10
)
instance.create(clusters=[cluster])

# Disable autoscaling
cluster.disable_autoscaling(serve_nodes=4)

  • Parameters

    serve_nodes (int) – The number of nodes in the cluster.

exists()

Check whether the cluster already exists.

For example:

from google.cloud.bigtable import Client

client = Client(admin=True)
instance = client.instance(INSTANCE_ID)
cluster = instance.cluster(CLUSTER_ID)
cluster_exists = cluster.exists()

  • Return type

    bool

  • Returns

    True if the table exists, else False.

classmethod from_pb(cluster_pb, instance)

Creates a cluster instance from a protobuf.

For example:

from google.cloud.bigtable import Client
from google.cloud.bigtable_admin_v2.types import instance as data_v2_pb2

client = Client(admin=True)
instance = client.instance(INSTANCE_ID)
cluster = instance.cluster(CLUSTER_ID)

name = cluster.name
cluster_state = cluster.state
serve_nodes = 1
cluster_pb = data_v2_pb2.Cluster(
    name=name,
    location=LOCATION_ID,
    state=cluster_state,
    serve_nodes=serve_nodes,
    default_storage_type=STORAGE_TYPE,
)

cluster2 = cluster.from_pb(cluster_pb, instance)

  • Parameters

  • Return type

    Cluster

  • Returns

    The Cluster parsed from the protobuf response.

  • Raises

    ValueError if the cluster name does not match projects/{project}/instances/{instance_id}/clusters/{cluster_id} or if the parsed instance ID does not match the istance ID on the client. or if the parsed project ID does not match the project ID on the client.

property kms_key_name()

Customer managed encryption key for the cluster.

property name()

Cluster name used in requests.

NOTE: This property will not change if _instance and cluster_id do not, but the return value is not cached.

For example:

from google.cloud.bigtable import Client

client = Client(admin=True)
instance = client.instance(INSTANCE_ID)
cluster = instance.cluster(CLUSTER_ID)
cluster_name = cluster.name

The cluster name is of the form

"projects/{project}/instances/{instance}/clusters/{cluster_id}"

  • Return type

    str

  • Returns

    The cluster name.

reload()

Reload the metadata for this cluster.

For example:

from google.cloud.bigtable import Client

client = Client(admin=True)
instance = client.instance(INSTANCE_ID)
cluster = instance.cluster(CLUSTER_ID)
cluster.reload()

property state()

state of cluster.

For example:

from google.cloud.bigtable import Client

client = Client(admin=True)
instance = client.instance(INSTANCE_ID)
cluster = instance.cluster(CLUSTER_ID)
cluster_state = cluster.state

  • Type

    google.cloud.bigtable.enums.Cluster.State

update()

Update this cluster.

For example:

from google.cloud.bigtable import Client

client = Client(admin=True)
instance = client.instance(INSTANCE_ID)
cluster = instance.cluster(CLUSTER_ID)
cluster.serve_nodes = 4
cluster.update()

NOTE: Updates the serve_nodes. If you’d like to change them before updating, reset the values via

cluster.serve_nodes = 8

before calling update().

If autoscaling is already enabled, manual scaling will be silently ignored. To disable autoscaling and enable manual scaling, use the disable_autoscaling() instead.

  • Return type

    Operation

  • Returns

    The long-running operation corresponding to the update operation.