As of January 1, 2020 this library no longer supports Python 2 on the latest released version. Library versions released prior to that date will continue to be available. For more information please visit Python 2 support on Google Cloud.

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)[source]¶

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) – (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) – (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) – (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()[source]¶

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()[source]¶

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)[source]¶

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()[source]¶

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)[source]¶

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

cluster_pb (instance.Cluster) – An instance protobuf object.
instance (google.cloud.bigtable.instance.Instance) – The instance that owns the cluster.

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.

Type: str

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()[source]¶

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()[source]¶

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.

Cluster¶

google-cloud-bigtable

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