New Cluster
Usage
new_cluster(
num_workers,
spark_version,
node_type_id,
driver_node_type_id = NULL,
autoscale = NULL,
cloud_attrs = NULL,
spark_conf = NULL,
spark_env_vars = NULL,
custom_tags = NULL,
ssh_public_keys = NULL,
log_conf = NULL,
init_scripts = NULL,
enable_elastic_disk = TRUE,
driver_instance_pool_id = NULL,
instance_pool_id = NULL
)
Arguments
- num_workers
Number of worker nodes that this cluster should have. A cluster has one Spark driver and
num_workers
executors for a total ofnum_workers
+ 1 Spark nodes.- spark_version
The runtime version of the cluster. You can retrieve a list of available runtime versions by using
db_cluster_runtime_versions()
.- node_type_id
The node type for the worker nodes.
db_cluster_list_node_types()
can be used to see available node types.- driver_node_type_id
The node type of the Spark driver. This field is optional; if unset, the driver node type will be set as the same value as
node_type_id
defined above.db_cluster_list_node_types()
can be used to see available node types.- autoscale
Instance of
cluster_autoscale()
.- cloud_attrs
Attributes related to clusters running on specific cloud provider. Defaults to
aws_attributes()
. Must be one ofaws_attributes()
,azure_attributes()
,gcp_attributes()
.- spark_conf
Named list. An object containing a set of optional, user-specified Spark configuration key-value pairs. You can also pass in a string of extra JVM options to the driver and the executors via
spark.driver.extraJavaOptions
andspark.executor.extraJavaOptions
respectively. E.g.list("spark.speculation" = true, "spark.streaming.ui.retainedBatches" = 5)
.- spark_env_vars
Named list. User-specified environment variable key-value pairs. In order to specify an additional set of
SPARK_DAEMON_JAVA_OPTS
, we recommend appending them to$SPARK_DAEMON_JAVA_OPTS
as shown in the following example. This ensures that all default Databricks managed environmental variables are included as well. E.g.{"SPARK_DAEMON_JAVA_OPTS": "$SPARK_DAEMON_JAVA_OPTS -Dspark.shuffle.service.enabled=true"}
Named list. An object containing a set of tags for cluster resources. Databricks tags all cluster resources with these tags in addition to
default_tags
. Databricks allows at most 45 custom tags.- ssh_public_keys
List. SSH public key contents that will be added to each Spark node in this cluster. The corresponding private keys can be used to login with the user name ubuntu on port 2200. Up to 10 keys can be specified.
- log_conf
Instance of
cluster_log_conf()
.- init_scripts
Instance of
init_script_info()
.- enable_elastic_disk
When enabled, this cluster will dynamically acquire additional disk space when its Spark workers are running low on disk space.
- driver_instance_pool_id
ID of the instance pool to use for the driver node. You must also specify
instance_pool_id
. Optional.- instance_pool_id
ID of the instance pool to use for cluster nodes. If
driver_instance_pool_id
is present,instance_pool_id
is used for worker nodes only. Otherwise, it is used for both the driver and worker nodes. Optional.
See also
Other Task Objects:
email_notifications()
,
libraries()
,
notebook_task()
,
pipeline_task()
,
python_wheel_task()
,
spark_jar_task()
,
spark_python_task()
,
spark_submit_task()