prefect_databricks.flows
¶
Module containing flows for interacting with Databricks
DatabricksJobInternalError
¶
Bases: Exception
Raised when Databricks jobs runs submit encounters internal error
Source code in prefect_databricks/flows.py
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DatabricksJobRunTimedOut
¶
Bases: Exception
Raised when Databricks jobs runs does not complete in the configured max wait seconds
Source code in prefect_databricks/flows.py
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DatabricksJobSkipped
¶
Bases: Exception
Raised when Databricks jobs runs submit skips
Source code in prefect_databricks/flows.py
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DatabricksJobTerminated
¶
Bases: Exception
Raised when Databricks jobs runs submit terminates
Source code in prefect_databricks/flows.py
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|
jobs_runs_submit_and_wait_for_completion
async
¶
Flow that triggers a job run and waits for the triggered run to complete.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
databricks_credentials |
DatabricksCredentials
|
Credentials to use for authentication with Databricks. |
required |
tasks |
Optional[List[RunSubmitTaskSettings]]
|
Tasks to run, e.g.
|
None
|
run_name |
Optional[str]
|
An optional name for the run. The default value is |
None
|
git_source |
Optional[GitSource]
|
This functionality is in Public Preview. An optional specification for
a remote repository containing the notebooks used by this
job's notebook tasks. Key-values:
- git_url:
URL of the repository to be cloned by this job. The maximum
length is 300 characters, e.g.
|
None
|
timeout_seconds |
Optional[int]
|
An optional timeout applied to each run of this job. The default
behavior is to have no timeout, e.g. |
None
|
idempotency_token |
Optional[str]
|
An optional token that can be used to guarantee the idempotency of job
run requests. If a run with the provided token already
exists, the request does not create a new run but returns
the ID of the existing run instead. If a run with the
provided token is deleted, an error is returned. If you
specify the idempotency token, upon failure you can retry
until the request succeeds. Databricks guarantees that
exactly one run is launched with that idempotency token.
This token must have at most 64 characters. For more
information, see How to ensure idempotency for
jobs,
e.g. |
None
|
access_control_list |
Optional[List[AccessControlRequest]]
|
List of permissions to set on the job. |
None
|
max_wait_seconds |
int
|
Maximum number of seconds to wait for the entire flow to complete. |
900
|
poll_frequency_seconds |
int
|
Number of seconds to wait in between checks for run completion. |
10
|
return_metadata |
bool
|
When True, method will return a tuple of notebook output as well as job run metadata; by default though, the method only returns notebook output |
False
|
job_submission_handler |
Optional[Callable]
|
An optional callable to intercept job submission. |
None
|
**jobs_runs_submit_kwargs |
Dict[str, Any]
|
Additional keyword arguments to pass to |
{}
|
Returns:
Type | Description |
---|---|
Union[NotebookOutput, Tuple[NotebookOutput, JobMetadata], None]
|
Either a dict or a tuple (depends on |
Union[NotebookOutput, Tuple[NotebookOutput, JobMetadata], None]
|
|
Union[NotebookOutput, Tuple[NotebookOutput, JobMetadata], None]
|
|
Examples:
Submit jobs runs and wait.
from prefect import flow
from prefect_databricks import DatabricksCredentials
from prefect_databricks.flows import jobs_runs_submit_and_wait_for_completion
from prefect_databricks.models.jobs import (
AutoScale,
AwsAttributes,
JobTaskSettings,
NotebookTask,
NewCluster,
)
@flow
def jobs_runs_submit_and_wait_for_completion_flow(notebook_path, **base_parameters):
databricks_credentials = await DatabricksCredentials.load("BLOCK_NAME")
# specify new cluster settings
aws_attributes = AwsAttributes(
availability="SPOT",
zone_id="us-west-2a",
ebs_volume_type="GENERAL_PURPOSE_SSD",
ebs_volume_count=3,
ebs_volume_size=100,
)
auto_scale = AutoScale(min_workers=1, max_workers=2)
new_cluster = NewCluster(
aws_attributes=aws_attributes,
autoscale=auto_scale,
node_type_id="m4.large",
spark_version="10.4.x-scala2.12",
spark_conf={"spark.speculation": True},
)
# specify notebook to use and parameters to pass
notebook_task = NotebookTask(
notebook_path=notebook_path,
base_parameters=base_parameters,
)
# compile job task settings
job_task_settings = JobTaskSettings(
new_cluster=new_cluster,
notebook_task=notebook_task,
task_key="prefect-task"
)
multi_task_runs = jobs_runs_submit_and_wait_for_completion(
databricks_credentials=databricks_credentials,
run_name="prefect-job",
tasks=[job_task_settings]
)
return multi_task_runs
Source code in prefect_databricks/flows.py
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|
jobs_runs_submit_by_id_and_wait_for_completion
async
¶
flow that triggers an existing job and waits for its completion
Parameters:
Name | Type | Description | Default |
---|---|---|---|
databricks_credentials |
DatabricksCredentials
|
Credentials to use for authentication with Databricks. |
required |
job_id |
int
|
Id of the databricks job. |
required |
idempotency_token |
Optional[str]
|
An optional token that can be used to guarantee the idempotency of job
run requests. If a run with the provided token already
exists, the request does not create a new run but returns
the ID of the existing run instead. If a run with the
provided token is deleted, an error is returned. If you
specify the idempotency token, upon failure you can retry
until the request succeeds. Databricks guarantees that
exactly one run is launched with that idempotency token.
This token must have at most 64 characters. For more
information, see How to ensure idempotency for
jobs,
e.g. |
None
|
jar_params |
Optional[List[str]]
|
A list of parameters for jobs with Spark JAR tasks, for example "jar_params" : ["john doe", "35"]. The parameters are used to invoke the main function of the main class specified in the Spark JAR task. If not specified upon run- now, it defaults to an empty list. jar_params cannot be specified in conjunction with notebook_params. The JSON representation of this field (for example {"jar_params": ["john doe","35"]}) cannot exceed 10,000 bytes. |
None
|
max_wait_seconds |
int
|
Maximum number of seconds to wait for the entire flow to complete. |
900
|
poll_frequency_seconds |
int
|
Number of seconds to wait in between checks for run completion. |
10
|
notebook_params |
Optional[Dict]
|
A map from keys to values for jobs with notebook task, for example "notebook_params": {"name": "john doe", "age": "35"}. The map is passed to the notebook and is accessible through the dbutils.widgets.get function. If not specified upon run-now, the triggered run uses the job’s base parameters. notebook_params cannot be specified in conjunction with jar_params. Use Task parameter variables to set parameters containing information about job runs. The JSON representation of this field (for example {"notebook_params":{"name":"john doe","age":"35"}}) cannot exceed 10,000 bytes. |
None
|
python_params |
Optional[List[str]]
|
A list of parameters for jobs with Python tasks, for example "python_params" :["john doe", "35"]. The parameters are passed to Python file as command- line parameters. If specified upon run-now, it would overwrite the parameters specified in job setting. The JSON representation of this field (for example {"python_params":["john doe","35"]}) cannot exceed 10,000 bytes Use Task parameter variables to set parameters containing information about job runs. These parameters accept only Latin characters (ASCII character set). Using non-ASCII characters returns an error. Examples of invalid, non-ASCII characters are Chinese, Japanese kanjis, and emojis. |
None
|
spark_submit_params |
Optional[List[str]]
|
A list of parameters for jobs with spark submit task, for example "spark_submit_params": ["--class", "org.apache.spark.examples.SparkPi"]. The parameters are passed to spark-submit script as command-line parameters. If specified upon run-now, it would overwrite the parameters specified in job setting. The JSON representation of this field (for example {"python_params":["john doe","35"]}) cannot exceed 10,000 bytes. Use Task parameter variables to set parameters containing information about job runs. These parameters accept only Latin characters (ASCII character set). Using non-ASCII characters returns an error. Examples of invalid, non-ASCII characters are Chinese, Japanese kanjis, and emojis. |
None
|
python_named_params |
Optional[Dict]
|
A map from keys to values for jobs with Python wheel task, for example "python_named_params": {"name": "task", "data": "dbfs:/path/to/data.json"}. |
None
|
pipeline_params |
Optional[str]
|
If
|
None
|
sql_params |
Optional[Dict]
|
A map from keys to values for SQL tasks, for example "sql_params": {"name": "john doe", "age": "35"}. The SQL alert task does not support custom parameters. |
None
|
dbt_commands |
Optional[List]
|
An array of commands to execute for jobs with the dbt task, for example "dbt_commands": ["dbt deps", "dbt seed", "dbt run"] |
None
|
job_submission_handler |
Optional[Callable]
|
An optional callable to intercept job submission |
None
|
Raises:
Type | Description |
---|---|
DatabricksJobTerminated
|
Raised when the Databricks job run is terminated with a non-successful result state. |
DatabricksJobSkipped
|
Raised when the Databricks job run is skipped. |
DatabricksJobInternalError
|
Raised when the Databricks job run encounters an internal error. |
Returns:
Name | Type | Description |
---|---|---|
Dict |
Dict
|
A dictionary containing information about the completed job run. |
Example
from prefect import flow
from prefect_databricks import DatabricksCredentials
from prefect_databricks.flows import (
jobs_runs_submit_by_id_and_wait_for_completion,
)
@flow
def submit_existing_job(block_name: str, job_id):
databricks_credentials = DatabricksCredentials.load(block_name)
run = jobs_runs_submit_by_id_and_wait_for_completion(
databricks_credentials=databricks_credentials, job_id=job_id
)
return run
submit_existing_job(block_name="db-creds", job_id=db_job_id)
Source code in prefect_databricks/flows.py
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jobs_runs_wait_for_completion
async
¶
Flow that triggers a job run and waits for the triggered run to complete.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
run_name |
Optional[str]
|
The name of the jobs runs task. |
None
|
multi_task_jobs_run_id |
The ID of the jobs runs task to watch. |
required | |
databricks_credentials |
DatabricksCredentials
|
Credentials to use for authentication with Databricks. |
required |
max_wait_seconds |
int
|
Maximum number of seconds to wait for the entire flow to complete. |
900
|
poll_frequency_seconds |
int
|
Number of seconds to wait in between checks for run completion. |
10
|
Returns:
Name | Type | Description |
---|---|---|
jobs_runs_state |
A dict containing the jobs runs life cycle state and message. |
|
jobs_runs_metadata |
A dict containing IDs of the jobs runs tasks. |
Example
Waits for completion on jobs runs.
from prefect import flow
from prefect_databricks import DatabricksCredentials
from prefect_databricks.flows import jobs_runs_wait_for_completion
@flow
def jobs_runs_wait_for_completion_flow():
databricks_credentials = DatabricksCredentials.load("BLOCK_NAME")
return jobs_runs_wait_for_completion(
multi_task_jobs_run_id=45429,
databricks_credentials=databricks_credentials,
run_name="my_run_name",
max_wait_seconds=1800, # 30 minutes
poll_frequency_seconds=120, # 2 minutes
)
Source code in prefect_databricks/flows.py
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