# Databricks Tasks


This module contains a collection of tasks for interacting with Databricks resources.

# DatabricksSubmitRun

class

prefect.tasks.databricks.databricks_submitjob.DatabricksSubmitRun

(databricks_conn_secret=None, json=None, spark_jar_task=None, notebook_task=None, new_cluster=None, existing_cluster_id=None, libraries=None, run_name=None, timeout_seconds=None, polling_period_seconds=30, databricks_retry_limit=3, databricks_retry_delay=1, **kwargs)[source]

Submits a Spark job run to Databricks using the api/2.0/jobs/runs/submit <https://docs.databricks.com/api/latest/jobs.html#runs-submit>_ API endpoint.

There are two ways to instantiate this task.

In the first way, you can take the JSON payload that you typically use to call the api/2.0/jobs/runs/submit endpoint and pass it directly to our DatabricksSubmitRun task through the json parameter. For example:

json = {
    'new_cluster': {
    'spark_version': '2.1.0-db3-scala2.11',
    'num_workers': 2
    },
    'notebook_task': {
    'notebook_path': '/Users/[email protected]/PrepareData',
    },
}

conn = PrefectSecret('DATABRICKS_CONNECTION_STRING')
notebook_run = DatabricksSubmitRun(databricks_conn_string=conn, json=json)

Another way to accomplish the same thing is to use the named parameters of the DatabricksSubmitRun directly. Note that there is exactly one named parameter for each top level parameter in the runs/submit endpoint. In this method, your code would look like this:

new_cluster = {
    'spark_version': '2.1.0-db3-scala2.11',
    'num_workers': 2
}
notebook_task = {
    'notebook_path': '/Users/[email protected]/PrepareData',
}

conn = PrefectSecret('DATABRICKS_CONNECTION_STRING')
notebook_run = DatabricksSubmitRun(
    databricks_conn_string=conn,
    new_cluster=new_cluster,
    notebook_task=notebook_task)

In the case where both the json parameter AND the named parameters are provided, they will be merged together. If there are conflicts during the merge, the named parameters will take precedence and override the top level json keys.

This task requires a Databricks connection to be specified as a Prefect secret and can be passed to the task like so:

from prefect.tasks.secrets import PrefectSecret
from prefect.contrib.tasks.databricks import DatabricksSubmitRun

with Flow('my flow') as flow:
    conn = PrefectSecret('DATABRICKS_CONNECTION_STRING')
    DatabricksSubmitRun(databricks_conn_string=conn, json=...)

Currently the named parameters that DatabricksSubmitRun task supports are

  • spark_jar_task - notebook_task - new_cluster - existing_cluster_id - libraries - run_name - timeout_seconds

Args:

  • databricks_conn_secret (dict, optional): Dictionary representation of the Databricks Connection String. Structure must be a string of valid JSON. To use token based authentication, provide the key token in the string for the connection and create the key host. PREFECT__CONTEXT__SECRETS__DATABRICKS_CONNECTION_STRING= '{"host": "abcdef.xyz", "login": "ghijklmn", "password": "opqrst"}' OR PREFECT__CONTEXT__SECRETS__DATABRICKS_CONNECTION_STRING= '{"host": "abcdef.xyz", "token": "ghijklmn"}' See documentation of the DatabricksSubmitRun Task to see how to pass in the connection string using PrefectSecret.
  • json (dict, optional): A JSON object containing API parameters which will be passed directly to the api/2.0/jobs/runs/submit endpoint. The other named parameters (i.e. spark_jar_task, notebook_task..) to this task will be merged with this json dictionary if they are provided. If there are conflicts during the merge, the named parameters will take precedence and override the top level json keys. (templated) For more information about templating see :ref:jinja-templating. https://docs.databricks.com/api/latest/jobs.html#runs-submit
  • spark_jar_task (dict, optional): The main class and parameters for the JAR task. Note that the actual JAR is specified in the libraries. EITHER spark_jar_task OR notebook_task should be specified. This field will be templated. https://docs.databricks.com/api/latest/jobs.html#jobssparkjartask
  • notebook_task (dict, optional): The notebook path and parameters for the notebook task. EITHER spark_jar_task OR notebook_task should be specified. This field will be templated. https://docs.databricks.com/api/latest/jobs.html#jobsnotebooktask
  • new_cluster (dict, optional): Specs for a new cluster on which this task will be run. EITHER new_cluster OR existing_cluster_id should be specified. This field will be templated. https://docs.databricks.com/api/latest/jobs.html#jobsclusterspecnewcluster
  • existing_cluster_id (str, optional): ID for existing cluster on which to run this task. EITHER new_cluster OR existing_cluster_id should be specified. This field will be templated.
  • libraries (list of dicts, optional): Libraries which this run will use. This field will be templated. https://docs.databricks.com/api/latest/libraries.html#managedlibrarieslibrary
  • run_name (str, optional): The run name used for this task. By default this will be set to the Prefect task_id. This task_id is a required parameter of the superclass Task. This field will be templated.
  • timeout_seconds (int, optional): The timeout for this run. By default a value of 0 is used which means to have no timeout. This field will be templated.
  • polling_period_seconds (int, optional): Controls the rate which we poll for the result of this run. By default the task will poll every 30 seconds.
  • databricks_retry_limit (int, optional): Amount of times retry if the Databricks backend is unreachable. Its value must be greater than or equal to 1.
  • databricks_retry_delay (float, optional): Number of seconds to wait between retries (it might be a floating point number).
  • **kwargs (dict, optional): additional keyword arguments to pass to the Task constructor

methods:                                                                                                                                                       

prefect.tasks.databricks.databricks_submitjob.DatabricksSubmitRun.get_hook

()[source]

prefect.tasks.databricks.databricks_submitjob.DatabricksSubmitRun.run

(databricks_conn_secret=None, json=None, spark_jar_task=None, notebook_task=None, new_cluster=None, existing_cluster_id=None, libraries=None, run_name=None, timeout_seconds=None, polling_period_seconds=30, databricks_retry_limit=3, databricks_retry_delay=1)[source]

Task run method.

Args:

  • databricks_conn_secret (dict, optional): Dictionary representation of the Databricks Connection String. Structure must be a string of valid JSON. To use token based authentication, provide the key token in the string for the connection and create the key host. PREFECT__CONTEXT__SECRETS__DATABRICKS_CONNECTION_STRING= '{"host": "abcdef.xyz", "login": "ghijklmn", "password": "opqrst"}' OR PREFECT__CONTEXT__SECRETS__DATABRICKS_CONNECTION_STRING= '{"host": "abcdef.xyz", "token": "ghijklmn"}' See documentation of the DatabricksSubmitRun Task to see how to pass in the connection string using PrefectSecret.
  • json (dict, optional): A JSON object containing API parameters which will be passed directly to the api/2.0/jobs/runs/submit endpoint. The other named parameters (i.e. spark_jar_task, notebook_task..) to this task will be merged with this json dictionary if they are provided. If there are conflicts during the merge, the named parameters will take precedence and override the top level json keys. (templated) For more information about templating see :ref:jinja-templating. https://docs.databricks.com/api/latest/jobs.html#runs-submit
  • spark_jar_task (dict, optional): The main class and parameters for the JAR task. Note that the actual JAR is specified in the libraries. EITHER spark_jar_task OR notebook_task should be specified. This field will be templated. https://docs.databricks.com/api/latest/jobs.html#jobssparkjartask
  • notebook_task (dict, optional): The notebook path and parameters for the notebook task. EITHER spark_jar_task OR notebook_task should be specified. This field will be templated. https://docs.databricks.com/api/latest/jobs.html#jobsnotebooktask
  • new_cluster (dict, optional): Specs for a new cluster on which this task will be run. EITHER new_cluster OR existing_cluster_id should be specified. This field will be templated. https://docs.databricks.com/api/latest/jobs.html#jobsclusterspecnewcluster
  • existing_cluster_id (str, optional): ID for existing cluster on which to run this task. EITHER new_cluster OR existing_cluster_id should be specified. This field will be templated.
  • libraries (list of dicts, optional): Libraries which this run will use. This field will be templated. https://docs.databricks.com/api/latest/libraries.html#managedlibrarieslibrary
  • run_name (str, optional): The run name used for this task. By default this will be set to the Prefect task_id. This task_id is a required parameter of the superclass Task. This field will be templated.
  • timeout_seconds (int, optional): The timeout for this run. By default a value of 0 is used which means to have no timeout. This field will be templated.
  • polling_period_seconds (int, optional): Controls the rate which we poll for the result of this run. By default the task will poll every 30 seconds.
  • databricks_retry_limit (int, optional): Amount of times retry if the Databricks backend is unreachable. Its value must be greater than or equal to 1.
  • databricks_retry_delay (float, optional): Number of seconds to wait between retries (it might be a floating point number).
Returns:
  • run_id (str): Run id of the submitted run



# DatabricksRunNow

class

prefect.tasks.databricks.databricks_submitjob.DatabricksRunNow

(databricks_conn_secret=None, job_id=None, json=None, notebook_params=None, python_params=None, spark_submit_params=None, polling_period_seconds=30, databricks_retry_limit=3, databricks_retry_delay=1, **kwargs)[source]

Runs an existing Spark job run to Databricks using the api/2.0/jobs/run-now <https://docs.databricks.com/api/latest/jobs.html#run-now>_ API endpoint.

There are two ways to instantiate this task.

In the first way, you can take the JSON payload that you typically use to call the api/2.0/jobs/run-now endpoint and pass it directly to our DatabricksRunNow task through the json parameter. For example:

json = {
      "job_id": 42,
      "notebook_params": {
        "dry-run": "true",
        "oldest-time-to-consider": "1457570074236"
      }
    }

conn = PrefectSecret('DATABRICKS_CONNECTION_STRING')
notebook_run = DatabricksRunNow(databricks_conn_string=conn, json=json)

Another way to accomplish the same thing is to use the named parameters of the DatabricksRunNow task directly. Note that there is exactly one named parameter for each top level parameter in the run-now endpoint. In this method, your code would look like this:

job_id=42

notebook_params = {
    "dry-run": "true",
    "oldest-time-to-consider": "1457570074236"
}

python_params = ["douglas adams", "42"]

spark_submit_params = ["--class", "org.apache.spark.examples.SparkPi"]

conn = PrefectSecret('DATABRICKS_CONNECTION_STRING')
notebook_run = DatabricksRunNow(
    databricks_conn_string=conn,
    notebook_params=notebook_params,
    python_params=python_params,
    spark_submit_params=spark_submit_params
)

In the case where both the json parameter AND the named parameters are provided, they will be merged together. If there are conflicts during the merge, the named parameters will take precedence and override the top level json keys.

This task requires a Databricks connection to be specified as a Prefect secret and can be passed to the task like so:

from prefect.tasks.secrets import PrefectSecret
from prefect.contrib.tasks.databricks import DatabricksRunNow

with Flow('my flow') as flow:
    conn = PrefectSecret('DATABRICKS_CONNECTION_STRING')
    DatabricksRunNow(databricks_conn_string=conn, json=...)

Currently the named parameters that DatabricksRunNow task supports are

  • job_id - json - notebook_params - python_params - spark_submit_params

Args:

  • databricks_conn_secret (dict, optional): Dictionary representation of the Databricks Connection String. Structure must be a string of valid JSON. To use token based authentication, provide the key token in the string for the connection and create the key host. PREFECT__CONTEXT__SECRETS__DATABRICKS_CONNECTION_STRING= '{"host": "abcdef.xyz", "login": "ghijklmn", "password": "opqrst"}' OR PREFECT__CONTEXT__SECRETS__DATABRICKS_CONNECTION_STRING= '{"host": "abcdef.xyz", "token": "ghijklmn"}' See documentation of the DatabricksSubmitRun Task to see how to pass in the connection string using PrefectSecret.
  • job_id (str, optional): The job_id of the existing Databricks job. https://docs.databricks.com/api/latest/jobs.html#run-now
  • json (dict, optional): A JSON object containing API parameters which will be passed directly to the api/2.0/jobs/run-now endpoint. The other named parameters (i.e. notebook_params, spark_submit_params..) to this operator will be merged with this json dictionary if they are provided. If there are conflicts during the merge, the named parameters will take precedence and override the top level json keys. (templated) https://docs.databricks.com/api/latest/jobs.html#run-now
  • notebook_params (dict, optional): A dict from keys to values for jobs with notebook task, e.g. "notebook_params": {"name": "john doe", "age": "35"}. The map is passed to the notebook and will be accessible through the dbutils.widgets.get function. See Widgets for more information. If not specified upon run-now, the triggered run will use the job’s base parameters. notebook_params cannot be specified in conjunction with jar_params. The json representation of this field (i.e. {"notebook_params":{"name":"john doe","age":"35"}}) cannot exceed 10,000 bytes. https://docs.databricks.com/user-guide/notebooks/widgets.html
  • python_params (list[str], optional): A list of parameters for jobs with python tasks, e.g. "python_params": ["john doe", "35"]. The parameters will be 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 (i.e. {"python_params":["john doe","35"]}) cannot exceed 10,000 bytes. https://docs.databricks.com/api/latest/jobs.html#run-now
  • spark_submit_params (list[str], optional): A list of parameters for jobs with spark submit task, e.g. "spark_submit_params": ["--class", "org.apache.spark.examples.SparkPi"]. The parameters will be 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 cannot exceed 10,000 bytes. https://docs.databricks.com/api/latest/jobs.html#run-now
  • timeout_seconds (int, optional): The timeout for this run. By default a value of 0 is used which means to have no timeout. This field will be templated.
  • polling_period_seconds (int, optional): Controls the rate which we poll for the result of this run. By default the task will poll every 30 seconds.
  • databricks_retry_limit (int, optional): Amount of times retry if the Databricks backend is unreachable. Its value must be greater than or equal to 1.
  • databricks_retry_delay (float, optional): Number of seconds to wait between retries (it might be a floating point number).
  • **kwargs (dict, optional): additional keyword arguments to pass to the Task constructor

methods:                                                                                                                                                       

prefect.tasks.databricks.databricks_submitjob.DatabricksRunNow.get_hook

()[source]

prefect.tasks.databricks.databricks_submitjob.DatabricksRunNow.run

(databricks_conn_secret=None, job_id=None, json=None, notebook_params=None, python_params=None, spark_submit_params=None, polling_period_seconds=30, databricks_retry_limit=3, databricks_retry_delay=1)[source]

Task run method.

Args:

  • databricks_conn_secret (dict, optional): Dictionary representation of the Databricks Connection String. Structure must be a string of valid JSON. To use token based authentication, provide the key token in the string for the connection and create the key host. PREFECT__CONTEXT__SECRETS__DATABRICKS_CONNECTION_STRING= '{"host": "abcdef.xyz", "login": "ghijklmn", "password": "opqrst"}' OR PREFECT__CONTEXT__SECRETS__DATABRICKS_CONNECTION_STRING= '{"host": "abcdef.xyz", "token": "ghijklmn"}' See documentation of the DatabricksSubmitRun Task to see how to pass in the connection string using PrefectSecret.
  • job_id (str, optional): The job_id of the existing Databricks job. https://docs.databricks.com/api/latest/jobs.html#run-now
  • json (dict, optional): A JSON object containing API parameters which will be passed directly to the api/2.0/jobs/run-now endpoint. The other named parameters (i.e. notebook_params, spark_submit_params..) to this operator will be merged with this json dictionary if they are provided. If there are conflicts during the merge, the named parameters will take precedence and override the top level json keys. (templated) https://docs.databricks.com/api/latest/jobs.html#run-now
  • notebook_params (dict, optional): A dict from keys to values for jobs with notebook task, e.g. "notebook_params": {"name": "john doe", "age": "35"}. The map is passed to the notebook and will be accessible through the dbutils.widgets.get function. See Widgets for more information. If not specified upon run-now, the triggered run will use the job’s base parameters. notebook_params cannot be specified in conjunction with jar_params. The json representation of this field (i.e. {"notebook_params":{"name":"john doe","age":"35"}}) cannot exceed 10,000 bytes. https://docs.databricks.com/user-guide/notebooks/widgets.html
  • python_params (list[str], optional): A list of parameters for jobs with python tasks, e.g. "python_params": ["john doe", "35"]. The parameters will be 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 (i.e. {"python_params":["john doe","35"]}) cannot exceed 10,000 bytes. https://docs.databricks.com/api/latest/jobs.html#run-now
  • spark_submit_params (list[str], optional): A list of parameters for jobs with spark submit task, e.g. "spark_submit_params": ["--class", "org.apache.spark.examples.SparkPi"]. The parameters will be 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 cannot exceed 10,000 bytes. https://docs.databricks.com/api/latest/jobs.html#run-now
  • polling_period_seconds (int, optional): Controls the rate which we poll for the result of this run. By default the task will poll every 30 seconds.
  • databricks_retry_limit (int, optional): Amount of times retry if the Databricks backend is unreachable. Its value must be greater than or equal to 1.
  • databricks_retry_delay (float, optional): Number of seconds to wait between retries (it might be a floating point number).
Returns:
  • run_id (str): Run id of the submitted run



This documentation was auto-generated from commit a0bf4db
on September 28, 2020 at 16:26 UTC