← Databricks

Run Job Now with Databricks API

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Trigger workflow on
HTTP requests, schedules and app events
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Run Job Now with the Databricks API
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Getting Started

Create a workflow to Run Job Now with the Databricks API. When you configure and deploy the workflow, it will run on Pipedream's servers 24x7 for free.

  1. Configure the Run Job Now action
    1. Connect your Databricks account
    2. Select a Job
    3. Optional- Configure JAR Params
    4. Optional- Configure Notebook Params
    5. Optional- Configure Python Params
    6. Optional- Configure Spark Submit Params
    7. Optional- Configure Idempotency Token
  2. Select a trigger to run your workflow on HTTP requests, schedules or app events
  3. Deploy the workflow
  4. Send a test event to validate your setup
  5. Turn on the trigger

Integrations

Run Job Now with Databricks API on New Requests (Payload Only) from HTTP / Webhook API
HTTP / Webhook + Databricks
 
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Run Job Now with Databricks API on New Submission from Typeform API
Typeform + Databricks
 
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Run Job Now with Databricks API on Custom Events from Zoom API
Zoom + Databricks
 
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Run Job Now with Databricks API on New Submission (Instant) from Jotform API
Jotform + Databricks
 
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Run Job Now with Databricks API on New Scheduled Tasks from Pipedream API
Pipedream + Databricks
 
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Details

This is a pre-built, source-available component from Pipedream's GitHub repo. The component is developed by Pipedream and the community, and verified and maintained by Pipedream.

To contribute an update to an existing component or create a new component, create a PR on GitHub. If you're new to Pipedream component development, you can start with quickstarts for trigger span and action development, and then review the component API reference.

Run Job Now on Databricks
Description:Run a job now and return the id of the triggered run. [See the documentation](https://docs.databricks.com/en/workflows/jobs/jobs-2.0-api.html#runs-list)
Version:0.0.1
Key:databricks-run-job-now

Code

import databricks from "../../databricks.app.mjs";

export default {
  key: "databricks-run-job-now",
  name: "Run Job Now",
  description: "Run a job now and return the id of the triggered run. [See the documentation](https://docs.databricks.com/en/workflows/jobs/jobs-2.0-api.html#runs-list)",
  version: "0.0.1",
  type: "action",
  props: {
    databricks,
    jobId: {
      propDefinition: [
        databricks,
        "jobId",
      ],
    },
    jarParams: {
      type: "string[]",
      label: "JAR Params",
      description: "A list of parameters for jobs with JAR tasks, e.g. \"jar_params\": [\"john doe\", \"35\"]. The parameters will be used to invoke the main function of the main class specified in the Spark JAR task. If not specified upon run-now, it will default to an empty list. jar_params cannot be specified in conjunction with notebook_params. The JSON representation of this field (i.e. {\"jar_params\":[\"john doe\",\"35\"]}) cannot exceed 10,000 bytes.",
      optional: true,
    },
    notebookParams: {
      type: "object",
      label: "Notebook Params",
      description: "A map 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 is accessible through the dbutils.widgets.get function. If not specified upon run-now, the triggered run uses the job’s base parameters. You cannot specify notebook_params 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.",
      optional: true,
    },
    pythonParams: {
      type: "string[]",
      label: "Python Params",
      description: "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.",
      optional: true,
    },
    sparkSubmitParams: {
      type: "string[]",
      label: "Spark Submit Params",
      description: "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.",
      optional: true,
    },
    idempotencyToken: {
      type: "string",
      label: "Idempotency Token",
      description: "An optional token 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](https://kb.databricks.com/jobs/jobs-idempotency.html).",
      optional: true,
    },
  },
  async run({ $ }) {
    const response = await this.databricks.runJobNow({
      data: {
        job_id: this.jobId,
        jar_params: this.jarParams,
        notebook_params: this.notebookParams,
        python_params: this.pythonParams,
        spark_submit_params: this.sparkSubmitParams,
        idempotency_token: this.idempotencyToken,
      },
      $,
    });

    if (response) {
      $.export("$summary", `Successfully initiated job with ID ${this.jobId}.`);
    }

    return response;
  },
};

Configuration

This component may be configured based on the props defined in the component code. Pipedream automatically prompts for input values in the UI and CLI.
LabelPropTypeDescription
DatabricksdatabricksappThis component uses the Databricks app.
JobjobIdstringSelect a value from the drop down menu.
JAR ParamsjarParamsstring[]

A list of parameters for jobs with JAR tasks, e.g. "jar_params": ["john doe", "35"]. The parameters will be used to invoke the main function of the main class specified in the Spark JAR task. If not specified upon run-now, it will default to an empty list. jar_params cannot be specified in conjunction with notebook_params. The JSON representation of this field (i.e. {"jar_params":["john doe","35"]}) cannot exceed 10,000 bytes.

Notebook ParamsnotebookParamsobject

A map 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 is accessible through the dbutils.widgets.get function. If not specified upon run-now, the triggered run uses the job’s base parameters. You cannot specify notebook_params 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.

Python ParamspythonParamsstring[]

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.

Spark Submit ParamssparkSubmitParamsstring[]

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.

Idempotency TokenidempotencyTokenstring

An optional token 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.

Authentication

Databricks uses API keys for authentication. When you connect your Databricks account, Pipedream securely stores the keys so you can easily authenticate to Databricks APIs in both code and no-code steps.

To retrieve your Personal Access Token:

  • Sign in to your Databricks account, and open your Databricks workspace.
  • From your workspace, click on your username in the top right corner,
  • Go to “User Settings” > "Developer" > “Access tokens”

Your domain is 1234 if your Databricks instance URL is https://1234.cloud.databricks.com/, except for the Accounts API whose domain is account regardless of instance.

About Databricks

Databricks is the lakehouse company, helping data teams solve the world’s toughest problems.

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Lists all runs available to the user. See the documentation

 
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