Run Job Now with Databricks API

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Run Job Now with the Databricks API

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Evaluation update: @pipedream has quite literally been a dream to work with! I’m excited to leverage this tool for all the various workflows I need to write. I’m currently at 11k invocations a day from the initial workflows I’ve written in the past couple weeks.
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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.

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
Select a trigger to run your workflow on HTTP requests, schedules or app events
Deploy the workflow
Send a test event to validate your setup
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

Try it

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

View on GitHub

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.

Label	Prop	Type	Description
Databricks	`databricks`	`app`	This component uses the Databricks app.
Job	`jobId`	`string`	Select a value from the drop down menu.
JAR Params	`jarParams`	`string[]`	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 Params	`notebookParams`	`object`	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 Params	`pythonParams`	`string[]`	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 Params	`sparkSubmitParams`	`string[]`	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 Token	`idempotencyToken`	`string`	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.