Create Job with Databricks API on New Scheduled Tasks from Pipedream API

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New Scheduled Tasks from the Pipedream API

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Getting Started#

This integration creates a workflow with a Pipedream trigger and Databricks action. When you configure and deploy the workflow, it will run on Pipedream's servers 24x7 for free.

Select this integration
Configure the New Scheduled Tasks trigger
1. Connect your Pipedream account
2. Optional- Configure Secret
Configure the Create Job action
1. Connect your Databricks account
2. Configure Tasks
3. Optional- Configure Job Name
4. Optional- Configure Tags
5. Optional- Configure Job Clusters
6. Optional- Configure Email Notifications
7. Optional- Configure Webhook Notifications
8. Optional- Configure Timeout Seconds
9. Optional- Configure Schedule
10. Optional- Configure Max Concurrent Runs
11. Optional- Configure Git Source
12. Optional- Configure Access Control List
Deploy the workflow
Send a test event to validate your setup
Turn on the trigger

Details#

This integration uses pre-built, source-available components from Pipedream's GitHub repo. These components are 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.

Trigger#

New Scheduled Tasks on Pipedream

Description:Exposes an HTTP API for scheduling messages to be emitted at a future time

Version:0.3.1

Key:pipedream-new-scheduled-tasks

View on GitHub

Pipedream Overview#

Pipedream is an API that allows you to build applications that can connect to
various data sources and processes them in real-time. You can use Pipedream to
create applications that can perform ETL (Extract, Transform, and Load) tasks,
as well as to create data-driven workflows.

Some examples of applications you can build using the Pipedream API include:

An application that can extract data from a database, transform it, and then
load it into another database.
An application that can monitor a data source for changes, and then trigger a
workflow in response to those changes.
An application that can poll an API for new data, and then process that data
in real-time.

Trigger Code#

import pipedream from "../../pipedream.app.mjs";
import sampleEmit from "./test-event.mjs";
import { uuid } from "uuidv4";

export default {
  key: "pipedream-new-scheduled-tasks",
  name: "New Scheduled Tasks",
  type: "source",
  description:
    "Exposes an HTTP API for scheduling messages to be emitted at a future time",
  version: "0.3.1",
  dedupe: "unique", // Dedupe on a UUID generated for every scheduled task
  props: {
    pipedream,
    secret: {
      type: "string",
      secret: true,
      label: "Secret",
      optional: true,
      description:
        "**Optional but recommended**: if you enter a secret here, you must pass this value in the `x-pd-secret` HTTP header when making requests",
    },
    http: {
      label: "Endpoint",
      description: "The endpoint where you'll send task scheduler requests",
      type: "$.interface.http",
      customResponse: true,
    },
    db: "$.service.db",
  },
  methods: {
    // To schedule future emits, we emit to the selfChannel of the component
    selfChannel() {
      return "self";
    },
    // Queue for future emits that haven't yet been delivered
    queuedEventsChannel() {
      return "$in";
    },
    httpRespond({
      status, body,
    }) {
      this.http.respond({
        headers: {
          "content-type": "application/json",
        },
        status,
        body,
      });
    },
    async selfSubscribe() {
      // Subscribe the component to itself. We do this here because even in
      // the activate hook, the component isn't available to take subscriptions.
      // Scheduled tasks are sent to the self channel, which emits the message at
      // the specified delivery_ts to this component.
      const isSubscribedToSelf = this.db.get("isSubscribedToSelf");
      if (!isSubscribedToSelf) {
        const componentId = process.env.PD_COMPONENT;
        const selfChannel = this.selfChannel();
        console.log(`Subscribing to ${selfChannel} channel for event source`);
        console.log(
          await this.pipedream.subscribe(componentId, componentId, selfChannel),
        );
        this.db.set("isSubscribedToSelf", true);
      }
    },
    validateEventBody(event, operation) {
      const errors = [];

      // Secrets are optional, so we first check if the user configured
      // a secret, then check its value against the prop (validation below)
      if (this.secret && event.headers["x-pd-secret"] !== this.secret) {
        errors.push(
          "Secret on incoming request doesn't match the configured secret",
        );
      }

      if (operation === "schedule") {
        const {
          timestamp,
          message,
        } = event.body;
        // timestamp should be an ISO 8601 string. Parse and check for validity below.
        const epoch = Date.parse(timestamp);

        if (!timestamp) {
          errors.push(
            "No timestamp included in payload. Please provide an ISO8601 timestamp in the 'timestamp' field",
          );
        }
        if (timestamp && !epoch) {
          errors.push("Timestamp isn't a valid ISO 8601 string");
        }
        if (!message) {
          errors.push("No message passed in payload");
        }
      }

      return errors;
    },
    scheduleTask(event) {
      const errors = this.validateEventBody(event, "schedule");
      let status, body;

      if (errors.length) {
        console.log(errors);
        status = 400;
        body = {
          errors,
        };
      } else {
        const id = this.emitScheduleEvent(event.body, event.body.timestamp);
        status = 200;
        body = {
          msg: "Successfully scheduled task",
          id,
        };
      }

      this.httpRespond({
        status,
        body,
      });
    },
    emitScheduleEvent(event, timestamp) {
      const selfChannel = this.selfChannel();
      const epoch = Date.parse(timestamp);
      const $id = uuid();

      console.log(`Scheduled event to emit on: ${new Date(epoch)}`);

      this.$emit(
        {
          ...event,
          $channel: selfChannel,
          $id,
        },
        {
          name: selfChannel,
          id: $id,
          delivery_ts: epoch,
        },
      );

      return $id;
    },
    async cancelTask(event) {
      const errors = this.validateEventBody(event, "cancel");
      let status, msg;

      if (errors.length) {
        console.log(errors);
        status = 400;
        msg = "Secret on incoming request doesn't match the configured secret";
      } else {
        try {
          const id = event.body.id;
          const isCanceled = await this.deleteEvent(event);
          if (isCanceled) {
            status = 200;
            msg = `Cancelled scheduled task for event ${id}`;
          } else {
            status = 404;
            msg = `No event with ${id} found`;
          }
        } catch (error) {
          console.log(error);
          status = 500;
          msg = "Failed to schedule task. Please see the logs";
        }
      }

      this.httpRespond({
        status,
        body: {
          msg,
        },
      });
    },
    async deleteEvent(event) {
      const componentId = process.env.PD_COMPONENT;
      const inChannel = this.queuedEventsChannel();

      // The user must pass a scheduled event UUID they'd like to cancel
      // We lookup the event by ID and delete it
      const { id } = event.body;

      // List events in the $in channel - the queue of scheduled events, to be emitted in the future
      const events = await this.pipedream.listEvents(
        componentId,
        inChannel,
      );
      console.log("Events: ", events);

      // Find the event in the list by id
      const eventToCancel = events.data.find((e) => {
        const { metadata } = e;
        return metadata.id === id;
      });

      console.log("Event to cancel: ", eventToCancel);

      if (!eventToCancel) {
        console.log(`No event with ${id} found`);
        return false;
      }

      // Delete the event
      await this.pipedream.deleteEvent(
        componentId,
        eventToCancel.id,
        inChannel,
      );
      return true;
    },
    emitEvent(event, summary) {
      // Delete the channel name and id from the incoming event, which were used only as metadata
      const id = event.$id;
      delete event.$channel;
      delete event.$id;

      this.$emit(event, {
        summary: summary ?? JSON.stringify(event),
        id,
        ts: +new Date(),
      });
    },
  },
  async run(event) {
    await this.selfSubscribe();

    const { path } = event;
    if (path === "/schedule") {
      this.scheduleTask(event);
    } else if (path === "/cancel") {
      await this.cancelTask(event);
    } else if (event.$channel === this.selfChannel()) {
      this.emitEvent(event);
    }
  },
  sampleEmit,
};

Trigger 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
Pipedream	`pipedream`	`app`	This component uses the Pipedream app.
Secret	`secret`	`string`	Optional but recommended: if you enter a secret here, you must pass this value in the `x-pd-secret` HTTP header when making requests
N/A	`http`	`$.interface.http`	This component uses `$.interface.http` to generate a unique URL when the component is first instantiated. Each request to the URL will trigger the `run()` method of the component.
N/A	`db`	`$.service.db`	This component uses `$.service.db` to maintain state between executions.

Trigger Authentication#

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

About Pipedream#

Integration platform for developers

Action#

Create Job on Databricks

Description:Create a job. [See the documentation](https://docs.databricks.com/api/workspace/jobs/create)

Version:0.0.1

Key:databricks-create-job

View on GitHub

Databricks Overview#

The Databricks API allows you to interact programmatically with Databricks services, enabling you to manage clusters, jobs, notebooks, and other resources within Databricks environments. Through Pipedream, you can leverage these APIs to create powerful automations and integrate with other apps for enhanced data processing, transformation, and analytics workflows. This unlocks possibilities like automating cluster management, dynamically running jobs based on external triggers, and orchestrating complex data pipelines with ease.

Action Code#

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

export default {
  key: "databricks-create-job",
  name: "Create Job",
  description: "Create a job. [See the documentation](https://docs.databricks.com/api/workspace/jobs/create)",
  version: "0.0.1",
  type: "action",
  props: {
    app,
    tasks: {
      type: "string[]",
      label: "Tasks",
      description: `A list of task specifications to be executed by this job. JSON string format. [See the API documentation](https://docs.databricks.com/api/workspace/jobs/create#tasks) for task specification details.

**Example:**
\`\`\`json
[
  {
    "notebook_task": {
      "notebook_path": "/Workspace/Users/sharky@databricks.com/weather_ingest"
    },
    "task_key": "weather_ocean_data"
  }
]
\`\`\`
      `,
    },
    name: {
      type: "string",
      label: "Job Name",
      description: "An optional name for the job",
      optional: true,
    },
    tags: {
      type: "object",
      label: "Tags",
      description: "A map of tags associated with the job. These are forwarded to the cluster as cluster tags for jobs clusters, and are subject to the same limitations as cluster tags",
      optional: true,
    },
    jobClusters: {
      type: "string[]",
      label: "Job Clusters",
      description: `A list of job cluster specifications that can be shared and reused by tasks of this job. JSON string format. [See the API documentation](https://docs.databricks.com/api/workspace/jobs/create#job_clusters) for job cluster specification details.

**Example:**
\`\`\`json
[
  {
    "job_cluster_key": "auto_scaling_cluster",
    "new_cluster": {
      "autoscale": {
        "max_workers": 16,
        "min_workers": 2
      },
      "node_type_id": null,
      "spark_conf": {
        "spark.speculation": true
      },
      "spark_version": "7.3.x-scala2.12"
    }
  }
]
\`\`\`
      `,
      optional: true,
    },
    emailNotifications: {
      type: "string",
      label: "Email Notifications",
      description: `An optional set of email addresses to notify when runs of this job begin, complete, or when the job is deleted. Specify as a JSON object with keys for each notification type. [See the API documentation](https://docs.databricks.com/api/workspace/jobs/create#email_notifications) for details on each field.

**Example:**
\`\`\`json
{
  "on_start": ["user1@example.com"],
  "on_success": ["user2@example.com"],
  "on_failure": ["user3@example.com"],
  "on_duration_warning_threshold_exceeded": ["user4@example.com"],
  "on_streaming_backlog_exceeded": ["user5@example.com"]
}
\`\`\`
`,
      optional: true,
    },
    webhookNotifications: {
      type: "string",
      label: "Webhook Notifications",
      description: `A collection of system notification IDs to notify when runs of this job begin, complete, or encounter specific events. Specify as a JSON object with keys for each notification type. Each key accepts an array of objects with an \`id\` property (system notification ID). A maximum of 3 destinations can be specified for each property.

Supported keys:
- \`on_start\`: Notified when the run starts.
- \`on_success\`: Notified when the run completes successfully.
- \`on_failure\`: Notified when the run fails.
- \`on_duration_warning_threshold_exceeded\`: Notified when the run duration exceeds the specified threshold.
- \`on_streaming_backlog_exceeded\`: Notified when streaming backlog thresholds are exceeded.

[See the API documentation](https://docs.databricks.com/api/workspace/jobs/create#webhook_notifications) for details.

**Example:**
\`\`\`json
{
  "on_success": [
    { "id": "https://eoiqkb8yzox6u2n.m.pipedream.net" }
  ],
  "on_failure": [
    { "id": "https://another-webhook-url.com/notify" }
  ]
}
\`\`\`
`,
      optional: true,
    },
    timeoutSeconds: {
      type: "integer",
      label: "Timeout Seconds",
      description: "An optional timeout applied to each run of this job. The default behavior is to have no timeout",
      optional: true,
    },
    schedule: {
      type: "string",
      label: "Schedule",
      description: `An optional periodic schedule for this job, specified as a JSON object. By default, the job only runs when triggered manually or via the API. The schedule object must include:

- \`quartz_cron_expression\` (**required**): A Cron expression using Quartz syntax that defines when the job runs. [See Cron Trigger details](https://docs.databricks.com/api/workspace/jobs/create#schedule).
- \`timezone_id\` (**required**): A Java timezone ID (e.g., "Europe/London") that determines the timezone for the schedule. [See Java TimeZone details](https://docs.databricks.com/api/workspace/jobs/create#schedule).
- \`pause_status\` (optional): Set to \`"UNPAUSED"\` (default) or \`"PAUSED"\` to control whether the schedule is active.

**Example:**
\`\`\`json
{
  "quartz_cron_expression": "0 0 12 * * ?",
  "timezone_id": "Asia/Ho_Chi_Minh",
  "pause_status": "UNPAUSED"
}
\`\`\`
`,
      optional: true,
    },
    maxConcurrentRuns: {
      type: "integer",
      label: "Max Concurrent Runs",
      description: "An optional maximum allowed number of concurrent runs of the job. Defaults to 1",
      optional: true,
    },
    gitSource: {
      type: "string",
      label: "Git Source",
      description: `An optional specification for a remote Git repository containing the source code used by tasks. Provide as a JSON string.

This enables version-controlled source code for notebook, dbt, Python script, and SQL File tasks. If \`git_source\` is set, these tasks retrieve files from the remote repository by default (can be overridden per task by setting \`source\` to \`WORKSPACE\`). **Note:** dbt and SQL File tasks require \`git_source\` to be defined. [See the API documentation](https://docs.databricks.com/api/workspace/jobs/create#git_source) for more details.

**Fields:**
- \`git_url\` (**required**): URL of the repository to be cloned (e.g., "https://github.com/databricks/databricks-cli").
- \`git_provider\` (**required**): Service hosting the repository. One of: \`gitHub\`, \`bitbucketCloud\`, \`azureDevOpsServices\`, \`gitHubEnterprise\`, \`bitbucketServer\`, \`gitLab\`, \`gitLabEnterpriseEdition\`, \`awsCodeCommit\`.
- \`git_branch\`: Name of the branch to check out (cannot be used with \`git_tag\` or \`git_commit\`).
- \`git_tag\`: Name of the tag to check out (cannot be used with \`git_branch\` or \`git_commit\`).
- \`git_commit\`: Commit hash to check out (cannot be used with \`git_branch\` or \`git_tag\`).

**Example:**
\`\`\`json
{
  "git_url": "https://github.com/databricks/databricks-cli",
  "git_provider": "gitHub",
  "git_branch": "main"
}
\`\`\`
`,
      optional: true,
    },
    accessControlList: {
      type: "string[]",
      label: "Access Control List",
      description: `A list of permissions to set on the job, specified as a JSON array of objects. Each object can define permissions for a user, group, or service principal. 

Each object may include:
- \`user_name\`: Name of the user.
- \`group_name\`: Name of the group.
- \`service_principal_name\`: Application ID of a service principal.
- \`permission_level\`: Permission level. One of: \`CAN_MANAGE\`, \`IS_OWNER\`, \`CAN_MANAGE_RUN\`, \`CAN_VIEW\`.

**Example:**
\`\`\`json
[
  {
    "permission_level": "IS_OWNER",
    "user_name": "jorge.c@turing.com"
  },
  {
    "permission_level": "CAN_VIEW",
    "group_name": "data-scientists"
  }
]
\`\`\`
[See the API documentation](https://docs.databricks.com/api/workspace/jobs/create#access_control_list) for more details.`,
      optional: true,
    },
  },
  async run({ $ }) {
    const {
      app,
      tasks,
      name,
      tags,
      jobClusters,
      emailNotifications,
      webhookNotifications,
      timeoutSeconds,
      schedule,
      maxConcurrentRuns,
      gitSource,
      accessControlList,
    } = this;

    const response = await app.createJob({
      $,
      data: {
        name,
        tags,
        tasks: utils.parseJsonInput(tasks),
        job_clusters: utils.parseJsonInput(jobClusters),
        email_notifications: utils.parseJsonInput(emailNotifications),
        webhook_notifications: utils.parseJsonInput(webhookNotifications),
        timeout_seconds: timeoutSeconds,
        schedule: utils.parseJsonInput(schedule),
        max_concurrent_runs: maxConcurrentRuns,
        git_source: utils.parseJsonInput(gitSource),
        access_control_list: utils.parseJsonInput(accessControlList),
      },
    });

    $.export("$summary", `Successfully created job with ID \`${response.job_id}\``);

    return response;
  },
};

Action Configuration#

This component may be configured based on the props defined in the component code. Pipedream automatically prompts for input values in the UI.

Label	Prop	Type	Description
Databricks	`app`	`app`	This component uses the Databricks app.
Tasks	`tasks`	`string[]`	A list of task specifications to be executed by this job. JSON string format. See the API documentation for task specification details. Example: `[ { "notebook_task": { "notebook_path": "/Workspace/Users/sharky@databricks.com/weather_ingest" }, "task_key": "weather_ocean_data" } ]`
Job Name	`name`	`string`	An optional name for the job
Tags	`tags`	`object`	A map of tags associated with the job. These are forwarded to the cluster as cluster tags for jobs clusters, and are subject to the same limitations as cluster tags
Job Clusters	`jobClusters`	`string[]`	A list of job cluster specifications that can be shared and reused by tasks of this job. JSON string format. See the API documentation for job cluster specification details. Example: `[ { "job_cluster_key": "auto_scaling_cluster", "new_cluster": { "autoscale": { "max_workers": 16, "min_workers": 2 }, "node_type_id": null, "spark_conf": { "spark.speculation": true }, "spark_version": "7.3.x-scala2.12" } } ]`
Email Notifications	`emailNotifications`	`string`	An optional set of email addresses to notify when runs of this job begin, complete, or when the job is deleted. Specify as a JSON object with keys for each notification type. See the API documentation for details on each field. Example: `{ "on_start": ["user1@example.com"], "on_success": ["user2@example.com"], "on_failure": ["user3@example.com"], "on_duration_warning_threshold_exceeded": ["user4@example.com"], "on_streaming_backlog_exceeded": ["user5@example.com"] }`
Webhook Notifications	`webhookNotifications`	`string`	A collection of system notification IDs to notify when runs of this job begin, complete, or encounter specific events. Specify as a JSON object with keys for each notification type. Each key accepts an array of objects with an `id` property (system notification ID). A maximum of 3 destinations can be specified for each property. Supported keys: `on_start`: Notified when the run starts. `on_success`: Notified when the run completes successfully. `on_failure`: Notified when the run fails. `on_duration_warning_threshold_exceeded`: Notified when the run duration exceeds the specified threshold. `on_streaming_backlog_exceeded`: Notified when streaming backlog thresholds are exceeded. See the API documentation for details. Example: `{ "on_success": [ { "id": "https://eoiqkb8yzox6u2n.m.pipedream.net" } ], "on_failure": [ { "id": "https://another-webhook-url.com/notify" } ] }`
Timeout Seconds	`timeoutSeconds`	`integer`	An optional timeout applied to each run of this job. The default behavior is to have no timeout
Schedule	`schedule`	`string`	An optional periodic schedule for this job, specified as a JSON object. By default, the job only runs when triggered manually or via the API. The schedule object must include: `quartz_cron_expression` (required): A Cron expression using Quartz syntax that defines when the job runs. See Cron Trigger details. `timezone_id` (required): A Java timezone ID (e.g., "Europe/London") that determines the timezone for the schedule. See Java TimeZone details. `pause_status` (optional): Set to `"UNPAUSED"` (default) or `"PAUSED"` to control whether the schedule is active. Example: `{ "quartz_cron_expression": "0 0 12 * * ?", "timezone_id": "Asia/Ho_Chi_Minh", "pause_status": "UNPAUSED" }`
Max Concurrent Runs	`maxConcurrentRuns`	`integer`	An optional maximum allowed number of concurrent runs of the job. Defaults to 1
Git Source	`gitSource`	`string`	An optional specification for a remote Git repository containing the source code used by tasks. Provide as a JSON string. This enables version-controlled source code for notebook, dbt, Python script, and SQL File tasks. If `git_source` is set, these tasks retrieve files from the remote repository by default (can be overridden per task by setting `source` to `WORKSPACE`). Note: dbt and SQL File tasks require `git_source` to be defined. See the API documentation for more details. Fields: `git_url` (required): URL of the repository to be cloned (e.g., "https://github.com/databricks/databricks-cli"). `git_provider` (required): Service hosting the repository. One of: `gitHub`, `bitbucketCloud`, `azureDevOpsServices`, `gitHubEnterprise`, `bitbucketServer`, `gitLab`, `gitLabEnterpriseEdition`, `awsCodeCommit`. `git_branch`: Name of the branch to check out (cannot be used with `git_tag` or `git_commit`). `git_tag`: Name of the tag to check out (cannot be used with `git_branch` or `git_commit`). `git_commit`: Commit hash to check out (cannot be used with `git_branch` or `git_tag`). Example: `{ "git_url": "https://github.com/databricks/databricks-cli", "git_provider": "gitHub", "git_branch": "main" }`
Access Control List	`accessControlList`	`string[]`	A list of permissions to set on the job, specified as a JSON array of objects. Each object can define permissions for a user, group, or service principal. Each object may include: `user_name`: Name of the user. `group_name`: Name of the group. `service_principal_name`: Application ID of a service principal. `permission_level`: Permission level. One of: `CAN_MANAGE`, `IS_OWNER`, `CAN_MANAGE_RUN`, `CAN_VIEW`. Example: `[ { "permission_level": "IS_OWNER", "user_name": "jorge.c@turing.com" }, { "permission_level": "CAN_VIEW", "group_name": "data-scientists" } ]` See the API documentation for more details.

Action 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.

About Databricks#

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

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Emit new event at a specified time before a card is due.

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New Upcoming Calendar Event from the Pipedream API

Emit new event when a Calendar event is upcoming, this source is using reminderMinutesBeforeStart property of the event to determine the time it should emit.

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