Create Job with Databricks API on New Row from Snowflake API

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New Row from the Snowflake API

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Create Job with the Databricks API

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Getting Started#

This integration creates a workflow with a Snowflake 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 Row trigger
1. Connect your Snowflake account
2. Configure timer
3. Select a Database
4. Select a Schema
5. Select a Table Name
6. Select a Unique Key
7. Optional- Configure Emit individual events
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 Row on Snowflake

Description:Emit new event when a row is added to a table

Version:0.2.3

Key:snowflake-new-row

View on GitHub

Snowflake Overview#

Snowflake offers a cloud database and related tools to help developers create robust, secure, and scalable data warehouses. See Snowflake's Key Concepts & Architecture

Getting Started

1. Create a user, role and warehouse in Snowflake

Snowflake recommends you create a new user, role, and warehouse when you integrate a third-party tool like Pipedream. This way, you can control permissions via the user / role, and separate Pipedream compute and costs with the warehouse. You can do this directly in the Snowflake UI

We recommend you create a read-only account if you only need to query Snowflake. If you need to insert data into Snowflake, add permissions on the appropriate objects after you create your user.

2. Enter those details in Pipedream

Visit https://pipedream.com/accounts. Click the button to Connect an App. Enter the required Snowflake account data.

You'll only need to connect your account once in Pipedream. You can connect this account to multiple workflows to run queries against Snowflake, insert data, and more.

3. Build your first workflow

Visit https://pipedream.com/new to build your first workflow. Pipedream workflows let you connect Snowflake with 1,000+ other apps. You can trigger workflows on Snowflake queries, sending results to Slack, Google Sheets, or any app that exposes an API. Or you can accept data from another app, transform it with Python, Node.js, Go or Bash code, and insert it into Snowflake.

Learn more at Pipedream University

Trigger Code#

import common from "../common-table-scan.mjs";

export default {
  ...common,
  type: "source",
  key: "snowflake-new-row",
  name: "New Row",
  description: "Emit new event when a row is added to a table",
  version: "0.2.3",
  methods: {
    ...common.methods,
    async getStatement(lastResultId) {
      const sqlText = `
        SELECT *
        FROM IDENTIFIER(:1)
        WHERE ${this.uniqueKey} > :2
        ORDER BY ${this.uniqueKey} ASC
      `;
      const binds = [
        this.tableName,
        lastResultId,
      ];
      return {
        sqlText,
        binds,
      };
    },
  },
};

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
Snowflake	`snowflake`	`app`	This component uses the Snowflake app.
N/A	`db`	`$.service.db`	This component uses `$.service.db` to maintain state between executions.
	`timer`	`$.interface.timer`	Watch for changes on this schedule
Database	`database`	`string`	Select a value from the drop down menu.
Schema	`schema`	`string`	Select a value from the drop down menu.
Table Name	`tableName`	`string`	Select a value from the drop down menu.
Unique Key	`uniqueKey`	`string`	Select a value from the drop down menu.
Emit individual events	`emitIndividualEvents`	`boolean`	Defaults to `true`, triggering workflows on each record in the result set. Set to `false` to emit records in batch (advanced)

Trigger Authentication#

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

We recommend you create a read-only account if you only need to query Snowflake. If you need to insert data into Snowflake, add permissions on the appropriate objects after you create your user.

About Snowflake#

A data warehouse built for the cloud

Action#

Create Job on Databricks

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

Version:0.0.3

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: "0.0.3",
  annotations: {
    destructiveHint: false,
    openWorldHint: true,
    readOnlyHint: false,
  },
  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.