Create SQL Warehouse with Databricks API on Meeting Created (Instant) from Zoom API

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Meeting Created (Instant) from the Zoom API

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Create SQL Warehouse with the Databricks API

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Getting Started#

This integration creates a workflow with a Zoom 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 Meeting Created (Instant) trigger
1. Connect your Zoom account
2. Configure apphook
Configure the Create SQL Warehouse action
1. Connect your Databricks account
2. Configure Warehouse Name
3. Select a Cluster Size
4. Optional- Configure Auto Stop (minutes)
5. Optional- Configure Min Number of Clusters
6. Optional- Configure Max Number of Clusters
7. Optional- Configure Enable Photon
8. Optional- Configure Enable Serverless Compute
9. Optional- Select a Warehouse Type
10. Optional- Select a Spot Instance Policy
11. Optional- Configure Channel
12. Optional- Configure Tags
13. Optional- Configure Instance Profile ARN (Deprecated)
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#

Meeting Created (Instant) on Zoom

Description:Emit new event each time a meeting is created where you're the host

Version:0.1.3

Key:zoom-meeting-created

View on GitHub

Zoom Overview#

The Zoom API lets you tap into a rich set of functionalities to enhance the video conferencing experience within your own app or workflow. With the Zoom API on Pipedream, you can automatically create meetings, manage users, send meeting notifications, and more, orchestrating these actions within a broader automation. This allows for seamless integration with other services, enabling both data collection and action triggers based on Zoom events.

Pipedream workflows allow you to run any Node.js code that connects to the Zoom API. Just create a new workflow, then add prebuilt Zoom actions (create a meeting, send a chat message, etc.) or write your own code. These workflows can be triggered by HTTP requests, timers, email, or on any app-based event (new tweets, a Github PR, Zoom events, etc).

Trigger Code#

import common from "../common/common.mjs";
import constants from "../common/constants.mjs";

export default {
  ...common,
  key: "zoom-meeting-created",
  name: "Meeting Created (Instant)",
  description: "Emit new event each time a meeting is created where you're the host",
  version: "0.1.3",
  type: "source",
  dedupe: "unique",
  props: {
    ...common.props,
    // eslint-disable-next-line pipedream/props-label, pipedream/props-description
    apphook: {
      type: "$.interface.apphook",
      appProp: "app",
      eventNames() {
        return [
          constants.CUSTOM_EVENT_TYPES.MEETING_CREATED_BY_ME,
          constants.CUSTOM_EVENT_TYPES.MEETING_CREATED_FOR_ME,
        ];
      },
    },
  },
  hooks: {
    async deploy() {
      const { meetings } = await this.app.listMeetings({
        params: {
          page_size: 25,
        },
      });
      if (!meetings || meetings.length === 0) {
        return;
      }
      const objects = this.sortByDate(meetings, "created_at");
      for (const object of objects) {
        this.emitEvent({
          object,
        }, object);
      }
    },
  },
  methods: {
    ...common.methods,
    emitEvent(payload, object) {
      const meta = this.generateMeta(object);
      this.$emit({
        event: "meeting.created",
        payload,
      }, meta);
    },
    generateMeta(object) {
      return {
        id: object.uuid,
        summary: `Meeting ${object.topic} created`,
        ts: +new Date(object.start_time),
      };
    },
  },
};

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
Zoom	`app`	`app`	This component uses the Zoom app.
	`apphook`	`$.interface.apphook`

Trigger Authentication#

Zoom uses OAuth authentication. When you connect your Zoom account, Pipedream will open a popup window where you can sign into Zoom and grant Pipedream permission to connect to your account. Pipedream securely stores and automatically refreshes the OAuth tokens so you can easily authenticate any Zoom API.

Pipedream requests the following authorization scopes when you connect your account:

About Zoom#

Zoom is the leader in modern enterprise video communications, with an easy, reliable cloud platform for video and audio conferencing, chat, and webinars.

Action#

Create SQL Warehouse on Databricks

Description:Creates a new SQL Warehouse in Databricks. [See the documentation](https://docs.databricks.com/api/workspace/warehouses/create)

Version:0.0.2

Key:databricks-create-sql-warehouse

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 databricks from "../../databricks.app.mjs";
import constants from "../../common/constants.mjs";
import utils from "../../common/utils.mjs";
import { ConfigurationError } from "@pipedream/platform";

export default {
  key: "databricks-create-sql-warehouse",
  name: "Create SQL Warehouse",
  description: "Creates a new SQL Warehouse in Databricks. [See the documentation](https://docs.databricks.com/api/workspace/warehouses/create)",
  version: "0.0.2",
  type: "action",
  props: {
    databricks,
    name: {
      type: "string",
      label: "Warehouse Name",
      description: "A human-readable name for the warehouse",
    },
    clusterSize: {
      type: "string",
      label: "Cluster Size",
      description: "Size of the cluster",
      options: constants.CLUSTER_SIZES,
    },
    autoStopMinutes: {
      type: "integer",
      label: "Auto Stop (minutes)",
      description:
        "Minutes of inactivity before auto-stop. 0 disables auto-stop. Must be 0 or ≥ 10.",
      optional: true,
      default: 10,
    },
    minNumClusters: {
      type: "integer",
      label: "Min Number of Clusters",
      description: "Minimum number of clusters to maintain (> 0 and ≤ min(max_num_clusters, 30)).",
      optional: true,
      default: 1,
    },
    maxNumClusters: {
      type: "integer",
      label: "Max Number of Clusters",
      description: "Maximum number of clusters for autoscaler (≥ min_num_clusters and ≤ 30).",
      optional: true,
      default: 1,
    },
    enablePhoton: {
      type: "boolean",
      label: "Enable Photon",
      description: "Whether the warehouse should use Photon optimized clusters.",
      optional: true,
    },
    enableServerlessCompute: {
      type: "boolean",
      label: "Enable Serverless Compute",
      description: "Whether the warehouse should use serverless compute.",
      optional: true,
    },
    warehouseType: {
      type: "string",
      label: "Warehouse Type",
      description:
        "Warehouse type: PRO or CLASSIC. Set PRO + enableServerlessCompute = true to use serverless.",
      options: [
        "TYPE_UNSPECIFIED",
        "CLASSIC",
        "PRO",
      ],
      optional: true,
    },
    spotInstancePolicy: {
      type: "string",
      label: "Spot Instance Policy",
      description: "Configures whether the warehouse should use spot instances.",
      options: [
        "POLICY_UNSPECIFIED",
        "COST_OPTIMIZED",
        "RELIABILITY_OPTIMIZED",
      ],
      optional: true,
    },
    channel: {
      type: "object",
      label: "Channel",
      description:
        "Channel details. Example: `{ \"name\": \"CHANNEL_NAME_CUSTOM\", \"dbsql_version\": \"2023.35\" }`",
      optional: true,
    },
    tags: {
      type: "object",
      label: "Tags",
      description:
        "Custom key-value tags for resources associated with this SQL Warehouse.",
      optional: true,
    },
    instanceProfileArn: {
      type: "string",
      label: "Instance Profile ARN (Deprecated)",
      description: "Deprecated. Instance profile used to pass IAM role to the cluster.",
      optional: true,
    },
  },

  async run({ $ }) {
    const payload = {
      name: this.name,
      cluster_size: this.clusterSize,
    };

    if (this.autoStopMinutes !== undefined) {
      if (this.autoStopMinutes !== 0 && this.autoStopMinutes < 10) {
        throw new ConfigurationError("autoStopMinutes must be 0 or ≥ 10.");
      }
      payload.auto_stop_mins = this.autoStopMinutes;
    }

    const minNumClusters = this.minNumClusters ?? 1;
    if (minNumClusters < 1 || minNumClusters > 30) {
      throw new ConfigurationError("minNumClusters must be between 1 and 30.");
    }
    payload.min_num_clusters = minNumClusters;

    if (this.maxNumClusters !== undefined) {
      if (
        this.maxNumClusters < payload.min_num_clusters ||
        this.maxNumClusters > 30
      ) {
        throw new ConfigurationError(
          `maxNumClusters must be ≥ minNumClusters (${payload.min_num_clusters}) and ≤ 30.`,
        );
      }
      payload.max_num_clusters = this.maxNumClusters;
    }

    const parsedTags = utils.parseObject(this.tags);
    const tagArray = Object.entries(parsedTags).map(([
      key,
      value,
    ]) => ({
      key,
      value,
    }));
    if (tagArray.length) {
      payload.tags = {
        custom_tags: tagArray,
      };
    }

    if (this.enablePhoton !== undefined)
      payload.enable_photon = this.enablePhoton;
    if (this.enableServerlessCompute !== undefined)
      payload.enable_serverless_compute = this.enableServerlessCompute;
    if (this.warehouseType) payload.warehouse_type = this.warehouseType;
    if (this.spotInstancePolicy)
      payload.spot_instance_policy = this.spotInstancePolicy;
    if (this.channel) payload.channel = utils.parseObject(this.channel);
    if (this.instanceProfileArn)
      payload.instance_profile_arn = this.instanceProfileArn;

    const response = await this.databricks.createSQLWarehouse({
      data: payload,
      $,
    });

    $.export(
      "$summary",
      `Successfully created SQL Warehouse: ${response?.name || this.name}`,
    );
    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	`databricks`	`app`	This component uses the Databricks app.
Warehouse Name	`name`	`string`	A human-readable name for the warehouse
Cluster Size	`clusterSize`	`string`	Select a value from the drop down menu:`2X-SmallX-SmallSmallMediumLargeX-Large2X-Large3X-Large4X-Large`
Auto Stop (minutes)	`autoStopMinutes`	`integer`	Minutes of inactivity before auto-stop. 0 disables auto-stop. Must be 0 or ≥ 10.
Min Number of Clusters	`minNumClusters`	`integer`	Minimum number of clusters to maintain (> 0 and ≤ min(max_num_clusters, 30)).
Max Number of Clusters	`maxNumClusters`	`integer`	Maximum number of clusters for autoscaler (≥ min_num_clusters and ≤ 30).
Enable Photon	`enablePhoton`	`boolean`	Whether the warehouse should use Photon optimized clusters.
Enable Serverless Compute	`enableServerlessCompute`	`boolean`	Whether the warehouse should use serverless compute.
Warehouse Type	`warehouseType`	`string`	Select a value from the drop down menu:`TYPE_UNSPECIFIEDCLASSICPRO`
Spot Instance Policy	`spotInstancePolicy`	`string`	Select a value from the drop down menu:`POLICY_UNSPECIFIEDCOST_OPTIMIZEDRELIABILITY_OPTIMIZED`
Channel	`channel`	`object`	Channel details. Example: `{ "name": "CHANNEL_NAME_CUSTOM", "dbsql_version": "2023.35" }`
Tags	`tags`	`object`	Custom key-value tags for resources associated with this SQL Warehouse.
Instance Profile ARN (Deprecated)	`instanceProfileArn`	`string`	Deprecated. Instance profile used to pass IAM role to the cluster.

Create SQL Warehouse with Databricks API on Meeting Created (Instant) from Zoom API

Pipedream makes it easy to connect APIs for Databricks, Zoom and 2,800+ other apps remarkably fast.

Trusted by 1,000,000+ developers from startups to Fortune 500 companies

Developers ♥ Pipedream

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