← npm + Databricks integrations

Create SQL Warehouse with Databricks API on New Download Counts from npm API

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New Download Counts from the npm 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 npm trigger and Databricks action. When you configure and deploy the workflow, it will run on Pipedream's servers 24x7 for free.

  1. Select this integration
  2. Configure the New Download Counts trigger
    1. Connect your npm account
    2. Configure timer
    3. Select a Period
    4. Optional- Configure Package
  3. 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)
  4. Deploy the workflow
  5. Send a test event to validate your setup
  6. 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

Description:Emit new event with the latest count of downloads for an npm package. [See the documentation](https://github.com/npm/registry/blob/main/docs/download-counts.md).
Version:0.1.0
Key:npm-download-counts

Trigger Code

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

export default {
  key: "npm-download-counts",
  name: "New Download Counts",
  description: "Emit new event with the latest count of downloads for an npm package. [See the documentation](https://github.com/npm/registry/blob/main/docs/download-counts.md).",
  version: "0.1.0",
  type: "source",
  props: {
    app,
    db: "$.service.db",
    timer: {
      type: "$.interface.timer",
      description: "One day interval time is recommended because NPM only update metrics once a day. [See the documentation](https://github.com/npm/registry/blob/main/docs/download-counts.md#data-source).",
      default: {
        intervalSeconds: 60 * 60 * 24,
      },
    },
    period: {
      type: "string",
      label: "Period",
      description: "Select last-day, last-week or last-month.",
      optional: false,
      default: "last-day",
      options: [
        "last-day",
        "last-week",
        "last-month",
      ],
    },
    packageName: {
      type: "string",
      label: "Package",
      description: "Enter an npm package name. Leave blank for all",
      optional: true,
    },
  },
  methods: {
    getDownloadCounts({
      period, packageName, ...args
    } = {}) {
      const basePath = `/downloads/point/${encodeURIComponent(period)}`;
      return this.app.makeRequest({
        path: packageName
          ? `${basePath}/${encodeURIComponent(packageName)}`
          : basePath,
        ...args,
      });
    },
  },
  async run({ timestamp: ts }) {
    const {
      getDownloadCounts,
      period,
      packageName,
    } = this;

    const response = await getDownloadCounts({
      period,
      packageName,
    });

    this.$emit(response, {
      id: ts,
      summary: `New Download Count ${response.downloads}`,
      ts,
    });
  },
};

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.
LabelPropTypeDescription
npmappappThis component uses the npm app.
N/Adb$.service.dbThis component uses $.service.db to maintain state between executions.
timer$.interface.timer

One day interval time is recommended because NPM only update metrics once a day. See the documentation

PeriodperiodstringSelect a value from the drop down menu:last-daylast-weeklast-month
PackagepackageNamestring

Enter an npm package name. Leave blank for all

Trigger Authentication

The npm API does not require authentication.

About npm

Node package manager

Action

Description:Creates a new SQL Warehouse in Databricks. [See the documentation](https://docs.databricks.com/api/workspace/warehouses/create)
Version:0.0.1
Key:databricks-create-sql-warehouse

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: "0.0.1",
  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.

LabelPropTypeDescription
DatabricksdatabricksappThis component uses the Databricks app.
Warehouse Namenamestring

A human-readable name for the warehouse

Cluster SizeclusterSizestringSelect a value from the drop down menu:2X-SmallX-SmallSmallMediumLargeX-Large2X-Large3X-Large4X-Large
Auto Stop (minutes)autoStopMinutesinteger

Minutes of inactivity before auto-stop. 0 disables auto-stop. Must be 0 or ≥ 10.

Min Number of ClustersminNumClustersinteger

Minimum number of clusters to maintain (> 0 and ≤ min(max_num_clusters, 30)).

Max Number of ClustersmaxNumClustersinteger

Maximum number of clusters for autoscaler (≥ min_num_clusters and ≤ 30).

Enable PhotonenablePhotonboolean

Whether the warehouse should use Photon optimized clusters.

Enable Serverless ComputeenableServerlessComputeboolean

Whether the warehouse should use serverless compute.

Warehouse TypewarehouseTypestringSelect a value from the drop down menu:TYPE_UNSPECIFIEDCLASSICPRO
Spot Instance PolicyspotInstancePolicystringSelect a value from the drop down menu:POLICY_UNSPECIFIEDCOST_OPTIMIZEDRELIABILITY_OPTIMIZED
Channelchannelobject

Channel details. Example: { "name": "CHANNEL_NAME_CUSTOM", "dbsql_version": "2023.35" }

Tagstagsobject

Custom key-value tags for resources associated with this SQL Warehouse.

Instance Profile ARN (Deprecated)instanceProfileArnstring

Deprecated. Instance profile used to pass IAM role to the cluster.

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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