← Schedule + Google Cloud integrations

Bigquery Insert Rows with Google Cloud API on Custom Interval from Schedule API

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Trigger workflow on
Custom Interval from the Schedule API
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Bigquery Insert Rows with the Google Cloud API
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Getting Started

This integration creates a workflow with a Schedule trigger and Google Cloud 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 Custom Interval trigger
    1. Connect your Schedule account
    2. Configure Cron Schedule
  3. Configure the Bigquery Insert Rows action
    1. Connect your Google Cloud account
    2. Select a Dataset ID
    3. Select a Table Name
    4. Configure Rows
  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:Trigger your workflow every N hours, minutes or seconds.
Version:0.0.2
Key:schedule-custom-interval

Schedule Overview

With Schedule - A trigger provided by Pipedream - You can easily build
automated workflows that run on regular times or intervals. Some examples of
things that you can build using the Schedule API include:

  • Automated data retrieval from a third-party service, like pulling stats from
    your Salesforce account on a set schedule.
  • Uploading new data sets to a database with a predetermined interval.
  • Automatic emails to customers or leads at a certain time of the day.
  • Automating data analysis based on a set schedule.
  • Automatically optimizing social media postings according to a specified
    timeline.
  • Updating webpages at a certain interval with newly available content.
  • Re-running reports on a periodic basis.
  • Refreshing a cache of data at a given frequency.

Trigger Code

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

export default {
  name: "Custom Interval",
  version: "0.0.2",
  key: "schedule-custom-interval",
  type: "source",
  description: "Trigger your workflow every N hours, minutes or seconds.",
  props: {
    schedule,
    cron: {
      propDefinition: [
        schedule,
        "cron",
      ],
    },
  },
};

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
SchedulescheduleappThis component uses the Schedule app.
Cron Schedulecron$.interface.timer

Enter a cron expression

Trigger Authentication

The Schedule API does not require authentication.

About Schedule

Trigger workflows on an interval or cron schedule.

Action

Description:Inserts rows into a BigQuery table. [See the docs](https://github.com/googleapis/nodejs-bigquery) and for an example [here](https://github.com/googleapis/nodejs-bigquery/blob/main/samples/insertRowsAsStream.js).
Version:0.0.3
Key:google_cloud-bigquery-insert-rows

Google Cloud Overview

The Google Cloud API allows developers to access a variety of Google Cloud
services from their own applications. Services that can be accessed include
Google Cloud Storage, Google Cloud Datastore, Google Cloud Functions, and
Google Cloud Pub/Sub. With the Google Cloud API, developers can build a variety
of applications that take advantage of Google Cloud services.

Action Code

import googleCloud from "../../google_cloud.app.mjs";
import utils from "../../common/utils.mjs";

export default {
  name: "Bigquery Insert Rows",
  version: "0.0.3",
  key: "google_cloud-bigquery-insert-rows",
  type: "action",
  description: "Inserts rows into a BigQuery table. [See the docs](https://github.com/googleapis/nodejs-bigquery) and for an example [here](https://github.com/googleapis/nodejs-bigquery/blob/main/samples/insertRowsAsStream.js).",
  props: {
    googleCloud,
    datasetId: {
      propDefinition: [
        googleCloud,
        "datasetId",
      ],
    },
    tableId: {
      propDefinition: [
        googleCloud,
        "tableId",
        ({ datasetId }) => ({
          datasetId,
        }),
      ],
    },
    rows: {
      type: "string[]",
      label: "Rows",
      description: "The rows to insert into the table. Each row is a JSON object with column names as keys and rows as values. E.g. `{\"name\": \"John\", \"age\": 20}`",
    },
  },
  async run({ $ }) {
    const {
      datasetId,
      tableId,
      rows,
    } = this;

    if (!Array.isArray(rows)) {
      throw new Error("Rows must be an array");
    }

    const rowsParsed = rows.map(utils.parse);

    try {
      const response = await this.googleCloud
        .getBigQueryClient()
        .dataset(datasetId)
        .table(tableId)
        .insert(rowsParsed);

      $.export("$summary", `Successfully inserted ${rows.length} rows into ${datasetId}.${tableId}`);

      return response;
    } catch (error) {
      console.log(JSON.stringify(error.errors, null, 2));
      throw error;
    }
  },
};

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
Google CloudgoogleCloudappThis component uses the Google Cloud app.
Dataset IDdatasetIdstringSelect a value from the drop down menu.
Table NametableIdstringSelect a value from the drop down menu.
Rowsrowsstring[]

The rows to insert into the table. Each row is a JSON object with column names as keys and rows as values. E.g. {"name": "John", "age": 20}

Action Authentication

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

  1. Create a service account in GCP and set the permissions you need for Pipedream workflows.

  2. Generate a service account key

  3. Download the key details in JSON format

  4. Open the JSON in a text editor, and copy and paste its contents here.

About Google Cloud

The Google Cloud Platform, including BigQuery

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