Execute SQL Query with Microsoft Azure SQL Database API on New Query Results from Snowflake API

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Trigger workflow on

New Query Results from the Snowflake API

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Execute SQL Query with the Microsoft Azure SQL Database API

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Getting Started#

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

Select this integration
Configure the New Query Results trigger
1. Connect your Snowflake account
2. Configure timer
3. Configure SQL Query
4. Optional- Configure Primary key
5. Optional- Configure Emit individual events
Configure the Execute SQL Query action
1. Connect your Microsoft Azure SQL Database account
2. Configure SQL Query
3. Optional- Configure Request Timeout
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 Query Results on Snowflake

Description:Run a SQL query on a schedule, triggering a workflow for each row of results

Version:0.2.2

Key:snowflake-query-results

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.mjs";
import { v4 as uuidv4 } from "uuid";

export default {
  ...common,
  type: "source",
  key: "snowflake-query-results",
  name: "New Query Results",
  // eslint-disable-next-line
  description: "Run a SQL query on a schedule, triggering a workflow for each row of results",
  version: "0.2.2",
  props: {
    ...common.props,
    sqlQuery: {
      type: "string",
      label: "SQL Query",
      description: "Run this query on a schedule, triggering the workflow for each row of results",
    },
    // Ordering props correctly
    timer: common.props.timer,
    dedupeKey: {
      type: "string",
      label: "Primary key",
      description: "The column in your query to use for de-duplication. Duplicate rows won't trigger your workflow",
      optional: true,
    },
    emitIndividualEvents: {
      propDefinition: [
        common.props.snowflake,
        "emitIndividualEvents",
      ],
    },
  },
  methods: {
    ...common.methods,
    generateMeta(data) {
      const {
        row: { [this.dedupeKey]: id = uuidv4() },
        timestamp: ts,
      } = data;
      const summary = `New event (ID: ${id})`;
      return {
        id,
        summary,
        ts,
      };
    },
    generateMetaForCollection(data) {
      const { timestamp: ts } = data;
      const id = uuidv4();
      const summary = `New event (ID: ${id})`;
      return {
        id,
        summary,
        ts,
      };
    },
    getStatement() {
      return {
        sqlText: this.sqlQuery,
      };
    },
  },
};

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
SQL Query	`sqlQuery`	`string`	Run this query on a schedule, triggering the workflow for each row of results
Primary key	`dedupeKey`	`string`	The column in your query to use for de-duplication. Duplicate rows won't trigger your workflow
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#

Execute SQL Query on Microsoft Azure SQL Database

Description:Execute a custom SQL query. See [our docs](https://pipedream.com/docs/databases/working-with-sql) to learn more about working with SQL in Pipedream.

Version:0.0.5

Key:azure_sql-execute-raw-query

View on GitHub

Microsoft Azure SQL Database Overview#

The Microsoft Azure SQL Database API allows you to manage and interact with your SQL databases hosted on Azure directly from Pipedream. It provides a serverless way to run SQL queries, manage tables, and handle database management tasks. You can create, read, update, and delete database records, execute stored procedures, and perform a variety of other SQL operations. Leveraging this API on Pipedream enables you to automate workflows, respond to database events in real-time, and integrate with countless other apps and services.

Action Code#

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

export default {
  key: "azure_sql-execute-raw-query",
  name: "Execute SQL Query",
  description: "Execute a custom SQL query. See [our docs](https://pipedream.com/docs/databases/working-with-sql) to learn more about working with SQL in Pipedream.",
  type: "action",
  version: "0.0.5",
  props: {
    app,
    sql: {
      type: "sql",
      auth: {
        app: "app",
      },
      label: "SQL Query",
    },
    requestTimeout: {
      propDefinition: [
        app,
        "requestTimeout",
      ],
    },
  },
  async run({ $ }) {
    const args = this.app.executeQueryAdapter(this.sql);
    args.requestTimeout = this.requestTimeout;
    const response = await this.app.executeQuery(args);
    $.export("$summary", "Successfully executed query.");
    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
Microsoft Azure SQL Database	`app`	`app`	This component uses the Microsoft Azure SQL Database app.
SQL Query	`sql`	`sql`
Request Timeout	`requestTimeout`	`integer`	The timeout for query execution in seconds. Default is 60 seconds if not specified.

Action Authentication#

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

Before you connect to your Microsoft Azure SQL database from Pipedream, please make sure your database is either:

Accessible from the public internet (You may need to add a firewall rule on 0.0.0.0/0 on port 1433), or
Accessible from a static IP that you've configured from a VPC in Pipedream, and enabled the workflow to connect through that VPC