send_google_chat_message¶

send_google_chat_message(message, webhook_url)

Description¶

Sends message to google chat space using incoming webhook.

To get the incoming webhook_url:

In a web browser, open Google Chat.

Go to the space to which you want to add a webhook.

At the top, next to space title, click Down Arrow arrow_drop_down > Apps & integrations.

Click Manage webhooks.

If this space already has other webhooks, click Add another. Otherwise, skip this step.

For Name, enter "Quickstart Webhook".

For Avatar URL, enter https://developers.google.com/chat/images/chat-product-icon.png.

Click SAVE.

To copy the full webhook URL, click Copy.

Usage¶

Call or Deploy send_google_chat_message ?

Call send_google_chat_message directly

The easiest way to use bigfunctions

send_google_chat_message function is deployed in 39 public datasets for all of the 39 BigQuery regions.
It can be called by anyone. Just copy / paste examples below in your BigQuery console. It just works!
(You need to use the dataset in the same region as your datasets otherwise you may have a function not found error)

Public BigFunctions Datasets

Region	Dataset
`eu`	`bigfunctions.eu`
`us`	`bigfunctions.us`
`europe-west1`	`bigfunctions.europe_west1`
`asia-east1`	`bigfunctions.asia_east1`
...	...

Deploy send_google_chat_message in your project

Why deploy?

You may prefer to deploy send_google_chat_message in your own project to build and manage your own catalog of functions.
This is particularly useful if you want to create private functions (for example calling your internal APIs).
Get started by reading the framework page

Deployment

send_google_chat_message function can be deployed with:

pip install bigfunctions
bigfun get send_google_chat_message
bigfun deploy send_google_chat_message

Examples¶

EUUSeurope-west1

select bigfunctions.eu.send_google_chat_message("Hello \ud83d\udc4b from bigfunctions!", "YOUR_WEBHOOK_URL")

select bigfunctions.us.send_google_chat_message("Hello \ud83d\udc4b from bigfunctions!", "YOUR_WEBHOOK_URL")

select bigfunctions.europe_west1.send_google_chat_message("Hello \ud83d\udc4b from bigfunctions!", "YOUR_WEBHOOK_URL")

+--------------------------------------------------------------------------------------------------+
| response                                                                                         |
+--------------------------------------------------------------------------------------------------+
| {
  "name": ...,
  "sender": ...,
  "createTime": ...,
  "text": "Hello 👋 from bigfunctions!"
}
 |
+--------------------------------------------------------------------------------------------------+

Use cases¶

Here are a few use cases for the send_google_chat_message BigQuery function:

1. Data Monitoring and Alerting:

Threshold breaches: Imagine you have a BigQuery table tracking website traffic. You can schedule a query to check if traffic drops below a certain threshold. If it does, use send_google_chat_message to send an alert to a Google Chat space dedicated to website monitoring. The message could include details like the current traffic level, the threshold breached, and a timestamp.
Data quality issues: A scheduled query can check for data quality issues, such as null values in critical columns or inconsistencies between tables. If a problem is detected, the function can send a notification to the data engineering team's Google Chat space.
Job completion status: After a long-running BigQuery job finishes (e.g., a large data import or a complex transformation), the function can send a message to the relevant team confirming completion (or failure, along with the error message).

2. Report Automation and Sharing:

Daily summaries: Generate a daily summary of key business metrics from your BigQuery data and send it to a Google Chat space for management review. The message could be formatted as a table or a short bullet-point list.
Weekly performance reports: Consolidate weekly performance data and send a report to the sales team's Google Chat space, highlighting top performers, areas for improvement, and key trends.
Ad-hoc data insights: After running an exploratory query that reveals an interesting insight, use the function to share the finding with colleagues in a Google Chat space, along with a link to the BigQuery query.

3. Workflow Integration:

Triggering downstream actions: When certain conditions are met in your BigQuery data (e.g., a new customer signs up, an order is placed), the function can send a message to a Google Chat space that integrates with other tools. This message could trigger a downstream action in another system, such as updating a CRM or sending a welcome email.
Human-in-the-loop processes: Some data processes might require human intervention. The function can be used to notify a human operator in a Google Chat space when their input is needed. The operator can then take the necessary action and update the relevant data in BigQuery.

Example (Data Monitoring):

#standardSQL
DECLARE threshold INT64 DEFAULT 1000;
DECLARE current_traffic INT64;

SET current_traffic = (SELECT COUNT(*) FROM `your-project.your_dataset.website_traffic` WHERE _PARTITIONTIME = CURRENT_DATE());

IF current_traffic < threshold THEN
  SELECT bigfunctions.us.send_google_chat_message(
    FORMAT("ALERT: Website traffic dropped below %d. Current traffic: %d", threshold, current_traffic),
    "YOUR_WEBHOOK_URL"
  );
END IF;

This demonstrates how send_google_chat_message can be integrated into a SQL script to provide real-time alerts based on data in BigQuery. You can adapt this pattern for various other use cases as needed. Remember to replace placeholders like "YOUR_WEBHOOK_URL", "your-project.your_dataset.website_traffic", and adjust the logic to suit your specific requirements. Also ensure you're calling the function from the correct regional dataset (e.g., bigfunctions.us, bigfunctions.eu).

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