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refresh_powerbi

refresh_powerbi(dataset_id, workspace_id, tenant_id, app_id, token_secret, custom_refresh_param)

Description

Refresh a Power BI dataset (semantic model) by it's id dataset_id.

Use case:

After model refresh, launch Power BI dataset (semantic model) refresh from BigQuery in SQL

graph refresh power bi

Optionnal:

on premium capacity, you can pass json argument (xmla like) to launch a custom refresh (ex: Full refresh only a given table )

Docs:

Encrypt your secrets

We advise NOT TO write your token in plain text in token_secret argument.

Otherwise, they will be stored in plain text in your BigQuery logs for months.

Instead, you can use the following snippet to generate an encrypted version of token_secret that you can copy safely as token_secret argument.

This public bigfunction (deployed on bigfunctions GCP project) will be able to decrypt it. But no one else can.

Usage

Call or Deploy refresh_powerbi ?
Call refresh_powerbi directly

The easiest way to use bigfunctions

  • refresh_powerbi 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 refresh_powerbi in your project

Why deploy?

  • You may prefer to deploy refresh_powerbi 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

refresh_powerbi function can be deployed with:

pip install bigfunctions
bigfun get refresh_powerbi
bigfun deploy refresh_powerbi

Requirements

refresh_powerbi uses the following secrets. Get them by reading the documentation link and store them in Google Secret Manager in the project where you deploy the function (and give Accessor role to the service account of the function):

name description documentation to get the secret
refresh_powerbi_rsa_private_key RSA Private Key used to decrypt secrets doc

Examples

1. Refresh of a dataset

select bigfunctions.eu.refresh_powerbi("xxx-xxx-xxx", "xxx-xxx-xxx", "xxx-xxx-xxx", "xxx-xxx-xxx", "ENCRYPTED_SECRET(GvVm...)", null)

select bigfunctions.us.refresh_powerbi("xxx-xxx-xxx", "xxx-xxx-xxx", "xxx-xxx-xxx", "xxx-xxx-xxx", "ENCRYPTED_SECRET(GvVm...)", null)

select bigfunctions.europe_west1.refresh_powerbi("xxx-xxx-xxx", "xxx-xxx-xxx", "xxx-xxx-xxx", "xxx-xxx-xxx", "ENCRYPTED_SECRET(GvVm...)", null)

+----------+
| response |
+----------+
| ok       |
+----------+

2. custom refresh (xmla like) - premium capacity only

select bigfunctions.eu.refresh_powerbi("xxx-xxx-xxx", "xxx-xxx-xxx", "xxx-xxx-xxx", "xxx-xxx-xxx", "ENCRYPTED_SECRET(GvVm...)", json '{ "type": "Full", "objects": [ { "table": "table_name" } ] }')

select bigfunctions.us.refresh_powerbi("xxx-xxx-xxx", "xxx-xxx-xxx", "xxx-xxx-xxx", "xxx-xxx-xxx", "ENCRYPTED_SECRET(GvVm...)", json '{ "type": "Full", "objects": [ { "table": "table_name" } ] }')

select bigfunctions.europe_west1.refresh_powerbi("xxx-xxx-xxx", "xxx-xxx-xxx", "xxx-xxx-xxx", "xxx-xxx-xxx", "ENCRYPTED_SECRET(GvVm...)", json '{ "type": "Full", "objects": [ { "table": "table_name" } ] }')

+----------+
| response |
+----------+
| ok       |
+----------+

Use cases

A common use case for the refresh_powerbi function is automating the refresh of a Power BI dataset after data in its connected BigQuery tables has been updated.

Scenario: Imagine you have a BigQuery data warehouse that is used as a source for a Power BI dashboard. You have a daily ETL process that updates several tables in BigQuery. After this process completes, you want to ensure that the Power BI dataset is refreshed so that the dashboard reflects the latest data.

Implementation: You could use an orchestration tool like Airflow, Cloud Composer, or Cloud Functions to schedule the ETL process and the subsequent Power BI dataset refresh. After the ETL tasks have successfully completed, a final task would call the refresh_powerbi function. This function would trigger the refresh of the Power BI dataset using the provided credentials and parameters.

Example (using Airflow):

from airflow import DAG
from airflow.providers.google.cloud.operators.bigquery import BigQueryInsertJobOperator
from datetime import datetime

with DAG(
    dag_id="refresh_powerbi_example",
    start_date=datetime(2023, 10, 26),
    schedule_interval="@daily",
    catchup=False,
) as dag:
    # ETL tasks (e.g., loading data into BigQuery)
    etl_task_1 = BigQueryInsertJobOperator(
        task_id="etl_task_1",
        configuration={
            "query": {
                "query": "your_etl_query_1",
                "useLegacySql": False,
            }
        },
    )

    etl_task_2 = BigQueryInsertJobOperator(
        task_id="etl_task_2",
        configuration={
            "query": {
                "query": "your_etl_query_2",
                "useLegacySql": False,
            }
        },
    )


    # Refresh Power BI dataset after ETL completes
    refresh_powerbi_task = BigQueryInsertJobOperator(
        task_id="refresh_powerbi",
        configuration={
            "query": {
                "query": f"""
                    SELECT bigfunctions.{your_region}.refresh_powerbi(
                        '{your_dataset_id}',
                        '{your_workspace_id}',
                        '{your_tenant_id}',
                        '{your_app_id}',
                        'ENCRYPTED_SECRET({your_encrypted_token})',
                        NULL
                    );
                """,
                "useLegacySql": False,
            }
        },
    )


    [etl_task_1, etl_task_2] >> refresh_powerbi_task

Replace the placeholder values with your actual configuration. This setup ensures that the Power BI dataset is automatically refreshed after the ETL process finishes, keeping the dashboard up-to-date. This automation simplifies data management and provides users with the most current insights.

Need help or Found a bug?
Get help using refresh_powerbi

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Report a bug about refresh_powerbi

If the function does not work as expected, please

  • report a bug so that it can be improved.
  • or open the discussion with the community on Slack.

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