Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

Awesome Lists | Featured Topics | Projects

https://github.com/wintermi/bqe-dataform

A Dataform project which aggregates BigQuery system metadata for the purpose of analysing the slot usage and storage within an organization by project.
https://github.com/wintermi/bqe-dataform

bigquery dataform google-cloud google-cloud-platform

Last synced: about 1 month ago
JSON representation

A Dataform project which aggregates BigQuery system metadata for the purpose of analysing the slot usage and storage within an organization by project.

Awesome Lists containing this project

README

        

# **BigQuery Slot Usage**

# About
A Dataform project which aggregates BigQuery metadata for the purpose of analysing the slot usage of all jobs submitted within an organization by project. The following BigQuery system views are required:

- [JOBS_TIMELINE_BY_ORGANIZATION](https://cloud.google.com/bigquery/docs/information-schema-jobs-timeline-by-organization)
- [TABLE_STORAGE_BY_ORGANIZATION](https://cloud.google.com/bigquery/docs/information-schema-table-storage-by-organization)

# Prerequisites

## Google Cloud Project

Google Cloud projects form the basis for creating, enabling, and using all Google Cloud services, such as Dataform and BigQuery.

If you do not already have a Google Cloud project for which you want to load the BigQuery Slot Usage dataset into, then you will need to create a new Google Cloud project. The documentation on how to do this can be found [here](https://cloud.google.com/resource-manager/docs/creating-managing-projects#creating_a_project).

Once you have a Google Cloud project, remember to take note of the Project Number and Project ID. These can be found on the Google Cloud project console welcome page, which you can find [here](https://console.cloud.google.com/welcome).

## Google Cloud Storage Bucket

Now you have a Google Cloud project, you need to create a Google Cloud Storage Bucket for which the BigQuery Slot Usage data will be collected into and then Dataform will use to source the data in which to load into BigQuery. The documentation on how to create a new storage bucket can be found [here](https://cloud.google.com/storage/docs/creating-buckets).

Remember to take note of the bucket name as this will be required for one of the Dataform config variables.

## Enable Dataform Service

Next, you will need to enable the Dataform service within the Google Cloud project just created. This can be achieved by clicking the "Enable" button [here](https://console.cloud.google.com/marketplace/product/google/dataform.googleapis.com).

## Create a Dataform Repository

After the Dataform Service has been enabled, you will be redirected to the BigQuery Dataform page within the Google Cloud console. For reference, this can be found [here](https://console.cloud.google.com/bigquery/dataform).

Go ahead and create a repository. For more information on how to do this, go to the documentation page found [here](https://cloud.google.com/dataform/docs/create-repository).

## Grant Permissions to Dataform Service Account

When you create your first Dataform repository, Dataform automatically generates a service account. Dataform uses the service account to interact with BigQuery on your behalf.

Your Dataform service account ID is in the following format:

```
service-YOUR_PROJECT_NUMBER@gcp-sa-dataform.iam.gserviceaccount.com
```

Replace YOUR_PROJECT_NUMBER with the Project Number of your Google Cloud project, which you previously took note of.

The Dataform service account requires a number of IAM roles with which to be able to execute the workflows in BigQuery and load data from the Google Cloud Storage Bucket. This can be achieved by following these steps:

1. In the Google Cloud console, go to the [IAM page](https://console.cloud.google.com/iam-admin).
2. Click Add.
3. In the New principals field, enter your Dataform service account ID.
4. In the Select a role drop-down list, select the BigQuery Job User role.
5. Click Add another role, and then in the Select a role drop-down list, select the BigQuery Data Editor role.
6. Click Add another role, and then in the Select a role drop-down list, select the BigQuery Data Viewer role.
7. Click Add another role, and then in the Select a role drop-down list, select the Storage Object Creator role.
8. Click Save.