Using Labels in BigQuery

🔍 What exactly are BigQuery Labels? They're key-value pairs that you can associate with different BigQuery resources like datasets, tables, views, and even jobs within a session. Consider them as 'tags' that streamline the organization, tracking, and management of your resources.

In the examples shared, we demonstrate how to label BigQuery jobs within a query and then fetch them using the INFORMATION_SCHEMA . JOBS view.

🌟 Wondering about how is it useful?

1️⃣ Expense Breakdown - With labels, you can categorize your BigQuery
expenses by department, project, or any other segment, promoting clear billing.

SET @@query_label = "cost_center:demo";


SELECT id, max(ds_date) AS max_date

FROM learning.data_source

GROUP BY id

SELECT creation_time, job_type, query, label.key, label.value, total_bytes_billed, total_bytes_processed, total_slot_ms

FROM `region-eu`.INFORMATION_SCHEMA.JOBS,

UNNEST(labels) AS label

WHERE label.key = 'cost_center'

2️⃣ Efficient Resource Handling - Recognize and handle resources based on their labels, facilitating a tidy and systematic workspace.

3️⃣ Streamlined Automation - Pair labels with Cloud Functions or other GCP tools to automate tasks based on specific labeled criteria.

If you haven't explored labels in BigQuery yet, I urge you to do so. They offer a straightforward approach to instill organization and transparency in your data workspace.

Enjoy your data exploration! 📊