This query used 1.66 GB of our free quota — and each similar query will have a similar cost. We can do better: Extract the data you are interested in to a new table. With BigQuery’s sandbox mode now you also get 10 GB of storage for free. So instead of running new queries every time over the whole dataset, we can extract all Tensorflow questions to a new table.

To create a new table, first create a dataset. Note that without a credit card associated to your account, BigQuery will limit the lifetime of any table to 60 days.

Create a new dataset inside your BigQuery project. Lifetime of a table will be limited to 60 days in sandbox mode.

To create a new table out of our previous query, BigQuery now supports DDL and DML SQL commands:

CREATE TABLE `deleting.tensorflow_questions`

AS

SELECT view_count, answer_count, DATE(creation_date) date, title

FROM `bigquery-public-data.stackoverflow.posts_questions`

WHERE 'tensorflow' IN UNNEST(SPLIT(tags, '|'))

Now I can write queries like this over my new table:

SELECT view_count, answer_count, date, title

FROM `deleting.tensorflow_questions`

ORDER BY view_count DESC

Good news: This query now scans only 3 MB, which gives me a lot more freedom to experiment. I can execute more than 300,000 queries like this for free every month!

Step 3: Share

With BigQuery you can share your results and findings with your closest friends or the whole world. This is still not implemented on the new web UI, but it’s really easy on the BigQuery classic web UI:

How to share a BigQuery table on the classic UI

Visualize with Data Studio

Multiple tools and frameworks can connect straight to BigQuery — we love them all. And now in the new BigQuery web UI you have a quick way to get your results into Data Studio: