Find Out the Cost of Running a BigQuery Query

B.

When using BigQuery's on-demand pricing, you pay for the amount of data that is processed by your query. Therefore, before running a query that is expected to return a large number of records, it is important to estimate the cost of the query.

The correct answer to this question is B. To estimate the cost of a query in BigQuery, you can use the command line to run a dry run query, which will provide an estimate of the number of bytes that will be read by the actual query. You can then use the BigQuery Pricing Calculator to convert the bytes estimate to dollars.

Here are the steps you would need to follow to estimate the cost of your query:

1. Use the command line to run a dry run query. The dry run query will not actually execute the query, but it will provide an estimate of the number of bytes that will be read by the query. You can use the following command to run a dry run query:

   cssCopy code
   bq query --dry_run 'SELECT * FROM mydataset.mytable' 

   Replace mydataset and mytable with the dataset and table that you want to query.

2. The output of the dry run query will include an estimate of the number of bytes that will be read by the query. Look for the totalBytesProcessed field in the output, which will provide an estimate of the number of bytes that will be processed by the actual query.

3. Use the BigQuery Pricing Calculator to estimate the cost of the query. The pricing calculator allows you to enter the number of bytes that will be processed and provides an estimate of the cost.

   To use the pricing calculator, go to the following website: https://cloud.google.com/products/calculator. Enter the estimated number of bytes that will be processed, select the appropriate region, and click "Calculate". The pricing calculator will provide an estimate of the cost of the query.

Note that switching to Flat-Rate pricing for a single query is not recommended as it requires minimum 90 days commitment and is designed for workloads with predictable query patterns. Therefore, it is better to estimate the cost using the on-demand pricing as described above.

Option C, estimating the number of bytes returned by the query, is not a good way to estimate the cost of the query as it does not take into account the amount of data that is processed by the query, which is what you are charged for in on-demand pricing.

Option D, running a select count (*) to get an idea of how many records your query will look through, is also not a good way to estimate the cost of the query as it does not take into account the amount of data that is processed by the query. The number of records in a table does not necessarily correspond to the amount of data that needs to be processed by a query.