You have a query that filters a BigQuery table using a WHERE clause on timestamp and ID columns. By using bq query - -dry_run you learn that the query triggers a full scan of the table, even though the filter on timestamp and ID select a tiny fraction of the overall data. You want to reduce the amount of data scanned by BigQuery with minimal changes to existing SQL queries. What should you do?
A) Create a separate table for each ID.
B) Use the LIMIT keyword to reduce the number of rows returned.
C) Recreate the table with a partitioning column and clustering column.
D) Use the bq query - -maximum_bytes_billed flag to restrict the number of bytes billed. Use the bq query - -maximum_bytes_billed flag to restrict the number of bytes billed.

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The Answer of You have a query that filters a BigQuery table using a WHERE clause on timestamp and ID columns. By using bq query - -dry_run you learn that the query triggers a full scan of the table, even though the filter on timestamp and ID select a tiny fraction of the overall data. You want to reduce the amount of data scanned by BigQuery with minimal changes to existing SQL queries. What should you do?
A) Create a separate table for each ID.
B) Use the LIMIT keyword to reduce the number of rows returned.
C) Recreate the table with a partitioning column and clustering column.
D) Use the bq query - -maximum_bytes_billed flag to restrict the number of bytes billed. Use the bq query - -maximum_bytes_billed flag to restrict the number of bytes billed.

You Have a Query That Filters a BigQuery Table Using