Sayle Matthews sayle-doit

## bq_tables_in_project.sql
  --
  --  This query will pull out all tables that exist inside of the currently
  --  selected project.
  --
  --  Note by default this hits the US multi-region, so if using a different
  --  region then change region-us below to that region name.
  --
SELECT
  CONCAT(table_catalog, ':', table_schema, '.', table_name) AS table_name
  -- This line uses the dot notation, so if you need that versus traditional

## bq_tables_queried_count.sql
  --
  --  This query will pull out a count of all tables referenced over the past
  --  7 days (configurable) by query jobs in the current project.
  --  Note this will pull in queries that query the information schema views.
  --
  --  Note by default this hits the US multi-region, so if using a different
  --  region then change region-us below to that region name.
  --

DECLARE start_time TIMESTAMP DEFAULT

## bq_per_table_storage_billing_recommendation.sql
/*
 *  This query will look at a single project (by default in US multi-region) and
 *  calculate the logical and physical billing prices for each table in all datasets
 *  contained inside of it then provide a recommendation on if it is better to put it
 *  into a dataset that uses the logical (uncompressed) or physical (compressed)
 *  storage billing models.
 *
 *  Physical (also called compressed) Storage went GA on July 5, 2023. It is set at
 *  the dataset level, so if two or more tables are better suited for different
 *  billing models in the same dataset it may be best to split them into separate

## bq_project_storage_model_recommendation.sql
/*
 *  This query will look at a single project (by default in US multi-region) and
 *  calculate the logical and physical billing prices for each dataset inside of it
 *  then provide a recommendation on whether to keep it on logical storage
 *  or switch to the physical billing model.
 *
 *  Physical (also called compressed) Storage will be GA and released for public
 *  consumption on July 5, 2023.
 *
 *  It also includes inside of the storage CTE lots of extra values that can be used

## bq_job_editions_cost_comparison_with_autoscaler.sql
/*
 *  This query will look at the past 30 days of job history to analyze it for costs under
 *  BigQuery Editions while utilizing the new autoscaling feature that was introduced.
 *  It does this for those using both PAYG (Pay As You Go) and commitment models.
 *  It will also compare this versus running the query with the on-demand model.
 *
 *  Note that this query utilizes some math modeling behaviors that the BigQuery
 *  autoscaler uses. Namely these are the up to 10 seconds "slot scale up time,"
 *  the minimum of 60 seconds "slot scale down time," and the behavior that the
 *  autoscaler scales up and down in factors of 100 slots for each job.

## bq_storage_across_org.sql
/*
 *  This query will run across an entire organization looking at tables across every project
 *  and shows how they will compare on compressed and uncompressed storage.
 *
 *  Region Notes:
 *  This query will only read from a single region or multi-region at a time. It's
 *  currently not possible to read this data from across all
 *
 *  By default this reads from the US multi-region, so this might need to be changed if
 *  your data lives elsewhere.
	--
	-- This query will pull out all tables that exist inside of the currently
	-- selected project.
	--
	-- Note by default this hits the US multi-region, so if using a different
	-- region then change region-us below to that region name.
	--
	SELECT
	CONCAT(table_catalog, ':', table_schema, '.', table_name) AS table_name
	-- This line uses the dot notation, so if you need that versus traditional
	--
	-- This query will pull out a count of all tables referenced over the past
	-- 7 days (configurable) by query jobs in the current project.
	-- Note this will pull in queries that query the information schema views.
	--
	-- Note by default this hits the US multi-region, so if using a different
	-- region then change region-us below to that region name.
	--

	DECLARE start_time TIMESTAMP DEFAULT
	/*
	* This query will look at a single project (by default in US multi-region) and
	* calculate the logical and physical billing prices for each table in all datasets
	* contained inside of it then provide a recommendation on if it is better to put it
	* into a dataset that uses the logical (uncompressed) or physical (compressed)
	* storage billing models.
	*
	* Physical (also called compressed) Storage went GA on July 5, 2023. It is set at
	* the dataset level, so if two or more tables are better suited for different
	* billing models in the same dataset it may be best to split them into separate
	/*
	* This query will look at a single project (by default in US multi-region) and
	* calculate the logical and physical billing prices for each dataset inside of it
	* then provide a recommendation on whether to keep it on logical storage
	* or switch to the physical billing model.
	*
	* Physical (also called compressed) Storage will be GA and released for public
	* consumption on July 5, 2023.
	*
	* It also includes inside of the storage CTE lots of extra values that can be used
	/*
	* This query will look at the past 30 days of job history to analyze it for costs under
	* BigQuery Editions while utilizing the new autoscaling feature that was introduced.
	* It does this for those using both PAYG (Pay As You Go) and commitment models.
	* It will also compare this versus running the query with the on-demand model.
	*
	* Note that this query utilizes some math modeling behaviors that the BigQuery
	* autoscaler uses. Namely these are the up to 10 seconds "slot scale up time,"
	* the minimum of 60 seconds "slot scale down time," and the behavior that the
	* autoscaler scales up and down in factors of 100 slots for each job.
	/*
	* This query will run across an entire organization looking at tables across every project
	* and shows how they will compare on compressed and uncompressed storage.
	*
	* Region Notes:
	* This query will only read from a single region or multi-region at a time. It's
	* currently not possible to read this data from across all
	*
	* By default this reads from the US multi-region, so this might need to be changed if
	* your data lives elsewhere.