How to get BigQuery storage size for a single table
Or from the GUI, you can use the metadata internal table __TABLES__ , for example this will give you the size in GB:
select
sum(size_bytes)/pow(10,9) as size
from
<your_dataset>.__TABLES__
where
table_id = '<your_table>'
There are a couple of ways to do this, but be aware the size of the table in bytes property is unavailable for tables that are actively receiving streaming inserts.
A. Using the BQ command line tool, and the JQ linux library to parse JSON.
bq --format=json show publicdata:samples.gsod | jq '.numBytes | tonumber'
This outpus:
17290009238
B. Using the REST api to do a Tables:get call
GET https://www.googleapis.com/bigquery/v2/projects/projectId/datasets/datasetId/tables/tableId
this returns a full JSON, that you can parse and get the numBytes.
{
"kind": "bigquery#table",
"description": "This dataset contains weather information collected by NOAA, such a…",
"creationTime": "1335916040125",
"tableReference": {
"projectId": "publicdata",
"tableId": "gsod",
"datasetId": "samples"
},
"numRows": "114420316",
"numBytes": "17290009238",
"etag": "\"Gn3Hpo5WaKnpFuT457VBDNMgZBw/MTQxMzkzNzk4Nzg0Ng\"",
"location": "US",
"lastModifiedTime": "1413937987846",
"type": "TABLE",
"id": "publicdata:samples.gsod",
"selfLink": "https://www.googleapis.com/bigquery/v2/projects/publicdata/datasets…",
"schema": {
"fields": [
{
"description": "The World Meteorological Organization (WMO) / DATSAV3 station numbe…",
"type": "INTEGER",
"name": "station_number",
"mode": "REQUIRED"
},
{
"description": "The Weather-Bureau-Army-Navy (WBAN) station number where the data w…",
"type": "INTEGER",
"name": "wban_number",
"mode": "NULLABLE"
},
{
"description": "The year the data was collected in",
"type": "INTEGER",
"name": "year",
"mode": "REQUIRED"
},
{
"description": "The month the data was collected in",
"type": "INTEGER",
"name": "month",
"mode": "REQUIRED"
},
{
"description": "The day the data was collected in.",
"type": "INTEGER",
"name": "day",
"mode": "REQUIRED"
},
{
"description": "The mean temperature of the day in degrees Fahrenheit, accurate to …",
"type": "FLOAT",
"name": "mean_temp",
"mode": "NULLABLE"
},
{
"description": "The number of observations used to calculate mean_temp.",
"type": "INTEGER",
"name": "num_mean_temp_samples",
"mode": "NULLABLE"
},
{
"description": "The mean dew point of the day in degrees Fahrenheit, accurate to on…",
"type": "FLOAT",
"name": "mean_dew_point",
"mode": "NULLABLE"
},
{
"description": "The number of observations used to calculate mean_dew_point.",
"type": "INTEGER",
"name": "num_mean_dew_point_samples",
"mode": "NULLABLE"
},
{
"description": "The mean sea level pressure of the day in millibars, accurate to on…",
"type": "FLOAT",
"name": "mean_sealevel_pressure",
"mode": "NULLABLE"
},
{
"description": "The number of observations used to calculate mean_sealevel_pressure…",
"type": "INTEGER",
"name": "num_mean_sealevel_pressure_samples",
"mode": "NULLABLE"
},
{
"description": "The mean station pressure of the day in millibars, accurate to one …",
"type": "FLOAT",
"name": "mean_station_pressure",
"mode": "NULLABLE"
},
{
"description": "The number of observations used to calculate mean_station_pressure.…",
"type": "INTEGER",
"name": "num_mean_station_pressure_samples",
"mode": "NULLABLE"
},
{
"description": "The mean visibility of the day in miles, accurate to one tenth of a…",
"type": "FLOAT",
"name": "mean_visibility",
"mode": "NULLABLE"
},
{
"description": "The number of observations used to calculate mean_visibility.",
"type": "INTEGER",
"name": "num_mean_visibility_samples",
"mode": "NULLABLE"
},
{
"description": "The mean wind speed of the day in knots, accurate to one tenth of a…",
"type": "FLOAT",
"name": "mean_wind_speed",
"mode": "NULLABLE"
},
{
"description": "The number of observations used to calculate mean_wind_speed.",
"type": "INTEGER",
"name": "num_mean_wind_speed_samples",
"mode": "NULLABLE"
},
{
"description": "The maximum sustained wind speed reported on the day in knots, accu…",
"type": "FLOAT",
"name": "max_sustained_wind_speed",
"mode": "NULLABLE"
},
{
"description": "The maximum wind gust speed reported on the day in knots, accurate …",
"type": "FLOAT",
"name": "max_gust_wind_speed",
"mode": "NULLABLE"
},
{
"description": "The maximum temperature of the day in degrees Fahrenheit, accurate …",
"type": "FLOAT",
"name": "max_temperature",
"mode": "NULLABLE"
},
{
"description": "Indicates the source of max_temperature.",
"type": "BOOLEAN",
"name": "max_temperature_explicit",
"mode": "NULLABLE"
},
{
"description": "The minimum temperature of the day in degrees Fahrenheit, accurate …",
"type": "FLOAT",
"name": "min_temperature",
"mode": "NULLABLE"
},
{
"description": "Indicates the source of min_temperature.",
"type": "BOOLEAN",
"name": "min_temperature_explicit",
"mode": "NULLABLE"
},
{
"description": "The total precipitation of the day in inches, accurate to one hundr…",
"type": "FLOAT",
"name": "total_precipitation",
"mode": "NULLABLE"
},
{
"description": "The snow depth of the day in inches, accurate to one tenth of an in…",
"type": "FLOAT",
"name": "snow_depth",
"mode": "NULLABLE"
},
{
"description": "Indicates if fog was reported on this day.",
"type": "BOOLEAN",
"name": "fog",
"mode": "NULLABLE"
},
{
"description": "Indicates if rain was reported on this day.",
"type": "BOOLEAN",
"name": "rain",
"mode": "NULLABLE"
},
{
"description": "Indicates if snow was reported on this day.",
"type": "BOOLEAN",
"name": "snow",
"mode": "NULLABLE"
},
{
"description": "Indicates if hail was reported on this day.",
"type": "BOOLEAN",
"name": "hail",
"mode": "NULLABLE"
},
{
"description": "Indicates if thunder was reported on this day.",
"type": "BOOLEAN",
"name": "thunder",
"mode": "NULLABLE"
},
{
"description": "Indicates if a tornado was reported on this day.",
"type": "BOOLEAN",
"name": "tornado",
"mode": "NULLABLE"
}
]
}
}
C. There are metatables called __TABLES__ and __TABLES_SUMMARY__
You can run a query like:
SELECT size_bytes FROM <dataset>.__TABLES__ WHERE table_id='mytablename'
The __TABLES__ portion of that query may look unfamiliar. __TABLES_SUMMARY__ is a meta-table containing information about tables in a dataset. You can use this meta-table yourself. For example, the query SELECT * FROM publicdata:samples.__TABLES_SUMMARY__ will return metadata about the tables in the publicdata:samples dataset. You can also do SELECT * FROM publicdata:samples.__TABLES__
Available Fields:
The fields of the __TABLES_SUMMARY__ meta-table (that are all available in the TABLE_QUERY query) include:
table_id: name of the table.creation_time: time, in milliseconds since 1/1/1970 UTC, that the table was created. This is the same as thecreation_timefield on the table.type: whether it is a view (2) or regular table (1).
The following fields are not available in TABLE_QUERY() since they are members of __TABLES__ but not __TABLES_SUMMARY__. They're kept here for historical interest and to partially document the __TABLES__ metatable:
last_modified_time: time, in milliseconds since 1/1/1970 UTC, that the table was updated (either metadata or table contents). Note that if you use thetabledata.insertAll()to stream records to your table, this might be a few minutes out of date.row_count: number of rows in the table.size_bytes: total size in bytes of the table.