Usage with Python projects
After installing Raster Loader, you can import the package into your Python project. For example:
from raster_loader import rasterio_to_bigquery, bigquery_to_records
Uploading a raster file to BigQuery
Currently, Raster Loader allows you to upload a local raster file to an existing
BigQuery table using the rasterio_to_bigquery()
function.
Note
Accessing BigQuery with Raster Loader requires the GOOGLE_APPLICATION_CREDENTIALS
environment variable to be set to the path of a JSON file containing your BigQuery
credentials. See the GCP documentation for more information.
For example:
rasterio_to_bigquery(
file_path = 'path/to/raster.tif',
project_id = 'my-project',
dataset_id = 'my_dataset',
table_id = 'my_table',
)
This function returns True if the upload was successful.
Note
To upload the raster to BigQuery in a quadbin format, set the output_quadbin
parameter of rasterio_to_bigquery()
to True
. This option requires a
GoogleMapsCompatible
input raster. You can make your raster compatible by
converting it with GDAL:
gdalwarp your_raster.tif -of COG -co TILING_SCHEME=GoogleMapsCompatible -co COMPRESS=DEFLATE your_compatible_raster.tif
Inspecting a raster file on BigQuery
You can also access and inspect a raster file located in a BigQuery table using the
bigquery_to_records()
function.
For example:
records_df = bigquery_to_records(
project_id = 'my-project',
dataset_id = 'my_dataset',
table_id = 'my_table',
)
This function returns a DataFrame with some samples from the raster table on BigQuery (10 rows by default).
See also
See the Module API reference for more details.