in dbconnectors/BQConnector.py [0:0]
def bq_specific_data_types():
return '''
BigQuery offers a wide variety of datatypes to store different types of data effectively. Here's a breakdown of the available categories:
Numeric Types -
INTEGER (INT64): Stores whole numbers within the range of -9,223,372,036,854,775,808 to 9,223,372,036,854,775,807. Ideal for non-fractional values.
FLOAT (FLOAT64): Stores approximate floating-point numbers with a range of -1.7E+308 to 1.7E+308. Suitable for decimals with a degree of imprecision.
NUMERIC: Stores exact fixed-precision decimal numbers, with up to 38 digits of precision and 9 digits to the right of the decimal point. Useful for precise financial and accounting calculations.
BIGNUMERIC: Similar to NUMERIC but with even larger scale and precision. Designed for extreme precision in calculations.
Character Types -
STRING: Stores variable-length Unicode character sequences. Enclosed using single, double, or triple quotes.
Boolean Type -
BOOLEAN: Stores logical values of TRUE or FALSE (case-insensitive).
Date and Time Types -
DATE: Stores dates without associated time information.
TIME: Stores time information independent of a specific date.
DATETIME: Stores both date and time information (without timezone information).
TIMESTAMP: Stores an exact moment in time with microsecond precision, including a timezone component for global accuracy.
Other Types
BYTES: Stores variable-length binary data. Distinguished from strings by using 'B' or 'b' prefix in values.
GEOGRAPHY: Stores points, lines, and polygons representing locations on the Earth's surface.
ARRAY: Stores an ordered collection of zero or more elements of the same (non-ARRAY) data type.
STRUCT: Stores an ordered collection of fields, each with its own name and data type (can be nested).
This list covers the most common datatypes in BigQuery.
'''