bigframes._config.SamplingOptions#

class bigframes._config.SamplingOptions(max_download_size: int | None = 500, enable_downsampling: bool = False, sampling_method: Literal['head', 'uniform'] = 'uniform', random_state: int | None = None)[source]#

Encapsulates the configuration for data sampling.

enable_downsampling: bool = False#

Whether to enable downsampling. Default False.

If max_download_size is exceeded when downloading data (e.g., to_pandas()), the data will be downsampled if enable_downsampling is True, otherwise, an error will be raised.

Examples:

>>> import bigframes.pandas as bpd
>>> bpd.options.sampling.enable_downsampling = True
max_download_size: int | None = 500#

Download size threshold in MB. Default 500.

If value set to None, the download size won’t be checked.

Examples:

>>> import bigframes.pandas as bpd
>>> bpd.options.sampling.max_download_size = 1000
random_state: int | None = None#

The seed for the uniform downsampling algorithm. Default None.

If provided, the uniform method may take longer to execute and require more computation.

Examples:

>>> import bigframes.pandas as bpd
>>> bpd.options.sampling.random_state = 42
sampling_method: Literal['head', 'uniform'] = 'uniform'#

Downsampling algorithms to be chosen from. Default “uniform”.

The choices are: “head”: This algorithm returns a portion of the data from the beginning. It is fast and requires minimal computations to perform the downsampling.; “uniform”: This algorithm returns uniform random samples of the data.

Examples:

>>> import bigframes.pandas as bpd
>>> bpd.options.sampling.sampling_method = "head"
with_disabled() SamplingOptions[source]#

Configures whether to disable downsampling

Returns:

The configuration for data sampling.

Return type:

bigframes._config.sampling_options.SamplingOptions

with_max_download_size(max_rows: int | None) SamplingOptions[source]#

Configures the maximum download size for data sampling in MB

Parameters:

max_rows (None or int) – An int value for the maximum row size.

Returns:

The configuration for data sampling.

Return type:

bigframes._config.sampling_options.SamplingOptions

with_method(method: Literal['head', 'uniform']) SamplingOptions[source]#

Configures the downsampling algorithms to be chosen from

Parameters:

method (None or Literal) – A literal string value of either head or uniform data sampling method.

Returns:

The configuration for data sampling.

Return type:

bigframes._config.sampling_options.SamplingOptions

with_random_state(state: int | None) SamplingOptions[source]#

Configures the seed for the uniform downsampling algorithm

Parameters:

state (None or int) – An int value for the data sampling random state

Returns:

The configuration for data sampling.

Return type:

bigframes._config.sampling_options.SamplingOptions