bigframes._config.ComputeOptions#

class bigframes._config.ComputeOptions(ai_ops_confirmation_threshold: int | None = 0, ai_ops_threshold_autofail: bool = False, allow_large_results: bool | None = None, enable_multi_query_execution: bool = False, maximum_bytes_billed: int | None = None, maximum_result_rows: int | None = None, semantic_ops_confirmation_threshold: int | None = 0)[source]#

Encapsulates the configuration for compute options.

Examples:

>>> import bigframes.pandas as bpd
>>> df = bpd.read_gbq("bigquery-public-data.ml_datasets.penguins")

>>> bpd.options.compute.maximum_bytes_billed = 500
>>> df.to_pandas() # this should fail
google.api_core.exceptions.InternalServerError: 500 Query exceeded limit for bytes billed: 500. 10485760 or higher required.

>>> bpd.options.compute.maximum_bytes_billed = None  # reset option

To add multiple extra labels to a query configuration, use the assign_extra_query_labels method with keyword arguments:

>>> bpd.options.compute.assign_extra_query_labels(test1=1, test2="abc")
>>> bpd.options.compute.extra_query_labels
{'test1': 1, 'test2': 'abc'}

Alternatively, you can add labels individually by directly accessing the extra_query_labels dictionary:

>>> bpd.options.compute.extra_query_labels["test3"] = False
>>> bpd.options.compute.extra_query_labels
{'test1': 1, 'test2': 'abc', 'test3': False}

To remove a label from the configuration, use the del keyword on the desired label key:

>>> del bpd.options.compute.extra_query_labels["test1"]
>>> bpd.options.compute.extra_query_labels
{'test2': 'abc', 'test3': False}

ai_ops_confirmation_threshold: int | None = 0#

Guards against unexpected processing of large amount of rows by semantic operators.

If the number of rows exceeds the threshold, the user will be asked to confirm their operations to resume. The default value is 0. Set the value to None to turn off the guard.

Examples:

>>> import bigframes.pandas as bpd
>>> bpd.options.compute.ai_ops_confirmation_threshold = 100

Returns:: Number of rows.
Return type:: Optional[int]

ai_ops_threshold_autofail: bool = False#

Guards against unexpected processing of large amount of rows by semantic operators.

When set to True, the operation automatically fails without asking for user inputs.

Examples:

>>> import bigframes.pandas as bpd
>>> bpd.options.compute.ai_ops_threshold_autofail = True

Returns:: True if the guard is enabled.
Return type:: bool

allow_large_results: bool | None = None#

Specifies whether query results can exceed 10 GB.

Defaults to False. Setting this to False (the default) restricts results to 10 GB for potentially faster execution; BigQuery will raise an error if this limit is exceeded. Setting to True removes this result size limit.

Examples:

>>> import bigframes.pandas as bpd
>>> bpd.options.compute.allow_large_results = True

Returns:: True if results > 10 GB are enabled.
Return type:: bool | None

assign_extra_query_labels(**kwargs: Any) → None[source]#

Assigns additional custom labels for query configuration. The method updates the extra_query_labels dictionary with new labels provided through keyword arguments.

Parameters:: kwargs (Any) – Custom labels provided as keyword arguments. Each key-value pair in kwargs represents a label name and its value.
Raises:: ValueError – If a key matches one of the reserved attribute names, specifically ‘maximum_bytes_billed’ or ‘enable_multi_query_execution’, to prevent conflicts with built-in settings.

enable_multi_query_execution: bool = False#

If enabled, large queries may be factored into multiple smaller queries.

This is in order to avoid generating queries that are too complex for the query engine to handle. However this comes at the cost of increase cost and latency.

Examples:

>>> import bigframes.pandas as bpd
>>> bpd.options.compute.enable_multi_query_execution = True

Returns:: True if enabled.
Return type:: bool | None

extra_query_labels: Dict[str, Any]#

Stores additional custom labels for query configuration.

Returns:: Additional labels.
Return type:: Dict[str, Any] | None

maximum_bytes_billed: int | None = None#

Limits the bytes billed for query jobs.

Queries that will have bytes billed beyond this limit will fail (without incurring a charge). If unspecified, this will be set to your project default. See maximum_bytes_billed: https://cloud.google.com/python/docs/reference/bigquery/latest/google.cloud.bigquery.job.QueryJobConfig#google_cloud_bigquery_job_QueryJobConfig_maximum_bytes_billed.

Examples:

>>> import bigframes.pandas as bpd
>>> bpd.options.compute.maximum_bytes_billed = 1000

Returns:: Number of bytes, if set.
Return type:: int | None

maximum_result_rows: int | None = None#

Limits the number of rows in an execution result.

When converting a BigQuery DataFrames object to a pandas DataFrame or Series (e.g., using .to_pandas(), .peek(), .__repr__(), direct iteration), the data is downloaded from BigQuery to the client machine. This option restricts the number of rows that can be downloaded. If the number of rows to be downloaded exceeds this limit, a bigframes.exceptions.MaximumResultRowsExceeded exception is raised.

Examples:

>>> import bigframes.pandas as bpd
>>> bpd.options.compute.maximum_result_rows = 1000

Returns:: Number of rows, if set.
Return type:: int | None

semantic_ops_confirmation_threshold: int | None = 0#: Deprecated.

Deprecated since version 1.42.0: Semantic operators are deprecated. Please use the functions in bigframes.bigquery.ai instead.

semantic_ops_threshold_autofail = False#: Deprecated.

Deprecated since version 1.42.0: Semantic operators are deprecated. Please use the functions in bigframes.bigquery.ai instead.

bigframes._config.ComputeOptions#

This Page