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Showing content from http://cloud.google.com/python/docs/reference/bigquery/3.35.0/google.cloud.bigquery.job.QueryJob below:

Class QueryJob (3.35.0) | Python client library

Skip to main content Class QueryJob (3.35.0)

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QueryJob(job_id, query, client, job_config=None)

Asynchronous job: query tables.

Parameters Name Description job_id str

the job's ID, within the project belonging to client.

query str

SQL query string.

client google.cloud.bigquery.client.Client

A client which holds credentials and project configuration for the dataset (which requires a project).

job_config Optional[google.cloud.bigquery.job.QueryJobConfig]

Extra configuration options for the query job.

Properties allow_large_results

See allow_large_results.

billing_tier Returns Type Description Optional[int] Billing tier used by the job, or None if job is not yet complete. cache_hit Returns Type Description Optional[bool] whether the query results were returned from cache, or None if job is not yet complete. clustering_fields

See clustering_fields.

configuration

The configuration for this query job.

connection_properties create_disposition

See create_disposition.

create_session ddl_operation_performed ddl_target_routine ddl_target_table default_dataset

See default_dataset.

destination

See destination.

destination_encryption_configuration dry_run

See dry_run.

estimated_bytes_processed Returns Type Description Optional[int] number of DML rows affected by the job, or None if job is not yet complete. flatten_results

See flatten_results.

maximum_billing_tier

See maximum_billing_tier.

maximum_bytes_billed

See maximum_bytes_billed.

num_dml_affected_rows Returns Type Description Optional[int] number of DML rows affected by the job, or None if job is not yet complete. priority

See priority.

query query_id

[Preview] ID of a completed query.

This ID is auto-generated and not guaranteed to be populated.

query_parameters

See query_parameters.

query_plan range_partitioning

See range_partitioning.

referenced_tables Returns Type Description List[Dict] mappings describing the query plan, or an empty list if the query has not yet completed. schema

The schema of the results.

Present only for successful dry run of non-legacy SQL queries.

schema_update_options

See schema_update_options.

search_stats

Returns a SearchStats object.

slot_millis

Union[int, None]: Slot-milliseconds used by this query job.

statement_type Returns Type Description Optional[str] type of statement used by the job, or None if job is not yet complete. table_definitions

See table_definitions.

time_partitioning

See time_partitioning.

timeline

List(TimelineEntry): Return the query execution timeline from job statistics.

total_bytes_billed Returns Type Description Optional[int] Total bytes processed by the job, or None if job is not yet complete. total_bytes_processed Returns Type Description Optional[int] Total bytes processed by the job, or None if job is not yet complete. udf_resources

See udf_resources.

undeclared_query_parameters use_legacy_sql

See use_legacy_sql.

use_query_cache

See use_query_cache.

write_disposition

See write_disposition.

Methods from_api_repr 
from_api_repr(resource: dict, client: Client) -> QueryJob

Factory: construct a job given its API representation

Parameters Name Description resource Dict

dataset job representation returned from the API

client google.cloud.bigquery.client.Client

Client which holds credentials and project configuration for the dataset.

Returns Type Description google.cloud.bigquery.job.QueryJob Job parsed from resource. result 
result(page_size: typing.Optional[int] = None, max_results: typing.Optional[int] = None, retry: typing.Optional[google.api_core.retry.retry_unary.Retry] = <google.api_core.retry.retry_unary.Retry object>, timeout: typing.Optional[typing.Union[float, object]] = <object object>, start_index: typing.Optional[int] = None, job_retry: typing.Optional[google.api_core.retry.retry_unary.Retry] = <google.api_core.retry.retry_unary.Retry object>) -> typing.Union[RowIterator, google.cloud.bigquery.table._EmptyRowIterator]

Start the job and wait for it to complete and get the result.

Parameters Name Description page_size Optional[int]

The maximum number of rows in each page of results from this request. Non-positive values are ignored.

max_results Optional[int]

The maximum total number of rows from this request.

retry Optional[google.api_core.retry.Retry]

How to retry the call that retrieves rows. This only applies to making RPC calls. It isn't used to retry failed jobs. This has a reasonable default that should only be overridden with care. If the job state is DONE, retrying is aborted early even if the results are not available, as this will not change anymore.

timeout Optional[Union[float, google.api_core.future.polling.PollingFuture._DEFAULT_VALUE, ]]

The number of seconds to wait for the underlying HTTP transport before using retry. If None, wait indefinitely unless an error is returned. If unset, only the underlying API calls have their default timeouts, but we still wait indefinitely for the job to finish.

start_index Optional[int]

The zero-based index of the starting row to read.

job_retry Optional[google.api_core.retry.Retry]

How to retry failed jobs. The default retries rate-limit-exceeded errors. Passing None disables job retry. Not all jobs can be retried. If job_id was provided to the query that created this job, then the job returned by the query will not be retryable, and an exception will be raised if non-None non-default job_retry is also provided.

Exceptions Type Description google.api_core.exceptions.GoogleAPICallError If the job failed and retries aren't successful. concurrent.futures.TimeoutError If the job did not complete in the given timeout. TypeError If Non-None and non-default job_retry is provided and the job is not retryable. Returns Type Description google.cloud.bigquery.table.RowIterator Iterator of row data Row-s. During each page, the iterator will have the total_rows attribute set, which counts the total number of rows **in the result set** (this is distinct from the total number of rows in the current page: iterator.page.num_items). If the query is a special query that produces no results, e.g. a DDL query, an _EmptyRowIterator instance is returned. to_api_repr

Generate a resource for _begin.

to_arrow 
to_arrow(
    progress_bar_type: typing.Optional[str] = None,
    bqstorage_client: typing.Optional[bigquery_storage.BigQueryReadClient] = None,
    create_bqstorage_client: bool = True,
    max_results: typing.Optional[int] = None,
) -> pyarrow.Table

[Beta] Create a class:pyarrow.Table by loading all pages of a table or query.

Parameters Name Description progress_bar_type Optional[str]

If set, use the tqdm https://tqdm.github.io/_ library to display a progress bar while the data downloads. Install the tqdm package to use this feature. Possible values of progress_bar_type include: None No progress bar. 'tqdm' Use the tqdm.tqdm function to print a progress bar to :data:sys.stdout. 'tqdm_notebook' Use the tqdm.notebook.tqdm function to display a progress bar as a Jupyter notebook widget. 'tqdm_gui' Use the tqdm.tqdm_gui function to display a progress bar as a graphical dialog box.

bqstorage_client Optional[google.cloud.bigquery_storage_v1.BigQueryReadClient]

A BigQuery Storage API client. If supplied, use the faster BigQuery Storage API to fetch rows from BigQuery. This API is a billable API. This method requires google-cloud-bigquery-storage library. Reading from a specific partition or snapshot is not currently supported by this method.

create_bqstorage_client Optional[bool]

If True (default), create a BigQuery Storage API client using the default API settings. The BigQuery Storage API is a faster way to fetch rows from BigQuery. See the bqstorage_client parameter for more information. This argument does nothing if bqstorage_client is supplied. .. versionadded:: 1.24.0

max_results Optional[int]

Maximum number of rows to include in the result. No limit by default. .. versionadded:: 2.21.0

Exceptions Type Description ValueError If the pyarrow library cannot be imported. .. versionadded:: 1.17.0 to_dataframe 
to_dataframe(
    bqstorage_client: typing.Optional[bigquery_storage.BigQueryReadClient] = None,
    dtypes: typing.Optional[typing.Dict[str, typing.Any]] = None,
    progress_bar_type: typing.Optional[str] = None,
    create_bqstorage_client: bool = True,
    max_results: typing.Optional[int] = None,
    geography_as_object: bool = False,
    bool_dtype: typing.Optional[typing.Any] = DefaultPandasDTypes.BOOL_DTYPE,
    int_dtype: typing.Optional[typing.Any] = DefaultPandasDTypes.INT_DTYPE,
    float_dtype: typing.Optional[typing.Any] = None,
    string_dtype: typing.Optional[typing.Any] = None,
    date_dtype: typing.Optional[typing.Any] = DefaultPandasDTypes.DATE_DTYPE,
    datetime_dtype: typing.Optional[typing.Any] = None,
    time_dtype: typing.Optional[typing.Any] = DefaultPandasDTypes.TIME_DTYPE,
    timestamp_dtype: typing.Optional[typing.Any] = None,
    range_date_dtype: typing.Optional[
        typing.Any
    ] = DefaultPandasDTypes.RANGE_DATE_DTYPE,
    range_datetime_dtype: typing.Optional[
        typing.Any
    ] = DefaultPandasDTypes.RANGE_DATETIME_DTYPE,
    range_timestamp_dtype: typing.Optional[
        typing.Any
    ] = DefaultPandasDTypes.RANGE_TIMESTAMP_DTYPE,
) -> pandas.DataFrame

Return a pandas DataFrame from a QueryJob

Parameters Name Description bqstorage_client Optional[google.cloud.bigquery_storage_v1.BigQueryReadClient]

A BigQuery Storage API client. If supplied, use the faster BigQuery Storage API to fetch rows from BigQuery. This API is a billable API. This method requires the fastavro and google-cloud-bigquery-storage libraries. Reading from a specific partition or snapshot is not currently supported by this method.

dtypes Optional[Map[str, Union[str, pandas.Series.dtype]]]

A dictionary of column names pandas dtypes. The provided dtype is used when constructing the series for the column specified. Otherwise, the default pandas behavior is used.

progress_bar_type Optional[str]

If set, use the tqdm https://tqdm.github.io/_ library to display a progress bar while the data downloads. Install the tqdm package to use this feature. See to_dataframe for details. .. versionadded:: 1.11.0

create_bqstorage_client Optional[bool]

If True (default), create a BigQuery Storage API client using the default API settings. The BigQuery Storage API is a faster way to fetch rows from BigQuery. See the bqstorage_client parameter for more information. This argument does nothing if bqstorage_client is supplied. .. versionadded:: 1.24.0

max_results Optional[int]

Maximum number of rows to include in the result. No limit by default. .. versionadded:: 2.21.0

geography_as_object Optional[bool]

If True, convert GEOGRAPHY data to shapely geometry objects. If False (default), don't cast geography data to shapely geometry objects. .. versionadded:: 2.24.0

bool_dtype Optional[pandas.Series.dtype, None]

If set, indicate a pandas ExtensionDtype (e.g. pandas.BooleanDtype()) to convert BigQuery Boolean type, instead of relying on the default pandas.BooleanDtype(). If you explicitly set the value to None, then the data type will be numpy.dtype("bool"). BigQuery Boolean type can be found at: https://cloud.google.com/bigquery/docs/reference/standard-sql/data-types#boolean_type .. versionadded:: 3.8.0

int_dtype Optional[pandas.Series.dtype, None]

If set, indicate a pandas ExtensionDtype (e.g. pandas.Int64Dtype()) to convert BigQuery Integer types, instead of relying on the default pandas.Int64Dtype(). If you explicitly set the value to None, then the data type will be numpy.dtype("int64"). A list of BigQuery Integer types can be found at: https://cloud.google.com/bigquery/docs/reference/standard-sql/data-types#integer_types .. versionadded:: 3.8.0

float_dtype Optional[pandas.Series.dtype, None]

If set, indicate a pandas ExtensionDtype (e.g. pandas.Float32Dtype()) to convert BigQuery Float type, instead of relying on the default numpy.dtype("float64"). If you explicitly set the value to None, then the data type will be numpy.dtype("float64"). BigQuery Float type can be found at: https://cloud.google.com/bigquery/docs/reference/standard-sql/data-types#floating_point_types .. versionadded:: 3.8.0

string_dtype Optional[pandas.Series.dtype, None]

If set, indicate a pandas ExtensionDtype (e.g. pandas.StringDtype()) to convert BigQuery String type, instead of relying on the default numpy.dtype("object"). If you explicitly set the value to None, then the data type will be numpy.dtype("object"). BigQuery String type can be found at: https://cloud.google.com/bigquery/docs/reference/standard-sql/data-types#string_type .. versionadded:: 3.8.0

date_dtype Optional[pandas.Series.dtype, None]

If set, indicate a pandas ExtensionDtype (e.g. pandas.ArrowDtype(pyarrow.date32())) to convert BigQuery Date type, instead of relying on the default db_dtypes.DateDtype(). If you explicitly set the value to None, then the data type will be numpy.dtype("datetime64[ns]") or object if out of bound. BigQuery Date type can be found at: https://cloud.google.com/bigquery/docs/reference/standard-sql/data-types#date_type .. versionadded:: 3.10.0

datetime_dtype Optional[pandas.Series.dtype, None]

If set, indicate a pandas ExtensionDtype (e.g. pandas.ArrowDtype(pyarrow.timestamp("us"))) to convert BigQuery Datetime type, instead of relying on the default numpy.dtype("datetime64[ns]. If you explicitly set the value to None, then the data type will be numpy.dtype("datetime64[ns]") or object if out of bound. BigQuery Datetime type can be found at: https://cloud.google.com/bigquery/docs/reference/standard-sql/data-types#datetime_type .. versionadded:: 3.10.0

time_dtype Optional[pandas.Series.dtype, None]

If set, indicate a pandas ExtensionDtype (e.g. pandas.ArrowDtype(pyarrow.time64("us"))) to convert BigQuery Time type, instead of relying on the default db_dtypes.TimeDtype(). If you explicitly set the value to None, then the data type will be numpy.dtype("object"). BigQuery Time type can be found at: https://cloud.google.com/bigquery/docs/reference/standard-sql/data-types#time_type .. versionadded:: 3.10.0

timestamp_dtype Optional[pandas.Series.dtype, None]

If set, indicate a pandas ExtensionDtype (e.g. pandas.ArrowDtype(pyarrow.timestamp("us", tz="UTC"))) to convert BigQuery Timestamp type, instead of relying on the default numpy.dtype("datetime64[ns, UTC]"). If you explicitly set the value to None, then the data type will be numpy.dtype("datetime64[ns, UTC]") or object if out of bound. BigQuery Datetime type can be found at: https://cloud.google.com/bigquery/docs/reference/standard-sql/data-types#timestamp_type .. versionadded:: 3.10.0

range_date_dtype Optional[pandas.Series.dtype, None]

If set, indicate a pandas ExtensionDtype, such as: .. code-block:: python pandas.ArrowDtype(pyarrow.struct( [("start", pyarrow.date32()), ("end", pyarrow.date32())] )) to convert BigQuery RANGE

range_datetime_dtype Optional[pandas.Series.dtype, None]

If set, indicate a pandas ExtensionDtype, such as: .. code-block:: python pandas.ArrowDtype(pyarrow.struct( [ ("start", pyarrow.timestamp("us")), ("end", pyarrow.timestamp("us")), ] )) to convert BigQuery RANGE

range_timestamp_dtype Optional[pandas.Series.dtype, None]

If set, indicate a pandas ExtensionDtype, such as: .. code-block:: python pandas.ArrowDtype(pyarrow.struct( [ ("start", pyarrow.timestamp("us", tz="UTC")), ("end", pyarrow.timestamp("us", tz="UTC")), ] )) to convert BigQuery RANGE

Exceptions Type Description ValueError If the pandas library cannot be imported, or the bigquery_storage_v1 module is required but cannot be imported. Also if geography_as_object is True, but the shapely library cannot be imported. Returns Type Description pandas.DataFrame A pandas.DataFrame populated with row data and column headers from the query results. The column headers are derived from the destination table's schema. to_geodataframe 
to_geodataframe(
    bqstorage_client: typing.Optional[bigquery_storage.BigQueryReadClient] = None,
    dtypes: typing.Optional[typing.Dict[str, typing.Any]] = None,
    progress_bar_type: typing.Optional[str] = None,
    create_bqstorage_client: bool = True,
    max_results: typing.Optional[int] = None,
    geography_column: typing.Optional[str] = None,
    bool_dtype: typing.Optional[typing.Any] = DefaultPandasDTypes.BOOL_DTYPE,
    int_dtype: typing.Optional[typing.Any] = DefaultPandasDTypes.INT_DTYPE,
    float_dtype: typing.Optional[typing.Any] = None,
    string_dtype: typing.Optional[typing.Any] = None,
) -> geopandas.GeoDataFrame

Return a GeoPandas GeoDataFrame from a QueryJob

Parameters Name Description bqstorage_client Optional[google.cloud.bigquery_storage_v1.BigQueryReadClient]

A BigQuery Storage API client. If supplied, use the faster BigQuery Storage API to fetch rows from BigQuery. This API is a billable API. This method requires the fastavro and google-cloud-bigquery-storage libraries. Reading from a specific partition or snapshot is not currently supported by this method.

dtypes Optional[Map[str, Union[str, pandas.Series.dtype]]]

A dictionary of column names pandas dtypes. The provided dtype is used when constructing the series for the column specified. Otherwise, the default pandas behavior is used.

progress_bar_type Optional[str]

If set, use the tqdm https://tqdm.github.io/_ library to display a progress bar while the data downloads. Install the tqdm package to use this feature. See to_dataframe for details. .. versionadded:: 1.11.0

create_bqstorage_client Optional[bool]

If True (default), create a BigQuery Storage API client using the default API settings. The BigQuery Storage API is a faster way to fetch rows from BigQuery. See the bqstorage_client parameter for more information. This argument does nothing if bqstorage_client is supplied. .. versionadded:: 1.24.0

max_results Optional[int]

Maximum number of rows to include in the result. No limit by default. .. versionadded:: 2.21.0

geography_column Optional[str]

If there are more than one GEOGRAPHY column, identifies which one to use to construct a GeoPandas GeoDataFrame. This option can be ommitted if there's only one GEOGRAPHY column.

bool_dtype Optional[pandas.Series.dtype, None]

If set, indicate a pandas ExtensionDtype (e.g. pandas.BooleanDtype()) to convert BigQuery Boolean type, instead of relying on the default pandas.BooleanDtype(). If you explicitly set the value to None, then the data type will be numpy.dtype("bool"). BigQuery Boolean type can be found at: https://cloud.google.com/bigquery/docs/reference/standard-sql/data-types#boolean_type

int_dtype Optional[pandas.Series.dtype, None]

If set, indicate a pandas ExtensionDtype (e.g. pandas.Int64Dtype()) to convert BigQuery Integer types, instead of relying on the default pandas.Int64Dtype(). If you explicitly set the value to None, then the data type will be numpy.dtype("int64"). A list of BigQuery Integer types can be found at: https://cloud.google.com/bigquery/docs/reference/standard-sql/data-types#integer_types

float_dtype Optional[pandas.Series.dtype, None]

If set, indicate a pandas ExtensionDtype (e.g. pandas.Float32Dtype()) to convert BigQuery Float type, instead of relying on the default numpy.dtype("float64"). If you explicitly set the value to None, then the data type will be numpy.dtype("float64"). BigQuery Float type can be found at: https://cloud.google.com/bigquery/docs/reference/standard-sql/data-types#floating_point_types

string_dtype Optional[pandas.Series.dtype, None]

If set, indicate a pandas ExtensionDtype (e.g. pandas.StringDtype()) to convert BigQuery String type, instead of relying on the default numpy.dtype("object"). If you explicitly set the value to None, then the data type will be numpy.dtype("object"). BigQuery String type can be found at: https://cloud.google.com/bigquery/docs/reference/standard-sql/data-types#string_type

Exceptions Type Description ValueError If the geopandas library cannot be imported, or the bigquery_storage_v1 module is required but cannot be imported. .. versionadded:: 2.24.0 Returns Type Description geopandas.GeoDataFrame A geopandas.GeoDataFrame populated with row data and column headers from the query results. The column headers are derived from the destination table's schema.

Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates.

Last updated 2025-08-07 UTC.

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