Source code for airflow.providers.google.cloud.operators.bigquery

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"""This module contains Google BigQuery operators."""
import enum
import hashlib
import json
import re
import uuid
import warnings
from datetime import datetime
from typing import TYPE_CHECKING, Any, Dict, Iterable, List, Optional, Sequence, Set, SupportsAbs, Union

import attr
from google.api_core.exceptions import Conflict

from airflow.exceptions import AirflowException
from airflow.models import BaseOperator, BaseOperatorLink
from airflow.models.xcom import XCom
from airflow.operators.sql import SQLCheckOperator, SQLIntervalCheckOperator, SQLValueCheckOperator
from airflow.providers.google.cloud.hooks.bigquery import BigQueryHook, BigQueryJob
from airflow.providers.google.cloud.hooks.gcs import GCSHook, _parse_gcs_url

if TYPE_CHECKING:
    from airflow.utils.context import Context




_DEPRECATION_MSG = (
    "The bigquery_conn_id parameter has been deprecated. You should pass the gcp_conn_id parameter."
)


[docs]class BigQueryUIColors(enum.Enum): """Hex colors for BigQuery operators"""
[docs] CHECK = "#C0D7FF"
[docs] QUERY = "#A1BBFF"
[docs] TABLE = "#81A0FF"
[docs] DATASET = "#5F86FF"
class _BigQueryDbHookMixin: def get_db_hook(self: 'BigQueryCheckOperator') -> BigQueryHook: # type:ignore[misc] """Get BigQuery DB Hook""" return BigQueryHook( gcp_conn_id=self.gcp_conn_id, use_legacy_sql=self.use_legacy_sql, location=self.location, impersonation_chain=self.impersonation_chain, labels=self.labels, )
[docs]class BigQueryCheckOperator(_BigQueryDbHookMixin, SQLCheckOperator): """ Performs checks against BigQuery. The ``BigQueryCheckOperator`` expects a sql query that will return a single row. Each value on that first row is evaluated using python ``bool`` casting. If any of the values return ``False`` the check is failed and errors out. .. seealso:: For more information on how to use this operator, take a look at the guide: :ref:`howto/operator:BigQueryCheckOperator` Note that Python bool casting evals the following as ``False``: * ``False`` * ``0`` * Empty string (``""``) * Empty list (``[]``) * Empty dictionary or set (``{}``) Given a query like ``SELECT COUNT(*) FROM foo``, it will fail only if the count ``== 0``. You can craft much more complex query that could, for instance, check that the table has the same number of rows as the source table upstream, or that the count of today's partition is greater than yesterday's partition, or that a set of metrics are less than 3 standard deviation for the 7 day average. This operator can be used as a data quality check in your pipeline, and depending on where you put it in your DAG, you have the choice to stop the critical path, preventing from publishing dubious data, or on the side and receive email alerts without stopping the progress of the DAG. :param sql: the sql to be executed :param gcp_conn_id: (Optional) The connection ID used to connect to Google Cloud. :param bigquery_conn_id: (Deprecated) The connection ID used to connect to Google Cloud. This parameter has been deprecated. You should pass the gcp_conn_id parameter instead. :param use_legacy_sql: Whether to use legacy SQL (true) or standard SQL (false). :param location: The geographic location of the job. See details at: https://cloud.google.com/bigquery/docs/locations#specifying_your_location :param impersonation_chain: Optional service account to impersonate using short-term credentials, or chained list of accounts required to get the access_token of the last account in the list, which will be impersonated in the request. If set as a string, the account must grant the originating account the Service Account Token Creator IAM role. If set as a sequence, the identities from the list must grant Service Account Token Creator IAM role to the directly preceding identity, with first account from the list granting this role to the originating account (templated). :param labels: a dictionary containing labels for the table, passed to BigQuery """
[docs] template_fields: Sequence[str] = ( 'sql', 'gcp_conn_id', 'impersonation_chain', 'labels',
)
[docs] template_ext: Sequence[str] = ('.sql',)
[docs] ui_color = BigQueryUIColors.CHECK.value
def __init__( self, *, sql: str, gcp_conn_id: str = 'google_cloud_default', bigquery_conn_id: Optional[str] = None, use_legacy_sql: bool = True, location: Optional[str] = None, impersonation_chain: Optional[Union[str, Sequence[str]]] = None, labels: Optional[dict] = None, **kwargs, ) -> None: super().__init__(sql=sql, **kwargs) if bigquery_conn_id: warnings.warn(_DEPRECATION_MSG, DeprecationWarning, stacklevel=3) gcp_conn_id = bigquery_conn_id self.gcp_conn_id = gcp_conn_id self.sql = sql self.use_legacy_sql = use_legacy_sql self.location = location self.impersonation_chain = impersonation_chain self.labels = labels
[docs]class BigQueryValueCheckOperator(_BigQueryDbHookMixin, SQLValueCheckOperator): """ Performs a simple value check using sql code. .. seealso:: For more information on how to use this operator, take a look at the guide: :ref:`howto/operator:BigQueryValueCheckOperator` :param sql: the sql to be executed :param use_legacy_sql: Whether to use legacy SQL (true) or standard SQL (false). :param gcp_conn_id: (Optional) The connection ID used to connect to Google Cloud. :param bigquery_conn_id: (Deprecated) The connection ID used to connect to Google Cloud. This parameter has been deprecated. You should pass the gcp_conn_id parameter instead. :param location: The geographic location of the job. See details at: https://cloud.google.com/bigquery/docs/locations#specifying_your_location :param impersonation_chain: Optional service account to impersonate using short-term credentials, or chained list of accounts required to get the access_token of the last account in the list, which will be impersonated in the request. If set as a string, the account must grant the originating account the Service Account Token Creator IAM role. If set as a sequence, the identities from the list must grant Service Account Token Creator IAM role to the directly preceding identity, with first account from the list granting this role to the originating account (templated). :param labels: a dictionary containing labels for the table, passed to BigQuery """
[docs] template_fields: Sequence[str] = ( 'sql', 'gcp_conn_id', 'pass_value', 'impersonation_chain', 'labels',
)
[docs] template_ext: Sequence[str] = ('.sql',)
[docs] ui_color = BigQueryUIColors.CHECK.value
def __init__( self, *, sql: str, pass_value: Any, tolerance: Any = None, gcp_conn_id: str = 'google_cloud_default', bigquery_conn_id: Optional[str] = None, use_legacy_sql: bool = True, location: Optional[str] = None, impersonation_chain: Optional[Union[str, Sequence[str]]] = None, labels: Optional[dict] = None, **kwargs, ) -> None: super().__init__(sql=sql, pass_value=pass_value, tolerance=tolerance, **kwargs) if bigquery_conn_id: warnings.warn(_DEPRECATION_MSG, DeprecationWarning, stacklevel=3) gcp_conn_id = bigquery_conn_id self.location = location self.gcp_conn_id = gcp_conn_id self.use_legacy_sql = use_legacy_sql self.impersonation_chain = impersonation_chain self.labels = labels
[docs]class BigQueryIntervalCheckOperator(_BigQueryDbHookMixin, SQLIntervalCheckOperator): """ Checks that the values of metrics given as SQL expressions are within a certain tolerance of the ones from days_back before. This method constructs a query like so :: SELECT {metrics_threshold_dict_key} FROM {table} WHERE {date_filter_column}=<date> .. seealso:: For more information on how to use this operator, take a look at the guide: :ref:`howto/operator:BigQueryIntervalCheckOperator` :param table: the table name :param days_back: number of days between ds and the ds we want to check against. Defaults to 7 days :param metrics_thresholds: a dictionary of ratios indexed by metrics, for example 'COUNT(*)': 1.5 would require a 50 percent or less difference between the current day, and the prior days_back. :param use_legacy_sql: Whether to use legacy SQL (true) or standard SQL (false). :param gcp_conn_id: (Optional) The connection ID used to connect to Google Cloud. :param bigquery_conn_id: (Deprecated) The connection ID used to connect to Google Cloud. This parameter has been deprecated. You should pass the gcp_conn_id parameter instead. :param location: The geographic location of the job. See details at: https://cloud.google.com/bigquery/docs/locations#specifying_your_location :param impersonation_chain: Optional service account to impersonate using short-term credentials, or chained list of accounts required to get the access_token of the last account in the list, which will be impersonated in the request. If set as a string, the account must grant the originating account the Service Account Token Creator IAM role. If set as a sequence, the identities from the list must grant Service Account Token Creator IAM role to the directly preceding identity, with first account from the list granting this role to the originating account (templated). :param labels: a dictionary containing labels for the table, passed to BigQuery """
[docs] template_fields: Sequence[str] = ( 'table', 'gcp_conn_id', 'sql1', 'sql2', 'impersonation_chain', 'labels',
)
[docs] ui_color = BigQueryUIColors.CHECK.value
def __init__( self, *, table: str, metrics_thresholds: dict, date_filter_column: str = 'ds', days_back: SupportsAbs[int] = -7, gcp_conn_id: str = 'google_cloud_default', bigquery_conn_id: Optional[str] = None, use_legacy_sql: bool = True, location: Optional[str] = None, impersonation_chain: Optional[Union[str, Sequence[str]]] = None, labels: Optional[Dict] = None, **kwargs, ) -> None: super().__init__( table=table, metrics_thresholds=metrics_thresholds, date_filter_column=date_filter_column, days_back=days_back, **kwargs, ) if bigquery_conn_id: warnings.warn(_DEPRECATION_MSG, DeprecationWarning, stacklevel=3) gcp_conn_id = bigquery_conn_id self.gcp_conn_id = gcp_conn_id self.use_legacy_sql = use_legacy_sql self.location = location self.impersonation_chain = impersonation_chain self.labels = labels
[docs]class BigQueryGetDataOperator(BaseOperator): """ Fetches the data from a BigQuery table (alternatively fetch data for selected columns) and returns data in a python list. The number of elements in the returned list will be equal to the number of rows fetched. Each element in the list will again be a list where element would represent the columns values for that row. **Example Result**: ``[['Tony', '10'], ['Mike', '20'], ['Steve', '15']]`` .. seealso:: For more information on how to use this operator, take a look at the guide: :ref:`howto/operator:BigQueryGetDataOperator` .. note:: If you pass fields to ``selected_fields`` which are in different order than the order of columns already in BQ table, the data will still be in the order of BQ table. For example if the BQ table has 3 columns as ``[A,B,C]`` and you pass 'B,A' in the ``selected_fields`` the data would still be of the form ``'A,B'``. **Example**: :: get_data = BigQueryGetDataOperator( task_id='get_data_from_bq', dataset_id='test_dataset', table_id='Transaction_partitions', max_results=100, selected_fields='DATE', gcp_conn_id='airflow-conn-id' ) :param dataset_id: The dataset ID of the requested table. (templated) :param table_id: The table ID of the requested table. (templated) :param max_results: The maximum number of records (rows) to be fetched from the table. (templated) :param selected_fields: List of fields to return (comma-separated). If unspecified, all fields are returned. :param gcp_conn_id: (Optional) The connection ID used to connect to Google Cloud. :param bigquery_conn_id: (Deprecated) The connection ID used to connect to Google Cloud. This parameter has been deprecated. You should pass the gcp_conn_id parameter instead. :param delegate_to: The account to impersonate using domain-wide delegation of authority, if any. For this to work, the service account making the request must have domain-wide delegation enabled. :param location: The location used for the operation. :param impersonation_chain: Optional service account to impersonate using short-term credentials, or chained list of accounts required to get the access_token of the last account in the list, which will be impersonated in the request. If set as a string, the account must grant the originating account the Service Account Token Creator IAM role. If set as a sequence, the identities from the list must grant Service Account Token Creator IAM role to the directly preceding identity, with first account from the list granting this role to the originating account (templated). """
[docs] template_fields: Sequence[str] = ( 'dataset_id', 'table_id', 'max_results', 'selected_fields', 'impersonation_chain',
)
[docs] ui_color = BigQueryUIColors.QUERY.value
def __init__( self, *, dataset_id: str, table_id: str, max_results: int = 100, selected_fields: Optional[str] = None, gcp_conn_id: str = 'google_cloud_default', bigquery_conn_id: Optional[str] = None, delegate_to: Optional[str] = None, location: Optional[str] = None, impersonation_chain: Optional[Union[str, Sequence[str]]] = None, **kwargs, ) -> None: super().__init__(**kwargs) if bigquery_conn_id: warnings.warn( "The bigquery_conn_id parameter has been deprecated. You should pass " "the gcp_conn_id parameter.", DeprecationWarning, stacklevel=3, ) gcp_conn_id = bigquery_conn_id self.dataset_id = dataset_id self.table_id = table_id self.max_results = int(max_results) self.selected_fields = selected_fields self.gcp_conn_id = gcp_conn_id self.delegate_to = delegate_to self.location = location self.impersonation_chain = impersonation_chain
[docs] def execute(self, context: 'Context') -> list: self.log.info( 'Fetching Data from %s.%s max results: %s', self.dataset_id, self.table_id, self.max_results ) hook = BigQueryHook( bigquery_conn_id=self.gcp_conn_id, delegate_to=self.delegate_to, impersonation_chain=self.impersonation_chain, ) rows = hook.list_rows( dataset_id=self.dataset_id, table_id=self.table_id, max_results=self.max_results, selected_fields=self.selected_fields, location=self.location, ) self.log.info('Total extracted rows: %s', len(rows)) table_data = [row.values() for row in rows] return table_data
[docs]class BigQueryExecuteQueryOperator(BaseOperator): """ Executes BigQuery SQL queries in a specific BigQuery database. This operator does not assert idempotency. This operator is deprecated. Please use :class:`airflow.providers.google.cloud.operators.bigquery.BigQueryInsertJobOperator` :param sql: the SQL code to be executed as a single string, or a list of str (sql statements), or a reference to a template file. Template references are recognized by str ending in '.sql' :param destination_dataset_table: A dotted ``(<project>.|<project>:)<dataset>.<table>`` that, if set, will store the results of the query. (templated) :param write_disposition: Specifies the action that occurs if the destination table already exists. (default: 'WRITE_EMPTY') :param create_disposition: Specifies whether the job is allowed to create new tables. (default: 'CREATE_IF_NEEDED') :param allow_large_results: Whether to allow large results. :param flatten_results: If true and query uses legacy SQL dialect, flattens all nested and repeated fields in the query results. ``allow_large_results`` must be ``true`` if this is set to ``false``. For standard SQL queries, this flag is ignored and results are never flattened. :param gcp_conn_id: (Optional) The connection ID used to connect to Google Cloud. :param bigquery_conn_id: (Deprecated) The connection ID used to connect to Google Cloud. This parameter has been deprecated. You should pass the gcp_conn_id parameter instead. :param delegate_to: The account to impersonate using domain-wide delegation of authority, if any. For this to work, the service account making the request must have domain-wide delegation enabled. :param udf_config: The User Defined Function configuration for the query. See https://cloud.google.com/bigquery/user-defined-functions for details. :param use_legacy_sql: Whether to use legacy SQL (true) or standard SQL (false). :param maximum_billing_tier: Positive integer that serves as a multiplier of the basic price. Defaults to None, in which case it uses the value set in the project. :param maximum_bytes_billed: Limits the bytes billed for this job. 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. :param api_resource_configs: a dictionary that contain params 'configuration' applied for Google BigQuery Jobs API: https://cloud.google.com/bigquery/docs/reference/rest/v2/jobs for example, {'query': {'useQueryCache': False}}. You could use it if you need to provide some params that are not supported by BigQueryOperator like args. :param schema_update_options: Allows the schema of the destination table to be updated as a side effect of the load job. :param query_params: a list of dictionary containing query parameter types and values, passed to BigQuery. The structure of dictionary should look like 'queryParameters' in Google BigQuery Jobs API: https://cloud.google.com/bigquery/docs/reference/rest/v2/jobs. For example, [{ 'name': 'corpus', 'parameterType': { 'type': 'STRING' }, 'parameterValue': { 'value': 'romeoandjuliet' } }]. (templated) :param labels: a dictionary containing labels for the job/query, passed to BigQuery :param priority: Specifies a priority for the query. Possible values include INTERACTIVE and BATCH. The default value is INTERACTIVE. :param time_partitioning: configure optional time partitioning fields i.e. partition by field, type and expiration as per API specifications. :param cluster_fields: Request that the result of this query be stored sorted by one or more columns. BigQuery supports clustering for both partitioned and non-partitioned tables. The order of columns given determines the sort order. :param location: The geographic location of the job. Required except for US and EU. See details at https://cloud.google.com/bigquery/docs/locations#specifying_your_location :param encryption_configuration: [Optional] Custom encryption configuration (e.g., Cloud KMS keys). **Example**: :: encryption_configuration = { "kmsKeyName": "projects/testp/locations/us/keyRings/test-kr/cryptoKeys/test-key" } :param impersonation_chain: Optional service account to impersonate using short-term credentials, or chained list of accounts required to get the access_token of the last account in the list, which will be impersonated in the request. If set as a string, the account must grant the originating account the Service Account Token Creator IAM role. If set as a sequence, the identities from the list must grant Service Account Token Creator IAM role to the directly preceding identity, with first account from the list granting this role to the originating account (templated). """
[docs] template_fields: Sequence[str] = ( 'sql', 'destination_dataset_table', 'labels', 'query_params', 'impersonation_chain',
)
[docs] template_ext: Sequence[str] = ('.sql',)
[docs] template_fields_renderers = {'sql': 'sql'}
[docs] ui_color = BigQueryUIColors.QUERY.value
@property def __init__( self, *, sql: Union[str, Iterable], destination_dataset_table: Optional[str] = None, write_disposition: str = 'WRITE_EMPTY', allow_large_results: bool = False, flatten_results: Optional[bool] = None, gcp_conn_id: str = 'google_cloud_default', bigquery_conn_id: Optional[str] = None, delegate_to: Optional[str] = None, udf_config: Optional[list] = None, use_legacy_sql: bool = True, maximum_billing_tier: Optional[int] = None, maximum_bytes_billed: Optional[float] = None, create_disposition: str = 'CREATE_IF_NEEDED', schema_update_options: Optional[Union[list, tuple, set]] = None, query_params: Optional[list] = None, labels: Optional[dict] = None, priority: str = 'INTERACTIVE', time_partitioning: Optional[dict] = None, api_resource_configs: Optional[dict] = None, cluster_fields: Optional[List[str]] = None, location: Optional[str] = None, encryption_configuration: Optional[dict] = None, impersonation_chain: Optional[Union[str, Sequence[str]]] = None, **kwargs, ) -> None: super().__init__(**kwargs) if bigquery_conn_id: warnings.warn( "The bigquery_conn_id parameter has been deprecated. You should pass " "the gcp_conn_id parameter.", DeprecationWarning, stacklevel=2, ) gcp_conn_id = bigquery_conn_id warnings.warn( "This operator is deprecated. Please use `BigQueryInsertJobOperator`.", DeprecationWarning, stacklevel=2, ) self.sql = sql self.destination_dataset_table = destination_dataset_table self.write_disposition = write_disposition self.create_disposition = create_disposition self.allow_large_results = allow_large_results self.flatten_results = flatten_results self.gcp_conn_id = gcp_conn_id self.delegate_to = delegate_to self.udf_config = udf_config self.use_legacy_sql = use_legacy_sql self.maximum_billing_tier = maximum_billing_tier self.maximum_bytes_billed = maximum_bytes_billed self.schema_update_options = schema_update_options self.query_params = query_params self.labels = labels self.priority = priority self.time_partitioning = time_partitioning self.api_resource_configs = api_resource_configs self.cluster_fields = cluster_fields self.location = location self.encryption_configuration = encryption_configuration self.hook = None # type: Optional[BigQueryHook] self.impersonation_chain = impersonation_chain
[docs] def execute(self, context: 'Context'): if self.hook is None: self.log.info('Executing: %s', self.sql) self.hook = BigQueryHook( gcp_conn_id=self.gcp_conn_id, use_legacy_sql=self.use_legacy_sql, delegate_to=self.delegate_to, location=self.location, impersonation_chain=self.impersonation_chain, ) if isinstance(self.sql, str): job_id: Union[str, List[str]] = self.hook.run_query( sql=self.sql, destination_dataset_table=self.destination_dataset_table, write_disposition=self.write_disposition, allow_large_results=self.allow_large_results, flatten_results=self.flatten_results, udf_config=self.udf_config, maximum_billing_tier=self.maximum_billing_tier, maximum_bytes_billed=self.maximum_bytes_billed, create_disposition=self.create_disposition, query_params=self.query_params, labels=self.labels, schema_update_options=self.schema_update_options, priority=self.priority, time_partitioning=self.time_partitioning, api_resource_configs=self.api_resource_configs, cluster_fields=self.cluster_fields, encryption_configuration=self.encryption_configuration, ) elif isinstance(self.sql, Iterable): job_id = [ self.hook.run_query( sql=s, destination_dataset_table=self.destination_dataset_table, write_disposition=self.write_disposition, allow_large_results=self.allow_large_results, flatten_results=self.flatten_results, udf_config=self.udf_config, maximum_billing_tier=self.maximum_billing_tier, maximum_bytes_billed=self.maximum_bytes_billed, create_disposition=self.create_disposition, query_params=self.query_params, labels=self.labels, schema_update_options=self.schema_update_options, priority=self.priority, time_partitioning=self.time_partitioning, api_resource_configs=self.api_resource_configs, cluster_fields=self.cluster_fields, encryption_configuration=self.encryption_configuration, ) for s in self.sql ] else: raise AirflowException(f"argument 'sql' of type {type(str)} is neither a string nor an iterable") context['task_instance'].xcom_push(key='job_id', value=job_id)
[docs] def on_kill(self) -> None: super().on_kill() if self.hook is not None: self.log.info('Cancelling running query') self.hook.cancel_query()
[docs]class BigQueryCreateEmptyTableOperator(BaseOperator): """ Creates a new, empty table in the specified BigQuery dataset, optionally with schema. The schema to be used for the BigQuery table may be specified in one of two ways. You may either directly pass the schema fields in, or you may point the operator to a Google Cloud Storage object name. The object in Google Cloud Storage must be a JSON file with the schema fields in it. You can also create a table without schema. .. seealso:: For more information on how to use this operator, take a look at the guide: :ref:`howto/operator:BigQueryCreateEmptyTableOperator` :param project_id: The project to create the table into. (templated) :param dataset_id: The dataset to create the table into. (templated) :param table_id: The Name of the table to be created. (templated) :param table_resource: Table resource as described in documentation: https://cloud.google.com/bigquery/docs/reference/rest/v2/tables#Table If provided all other parameters are ignored. :param schema_fields: If set, the schema field list as defined here: https://cloud.google.com/bigquery/docs/reference/rest/v2/jobs#configuration.load.schema **Example**: :: schema_fields=[{"name": "emp_name", "type": "STRING", "mode": "REQUIRED"}, {"name": "salary", "type": "INTEGER", "mode": "NULLABLE"}] :param gcs_schema_object: Full path to the JSON file containing schema (templated). For example: ``gs://test-bucket/dir1/dir2/employee_schema.json`` :param time_partitioning: configure optional time partitioning fields i.e. partition by field, type and expiration as per API specifications. .. seealso:: https://cloud.google.com/bigquery/docs/reference/rest/v2/tables#timePartitioning :param bigquery_conn_id: [Optional] The connection ID used to connect to Google Cloud and interact with the Bigquery service. :param google_cloud_storage_conn_id: [Optional] The connection ID used to connect to Google Cloud. and interact with the Google Cloud Storage service. :param delegate_to: The account to impersonate using domain-wide delegation of authority, if any. For this to work, the service account making the request must have domain-wide delegation enabled. :param labels: a dictionary containing labels for the table, passed to BigQuery **Example (with schema JSON in GCS)**: :: CreateTable = BigQueryCreateEmptyTableOperator( task_id='BigQueryCreateEmptyTableOperator_task', dataset_id='ODS', table_id='Employees', project_id='internal-gcp-project', gcs_schema_object='gs://schema-bucket/employee_schema.json', bigquery_conn_id='airflow-conn-id', google_cloud_storage_conn_id='airflow-conn-id' ) **Corresponding Schema file** (``employee_schema.json``): :: [ { "mode": "NULLABLE", "name": "emp_name", "type": "STRING" }, { "mode": "REQUIRED", "name": "salary", "type": "INTEGER" } ] **Example (with schema in the DAG)**: :: CreateTable = BigQueryCreateEmptyTableOperator( task_id='BigQueryCreateEmptyTableOperator_task', dataset_id='ODS', table_id='Employees', project_id='internal-gcp-project', schema_fields=[{"name": "emp_name", "type": "STRING", "mode": "REQUIRED"}, {"name": "salary", "type": "INTEGER", "mode": "NULLABLE"}], bigquery_conn_id='airflow-conn-id-account', google_cloud_storage_conn_id='airflow-conn-id' ) :param view: [Optional] A dictionary containing definition for the view. If set, it will create a view instead of a table: .. seealso:: https://cloud.google.com/bigquery/docs/reference/rest/v2/tables#ViewDefinition :param materialized_view: [Optional] The materialized view definition. :param encryption_configuration: [Optional] Custom encryption configuration (e.g., Cloud KMS keys). **Example**: :: encryption_configuration = { "kmsKeyName": "projects/testp/locations/us/keyRings/test-kr/cryptoKeys/test-key" } :param location: The location used for the operation. :param cluster_fields: [Optional] The fields used for clustering. BigQuery supports clustering for both partitioned and non-partitioned tables. .. seealso:: https://cloud.google.com/bigquery/docs/reference/rest/v2/tables#clustering.fields :param impersonation_chain: Optional service account to impersonate using short-term credentials, or chained list of accounts required to get the access_token of the last account in the list, which will be impersonated in the request. If set as a string, the account must grant the originating account the Service Account Token Creator IAM role. If set as a sequence, the identities from the list must grant Service Account Token Creator IAM role to the directly preceding identity, with first account from the list granting this role to the originating account (templated). :param exists_ok: If ``True``, ignore "already exists" errors when creating the table. """
[docs] template_fields: Sequence[str] = ( 'dataset_id', 'table_id', 'project_id', 'gcs_schema_object', 'labels', 'view', 'materialized_view', 'impersonation_chain',
)
[docs] template_fields_renderers = {"table_resource": "json", "materialized_view": "json"}
[docs] ui_color = BigQueryUIColors.TABLE.value
def __init__( self, *, dataset_id: str, table_id: str, table_resource: Optional[Dict[str, Any]] = None, project_id: Optional[str] = None, schema_fields: Optional[List] = None, gcs_schema_object: Optional[str] = None, time_partitioning: Optional[Dict] = None, bigquery_conn_id: str = 'google_cloud_default', google_cloud_storage_conn_id: str = 'google_cloud_default', delegate_to: Optional[str] = None, labels: Optional[Dict] = None, view: Optional[Dict] = None, materialized_view: Optional[Dict] = None, encryption_configuration: Optional[Dict] = None, location: Optional[str] = None, cluster_fields: Optional[List[str]] = None, impersonation_chain: Optional[Union[str, Sequence[str]]] = None, exists_ok: bool = False, **kwargs, ) -> None: super().__init__(**kwargs) self.project_id = project_id self.dataset_id = dataset_id self.table_id = table_id self.schema_fields = schema_fields self.gcs_schema_object = gcs_schema_object self.bigquery_conn_id = bigquery_conn_id self.google_cloud_storage_conn_id = google_cloud_storage_conn_id self.delegate_to = delegate_to self.time_partitioning = {} if time_partitioning is None else time_partitioning self.labels = labels self.view = view self.materialized_view = materialized_view self.encryption_configuration = encryption_configuration self.location = location self.cluster_fields = cluster_fields self.table_resource = table_resource self.impersonation_chain = impersonation_chain self.exists_ok = exists_ok
[docs] def execute(self, context: 'Context') -> None: bq_hook = BigQueryHook( gcp_conn_id=self.bigquery_conn_id, delegate_to=self.delegate_to, location=self.location, impersonation_chain=self.impersonation_chain, ) if not self.schema_fields and self.gcs_schema_object: gcs_bucket, gcs_object = _parse_gcs_url(self.gcs_schema_object) gcs_hook = GCSHook( gcp_conn_id=self.google_cloud_storage_conn_id, delegate_to=self.delegate_to, impersonation_chain=self.impersonation_chain, ) schema_fields_string = gcs_hook.download_as_byte_array(gcs_bucket, gcs_object).decode("utf-8") schema_fields = json.loads(schema_fields_string) else: schema_fields = self.schema_fields try: self.log.info('Creating table') table = bq_hook.create_empty_table( project_id=self.project_id, dataset_id=self.dataset_id, table_id=self.table_id, schema_fields=schema_fields, time_partitioning=self.time_partitioning, cluster_fields=self.cluster_fields, labels=self.labels, view=self.view, materialized_view=self.materialized_view, encryption_configuration=self.encryption_configuration, table_resource=self.table_resource, exists_ok=self.exists_ok, ) self.log.info( 'Table %s.%s.%s created successfully', table.project, table.dataset_id, table.table_id ) except Conflict: self.log.info('Table %s.%s already exists.', self.dataset_id, self.table_id)
[docs]class BigQueryCreateExternalTableOperator(BaseOperator): """ Creates a new external table in the dataset with the data from Google Cloud Storage. The schema to be used for the BigQuery table may be specified in one of two ways. You may either directly pass the schema fields in, or you may point the operator to a Google Cloud Storage object name. The object in Google Cloud Storage must be a JSON file with the schema fields in it. .. seealso:: For more information on how to use this operator, take a look at the guide: :ref:`howto/operator:BigQueryCreateExternalTableOperator` :param bucket: The bucket to point the external table to. (templated) :param source_objects: List of Google Cloud Storage URIs to point table to. If source_format is 'DATASTORE_BACKUP', the list must only contain a single URI. :param destination_project_dataset_table: The dotted ``(<project>.)<dataset>.<table>`` BigQuery table to load data into (templated). If ``<project>`` is not included, project will be the project defined in the connection json. :param schema_fields: If set, the schema field list as defined here: https://cloud.google.com/bigquery/docs/reference/rest/v2/jobs#configuration.load.schema **Example**: :: schema_fields=[{"name": "emp_name", "type": "STRING", "mode": "REQUIRED"}, {"name": "salary", "type": "INTEGER", "mode": "NULLABLE"}] Should not be set when source_format is 'DATASTORE_BACKUP'. :param table_resource: Table resource as described in documentation: https://cloud.google.com/bigquery/docs/reference/rest/v2/tables#Table If provided all other parameters are ignored. External schema from object will be resolved. :param schema_object: If set, a GCS object path pointing to a .json file that contains the schema for the table. (templated) :param source_format: File format of the data. :param compression: [Optional] The compression type of the data source. Possible values include GZIP and NONE. The default value is NONE. This setting is ignored for Google Cloud Bigtable, Google Cloud Datastore backups and Avro formats. :param skip_leading_rows: Number of rows to skip when loading from a CSV. :param field_delimiter: The delimiter to use for the CSV. :param max_bad_records: The maximum number of bad records that BigQuery can ignore when running the job. :param quote_character: The value that is used to quote data sections in a CSV file. :param allow_quoted_newlines: Whether to allow quoted newlines (true) or not (false). :param allow_jagged_rows: Accept rows that are missing trailing optional columns. The missing values are treated as nulls. If false, records with missing trailing columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. Only applicable to CSV, ignored for other formats. :param bigquery_conn_id: (Optional) The connection ID used to connect to Google Cloud and interact with the Bigquery service. :param google_cloud_storage_conn_id: (Optional) The connection ID used to connect to Google Cloud and interact with the Google Cloud Storage service. :param delegate_to: The account to impersonate using domain-wide delegation of authority, if any. For this to work, the service account making the request must have domain-wide delegation enabled. :param src_fmt_configs: configure optional fields specific to the source format :param labels: a dictionary containing labels for the table, passed to BigQuery :param encryption_configuration: [Optional] Custom encryption configuration (e.g., Cloud KMS keys). **Example**: :: encryption_configuration = { "kmsKeyName": "projects/testp/locations/us/keyRings/test-kr/cryptoKeys/test-key" } :param location: The location used for the operation. :param impersonation_chain: Optional service account to impersonate using short-term credentials, or chained list of accounts required to get the access_token of the last account in the list, which will be impersonated in the request. If set as a string, the account must grant the originating account the Service Account Token Creator IAM role. If set as a sequence, the identities from the list must grant Service Account Token Creator IAM role to the directly preceding identity, with first account from the list granting this role to the originating account (templated). """
[docs] template_fields: Sequence[str] = ( 'bucket', 'source_objects', 'schema_object', 'destination_project_dataset_table', 'labels', 'table_resource', 'impersonation_chain',
)
[docs] template_fields_renderers = {"table_resource": "json"}
[docs] ui_color = BigQueryUIColors.TABLE.value
def __init__( self, *, bucket: Optional[str] = None, source_objects: Optional[List[str]] = None, destination_project_dataset_table: Optional[str] = None, table_resource: Optional[Dict[str, Any]] = None, schema_fields: Optional[List] = None, schema_object: Optional[str] = None, source_format: Optional[str] = None, compression: Optional[str] = None, skip_leading_rows: Optional[int] = None, field_delimiter: Optional[str] = None, max_bad_records: int = 0, quote_character: Optional[str] = None, allow_quoted_newlines: bool = False, allow_jagged_rows: bool = False, bigquery_conn_id: str = 'google_cloud_default', google_cloud_storage_conn_id: str = 'google_cloud_default', delegate_to: Optional[str] = None, src_fmt_configs: Optional[dict] = None, labels: Optional[Dict] = None, encryption_configuration: Optional[Dict] = None, location: Optional[str] = None, impersonation_chain: Optional[Union[str, Sequence[str]]] = None, **kwargs, ) -> None: super().__init__(**kwargs) # BQ config kwargs_passed = any( [ destination_project_dataset_table, schema_fields, source_format, compression, skip_leading_rows, field_delimiter, max_bad_records, quote_character, allow_quoted_newlines, allow_jagged_rows, src_fmt_configs, labels, encryption_configuration, ] ) if not table_resource: warnings.warn( "Passing table parameters via keywords arguments will be deprecated. " "Please provide table definition using `table_resource` parameter.", DeprecationWarning, stacklevel=2, ) if not bucket: raise ValueError("`bucket` is required when not using `table_resource`.") if not source_objects: raise ValueError("`source_objects` is required when not using `table_resource`.") if not source_format: source_format = 'CSV' if not compression: compression = 'NONE' if not skip_leading_rows: skip_leading_rows = 0 if not field_delimiter: field_delimiter = "," if not destination_project_dataset_table: raise ValueError( "`destination_project_dataset_table` is required when not using `table_resource`." ) self.bucket = bucket self.source_objects = source_objects self.schema_object = schema_object self.destination_project_dataset_table = destination_project_dataset_table self.schema_fields = schema_fields self.source_format = source_format self.compression = compression self.skip_leading_rows = skip_leading_rows self.field_delimiter = field_delimiter self.table_resource = None else: self.table_resource = table_resource self.bucket = "" self.source_objects = [] self.schema_object = None self.destination_project_dataset_table = "" if table_resource and kwargs_passed: raise ValueError("You provided both `table_resource` and exclusive keywords arguments.") self.max_bad_records = max_bad_records self.quote_character = quote_character self.allow_quoted_newlines = allow_quoted_newlines self.allow_jagged_rows = allow_jagged_rows self.bigquery_conn_id = bigquery_conn_id self.google_cloud_storage_conn_id = google_cloud_storage_conn_id self.delegate_to = delegate_to self.src_fmt_configs = src_fmt_configs or {} self.labels = labels self.encryption_configuration = encryption_configuration self.location = location self.impersonation_chain = impersonation_chain
[docs] def execute(self, context: 'Context') -> None: bq_hook = BigQueryHook( gcp_conn_id=self.bigquery_conn_id, delegate_to=self.delegate_to, location=self.location, impersonation_chain=self.impersonation_chain, ) if self.table_resource: bq_hook.create_empty_table( table_resource=self.table_resource, ) return if not self.schema_fields and self.schema_object and self.source_format != 'DATASTORE_BACKUP': gcs_hook = GCSHook( gcp_conn_id=self.google_cloud_storage_conn_id, delegate_to=self.delegate_to, impersonation_chain=self.impersonation_chain, ) schema_fields = json.loads(gcs_hook.download(self.bucket, self.schema_object).decode("utf-8")) else: schema_fields = self.schema_fields source_uris = [f"gs://{self.bucket}/{source_object}" for source_object in self.source_objects] bq_hook.create_external_table( external_project_dataset_table=self.destination_project_dataset_table, schema_fields=schema_fields, source_uris=source_uris, source_format=self.source_format, compression=self.compression, skip_leading_rows=self.skip_leading_rows, field_delimiter=self.field_delimiter, max_bad_records=self.max_bad_records, quote_character=self.quote_character, allow_quoted_newlines=self.allow_quoted_newlines, allow_jagged_rows=self.allow_jagged_rows, src_fmt_configs=self.src_fmt_configs, labels=self.labels, encryption_configuration=self.encryption_configuration,
)
[docs]class BigQueryDeleteDatasetOperator(BaseOperator): """ This operator deletes an existing dataset from your Project in Big query. https://cloud.google.com/bigquery/docs/reference/rest/v2/datasets/delete .. seealso:: For more information on how to use this operator, take a look at the guide: :ref:`howto/operator:BigQueryDeleteDatasetOperator` :param project_id: The project id of the dataset. :param dataset_id: The dataset to be deleted. :param delete_contents: (Optional) Whether to force the deletion even if the dataset is not empty. Will delete all tables (if any) in the dataset if set to True. Will raise HttpError 400: "{dataset_id} is still in use" if set to False and dataset is not empty. The default value is False. :param gcp_conn_id: (Optional) The connection ID used to connect to Google Cloud. :param bigquery_conn_id: (Deprecated) The connection ID used to connect to Google Cloud. This parameter has been deprecated. You should pass the gcp_conn_id parameter instead. :param delegate_to: The account to impersonate using domain-wide delegation of authority, if any. For this to work, the service account making the request must have domain-wide delegation enabled. :param impersonation_chain: Optional service account to impersonate using short-term credentials, or chained list of accounts required to get the access_token of the last account in the list, which will be impersonated in the request. If set as a string, the account must grant the originating account the Service Account Token Creator IAM role. If set as a sequence, the identities from the list must grant Service Account Token Creator IAM role to the directly preceding identity, with first account from the list granting this role to the originating account (templated). **Example**: :: delete_temp_data = BigQueryDeleteDatasetOperator( dataset_id='temp-dataset', project_id='temp-project', delete_contents=True, # Force the deletion of the dataset as well as its tables (if any). gcp_conn_id='_my_gcp_conn_', task_id='Deletetemp', dag=dag) """
[docs] template_fields: Sequence[str] = ( 'dataset_id', 'project_id', 'impersonation_chain',
)
[docs] ui_color = BigQueryUIColors.DATASET.value
def __init__( self, *, dataset_id: str, project_id: Optional[str] = None, delete_contents: bool = False, gcp_conn_id: str = 'google_cloud_default', bigquery_conn_id: Optional[str] = None, delegate_to: Optional[str] = None, impersonation_chain: Optional[Union[str, Sequence[str]]] = None, **kwargs, ) -> None: if bigquery_conn_id: warnings.warn( "The bigquery_conn_id parameter has been deprecated. You should pass " "the gcp_conn_id parameter.", DeprecationWarning, stacklevel=3, ) gcp_conn_id = bigquery_conn_id self.dataset_id = dataset_id self.project_id = project_id self.delete_contents = delete_contents self.gcp_conn_id = gcp_conn_id self.delegate_to = delegate_to self.impersonation_chain = impersonation_chain super().__init__(**kwargs)
[docs] def execute(self, context: 'Context') -> None: self.log.info('Dataset id: %s Project id: %s', self.dataset_id, self.project_id) bq_hook = BigQueryHook( gcp_conn_id=self.gcp_conn_id, delegate_to=self.delegate_to, impersonation_chain=self.impersonation_chain, ) bq_hook.delete_dataset( project_id=self.project_id, dataset_id=self.dataset_id, delete_contents=self.delete_contents
)
[docs]class BigQueryCreateEmptyDatasetOperator(BaseOperator): """ This operator is used to create new dataset for your Project in BigQuery. https://cloud.google.com/bigquery/docs/reference/rest/v2/datasets#resource .. seealso:: For more information on how to use this operator, take a look at the guide: :ref:`howto/operator:BigQueryCreateEmptyDatasetOperator` :param project_id: The name of the project where we want to create the dataset. :param dataset_id: The id of dataset. Don't need to provide, if datasetId in dataset_reference. :param location: The geographic location where the dataset should reside. :param dataset_reference: Dataset reference that could be provided with request body. More info: https://cloud.google.com/bigquery/docs/reference/rest/v2/datasets#resource :param gcp_conn_id: (Optional) The connection ID used to connect to Google Cloud. :param bigquery_conn_id: (Deprecated) The connection ID used to connect to Google Cloud. This parameter has been deprecated. You should pass the gcp_conn_id parameter instead. :param delegate_to: The account to impersonate using domain-wide delegation of authority, if any. For this to work, the service account making the request must have domain-wide delegation enabled. :param impersonation_chain: Optional service account to impersonate using short-term credentials, or chained list of accounts required to get the access_token of the last account in the list, which will be impersonated in the request. If set as a string, the account must grant the originating account the Service Account Token Creator IAM role. If set as a sequence, the identities from the list must grant Service Account Token Creator IAM role to the directly preceding identity, with first account from the list granting this role to the originating account (templated). :param exists_ok: If ``True``, ignore "already exists" errors when creating the dataset. **Example**: :: create_new_dataset = BigQueryCreateEmptyDatasetOperator( dataset_id='new-dataset', project_id='my-project', dataset_reference={"friendlyName": "New Dataset"} gcp_conn_id='_my_gcp_conn_', task_id='newDatasetCreator', dag=dag) """
[docs] template_fields: Sequence[str] = ( 'dataset_id', 'project_id', 'dataset_reference', 'impersonation_chain',
)
[docs] template_fields_renderers = {"dataset_reference": "json"}
[docs] ui_color = BigQueryUIColors.DATASET.value
def __init__( self, *, dataset_id: Optional[str] = None, project_id: Optional[str] = None, dataset_reference: Optional[Dict] = None, location: Optional[str] = None, gcp_conn_id: str = 'google_cloud_default', bigquery_conn_id: Optional[str] = None, delegate_to: Optional[str] = None, impersonation_chain: Optional[Union[str, Sequence[str]]] = None, exists_ok: bool = False, **kwargs, ) -> None: if bigquery_conn_id: warnings.warn( "The bigquery_conn_id parameter has been deprecated. You should pass " "the gcp_conn_id parameter.", DeprecationWarning, stacklevel=3, ) gcp_conn_id = bigquery_conn_id self.dataset_id = dataset_id self.project_id = project_id self.location = location self.gcp_conn_id = gcp_conn_id self.dataset_reference = dataset_reference if dataset_reference else {} self.delegate_to = delegate_to self.impersonation_chain = impersonation_chain self.exists_ok = exists_ok super().__init__(**kwargs)
[docs] def execute(self, context: 'Context') -> None: bq_hook = BigQueryHook( gcp_conn_id=self.gcp_conn_id, delegate_to=self.delegate_to, location=self.location, impersonation_chain=self.impersonation_chain, ) try: bq_hook.create_empty_dataset( project_id=self.project_id, dataset_id=self.dataset_id, dataset_reference=self.dataset_reference, location=self.location, exists_ok=self.exists_ok, ) except Conflict: dataset_id = self.dataset_reference.get("datasetReference", {}).get("datasetId", self.dataset_id) self.log.info('Dataset %s already exists.', dataset_id)
[docs]class BigQueryGetDatasetOperator(BaseOperator): """ This operator is used to return the dataset specified by dataset_id. .. seealso:: For more information on how to use this operator, take a look at the guide: :ref:`howto/operator:BigQueryGetDatasetOperator` :param dataset_id: The id of dataset. Don't need to provide, if datasetId in dataset_reference. :param project_id: The name of the project where we want to create the dataset. Don't need to provide, if projectId in dataset_reference. :param gcp_conn_id: (Optional) The connection ID used to connect to Google Cloud. :param delegate_to: The account to impersonate using domain-wide delegation of authority, if any. For this to work, the service account making the request must have domain-wide delegation enabled. :param impersonation_chain: Optional service account to impersonate using short-term credentials, or chained list of accounts required to get the access_token of the last account in the list, which will be impersonated in the request. If set as a string, the account must grant the originating account the Service Account Token Creator IAM role. If set as a sequence, the identities from the list must grant Service Account Token Creator IAM role to the directly preceding identity, with first account from the list granting this role to the originating account (templated). :rtype: dataset https://cloud.google.com/bigquery/docs/reference/rest/v2/datasets#resource """
[docs] template_fields: Sequence[str] = ( 'dataset_id', 'project_id', 'impersonation_chain',
)
[docs] ui_color = BigQueryUIColors.DATASET.value
def __init__( self, *, dataset_id: str, project_id: Optional[str] = None, gcp_conn_id: str = 'google_cloud_default', delegate_to: Optional[str] = None, impersonation_chain: Optional[Union[str, Sequence[str]]] = None, **kwargs, ) -> None: self.dataset_id = dataset_id self.project_id = project_id self.gcp_conn_id = gcp_conn_id self.delegate_to = delegate_to self.impersonation_chain = impersonation_chain super().__init__(**kwargs)
[docs] def execute(self, context: 'Context'): bq_hook = BigQueryHook( gcp_conn_id=self.gcp_conn_id, delegate_to=self.delegate_to, impersonation_chain=self.impersonation_chain, ) self.log.info('Start getting dataset: %s:%s', self.project_id, self.dataset_id) dataset = bq_hook.get_dataset(dataset_id=self.dataset_id, project_id=self.project_id) return dataset.to_api_repr()
[docs]class BigQueryGetDatasetTablesOperator(BaseOperator): """ This operator retrieves the list of tables in the specified dataset. .. seealso:: For more information on how to use this operator, take a look at the guide: :ref:`howto/operator:BigQueryGetDatasetTablesOperator` :param dataset_id: the dataset ID of the requested dataset. :param project_id: (Optional) the project of the requested dataset. If None, self.project_id will be used. :param max_results: (Optional) the maximum number of tables to return. :param gcp_conn_id: (Optional) The connection ID used to connect to Google Cloud. :param delegate_to: The account to impersonate using domain-wide delegation of authority, if any. For this to work, the service account making the request must have domain-wide delegation enabled. :param impersonation_chain: Optional service account to impersonate using short-term credentials, or chained list of accounts required to get the access_token of the last account in the list, which will be impersonated in the request. If set as a string, the account must grant the originating account the Service Account Token Creator IAM role. If set as a sequence, the identities from the list must grant Service Account Token Creator IAM role to the directly preceding identity, with first account from the list granting this role to the originating account (templated). """
[docs] template_fields: Sequence[str] = ( 'dataset_id', 'project_id', 'impersonation_chain',
)
[docs] ui_color = BigQueryUIColors.DATASET.value
def __init__( self, *, dataset_id: str, project_id: Optional[str] = None, max_results: Optional[int] = None, gcp_conn_id: str = 'google_cloud_default', delegate_to: Optional[str] = None, impersonation_chain: Optional[Union[str, Sequence[str]]] = None, **kwargs, ) -> None: self.dataset_id = dataset_id self.project_id = project_id self.max_results = max_results self.gcp_conn_id = gcp_conn_id self.delegate_to = delegate_to self.impersonation_chain = impersonation_chain super().__init__(**kwargs)
[docs] def execute(self, context: 'Context'): bq_hook = BigQueryHook( gcp_conn_id=self.gcp_conn_id, delegate_to=self.delegate_to, impersonation_chain=self.impersonation_chain, ) return bq_hook.get_dataset_tables( dataset_id=self.dataset_id, project_id=self.project_id, max_results=self.max_results,
)
[docs]class BigQueryPatchDatasetOperator(BaseOperator): """ This operator is used to patch dataset for your Project in BigQuery. It only replaces fields that are provided in the submitted dataset resource. This operator is deprecated. Please use :class:`airflow.providers.google.cloud.operators.bigquery.BigQueryUpdateTableOperator` :param dataset_id: The id of dataset. Don't need to provide, if datasetId in dataset_reference. :param dataset_resource: Dataset resource that will be provided with request body. https://cloud.google.com/bigquery/docs/reference/rest/v2/datasets#resource :param project_id: The name of the project where we want to create the dataset. Don't need to provide, if projectId in dataset_reference. :param gcp_conn_id: (Optional) The connection ID used to connect to Google Cloud. :param delegate_to: The account to impersonate using domain-wide delegation of authority, if any. For this to work, the service account making the request must have domain-wide delegation enabled. :param impersonation_chain: Optional service account to impersonate using short-term credentials, or chained list of accounts required to get the access_token of the last account in the list, which will be impersonated in the request. If set as a string, the account must grant the originating account the Service Account Token Creator IAM role. If set as a sequence, the identities from the list must grant Service Account Token Creator IAM role to the directly preceding identity, with first account from the list granting this role to the originating account (templated). :rtype: dataset https://cloud.google.com/bigquery/docs/reference/rest/v2/datasets#resource """
[docs] template_fields: Sequence[str] = ( 'dataset_id', 'project_id', 'impersonation_chain',
)
[docs] template_fields_renderers = {"dataset_resource": "json"}
[docs] ui_color = BigQueryUIColors.DATASET.value
def __init__( self, *, dataset_id: str, dataset_resource: dict, project_id: Optional[str] = None, gcp_conn_id: str = 'google_cloud_default', delegate_to: Optional[str] = None, impersonation_chain: Optional[Union[str, Sequence[str]]] = None, **kwargs, ) -> None: warnings.warn( "This operator is deprecated. Please use BigQueryUpdateDatasetOperator.", DeprecationWarning, stacklevel=2, ) self.dataset_id = dataset_id self.project_id = project_id self.gcp_conn_id = gcp_conn_id self.dataset_resource = dataset_resource self.delegate_to = delegate_to self.impersonation_chain = impersonation_chain super().__init__(**kwargs)
[docs] def execute(self, context: 'Context'): bq_hook = BigQueryHook( gcp_conn_id=self.gcp_conn_id, delegate_to=self.delegate_to, impersonation_chain=self.impersonation_chain, ) return bq_hook.patch_dataset( dataset_id=self.dataset_id, dataset_resource=self.dataset_resource, project_id=self.project_id,
)
[docs]class BigQueryUpdateTableOperator(BaseOperator): """ This operator is used to update table for your Project in BigQuery. Use ``fields`` to specify which fields of table to update. If a field is listed in ``fields`` and is ``None`` in table, it will be deleted. .. seealso:: For more information on how to use this operator, take a look at the guide: :ref:`howto/operator:BigQueryUpdateTableOperator` :param dataset_id: The id of dataset. Don't need to provide, if datasetId in table_reference. :param table_id: The id of table. Don't need to provide, if tableId in table_reference. :param table_resource: Dataset resource that will be provided with request body. https://cloud.google.com/bigquery/docs/reference/rest/v2/tables#resource :param fields: The fields of ``table`` to change, spelled as the Table properties (e.g. "friendly_name"). :param project_id: The name of the project where we want to create the table. Don't need to provide, if projectId in table_reference. :param gcp_conn_id: (Optional) The connection ID used to connect to Google Cloud. :param delegate_to: The account to impersonate using domain-wide delegation of authority, if any. For this to work, the service account making the request must have domain-wide delegation enabled. :param impersonation_chain: Optional service account to impersonate using short-term credentials, or chained list of accounts required to get the access_token of the last account in the list, which will be impersonated in the request. If set as a string, the account must grant the originating account the Service Account Token Creator IAM role. If set as a sequence, the identities from the list must grant Service Account Token Creator IAM role to the directly preceding identity, with first account from the list granting this role to the originating account (templated). :rtype: table https://cloud.google.com/bigquery/docs/reference/rest/v2/tables#resource """
[docs] template_fields: Sequence[str] = ( 'dataset_id', 'table_id', 'project_id', 'impersonation_chain',
)
[docs] template_fields_renderers = {"table_resource": "json"}
[docs] ui_color = BigQueryUIColors.TABLE.value
def __init__( self, *, table_resource: Dict[str, Any], fields: Optional[List[str]] = None, dataset_id: Optional[str] = None, table_id: Optional[str] = None, project_id: Optional[str] = None, gcp_conn_id: str = 'google_cloud_default', delegate_to: Optional[str] = None, impersonation_chain: Optional[Union[str, Sequence[str]]] = None, **kwargs, ) -> None: self.dataset_id = dataset_id self.table_id = table_id self.project_id = project_id self.fields = fields self.gcp_conn_id = gcp_conn_id self.table_resource = table_resource self.delegate_to = delegate_to self.impersonation_chain = impersonation_chain super().__init__(**kwargs)
[docs] def execute(self, context: 'Context'): bq_hook = BigQueryHook( gcp_conn_id=self.gcp_conn_id, delegate_to=self.delegate_to, impersonation_chain=self.impersonation_chain, ) return bq_hook.update_table( table_resource=self.table_resource, fields=self.fields, dataset_id=self.dataset_id, table_id=self.table_id, project_id=self.project_id,
)
[docs]class BigQueryUpdateDatasetOperator(BaseOperator): """ This operator is used to update dataset for your Project in BigQuery. Use ``fields`` to specify which fields of dataset to update. If a field is listed in ``fields`` and is ``None`` in dataset, it will be deleted. If no ``fields`` are provided then all fields of provided ``dataset_resource`` will be used. .. seealso:: For more information on how to use this operator, take a look at the guide: :ref:`howto/operator:BigQueryUpdateDatasetOperator` :param dataset_id: The id of dataset. Don't need to provide, if datasetId in dataset_reference. :param dataset_resource: Dataset resource that will be provided with request body. https://cloud.google.com/bigquery/docs/reference/rest/v2/datasets#resource :param fields: The properties of dataset to change (e.g. "friendly_name"). :param project_id: The name of the project where we want to create the dataset. Don't need to provide, if projectId in dataset_reference. :param gcp_conn_id: (Optional) The connection ID used to connect to Google Cloud. :param delegate_to: The account to impersonate using domain-wide delegation of authority, if any. For this to work, the service account making the request must have domain-wide delegation enabled. :param impersonation_chain: Optional service account to impersonate using short-term credentials, or chained list of accounts required to get the access_token of the last account in the list, which will be impersonated in the request. If set as a string, the account must grant the originating account the Service Account Token Creator IAM role. If set as a sequence, the identities from the list must grant Service Account Token Creator IAM role to the directly preceding identity, with first account from the list granting this role to the originating account (templated). :rtype: dataset https://cloud.google.com/bigquery/docs/reference/rest/v2/datasets#resource """
[docs] template_fields: Sequence[str] = ( 'dataset_id', 'project_id', 'impersonation_chain',
)
[docs] template_fields_renderers = {"dataset_resource": "json"}
[docs] ui_color = BigQueryUIColors.DATASET.value
def __init__( self, *, dataset_resource: Dict[str, Any], fields: Optional[List[str]] = None, dataset_id: Optional[str] = None, project_id: Optional[str] = None, gcp_conn_id: str = 'google_cloud_default', delegate_to: Optional[str] = None, impersonation_chain: Optional[Union[str, Sequence[str]]] = None, **kwargs, ) -> None: self.dataset_id = dataset_id self.project_id = project_id self.fields = fields self.gcp_conn_id = gcp_conn_id self.dataset_resource = dataset_resource self.delegate_to = delegate_to self.impersonation_chain = impersonation_chain super().__init__(**kwargs)
[docs] def execute(self, context: 'Context'): bq_hook = BigQueryHook( gcp_conn_id=self.gcp_conn_id, delegate_to=self.delegate_to, impersonation_chain=self.impersonation_chain, ) fields = self.fields or list(self.dataset_resource.keys()) dataset = bq_hook.update_dataset( dataset_resource=self.dataset_resource, project_id=self.project_id, dataset_id=self.dataset_id, fields=fields, ) return dataset.to_api_repr()
[docs]class BigQueryDeleteTableOperator(BaseOperator): """ Deletes BigQuery tables .. seealso:: For more information on how to use this operator, take a look at the guide: :ref:`howto/operator:BigQueryDeleteTableOperator` :param deletion_dataset_table: A dotted ``(<project>.|<project>:)<dataset>.<table>`` that indicates which table will be deleted. (templated) :param gcp_conn_id: (Optional) The connection ID used to connect to Google Cloud. :param bigquery_conn_id: (Deprecated) The connection ID used to connect to Google Cloud. This parameter has been deprecated. You should pass the gcp_conn_id parameter instead. :param delegate_to: The account to impersonate using domain-wide delegation of authority, if any. For this to work, the service account making the request must have domain-wide delegation enabled. :param ignore_if_missing: if True, then return success even if the requested table does not exist. :param location: The location used for the operation. :param impersonation_chain: Optional service account to impersonate using short-term credentials, or chained list of accounts required to get the access_token of the last account in the list, which will be impersonated in the request. If set as a string, the account must grant the originating account the Service Account Token Creator IAM role. If set as a sequence, the identities from the list must grant Service Account Token Creator IAM role to the directly preceding identity, with first account from the list granting this role to the originating account (templated). """
[docs] template_fields: Sequence[str] = ( 'deletion_dataset_table', 'impersonation_chain',
)
[docs] ui_color = BigQueryUIColors.TABLE.value
def __init__( self, *, deletion_dataset_table: str, gcp_conn_id: str = 'google_cloud_default', bigquery_conn_id: Optional[str] = None, delegate_to: Optional[str] = None, ignore_if_missing: bool = False, location: Optional[str] = None, impersonation_chain: Optional[Union[str, Sequence[str]]] = None, **kwargs, ) -> None: super().__init__(**kwargs) if bigquery_conn_id: warnings.warn( "The bigquery_conn_id parameter has been deprecated. You should pass " "the gcp_conn_id parameter.", DeprecationWarning, stacklevel=3, ) gcp_conn_id = bigquery_conn_id self.deletion_dataset_table = deletion_dataset_table self.gcp_conn_id = gcp_conn_id self.delegate_to = delegate_to self.ignore_if_missing = ignore_if_missing self.location = location self.impersonation_chain = impersonation_chain
[docs] def execute(self, context: 'Context') -> None: self.log.info('Deleting: %s', self.deletion_dataset_table) hook = BigQueryHook( gcp_conn_id=self.gcp_conn_id, delegate_to=self.delegate_to, location=self.location, impersonation_chain=self.impersonation_chain, ) hook.delete_table(table_id=self.deletion_dataset_table, not_found_ok=self.ignore_if_missing)
[docs]class BigQueryUpsertTableOperator(BaseOperator): """ Upsert BigQuery table .. seealso:: For more information on how to use this operator, take a look at the guide: :ref:`howto/operator:BigQueryUpsertTableOperator` :param dataset_id: A dotted ``(<project>.|<project>:)<dataset>`` that indicates which dataset will be updated. (templated) :param table_resource: a table resource. see https://cloud.google.com/bigquery/docs/reference/v2/tables#resource :param project_id: The name of the project where we want to update the dataset. Don't need to provide, if projectId in dataset_reference. :param gcp_conn_id: (Optional) The connection ID used to connect to Google Cloud. :param bigquery_conn_id: (Deprecated) The connection ID used to connect to Google Cloud. This parameter has been deprecated. You should pass the gcp_conn_id parameter instead. :param delegate_to: The account to impersonate, if any. For this to work, the service account making the request must have domain-wide delegation enabled. :param location: The location used for the operation. :param impersonation_chain: Optional service account to impersonate using short-term credentials, or chained list of accounts required to get the access_token of the last account in the list, which will be impersonated in the request. If set as a string, the account must grant the originating account the Service Account Token Creator IAM role. If set as a sequence, the identities from the list must grant Service Account Token Creator IAM role to the directly preceding identity, with first account from the list granting this role to the originating account (templated). """
[docs] template_fields: Sequence[str] = ( 'dataset_id', 'table_resource', 'impersonation_chain',
)
[docs] template_fields_renderers = {"table_resource": "json"}
[docs] ui_color = BigQueryUIColors.TABLE.value
def __init__( self, *, dataset_id: str, table_resource: dict, project_id: Optional[str] = None, gcp_conn_id: str = 'google_cloud_default', bigquery_conn_id: Optional[str] = None, delegate_to: Optional[str] = None, location: Optional[str] = None, impersonation_chain: Optional[Union[str, Sequence[str]]] = None, **kwargs, ) -> None: super().__init__(**kwargs) if bigquery_conn_id: warnings.warn( "The bigquery_conn_id parameter has been deprecated. You should pass " "the gcp_conn_id parameter.", DeprecationWarning, stacklevel=3, ) gcp_conn_id = bigquery_conn_id self.dataset_id = dataset_id self.table_resource = table_resource self.project_id = project_id self.gcp_conn_id = gcp_conn_id self.delegate_to = delegate_to self.location = location self.impersonation_chain = impersonation_chain
[docs] def execute(self, context: 'Context') -> None: self.log.info('Upserting Dataset: %s with table_resource: %s', self.dataset_id, self.table_resource) hook = BigQueryHook( bigquery_conn_id=self.gcp_conn_id, delegate_to=self.delegate_to, location=self.location, impersonation_chain=self.impersonation_chain, ) hook.run_table_upsert( dataset_id=self.dataset_id, table_resource=self.table_resource, project_id=self.project_id,
)
[docs]class BigQueryUpdateTableSchemaOperator(BaseOperator): """ Update BigQuery Table Schema Updates fields on a table schema based on contents of the supplied schema_fields_updates parameter. The supplied schema does not need to be complete, if the field already exists in the schema you only need to supply keys & values for the items you want to patch, just ensure the "name" key is set. .. seealso:: For more information on how to use this operator, take a look at the guide: :ref:`howto/operator:BigQueryUpdateTableSchemaOperator` :param schema_fields_updates: a partial schema resource. see https://cloud.google.com/bigquery/docs/reference/rest/v2/tables#TableSchema **Example**: :: schema_fields_updates=[ {"name": "emp_name", "description": "Some New Description"}, {"name": "salary", "policyTags": {'names': ['some_new_policy_tag']},}, {"name": "departments", "fields": [ {"name": "name", "description": "Some New Description"}, {"name": "type", "description": "Some New Description"} ]}, ] :param include_policy_tags: (Optional) If set to True policy tags will be included in the update request which requires special permissions even if unchanged (default False) see https://cloud.google.com/bigquery/docs/column-level-security#roles :param dataset_id: A dotted ``(<project>.|<project>:)<dataset>`` that indicates which dataset will be updated. (templated) :param table_id: The table ID of the requested table. (templated) :param project_id: The name of the project where we want to update the dataset. Don't need to provide, if projectId in dataset_reference. :param gcp_conn_id: (Optional) The connection ID used to connect to Google Cloud. :param bigquery_conn_id: (Deprecated) The connection ID used to connect to Google Cloud. This parameter has been deprecated. You should pass the gcp_conn_id parameter instead. :param delegate_to: The account to impersonate, if any. For this to work, the service account making the request must have domain-wide delegation enabled. :param location: The location used for the operation. :param impersonation_chain: Optional service account to impersonate using short-term credentials, or chained list of accounts required to get the access_token of the last account in the list, which will be impersonated in the request. If set as a string, the account must grant the originating account the Service Account Token Creator IAM role. If set as a sequence, the identities from the list must grant Service Account Token Creator IAM role to the directly preceding identity, with first account from the list granting this role to the originating account (templated). """
[docs] template_fields: Sequence[str] = ( 'schema_fields_updates', 'dataset_id', 'table_id', 'project_id', 'impersonation_chain',
)
[docs] template_fields_renderers = {"schema_fields_updates": "json"}
[docs] ui_color = BigQueryUIColors.TABLE.value
def __init__( self, *, schema_fields_updates: List[Dict[str, Any]], dataset_id: str, table_id: str, include_policy_tags: bool = False, project_id: Optional[str] = None, gcp_conn_id: str = 'google_cloud_default', delegate_to: Optional[str] = None, impersonation_chain: Optional[Union[str, Sequence[str]]] = None, **kwargs, ) -> None: self.schema_fields_updates = schema_fields_updates self.include_policy_tags = include_policy_tags self.table_id = table_id self.dataset_id = dataset_id self.project_id = project_id self.gcp_conn_id = gcp_conn_id self.delegate_to = delegate_to self.impersonation_chain = impersonation_chain super().__init__(**kwargs)
[docs] def execute(self, context: 'Context'): bq_hook = BigQueryHook( gcp_conn_id=self.gcp_conn_id, delegate_to=self.delegate_to, impersonation_chain=self.impersonation_chain, ) return bq_hook.update_table_schema( schema_fields_updates=self.schema_fields_updates, include_policy_tags=self.include_policy_tags, dataset_id=self.dataset_id, table_id=self.table_id, project_id=self.project_id,
)
[docs]class BigQueryInsertJobOperator(BaseOperator): """ Executes a BigQuery job. Waits for the job to complete and returns job id. This operator work in the following way: - it calculates a unique hash of the job using job's configuration or uuid if ``force_rerun`` is True - creates ``job_id`` in form of ``[provided_job_id | airflow_{dag_id}_{task_id}_{exec_date}]_{uniqueness_suffix}`` - submits a BigQuery job using the ``job_id`` - if job with given id already exists then it tries to reattach to the job if its not done and its state is in ``reattach_states``. If the job is done the operator will raise ``AirflowException``. Using ``force_rerun`` will submit a new job every time without attaching to already existing ones. For job definition see here: https://cloud.google.com/bigquery/docs/reference/v2/jobs .. seealso:: For more information on how to use this operator, take a look at the guide: :ref:`howto/operator:BigQueryInsertJobOperator` :param configuration: The configuration parameter maps directly to BigQuery's configuration field in the job object. For more details see https://cloud.google.com/bigquery/docs/reference/v2/jobs :param job_id: The ID of the job. It will be suffixed with hash of job configuration unless ``force_rerun`` is True. The ID must contain only letters (a-z, A-Z), numbers (0-9), underscores (_), or dashes (-). The maximum length is 1,024 characters. If not provided then uuid will be generated. :param force_rerun: If True then operator will use hash of uuid as job id suffix :param reattach_states: Set of BigQuery job's states in case of which we should reattach to the job. Should be other than final states. :param project_id: Google Cloud Project where the job is running :param location: location the job is running :param gcp_conn_id: The connection ID used to connect to Google Cloud. :param delegate_to: The account to impersonate using domain-wide delegation of authority, if any. For this to work, the service account making the request must have domain-wide delegation enabled. :param impersonation_chain: Optional service account to impersonate using short-term credentials, or chained list of accounts required to get the access_token of the last account in the list, which will be impersonated in the request. If set as a string, the account must grant the originating account the Service Account Token Creator IAM role. If set as a sequence, the identities from the list must grant Service Account Token Creator IAM role to the directly preceding identity, with first account from the list granting this role to the originating account (templated). :param cancel_on_kill: Flag which indicates whether cancel the hook's job or not, when on_kill is called """
[docs] template_fields: Sequence[str] = ( "configuration", "job_id", "impersonation_chain",
)
[docs] template_ext: Sequence[str] = (".json",)
[docs] template_fields_renderers = {"configuration": "json", "configuration.query.query": "sql"}
[docs] ui_color = BigQueryUIColors.QUERY.value
def __init__( self, configuration: Dict[str, Any], project_id: Optional[str] = None, location: Optional[str] = None, job_id: Optional[str] = None, force_rerun: bool = True, reattach_states: Optional[Set[str]] = None, gcp_conn_id: str = 'google_cloud_default', delegate_to: Optional[str] = None, impersonation_chain: Optional[Union[str, Sequence[str]]] = None, cancel_on_kill: bool = True, **kwargs, ) -> None: super().__init__(**kwargs) self.configuration = configuration self.location = location self.job_id = job_id self.project_id = project_id self.gcp_conn_id = gcp_conn_id self.delegate_to = delegate_to self.force_rerun = force_rerun self.reattach_states: Set[str] = reattach_states or set() self.impersonation_chain = impersonation_chain self.cancel_on_kill = cancel_on_kill self.hook: Optional[BigQueryHook] = None
[docs] def prepare_template(self) -> None: # If .json is passed then we have to read the file if isinstance(self.configuration, str) and self.configuration.endswith('.json'): with open(self.configuration) as file: self.configuration = json.loads(file.read())
def _submit_job( self, hook: BigQueryHook, job_id: str, ) -> BigQueryJob: # Submit a new job and wait for it to complete and get the result. return hook.insert_job( configuration=self.configuration, project_id=self.project_id, location=self.location, job_id=job_id, ) @staticmethod def _handle_job_error(job: BigQueryJob) -> None: if job.error_result: raise AirflowException(f"BigQuery job {job.job_id} failed: {job.error_result}") def _job_id(self, context): if self.force_rerun: hash_base = str(uuid.uuid4()) else: hash_base = json.dumps(self.configuration, sort_keys=True) uniqueness_suffix = hashlib.md5(hash_base.encode()).hexdigest() if self.job_id: return f"{self.job_id}_{uniqueness_suffix}" exec_date = context['execution_date'].isoformat() job_id = f"airflow_{self.dag_id}_{self.task_id}_{exec_date}_{uniqueness_suffix}" return re.sub(r"[:\-+.]", "_", job_id)
[docs] def execute(self, context: Any): hook = BigQueryHook( gcp_conn_id=self.gcp_conn_id, delegate_to=self.delegate_to, impersonation_chain=self.impersonation_chain, ) self.hook = hook job_id = self._job_id(context) try: job = self._submit_job(hook, job_id) self._handle_job_error(job) except Conflict: # If the job already exists retrieve it job = hook.get_job( project_id=self.project_id, location=self.location, job_id=job_id, ) if job.state in self.reattach_states: # We are reattaching to a job job.result() self._handle_job_error(job) else: # Same job configuration so we need force_rerun raise AirflowException( f"Job with id: {job_id} already exists and is in {job.state} state. If you " f"want to force rerun it consider setting `force_rerun=True`." f"Or, if you want to reattach in this scenario add {job.state} to `reattach_states`" ) self.job_id = job.job_id return job.job_id
[docs] def on_kill(self) -> None: if self.job_id and self.cancel_on_kill: self.hook.cancel_job( # type: ignore[union-attr] job_id=self.job_id, project_id=self.project_id, location=self.location
)

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