job.py

# Copyright 2015 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

"""Define API Jobs."""

from __future__ import division

import concurrent.futures
import copy
import re
import threading
import time

import requests
import six
from six.moves import http_client

import google.api_core.future.polling
from google.cloud import exceptions
from google.cloud.exceptions import NotFound
from google.cloud.bigquery.dataset import Dataset
from google.cloud.bigquery.dataset import DatasetListItem
from google.cloud.bigquery.dataset import DatasetReference
from google.cloud.bigquery.encryption_configuration import EncryptionConfiguration
from google.cloud.bigquery.external_config import ExternalConfig
from google.cloud.bigquery.external_config import HivePartitioningOptions
from google.cloud.bigquery import _helpers
from google.cloud.bigquery.model import ModelReference
from google.cloud.bigquery.query import _query_param_from_api_repr
from google.cloud.bigquery.query import ArrayQueryParameter
from google.cloud.bigquery.query import ScalarQueryParameter
from google.cloud.bigquery.query import StructQueryParameter
from google.cloud.bigquery.query import UDFResource
from google.cloud.bigquery.retry import DEFAULT_RETRY
from google.cloud.bigquery.routine import RoutineReference
from google.cloud.bigquery.schema import SchemaField
from google.cloud.bigquery.schema import _to_schema_fields
from google.cloud.bigquery.table import _EmptyRowIterator
from google.cloud.bigquery.table import RangePartitioning
from google.cloud.bigquery.table import _table_arg_to_table_ref
from google.cloud.bigquery.table import Table
from google.cloud.bigquery.table import TableListItem
from google.cloud.bigquery.table import TableReference
from google.cloud.bigquery.table import TimePartitioning
from google.cloud.bigquery._tqdm_helpers import _get_progress_bar

_DONE_STATE = "DONE"
_STOPPED_REASON = "stopped"
_TIMEOUT_BUFFER_SECS = 0.1
_CONTAINS_ORDER_BY = re.compile(r"ORDER\s+BY", re.IGNORECASE)

_ERROR_REASON_TO_EXCEPTION = {
    "accessDenied": http_client.FORBIDDEN,
    "backendError": http_client.INTERNAL_SERVER_ERROR,
    "billingNotEnabled": http_client.FORBIDDEN,
    "billingTierLimitExceeded": http_client.BAD_REQUEST,
    "blocked": http_client.FORBIDDEN,
    "duplicate": http_client.CONFLICT,
    "internalError": http_client.INTERNAL_SERVER_ERROR,
    "invalid": http_client.BAD_REQUEST,
    "invalidQuery": http_client.BAD_REQUEST,
    "notFound": http_client.NOT_FOUND,
    "notImplemented": http_client.NOT_IMPLEMENTED,
    "quotaExceeded": http_client.FORBIDDEN,
    "rateLimitExceeded": http_client.FORBIDDEN,
    "resourceInUse": http_client.BAD_REQUEST,
    "resourcesExceeded": http_client.BAD_REQUEST,
    "responseTooLarge": http_client.FORBIDDEN,
    "stopped": http_client.OK,
    "tableUnavailable": http_client.BAD_REQUEST,
}


def _error_result_to_exception(error_result):
    """Maps BigQuery error reasons to an exception.

    The reasons and their matching HTTP status codes are documented on
    the `troubleshooting errors`_ page.

    .. _troubleshooting errors: https://cloud.google.com/bigquery\
        /troubleshooting-errors

    Args:
        error_result (Mapping[str, str]): The error result from BigQuery.

    Returns:
        google.cloud.exceptions.GoogleCloudError: The mapped exception.
    """
    reason = error_result.get("reason")
    status_code = _ERROR_REASON_TO_EXCEPTION.get(
        reason, http_client.INTERNAL_SERVER_ERROR
    )
    return exceptions.from_http_status(
        status_code, error_result.get("message", ""), errors=[error_result]
    )


def _contains_order_by(query):
    """Do we need to preserve the order of the query results?

    This function has known false positives, such as with ordered window
    functions:

    .. code-block:: sql

       SELECT SUM(x) OVER (
           window_name
           PARTITION BY...
           ORDER BY...
           window_frame_clause)
       FROM ...

    This false positive failure case means the behavior will be correct, but
    downloading results with the BigQuery Storage API may be slower than it
    otherwise would. This is preferable to the false negative case, where
    results are expected to be in order but are not (due to parallel reads).
    """
    return query and _CONTAINS_ORDER_BY.search(query)


class Compression(object):
    """The compression type to use for exported files. The default value is
    :attr:`NONE`.

    :attr:`DEFLATE` and :attr:`SNAPPY` are
    only supported for Avro.
    """

    GZIP = "GZIP"
    """Specifies GZIP format."""

    DEFLATE = "DEFLATE"
    """Specifies DEFLATE format."""

    SNAPPY = "SNAPPY"
    """Specifies SNAPPY format."""

    NONE = "NONE"
    """Specifies no compression."""


class CreateDisposition(object):
    """Specifies whether the job is allowed to create new tables. The default
    value is :attr:`CREATE_IF_NEEDED`.

    Creation, truncation and append actions occur as one atomic update
    upon job completion.
    """

    CREATE_IF_NEEDED = "CREATE_IF_NEEDED"
    """If the table does not exist, BigQuery creates the table."""

    CREATE_NEVER = "CREATE_NEVER"
    """The table must already exist. If it does not, a 'notFound' error is
    returned in the job result."""


class DestinationFormat(object):
    """The exported file format. The default value is :attr:`CSV`.

    Tables with nested or repeated fields cannot be exported as CSV.
    """

    CSV = "CSV"
    """Specifies CSV format."""

    NEWLINE_DELIMITED_JSON = "NEWLINE_DELIMITED_JSON"
    """Specifies newline delimited JSON format."""

    AVRO = "AVRO"
    """Specifies Avro format."""


class Encoding(object):
    """The character encoding of the data. The default is :attr:`UTF_8`.

    BigQuery decodes the data after the raw, binary data has been
    split using the values of the quote and fieldDelimiter properties.
    """

    UTF_8 = "UTF-8"
    """Specifies UTF-8 encoding."""

    ISO_8859_1 = "ISO-8859-1"
    """Specifies ISO-8859-1 encoding."""


class QueryPriority(object):
    """Specifies a priority for the query. The default value is
    :attr:`INTERACTIVE`.
    """

    INTERACTIVE = "INTERACTIVE"
    """Specifies interactive priority."""

    BATCH = "BATCH"
    """Specifies batch priority."""


class SourceFormat(object):
    """The format of the data files. The default value is :attr:`CSV`.

    Note that the set of allowed values for loading data is different
    than the set used for external data sources (see
    :class:`~google.cloud.bigquery.external_config.ExternalSourceFormat`).
    """

    CSV = "CSV"
    """Specifies CSV format."""

    DATASTORE_BACKUP = "DATASTORE_BACKUP"
    """Specifies datastore backup format"""

    NEWLINE_DELIMITED_JSON = "NEWLINE_DELIMITED_JSON"
    """Specifies newline delimited JSON format."""

    AVRO = "AVRO"
    """Specifies Avro format."""

    PARQUET = "PARQUET"
    """Specifies Parquet format."""

    ORC = "ORC"
    """Specifies Orc format."""


class WriteDisposition(object):
    """Specifies the action that occurs if destination table already exists.

    The default value is :attr:`WRITE_APPEND`.

    Each action is atomic and only occurs if BigQuery is able to complete
    the job successfully. Creation, truncation and append actions occur as one
    atomic update upon job completion.
    """

    WRITE_APPEND = "WRITE_APPEND"
    """If the table already exists, BigQuery appends the data to the table."""

    WRITE_TRUNCATE = "WRITE_TRUNCATE"
    """If the table already exists, BigQuery overwrites the table data."""

    WRITE_EMPTY = "WRITE_EMPTY"
    """If the table already exists and contains data, a 'duplicate' error is
    returned in the job result."""


class SchemaUpdateOption(object):
    """Specifies an update to the destination table schema as a side effect of
    a load job.
    """

    ALLOW_FIELD_ADDITION = "ALLOW_FIELD_ADDITION"
    """Allow adding a nullable field to the schema."""

    ALLOW_FIELD_RELAXATION = "ALLOW_FIELD_RELAXATION"
    """Allow relaxing a required field in the original schema to nullable."""


class _JobReference(object):
    """A reference to a job.

    Args:
        job_id (str): ID of the job to run.
        project (str): ID of the project where the job runs.
        location (str): Location of where the job runs.
    """

    def __init__(self, job_id, project, location):
        self._properties = {"jobId": job_id, "projectId": project}
        # The location field must not be populated if it is None.
        if location:
            self._properties["location"] = location

    @property
    def job_id(self):
        """str: ID of the job."""
        return self._properties.get("jobId")

    @property
    def project(self):
        """str: ID of the project where the job runs."""
        return self._properties.get("projectId")

    @property
    def location(self):
        """str: Location where the job runs."""
        return self._properties.get("location")

    def _to_api_repr(self):
        """Returns the API resource representation of the job reference."""
        return copy.deepcopy(self._properties)

    @classmethod
    def _from_api_repr(cls, resource):
        """Returns a job reference for an API resource representation."""
        job_id = resource.get("jobId")
        project = resource.get("projectId")
        location = resource.get("location")
        job_ref = cls(job_id, project, location)
        return job_ref


class _AsyncJob(google.api_core.future.polling.PollingFuture):
    """Base class for asynchronous jobs.

    Args:
        job_id (Union[str, _JobReference]):
            Job's ID in the project associated with the client or a
            fully-qualified job reference.
        client (google.cloud.bigquery.client.Client):
            Client which holds credentials and project configuration.
    """

    def __init__(self, job_id, client):
        super(_AsyncJob, self).__init__()

        # The job reference can be either a plain job ID or the full resource.
        # Populate the properties dictionary consistently depending on what has
        # been passed in.
        job_ref = job_id
        if not isinstance(job_id, _JobReference):
            job_ref = _JobReference(job_id, client.project, None)
        self._properties = {"jobReference": job_ref._to_api_repr()}

        self._client = client
        self._result_set = False
        self._completion_lock = threading.Lock()

    @property
    def job_id(self):
        """str: ID of the job."""
        return _helpers._get_sub_prop(self._properties, ["jobReference", "jobId"])

    @property
    def parent_job_id(self):
        """Return the ID of the parent job.

        See:
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobStatistics.FIELDS.parent_job_id

        Returns:
            Optional[str]: parent job id.
        """
        return _helpers._get_sub_prop(self._properties, ["statistics", "parentJobId"])

    @property
    def script_statistics(self):
        resource = _helpers._get_sub_prop(
            self._properties, ["statistics", "scriptStatistics"]
        )
        if resource is None:
            return None
        return ScriptStatistics(resource)

    @property
    def num_child_jobs(self):
        """The number of child jobs executed.

        See:
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobStatistics.FIELDS.num_child_jobs

        Returns:
            int
        """
        count = _helpers._get_sub_prop(self._properties, ["statistics", "numChildJobs"])
        return int(count) if count is not None else 0

    @property
    def project(self):
        """Project bound to the job.

        Returns:
            str: the project (derived from the client).
        """
        return _helpers._get_sub_prop(self._properties, ["jobReference", "projectId"])

    @property
    def location(self):
        """str: Location where the job runs."""
        return _helpers._get_sub_prop(self._properties, ["jobReference", "location"])

    def _require_client(self, client):
        """Check client or verify over-ride.

        Args:
            client (Optional[google.cloud.bigquery.client.Client]):
                the client to use.  If not passed, falls back to the
                ``client`` stored on the current dataset.

        Returns:
            google.cloud.bigquery.client.Client:
                The client passed in or the currently bound client.
        """
        if client is None:
            client = self._client
        return client

    @property
    def job_type(self):
        """Type of job.

        Returns:
            str: one of 'load', 'copy', 'extract', 'query'.
        """
        return self._JOB_TYPE

    @property
    def path(self):
        """URL path for the job's APIs.

        Returns:
            str: the path based on project and job ID.
        """
        return "/projects/%s/jobs/%s" % (self.project, self.job_id)

    @property
    def labels(self):
        """Dict[str, str]: Labels for the job."""
        return self._properties.setdefault("labels", {})

    @property
    def etag(self):
        """ETag for the job resource.

        Returns:
            Optional[str]: the ETag (None until set from the server).
        """
        return self._properties.get("etag")

    @property
    def self_link(self):
        """URL for the job resource.

        Returns:
            Optional[str]: the URL (None until set from the server).
        """
        return self._properties.get("selfLink")

    @property
    def user_email(self):
        """E-mail address of user who submitted the job.

        Returns:
            Optional[str]: the URL (None until set from the server).
        """
        return self._properties.get("user_email")

    @property
    def created(self):
        """Datetime at which the job was created.

        Returns:
            Optional[datetime.datetime]:
                the creation time (None until set from the server).
        """
        millis = _helpers._get_sub_prop(
            self._properties, ["statistics", "creationTime"]
        )
        if millis is not None:
            return _helpers._datetime_from_microseconds(millis * 1000.0)

    @property
    def started(self):
        """Datetime at which the job was started.

        Returns:
            Optional[datetime.datetime]:
                the start time (None until set from the server).
        """
        millis = _helpers._get_sub_prop(self._properties, ["statistics", "startTime"])
        if millis is not None:
            return _helpers._datetime_from_microseconds(millis * 1000.0)

    @property
    def ended(self):
        """Datetime at which the job finished.

        Returns:
            Optional[datetime.datetime]:
                the end time (None until set from the server).
        """
        millis = _helpers._get_sub_prop(self._properties, ["statistics", "endTime"])
        if millis is not None:
            return _helpers._datetime_from_microseconds(millis * 1000.0)

    def _job_statistics(self):
        """Helper for job-type specific statistics-based properties."""
        statistics = self._properties.get("statistics", {})
        return statistics.get(self._JOB_TYPE, {})

    @property
    def error_result(self):
        """Error information about the job as a whole.

        Returns:
            Optional[Mapping]: the error information (None until set from the server).
        """
        status = self._properties.get("status")
        if status is not None:
            return status.get("errorResult")

    @property
    def errors(self):
        """Information about individual errors generated by the job.

        Returns:
            Optional[List[Mapping]]:
                the error information (None until set from the server).
        """
        status = self._properties.get("status")
        if status is not None:
            return status.get("errors")

    @property
    def state(self):
        """Status of the job.

        Returns:
            Optional[str]:
                the state (None until set from the server).
        """
        status = self._properties.get("status", {})
        return status.get("state")

    def _set_properties(self, api_response):
        """Update properties from resource in body of ``api_response``

        Args:
            api_response (Dict): response returned from an API call.
        """
        cleaned = api_response.copy()

        statistics = cleaned.get("statistics", {})
        if "creationTime" in statistics:
            statistics["creationTime"] = float(statistics["creationTime"])
        if "startTime" in statistics:
            statistics["startTime"] = float(statistics["startTime"])
        if "endTime" in statistics:
            statistics["endTime"] = float(statistics["endTime"])

        # Save configuration to keep reference same in self._configuration.
        cleaned_config = cleaned.pop("configuration", {})
        configuration = self._properties.pop("configuration", {})
        self._properties.clear()
        self._properties.update(cleaned)
        self._properties["configuration"] = configuration
        self._properties["configuration"].update(cleaned_config)

        # For Future interface
        self._set_future_result()

    @classmethod
    def _check_resource_config(cls, resource):
        """Helper for :meth:`from_api_repr`

        Args:
            resource (Dict): resource for the job.

        Raises:
            KeyError:
                If the resource has no identifier, or
                is missing the appropriate configuration.
        """
        if "jobReference" not in resource or "jobId" not in resource["jobReference"]:
            raise KeyError(
                "Resource lacks required identity information: "
                '["jobReference"]["jobId"]'
            )
        if (
            "configuration" not in resource
            or cls._JOB_TYPE not in resource["configuration"]
        ):
            raise KeyError(
                "Resource lacks required configuration: "
                '["configuration"]["%s"]' % cls._JOB_TYPE
            )

    def to_api_repr(self):
        """Generate a resource for the job."""
        return copy.deepcopy(self._properties)

    _build_resource = to_api_repr  # backward-compatibility alias

    def _begin(self, client=None, retry=DEFAULT_RETRY, timeout=None):
        """API call:  begin the job via a POST request

        See
        https://cloud.google.com/bigquery/docs/reference/rest/v2/jobs/insert

        Args:
            client (Optional[google.cloud.bigquery.client.Client]):
                The client to use. If not passed, falls back to the ``client``
                associated with the job object or``NoneType``
            retry (Optional[google.api_core.retry.Retry]):
                How to retry the RPC.
            timeout (Optional[float]):
                The number of seconds to wait for the underlying HTTP transport
                before using ``retry``.

        Raises:
            ValueError:
                If the job has already begun.
        """
        if self.state is not None:
            raise ValueError("Job already begun.")

        client = self._require_client(client)
        path = "/projects/%s/jobs" % (self.project,)

        # jobs.insert is idempotent because we ensure that every new
        # job has an ID.
        span_attributes = {"path": path}
        api_response = client._call_api(
            retry,
            span_name="BigQuery.job.begin",
            span_attributes=span_attributes,
            job_ref=self,
            method="POST",
            path=path,
            data=self.to_api_repr(),
            timeout=timeout,
        )
        self._set_properties(api_response)

    def exists(self, client=None, retry=DEFAULT_RETRY, timeout=None):
        """API call:  test for the existence of the job via a GET request

        See
        https://cloud.google.com/bigquery/docs/reference/rest/v2/jobs/get

        Args:
            client (Optional[google.cloud.bigquery.client.Client]):
                the client to use.  If not passed, falls back to the
                ``client`` stored on the current dataset.

            retry (Optional[google.api_core.retry.Retry]): How to retry the RPC.
            timeout (Optional[float]):
                The number of seconds to wait for the underlying HTTP transport
                before using ``retry``.

        Returns:
            bool: Boolean indicating existence of the job.
        """
        client = self._require_client(client)

        extra_params = {"fields": "id"}
        if self.location:
            extra_params["location"] = self.location

        try:
            span_attributes = {"path": self.path}

            client._call_api(
                retry,
                span_name="BigQuery.job.exists",
                span_attributes=span_attributes,
                job_ref=self,
                method="GET",
                path=self.path,
                query_params=extra_params,
                timeout=timeout,
            )
        except NotFound:
            return False
        else:
            return True

    def reload(self, client=None, retry=DEFAULT_RETRY, timeout=None):
        """API call:  refresh job properties via a GET request.

        See
        https://cloud.google.com/bigquery/docs/reference/rest/v2/jobs/get

        Args:
            client (Optional[google.cloud.bigquery.client.Client]):
                the client to use.  If not passed, falls back to the
                ``client`` stored on the current dataset.

            retry (Optional[google.api_core.retry.Retry]): How to retry the RPC.
            timeout (Optional[float]):
                The number of seconds to wait for the underlying HTTP transport
                before using ``retry``.
        """
        client = self._require_client(client)

        extra_params = {}
        if self.location:
            extra_params["location"] = self.location
        span_attributes = {"path": self.path}

        api_response = client._call_api(
            retry,
            span_name="BigQuery.job.reload",
            span_attributes=span_attributes,
            job_ref=self,
            method="GET",
            path=self.path,
            query_params=extra_params,
            timeout=timeout,
        )
        self._set_properties(api_response)

    def cancel(self, client=None, retry=DEFAULT_RETRY, timeout=None):
        """API call:  cancel job via a POST request

        See
        https://cloud.google.com/bigquery/docs/reference/rest/v2/jobs/cancel

        Args:
            client (Optional[google.cloud.bigquery.client.Client]):
                the client to use.  If not passed, falls back to the
                ``client`` stored on the current dataset.
            retry (Optional[google.api_core.retry.Retry]): How to retry the RPC.
            timeout (Optional[float]):
                The number of seconds to wait for the underlying HTTP transport
                before using ``retry``

        Returns:
            bool: Boolean indicating that the cancel request was sent.
        """
        client = self._require_client(client)

        extra_params = {}
        if self.location:
            extra_params["location"] = self.location

        path = "{}/cancel".format(self.path)
        span_attributes = {"path": path}

        api_response = client._call_api(
            retry,
            span_name="BigQuery.job.cancel",
            span_attributes=span_attributes,
            job_ref=self,
            method="POST",
            path=path,
            query_params=extra_params,
            timeout=timeout,
        )
        self._set_properties(api_response["job"])
        # The Future interface requires that we return True if the *attempt*
        # to cancel was successful.
        return True

    # The following methods implement the PollingFuture interface. Note that
    # the methods above are from the pre-Future interface and are left for
    # compatibility. The only "overloaded" method is :meth:`cancel`, which
    # satisfies both interfaces.

    def _set_future_result(self):
        """Set the result or exception from the job if it is complete."""
        # This must be done in a lock to prevent the polling thread
        # and main thread from both executing the completion logic
        # at the same time.
        with self._completion_lock:
            # If the operation isn't complete or if the result has already been
            # set, do not call set_result/set_exception again.
            # Note: self._result_set is set to True in set_result and
            # set_exception, in case those methods are invoked directly.
            if not self.done(reload=False) or self._result_set:
                return

            if self.error_result is not None:
                exception = _error_result_to_exception(self.error_result)
                self.set_exception(exception)
            else:
                self.set_result(self)

    def done(self, retry=DEFAULT_RETRY, timeout=None, reload=True):
        """Checks if the job is complete.

        Args:
            retry (Optional[google.api_core.retry.Retry]): How to retry the RPC.
            timeout (Optional[float]):
                The number of seconds to wait for the underlying HTTP transport
                before using ``retry``.
            reload (Optional[bool]):
                If ``True``, make an API call to refresh the job state of
                unfinished jobs before checking. Default ``True``.

        Returns:
            bool: True if the job is complete, False otherwise.
        """
        # Do not refresh is the state is already done, as the job will not
        # change once complete.
        if self.state != _DONE_STATE and reload:
            self.reload(retry=retry, timeout=timeout)
        return self.state == _DONE_STATE

    def result(self, retry=DEFAULT_RETRY, timeout=None):
        """Start the job and wait for it to complete and get the result.

        Args:
            retry (Optional[google.api_core.retry.Retry]): How to retry the RPC.
            timeout (Optional[float]):
                The number of seconds to wait for the underlying HTTP transport
                before using ``retry``.
                If multiple requests are made under the hood, ``timeout``
                applies to each individual request.

        Returns:
            _AsyncJob: This instance.

        Raises:
            google.cloud.exceptions.GoogleCloudError:
                if the job failed.
            concurrent.futures.TimeoutError:
                if the job did not complete in the given timeout.
        """
        if self.state is None:
            self._begin(retry=retry, timeout=timeout)
        # TODO: modify PollingFuture so it can pass a retry argument to done().
        return super(_AsyncJob, self).result(timeout=timeout)

    def cancelled(self):
        """Check if the job has been cancelled.

        This always returns False. It's not possible to check if a job was
        cancelled in the API. This method is here to satisfy the interface
        for :class:`google.api_core.future.Future`.

        Returns:
            bool: False
        """
        return (
            self.error_result is not None
            and self.error_result.get("reason") == _STOPPED_REASON
        )


class _JobConfig(object):
    """Abstract base class for job configuration objects.

    Args:
        job_type (str): The key to use for the job configuration.
    """

    def __init__(self, job_type, **kwargs):
        self._job_type = job_type
        self._properties = {job_type: {}}
        for prop, val in kwargs.items():
            setattr(self, prop, val)

    @property
    def labels(self):
        """Dict[str, str]: Labels for the job.

        This method always returns a dict. To change a job's labels,
        modify the dict, then call ``Client.update_job``. To delete a
        label, set its value to :data:`None` before updating.

        Raises:
            ValueError: If ``value`` type is invalid.
        """
        return self._properties.setdefault("labels", {})

    @labels.setter
    def labels(self, value):
        if not isinstance(value, dict):
            raise ValueError("Pass a dict")
        self._properties["labels"] = value

    def _get_sub_prop(self, key, default=None):
        """Get a value in the ``self._properties[self._job_type]`` dictionary.

        Most job properties are inside the dictionary related to the job type
        (e.g. 'copy', 'extract', 'load', 'query'). Use this method to access
        those properties::

            self._get_sub_prop('destinationTable')

        This is equivalent to using the ``_helpers._get_sub_prop`` function::

            _helpers._get_sub_prop(
                self._properties, ['query', 'destinationTable'])

        Args:
            key (str):
                Key for the value to get in the
                ``self._properties[self._job_type]`` dictionary.
            default (Optional[object]):
                Default value to return if the key is not found.
                Defaults to :data:`None`.

        Returns:
            object: The value if present or the default.
        """
        return _helpers._get_sub_prop(
            self._properties, [self._job_type, key], default=default
        )

    def _set_sub_prop(self, key, value):
        """Set a value in the ``self._properties[self._job_type]`` dictionary.

        Most job properties are inside the dictionary related to the job type
        (e.g. 'copy', 'extract', 'load', 'query'). Use this method to set
        those properties::

            self._set_sub_prop('useLegacySql', False)

        This is equivalent to using the ``_helper._set_sub_prop`` function::

            _helper._set_sub_prop(
                self._properties, ['query', 'useLegacySql'], False)

        Args:
            key (str):
                Key to set in the ``self._properties[self._job_type]``
                dictionary.
            value (object): Value to set.
        """
        _helpers._set_sub_prop(self._properties, [self._job_type, key], value)

    def _del_sub_prop(self, key):
        """Remove ``key`` from the ``self._properties[self._job_type]`` dict.

        Most job properties are inside the dictionary related to the job type
        (e.g. 'copy', 'extract', 'load', 'query'). Use this method to clear
        those properties::

            self._del_sub_prop('useLegacySql')

        This is equivalent to using the ``_helper._del_sub_prop`` function::

            _helper._del_sub_prop(
                self._properties, ['query', 'useLegacySql'])

        Args:
            key (str):
                Key to remove in the ``self._properties[self._job_type]``
                dictionary.
        """
        _helpers._del_sub_prop(self._properties, [self._job_type, key])

    def to_api_repr(self):
        """Build an API representation of the job config.

        Returns:
            Dict: A dictionary in the format used by the BigQuery API.
        """
        return copy.deepcopy(self._properties)

    def _fill_from_default(self, default_job_config):
        """Merge this job config with a default job config.

        The keys in this object take precedence over the keys in the default
        config. The merge is done at the top-level as well as for keys one
        level below the job type.

        Args:
            default_job_config (google.cloud.bigquery.job._JobConfig):
                The default job config that will be used to fill in self.

        Returns:
            google.cloud.bigquery.job._JobConfig: A new (merged) job config.
        """
        if self._job_type != default_job_config._job_type:
            raise TypeError(
                "attempted to merge two incompatible job types: "
                + repr(self._job_type)
                + ", "
                + repr(default_job_config._job_type)
            )

        new_job_config = self.__class__()

        default_job_properties = copy.deepcopy(default_job_config._properties)
        for key in self._properties:
            if key != self._job_type:
                default_job_properties[key] = self._properties[key]

        default_job_properties[self._job_type].update(self._properties[self._job_type])
        new_job_config._properties = default_job_properties

        return new_job_config

    @classmethod
    def from_api_repr(cls, resource):
        """Factory: construct a job configuration given its API representation

        Args:
            resource (Dict):
                A job configuration in the same representation as is returned
                from the API.

        Returns:
            google.cloud.bigquery.job._JobConfig: Configuration parsed from ``resource``.
        """
        job_config = cls()
        job_config._properties = resource
        return job_config


class LoadJobConfig(_JobConfig):
    """Configuration options for load jobs.

    All properties in this class are optional. Values which are :data:`None` ->
    server defaults. Set properties on the constructed configuration by using
    the property name as the name of a keyword argument.
    """

    def __init__(self, **kwargs):
        super(LoadJobConfig, self).__init__("load", **kwargs)

    @property
    def allow_jagged_rows(self):
        """Optional[bool]: Allow missing trailing optional columns (CSV only).

        See:
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationLoad.FIELDS.allow_jagged_rows
        """
        return self._get_sub_prop("allowJaggedRows")

    @allow_jagged_rows.setter
    def allow_jagged_rows(self, value):
        self._set_sub_prop("allowJaggedRows", value)

    @property
    def allow_quoted_newlines(self):
        """Optional[bool]: Allow quoted data containing newline characters (CSV only).

        See:
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationLoad.FIELDS.allow_quoted_newlines
        """
        return self._get_sub_prop("allowQuotedNewlines")

    @allow_quoted_newlines.setter
    def allow_quoted_newlines(self, value):
        self._set_sub_prop("allowQuotedNewlines", value)

    @property
    def autodetect(self):
        """Optional[bool]: Automatically infer the schema from a sample of the data.

        See:
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationLoad.FIELDS.autodetect
        """
        return self._get_sub_prop("autodetect")

    @autodetect.setter
    def autodetect(self, value):
        self._set_sub_prop("autodetect", value)

    @property
    def clustering_fields(self):
        """Optional[List[str]]: Fields defining clustering for the table

        (Defaults to :data:`None`).

        Clustering fields are immutable after table creation.

        .. note::

           BigQuery supports clustering for both partitioned and
           non-partitioned tables.
        """
        prop = self._get_sub_prop("clustering")
        if prop is not None:
            return list(prop.get("fields", ()))

    @clustering_fields.setter
    def clustering_fields(self, value):
        """Optional[List[str]]: Fields defining clustering for the table

        (Defaults to :data:`None`).
        """
        if value is not None:
            self._set_sub_prop("clustering", {"fields": value})
        else:
            self._del_sub_prop("clustering")

    @property
    def create_disposition(self):
        """Optional[google.cloud.bigquery.job.CreateDisposition]: Specifies behavior
        for creating tables.

        See:
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationLoad.FIELDS.create_disposition
        """
        return self._get_sub_prop("createDisposition")

    @create_disposition.setter
    def create_disposition(self, value):
        self._set_sub_prop("createDisposition", value)

    @property
    def destination_encryption_configuration(self):
        """Optional[google.cloud.bigquery.encryption_configuration.EncryptionConfiguration]: Custom
        encryption configuration for the destination table.

        Custom encryption configuration (e.g., Cloud KMS keys) or :data:`None`
        if using default encryption.

        See:
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationLoad.FIELDS.destination_encryption_configuration
        """
        prop = self._get_sub_prop("destinationEncryptionConfiguration")
        if prop is not None:
            prop = EncryptionConfiguration.from_api_repr(prop)
        return prop

    @destination_encryption_configuration.setter
    def destination_encryption_configuration(self, value):
        api_repr = value
        if value is not None:
            api_repr = value.to_api_repr()
            self._set_sub_prop("destinationEncryptionConfiguration", api_repr)
        else:
            self._del_sub_prop("destinationEncryptionConfiguration")

    @property
    def destination_table_description(self):
        """Optional[str]: Name given to destination table.

        See:
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#DestinationTableProperties.FIELDS.description
        """
        prop = self._get_sub_prop("destinationTableProperties")
        if prop is not None:
            return prop["description"]

    @destination_table_description.setter
    def destination_table_description(self, value):
        keys = [self._job_type, "destinationTableProperties", "description"]
        if value is not None:
            _helpers._set_sub_prop(self._properties, keys, value)
        else:
            _helpers._del_sub_prop(self._properties, keys)

    @property
    def destination_table_friendly_name(self):
        """Optional[str]: Name given to destination table.

        See:
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#DestinationTableProperties.FIELDS.friendly_name
        """
        prop = self._get_sub_prop("destinationTableProperties")
        if prop is not None:
            return prop["friendlyName"]

    @destination_table_friendly_name.setter
    def destination_table_friendly_name(self, value):
        keys = [self._job_type, "destinationTableProperties", "friendlyName"]
        if value is not None:
            _helpers._set_sub_prop(self._properties, keys, value)
        else:
            _helpers._del_sub_prop(self._properties, keys)

    @property
    def encoding(self):
        """Optional[google.cloud.bigquery.job.Encoding]: The character encoding of the
        data.

        See:
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationLoad.FIELDS.encoding
        """
        return self._get_sub_prop("encoding")

    @encoding.setter
    def encoding(self, value):
        self._set_sub_prop("encoding", value)

    @property
    def field_delimiter(self):
        """Optional[str]: The separator for fields in a CSV file.

        See:
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationLoad.FIELDS.field_delimiter
        """
        return self._get_sub_prop("fieldDelimiter")

    @field_delimiter.setter
    def field_delimiter(self, value):
        self._set_sub_prop("fieldDelimiter", value)

    @property
    def hive_partitioning(self):
        """Optional[:class:`~.external_config.HivePartitioningOptions`]: [Beta] When set, \
        it configures hive partitioning support.

        .. note::
            **Experimental**. This feature is experimental and might change or
            have limited support.

        See:
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationLoad.FIELDS.hive_partitioning_options
        """
        prop = self._get_sub_prop("hivePartitioningOptions")
        if prop is None:
            return None
        return HivePartitioningOptions.from_api_repr(prop)

    @hive_partitioning.setter
    def hive_partitioning(self, value):
        if value is not None:
            if isinstance(value, HivePartitioningOptions):
                value = value.to_api_repr()
            else:
                raise TypeError("Expected a HivePartitioningOptions instance or None.")

        self._set_sub_prop("hivePartitioningOptions", value)

    @property
    def ignore_unknown_values(self):
        """Optional[bool]: Ignore extra values not represented in the table schema.

        See:
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationLoad.FIELDS.ignore_unknown_values
        """
        return self._get_sub_prop("ignoreUnknownValues")

    @ignore_unknown_values.setter
    def ignore_unknown_values(self, value):
        self._set_sub_prop("ignoreUnknownValues", value)

    @property
    def max_bad_records(self):
        """Optional[int]: Number of invalid rows to ignore.

        See:
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationLoad.FIELDS.max_bad_records
        """
        return _helpers._int_or_none(self._get_sub_prop("maxBadRecords"))

    @max_bad_records.setter
    def max_bad_records(self, value):
        self._set_sub_prop("maxBadRecords", value)

    @property
    def null_marker(self):
        """Optional[str]: Represents a null value (CSV only).

        See:
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationLoad.FIELDS.null_marker
        """
        return self._get_sub_prop("nullMarker")

    @null_marker.setter
    def null_marker(self, value):
        self._set_sub_prop("nullMarker", value)

    @property
    def quote_character(self):
        """Optional[str]: Character used to quote data sections (CSV only).

        See:
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationLoad.FIELDS.quote
        """
        return self._get_sub_prop("quote")

    @quote_character.setter
    def quote_character(self, value):
        self._set_sub_prop("quote", value)

    @property
    def range_partitioning(self):
        """Optional[google.cloud.bigquery.table.RangePartitioning]:
        Configures range-based partitioning for destination table.

        .. note::
            **Beta**. The integer range partitioning feature is in a
            pre-release state and might change or have limited support.

        Only specify at most one of
        :attr:`~google.cloud.bigquery.job.LoadJobConfig.time_partitioning` or
        :attr:`~google.cloud.bigquery.job.LoadJobConfig.range_partitioning`.

        Raises:
            ValueError:
                If the value is not
                :class:`~google.cloud.bigquery.table.RangePartitioning` or
                :data:`None`.
        """
        resource = self._get_sub_prop("rangePartitioning")
        if resource is not None:
            return RangePartitioning(_properties=resource)

    @range_partitioning.setter
    def range_partitioning(self, value):
        resource = value
        if isinstance(value, RangePartitioning):
            resource = value._properties
        elif value is not None:
            raise ValueError(
                "Expected value to be RangePartitioning or None, got {}.".format(value)
            )
        self._set_sub_prop("rangePartitioning", resource)

    @property
    def schema(self):
        """Optional[Sequence[Union[ \
            :class:`~google.cloud.bigquery.schema.SchemaField`, \
            Mapping[str, Any] \
        ]]]: Schema of the destination table.

        See:
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationLoad.FIELDS.schema
        """
        schema = _helpers._get_sub_prop(self._properties, ["load", "schema", "fields"])
        if schema is None:
            return
        return [SchemaField.from_api_repr(field) for field in schema]

    @schema.setter
    def schema(self, value):
        if value is None:
            self._del_sub_prop("schema")
            return

        value = _to_schema_fields(value)

        _helpers._set_sub_prop(
            self._properties,
            ["load", "schema", "fields"],
            [field.to_api_repr() for field in value],
        )

    @property
    def schema_update_options(self):
        """Optional[List[google.cloud.bigquery.job.SchemaUpdateOption]]: Specifies
        updates to the destination table schema to allow as a side effect of
        the load job.
        """
        return self._get_sub_prop("schemaUpdateOptions")

    @schema_update_options.setter
    def schema_update_options(self, values):
        self._set_sub_prop("schemaUpdateOptions", values)

    @property
    def skip_leading_rows(self):
        """Optional[int]: Number of rows to skip when reading data (CSV only).

        See:
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationLoad.FIELDS.skip_leading_rows
        """
        return _helpers._int_or_none(self._get_sub_prop("skipLeadingRows"))

    @skip_leading_rows.setter
    def skip_leading_rows(self, value):
        self._set_sub_prop("skipLeadingRows", str(value))

    @property
    def source_format(self):
        """Optional[google.cloud.bigquery.job.SourceFormat]: File format of the data.

        See:
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationLoad.FIELDS.source_format
        """
        return self._get_sub_prop("sourceFormat")

    @source_format.setter
    def source_format(self, value):
        self._set_sub_prop("sourceFormat", value)

    @property
    def time_partitioning(self):
        """Optional[google.cloud.bigquery.table.TimePartitioning]: Specifies time-based
        partitioning for the destination table.

        Only specify at most one of
        :attr:`~google.cloud.bigquery.job.LoadJobConfig.time_partitioning` or
        :attr:`~google.cloud.bigquery.job.LoadJobConfig.range_partitioning`.
        """
        prop = self._get_sub_prop("timePartitioning")
        if prop is not None:
            prop = TimePartitioning.from_api_repr(prop)
        return prop

    @time_partitioning.setter
    def time_partitioning(self, value):
        api_repr = value
        if value is not None:
            api_repr = value.to_api_repr()
            self._set_sub_prop("timePartitioning", api_repr)
        else:
            self._del_sub_prop("timePartitioning")

    @property
    def use_avro_logical_types(self):
        """Optional[bool]: For loads of Avro data, governs whether Avro logical types are
        converted to their corresponding BigQuery types (e.g. TIMESTAMP) rather than
        raw types (e.g. INTEGER).
        """
        return self._get_sub_prop("useAvroLogicalTypes")

    @use_avro_logical_types.setter
    def use_avro_logical_types(self, value):
        self._set_sub_prop("useAvroLogicalTypes", bool(value))

    @property
    def write_disposition(self):
        """Optional[google.cloud.bigquery.job.WriteDisposition]: Action that occurs if
        the destination table already exists.

        See:
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationLoad.FIELDS.write_disposition
        """
        return self._get_sub_prop("writeDisposition")

    @write_disposition.setter
    def write_disposition(self, value):
        self._set_sub_prop("writeDisposition", value)


class LoadJob(_AsyncJob):
    """Asynchronous job for loading data into a table.

    Can load from Google Cloud Storage URIs or from a file.

    Args:
        job_id (str): the job's ID

        source_uris (Optional[Sequence[str]]):
            URIs of one or more data files to be loaded.  See
            https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationLoad.FIELDS.source_uris
            for supported URI formats. Pass None for jobs that load from a file.

        destination (google.cloud.bigquery.table.TableReference): reference to table into which data is to be loaded.

        client (google.cloud.bigquery.client.Client):
            A client which holds credentials and project configuration
            for the dataset (which requires a project).
    """

    _JOB_TYPE = "load"

    def __init__(self, job_id, source_uris, destination, client, job_config=None):
        super(LoadJob, self).__init__(job_id, client)

        if not job_config:
            job_config = LoadJobConfig()

        self._configuration = job_config
        self._properties["configuration"] = job_config._properties

        if source_uris is not None:
            _helpers._set_sub_prop(
                self._properties, ["configuration", "load", "sourceUris"], source_uris
            )

        if destination is not None:
            _helpers._set_sub_prop(
                self._properties,
                ["configuration", "load", "destinationTable"],
                destination.to_api_repr(),
            )

    @property
    def destination(self):
        """google.cloud.bigquery.table.TableReference: table where loaded rows are written

        See:
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationLoad.FIELDS.destination_table
        """
        dest_config = _helpers._get_sub_prop(
            self._properties, ["configuration", "load", "destinationTable"]
        )
        return TableReference.from_api_repr(dest_config)

    @property
    def source_uris(self):
        """Optional[Sequence[str]]: URIs of data files to be loaded. See
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationLoad.FIELDS.source_uris
        for supported URI formats. None for jobs that load from a file.
        """
        return _helpers._get_sub_prop(
            self._properties, ["configuration", "load", "sourceUris"]
        )

    @property
    def allow_jagged_rows(self):
        """See
        :attr:`google.cloud.bigquery.job.LoadJobConfig.allow_jagged_rows`.
        """
        return self._configuration.allow_jagged_rows

    @property
    def allow_quoted_newlines(self):
        """See
        :attr:`google.cloud.bigquery.job.LoadJobConfig.allow_quoted_newlines`.
        """
        return self._configuration.allow_quoted_newlines

    @property
    def autodetect(self):
        """See
        :attr:`google.cloud.bigquery.job.LoadJobConfig.autodetect`.
        """
        return self._configuration.autodetect

    @property
    def create_disposition(self):
        """See
        :attr:`google.cloud.bigquery.job.LoadJobConfig.create_disposition`.
        """
        return self._configuration.create_disposition

    @property
    def encoding(self):
        """See
        :attr:`google.cloud.bigquery.job.LoadJobConfig.encoding`.
        """
        return self._configuration.encoding

    @property
    def field_delimiter(self):
        """See
        :attr:`google.cloud.bigquery.job.LoadJobConfig.field_delimiter`.
        """
        return self._configuration.field_delimiter

    @property
    def ignore_unknown_values(self):
        """See
        :attr:`google.cloud.bigquery.job.LoadJobConfig.ignore_unknown_values`.
        """
        return self._configuration.ignore_unknown_values

    @property
    def max_bad_records(self):
        """See
        :attr:`google.cloud.bigquery.job.LoadJobConfig.max_bad_records`.
        """
        return self._configuration.max_bad_records

    @property
    def null_marker(self):
        """See
        :attr:`google.cloud.bigquery.job.LoadJobConfig.null_marker`.
        """
        return self._configuration.null_marker

    @property
    def quote_character(self):
        """See
        :attr:`google.cloud.bigquery.job.LoadJobConfig.quote_character`.
        """
        return self._configuration.quote_character

    @property
    def skip_leading_rows(self):
        """See
        :attr:`google.cloud.bigquery.job.LoadJobConfig.skip_leading_rows`.
        """
        return self._configuration.skip_leading_rows

    @property
    def source_format(self):
        """See
        :attr:`google.cloud.bigquery.job.LoadJobConfig.source_format`.
        """
        return self._configuration.source_format

    @property
    def write_disposition(self):
        """See
        :attr:`google.cloud.bigquery.job.LoadJobConfig.write_disposition`.
        """
        return self._configuration.write_disposition

    @property
    def schema(self):
        """See
        :attr:`google.cloud.bigquery.job.LoadJobConfig.schema`.
        """
        return self._configuration.schema

    @property
    def destination_encryption_configuration(self):
        """google.cloud.bigquery.encryption_configuration.EncryptionConfiguration: Custom
        encryption configuration for the destination table.

        Custom encryption configuration (e.g., Cloud KMS keys)
        or :data:`None` if using default encryption.

        See
        :attr:`google.cloud.bigquery.job.LoadJobConfig.destination_encryption_configuration`.
        """
        return self._configuration.destination_encryption_configuration

    @property
    def destination_table_description(self):
        """Optional[str] name given to destination table.

        See:
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#DestinationTableProperties.FIELDS.description
        """
        return self._configuration.destination_table_description

    @property
    def destination_table_friendly_name(self):
        """Optional[str] name given to destination table.

        See:
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#DestinationTableProperties.FIELDS.friendly_name
        """
        return self._configuration.destination_table_friendly_name

    @property
    def range_partitioning(self):
        """See
        :attr:`google.cloud.bigquery.job.LoadJobConfig.range_partitioning`.
        """
        return self._configuration.range_partitioning

    @property
    def time_partitioning(self):
        """See
        :attr:`google.cloud.bigquery.job.LoadJobConfig.time_partitioning`.
        """
        return self._configuration.time_partitioning

    @property
    def use_avro_logical_types(self):
        """See
        :attr:`google.cloud.bigquery.job.LoadJobConfig.use_avro_logical_types`.
        """
        return self._configuration.use_avro_logical_types

    @property
    def clustering_fields(self):
        """See
        :attr:`google.cloud.bigquery.job.LoadJobConfig.clustering_fields`.
        """
        return self._configuration.clustering_fields

    @property
    def schema_update_options(self):
        """See
        :attr:`google.cloud.bigquery.job.LoadJobConfig.schema_update_options`.
        """
        return self._configuration.schema_update_options

    @property
    def input_file_bytes(self):
        """Count of bytes loaded from source files.

        Returns:
            Optional[int]: the count (None until set from the server).

        Raises:
            ValueError: for invalid value types.
        """
        return _helpers._int_or_none(
            _helpers._get_sub_prop(
                self._properties, ["statistics", "load", "inputFileBytes"]
            )
        )

    @property
    def input_files(self):
        """Count of source files.

        Returns:
            Optional[int]: the count (None until set from the server).
        """
        return _helpers._int_or_none(
            _helpers._get_sub_prop(
                self._properties, ["statistics", "load", "inputFiles"]
            )
        )

    @property
    def output_bytes(self):
        """Count of bytes saved to destination table.

        Returns:
            Optional[int]: the count (None until set from the server).
        """
        return _helpers._int_or_none(
            _helpers._get_sub_prop(
                self._properties, ["statistics", "load", "outputBytes"]
            )
        )

    @property
    def output_rows(self):
        """Count of rows saved to destination table.

        Returns:
            Optional[int]: the count (None until set from the server).
        """
        return _helpers._int_or_none(
            _helpers._get_sub_prop(
                self._properties, ["statistics", "load", "outputRows"]
            )
        )

    def to_api_repr(self):
        """Generate a resource for :meth:`_begin`."""
        # Exclude statistics, if set.
        return {
            "jobReference": self._properties["jobReference"],
            "configuration": self._properties["configuration"],
        }

    @classmethod
    def from_api_repr(cls, resource, client):
        """Factory:  construct a job given its API representation

        .. note:

           This method assumes that the project found in the resource matches
           the client's project.

        Args:
            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:
            google.cloud.bigquery.job.LoadJob: Job parsed from ``resource``.
        """
        cls._check_resource_config(resource)
        job_ref = _JobReference._from_api_repr(resource["jobReference"])
        job = cls(job_ref, None, None, client)
        job._set_properties(resource)
        return job


class CopyJobConfig(_JobConfig):
    """Configuration options for copy jobs.

    All properties in this class are optional. Values which are :data:`None` ->
    server defaults. Set properties on the constructed configuration by using
    the property name as the name of a keyword argument.
    """

    def __init__(self, **kwargs):
        super(CopyJobConfig, self).__init__("copy", **kwargs)

    @property
    def create_disposition(self):
        """google.cloud.bigquery.job.CreateDisposition: Specifies behavior
        for creating tables.

        See
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationTableCopy.FIELDS.create_disposition
        """
        return self._get_sub_prop("createDisposition")

    @create_disposition.setter
    def create_disposition(self, value):
        self._set_sub_prop("createDisposition", value)

    @property
    def write_disposition(self):
        """google.cloud.bigquery.job.WriteDisposition: Action that occurs if
        the destination table already exists.

        See
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationTableCopy.FIELDS.write_disposition
        """
        return self._get_sub_prop("writeDisposition")

    @write_disposition.setter
    def write_disposition(self, value):
        self._set_sub_prop("writeDisposition", value)

    @property
    def destination_encryption_configuration(self):
        """google.cloud.bigquery.encryption_configuration.EncryptionConfiguration: Custom
        encryption configuration for the destination table.

        Custom encryption configuration (e.g., Cloud KMS keys) or :data:`None`
        if using default encryption.

        See
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationTableCopy.FIELDS.destination_encryption_configuration
        """
        prop = self._get_sub_prop("destinationEncryptionConfiguration")
        if prop is not None:
            prop = EncryptionConfiguration.from_api_repr(prop)
        return prop

    @destination_encryption_configuration.setter
    def destination_encryption_configuration(self, value):
        api_repr = value
        if value is not None:
            api_repr = value.to_api_repr()
        self._set_sub_prop("destinationEncryptionConfiguration", api_repr)


class CopyJob(_AsyncJob):
    """Asynchronous job: copy data into a table from other tables.

    Args:
        job_id (str): the job's ID, within the project belonging to ``client``.

        sources (List[google.cloud.bigquery.table.TableReference]): Table from which data is to be loaded.

        destination (google.cloud.bigquery.table.TableReference): Table into which data is to be loaded.

        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.CopyJobConfig]):
            Extra configuration options for the copy job.
    """

    _JOB_TYPE = "copy"

    def __init__(self, job_id, sources, destination, client, job_config=None):
        super(CopyJob, self).__init__(job_id, client)

        if not job_config:
            job_config = CopyJobConfig()

        self._configuration = job_config
        self._properties["configuration"] = job_config._properties

        if destination:
            _helpers._set_sub_prop(
                self._properties,
                ["configuration", "copy", "destinationTable"],
                destination.to_api_repr(),
            )

        if sources:
            source_resources = [source.to_api_repr() for source in sources]
            _helpers._set_sub_prop(
                self._properties,
                ["configuration", "copy", "sourceTables"],
                source_resources,
            )

    @property
    def destination(self):
        """google.cloud.bigquery.table.TableReference: Table into which data
        is to be loaded.
        """
        return TableReference.from_api_repr(
            _helpers._get_sub_prop(
                self._properties, ["configuration", "copy", "destinationTable"],
            )
        )

    @property
    def sources(self):
        """List[google.cloud.bigquery.table.TableReference]): Table(s) from
        which data is to be loaded.
        """
        source_configs = _helpers._get_sub_prop(
            self._properties, ["configuration", "copy", "sourceTables"]
        )
        if source_configs is None:
            single = _helpers._get_sub_prop(
                self._properties, ["configuration", "copy", "sourceTable"]
            )
            if single is None:
                raise KeyError("Resource missing 'sourceTables' / 'sourceTable'")
            source_configs = [single]

        sources = []
        for source_config in source_configs:
            table_ref = TableReference.from_api_repr(source_config)
            sources.append(table_ref)
        return sources

    @property
    def create_disposition(self):
        """See
        :attr:`google.cloud.bigquery.job.CopyJobConfig.create_disposition`.
        """
        return self._configuration.create_disposition

    @property
    def write_disposition(self):
        """See
        :attr:`google.cloud.bigquery.job.CopyJobConfig.write_disposition`.
        """
        return self._configuration.write_disposition

    @property
    def destination_encryption_configuration(self):
        """google.cloud.bigquery.encryption_configuration.EncryptionConfiguration: Custom
        encryption configuration for the destination table.

        Custom encryption configuration (e.g., Cloud KMS keys) or :data:`None`
        if using default encryption.

        See
        :attr:`google.cloud.bigquery.job.CopyJobConfig.destination_encryption_configuration`.
        """
        return self._configuration.destination_encryption_configuration

    def to_api_repr(self):
        """Generate a resource for :meth:`_begin`."""
        # Exclude statistics, if set.
        return {
            "jobReference": self._properties["jobReference"],
            "configuration": self._properties["configuration"],
        }

    @classmethod
    def from_api_repr(cls, resource, client):
        """Factory: construct a job given its API representation

        .. note:

           This method assumes that the project found in the resource matches
           the client's project.

        Args:
            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:
            google.cloud.bigquery.job.CopyJob: Job parsed from ``resource``.
        """
        cls._check_resource_config(resource)
        job_ref = _JobReference._from_api_repr(resource["jobReference"])
        job = cls(job_ref, None, None, client=client)
        job._set_properties(resource)
        return job


class ExtractJobConfig(_JobConfig):
    """Configuration options for extract jobs.

    All properties in this class are optional. Values which are :data:`None` ->
    server defaults. Set properties on the constructed configuration by using
    the property name as the name of a keyword argument.
    """

    def __init__(self, **kwargs):
        super(ExtractJobConfig, self).__init__("extract", **kwargs)

    @property
    def compression(self):
        """google.cloud.bigquery.job.Compression: Compression type to use for
        exported files.

        See
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationExtract.FIELDS.compression
        """
        return self._get_sub_prop("compression")

    @compression.setter
    def compression(self, value):
        self._set_sub_prop("compression", value)

    @property
    def destination_format(self):
        """google.cloud.bigquery.job.DestinationFormat: Exported file format.

        See
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationExtract.FIELDS.destination_format
        """
        return self._get_sub_prop("destinationFormat")

    @destination_format.setter
    def destination_format(self, value):
        self._set_sub_prop("destinationFormat", value)

    @property
    def field_delimiter(self):
        """str: Delimiter to use between fields in the exported data.

        See
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationExtract.FIELDS.field_delimiter
        """
        return self._get_sub_prop("fieldDelimiter")

    @field_delimiter.setter
    def field_delimiter(self, value):
        self._set_sub_prop("fieldDelimiter", value)

    @property
    def print_header(self):
        """bool: Print a header row in the exported data.

        See
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationExtract.FIELDS.print_header
        """
        return self._get_sub_prop("printHeader")

    @print_header.setter
    def print_header(self, value):
        self._set_sub_prop("printHeader", value)

    @property
    def use_avro_logical_types(self):
        """bool: For loads of Avro data, governs whether Avro logical types are
        converted to their corresponding BigQuery types (e.g. TIMESTAMP) rather than
        raw types (e.g. INTEGER).
        """
        return self._get_sub_prop("useAvroLogicalTypes")

    @use_avro_logical_types.setter
    def use_avro_logical_types(self, value):
        self._set_sub_prop("useAvroLogicalTypes", bool(value))


class ExtractJob(_AsyncJob):
    """Asynchronous job: extract data from a table into Cloud Storage.

    Args:
        job_id (str): the job's ID.

        source (Union[ \
            google.cloud.bigquery.table.TableReference, \
            google.cloud.bigquery.model.ModelReference \
        ]):
            Table or Model from which data is to be loaded or extracted.

        destination_uris (List[str]):
            URIs describing where the extracted data will be written in Cloud
            Storage, using the format ``gs://<bucket_name>/<object_name_or_glob>``.

        client (google.cloud.bigquery.client.Client):
            A client which holds credentials and project configuration.

        job_config (Optional[google.cloud.bigquery.job.ExtractJobConfig]):
            Extra configuration options for the extract job.
    """

    _JOB_TYPE = "extract"

    def __init__(self, job_id, source, destination_uris, client, job_config=None):
        super(ExtractJob, self).__init__(job_id, client)

        if job_config is None:
            job_config = ExtractJobConfig()

        self._properties["configuration"] = job_config._properties
        self._configuration = job_config

        if source:
            source_ref = {
                "projectId": source.project,
                "datasetId": source.dataset_id,
            }

            if isinstance(source, (Table, TableListItem, TableReference)):
                source_ref["tableId"] = source.table_id
                source_key = "sourceTable"
            else:
                source_ref["modelId"] = source.model_id
                source_key = "sourceModel"

            _helpers._set_sub_prop(
                self._properties, ["configuration", "extract", source_key], source_ref
            )

        if destination_uris:
            _helpers._set_sub_prop(
                self._properties,
                ["configuration", "extract", "destinationUris"],
                destination_uris,
            )

    @property
    def source(self):
        """Union[ \
            google.cloud.bigquery.table.TableReference, \
            google.cloud.bigquery.model.ModelReference \
        ]: Table or Model from which data is to be loaded or extracted.
        """
        source_config = _helpers._get_sub_prop(
            self._properties, ["configuration", "extract", "sourceTable"]
        )
        if source_config:
            return TableReference.from_api_repr(source_config)
        else:
            source_config = _helpers._get_sub_prop(
                self._properties, ["configuration", "extract", "sourceModel"]
            )
            return ModelReference.from_api_repr(source_config)

    @property
    def destination_uris(self):
        """List[str]: URIs describing where the extracted data will be
        written in Cloud Storage, using the format
        ``gs://<bucket_name>/<object_name_or_glob>``.
        """
        return _helpers._get_sub_prop(
            self._properties, ["configuration", "extract", "destinationUris"]
        )

    @property
    def compression(self):
        """See
        :attr:`google.cloud.bigquery.job.ExtractJobConfig.compression`.
        """
        return self._configuration.compression

    @property
    def destination_format(self):
        """See
        :attr:`google.cloud.bigquery.job.ExtractJobConfig.destination_format`.
        """
        return self._configuration.destination_format

    @property
    def field_delimiter(self):
        """See
        :attr:`google.cloud.bigquery.job.ExtractJobConfig.field_delimiter`.
        """
        return self._configuration.field_delimiter

    @property
    def print_header(self):
        """See
        :attr:`google.cloud.bigquery.job.ExtractJobConfig.print_header`.
        """
        return self._configuration.print_header

    @property
    def destination_uri_file_counts(self):
        """Return file counts from job statistics, if present.

        See:
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobStatistics4.FIELDS.destination_uri_file_counts

        Returns:
            List[int]:
                A list of integer counts, each representing the number of files
                per destination URI or URI pattern specified in the extract
                configuration. These values will be in the same order as the URIs
                specified in the 'destinationUris' field.  Returns None if job is
                not yet complete.
        """
        counts = self._job_statistics().get("destinationUriFileCounts")
        if counts is not None:
            return [int(count) for count in counts]
        return None

    def to_api_repr(self):
        """Generate a resource for :meth:`_begin`."""
        # Exclude statistics, if set.
        return {
            "jobReference": self._properties["jobReference"],
            "configuration": self._properties["configuration"],
        }

    @classmethod
    def from_api_repr(cls, resource, client):
        """Factory:  construct a job given its API representation

        .. note:

           This method assumes that the project found in the resource matches
           the client's project.

        Args:
            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:
            google.cloud.bigquery.job.ExtractJob: Job parsed from ``resource``.
        """
        cls._check_resource_config(resource)
        job_ref = _JobReference._from_api_repr(resource["jobReference"])
        job = cls(job_ref, None, None, client=client)
        job._set_properties(resource)
        return job


def _from_api_repr_query_parameters(resource):
    return [_query_param_from_api_repr(mapping) for mapping in resource]


def _to_api_repr_query_parameters(value):
    return [query_parameter.to_api_repr() for query_parameter in value]


def _from_api_repr_udf_resources(resource):
    udf_resources = []
    for udf_mapping in resource:
        for udf_type, udf_value in udf_mapping.items():
            udf_resources.append(UDFResource(udf_type, udf_value))
    return udf_resources


def _to_api_repr_udf_resources(value):
    return [{udf_resource.udf_type: udf_resource.value} for udf_resource in value]


def _from_api_repr_table_defs(resource):
    return {k: ExternalConfig.from_api_repr(v) for k, v in resource.items()}


def _to_api_repr_table_defs(value):
    return {k: ExternalConfig.to_api_repr(v) for k, v in value.items()}


class QueryJobConfig(_JobConfig):
    """Configuration options for query jobs.

    All properties in this class are optional. Values which are :data:`None` ->
    server defaults. Set properties on the constructed configuration by using
    the property name as the name of a keyword argument.
    """

    def __init__(self, **kwargs):
        super(QueryJobConfig, self).__init__("query", **kwargs)

    @property
    def destination_encryption_configuration(self):
        """google.cloud.bigquery.encryption_configuration.EncryptionConfiguration: Custom
        encryption configuration for the destination table.

        Custom encryption configuration (e.g., Cloud KMS keys) or :data:`None`
        if using default encryption.

        See
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationQuery.FIELDS.destination_encryption_configuration
        """
        prop = self._get_sub_prop("destinationEncryptionConfiguration")
        if prop is not None:
            prop = EncryptionConfiguration.from_api_repr(prop)
        return prop

    @destination_encryption_configuration.setter
    def destination_encryption_configuration(self, value):
        api_repr = value
        if value is not None:
            api_repr = value.to_api_repr()
        self._set_sub_prop("destinationEncryptionConfiguration", api_repr)

    @property
    def allow_large_results(self):
        """bool: Allow large query results tables (legacy SQL, only)

        See
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationQuery.FIELDS.allow_large_results
        """
        return self._get_sub_prop("allowLargeResults")

    @allow_large_results.setter
    def allow_large_results(self, value):
        self._set_sub_prop("allowLargeResults", value)

    @property
    def create_disposition(self):
        """google.cloud.bigquery.job.CreateDisposition: Specifies behavior
        for creating tables.

        See
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationQuery.FIELDS.create_disposition
        """
        return self._get_sub_prop("createDisposition")

    @create_disposition.setter
    def create_disposition(self, value):
        self._set_sub_prop("createDisposition", value)

    @property
    def default_dataset(self):
        """google.cloud.bigquery.dataset.DatasetReference: the default dataset
        to use for unqualified table names in the query or :data:`None` if not
        set.

        The ``default_dataset`` setter accepts:

        - a :class:`~google.cloud.bigquery.dataset.Dataset`, or
        - a :class:`~google.cloud.bigquery.dataset.DatasetReference`, or
        - a :class:`str` of the fully-qualified dataset ID in standard SQL
          format. The value must included a project ID and dataset ID
          separated by ``.``. For example: ``your-project.your_dataset``.

        See
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationQuery.FIELDS.default_dataset
        """
        prop = self._get_sub_prop("defaultDataset")
        if prop is not None:
            prop = DatasetReference.from_api_repr(prop)
        return prop

    @default_dataset.setter
    def default_dataset(self, value):
        if value is None:
            self._set_sub_prop("defaultDataset", None)
            return

        if isinstance(value, six.string_types):
            value = DatasetReference.from_string(value)

        if isinstance(value, (Dataset, DatasetListItem)):
            value = value.reference

        resource = value.to_api_repr()
        self._set_sub_prop("defaultDataset", resource)

    @property
    def destination(self):
        """google.cloud.bigquery.table.TableReference: table where results are
        written or :data:`None` if not set.

        The ``destination`` setter accepts:

        - a :class:`~google.cloud.bigquery.table.Table`, or
        - a :class:`~google.cloud.bigquery.table.TableReference`, or
        - a :class:`str` of the fully-qualified table ID in standard SQL
          format. The value must included a project ID, dataset ID, and table
          ID, each separated by ``.``. For example:
          ``your-project.your_dataset.your_table``.

        See
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationQuery.FIELDS.destination_table
        """
        prop = self._get_sub_prop("destinationTable")
        if prop is not None:
            prop = TableReference.from_api_repr(prop)
        return prop

    @destination.setter
    def destination(self, value):
        if value is None:
            self._set_sub_prop("destinationTable", None)
            return

        value = _table_arg_to_table_ref(value)
        resource = value.to_api_repr()
        self._set_sub_prop("destinationTable", resource)

    @property
    def dry_run(self):
        """bool: :data:`True` if this query should be a dry run to estimate
        costs.

        See
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfiguration.FIELDS.dry_run
        """
        return self._properties.get("dryRun")

    @dry_run.setter
    def dry_run(self, value):
        self._properties["dryRun"] = value

    @property
    def flatten_results(self):
        """bool: Flatten nested/repeated fields in results. (Legacy SQL only)

        See
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationQuery.FIELDS.flatten_results
        """
        return self._get_sub_prop("flattenResults")

    @flatten_results.setter
    def flatten_results(self, value):
        self._set_sub_prop("flattenResults", value)

    @property
    def maximum_billing_tier(self):
        """int: Deprecated. Changes the billing tier to allow high-compute
        queries.

        See
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationQuery.FIELDS.maximum_billing_tier
        """
        return self._get_sub_prop("maximumBillingTier")

    @maximum_billing_tier.setter
    def maximum_billing_tier(self, value):
        self._set_sub_prop("maximumBillingTier", value)

    @property
    def maximum_bytes_billed(self):
        """int: Maximum bytes to be billed for this job or :data:`None` if not set.

        See
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationQuery.FIELDS.maximum_bytes_billed
        """
        return _helpers._int_or_none(self._get_sub_prop("maximumBytesBilled"))

    @maximum_bytes_billed.setter
    def maximum_bytes_billed(self, value):
        self._set_sub_prop("maximumBytesBilled", str(value))

    @property
    def priority(self):
        """google.cloud.bigquery.job.QueryPriority: Priority of the query.

        See
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationQuery.FIELDS.priority
        """
        return self._get_sub_prop("priority")

    @priority.setter
    def priority(self, value):
        self._set_sub_prop("priority", value)

    @property
    def query_parameters(self):
        """List[Union[google.cloud.bigquery.query.ArrayQueryParameter, \
        google.cloud.bigquery.query.ScalarQueryParameter, \
        google.cloud.bigquery.query.StructQueryParameter]]: list of parameters
        for parameterized query (empty by default)

        See:
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationQuery.FIELDS.query_parameters
        """
        prop = self._get_sub_prop("queryParameters", default=[])
        return _from_api_repr_query_parameters(prop)

    @query_parameters.setter
    def query_parameters(self, values):
        self._set_sub_prop("queryParameters", _to_api_repr_query_parameters(values))

    @property
    def range_partitioning(self):
        """Optional[google.cloud.bigquery.table.RangePartitioning]:
        Configures range-based partitioning for destination table.

        .. note::
            **Beta**. The integer range partitioning feature is in a
            pre-release state and might change or have limited support.

        Only specify at most one of
        :attr:`~google.cloud.bigquery.job.LoadJobConfig.time_partitioning` or
        :attr:`~google.cloud.bigquery.job.LoadJobConfig.range_partitioning`.

        Raises:
            ValueError:
                If the value is not
                :class:`~google.cloud.bigquery.table.RangePartitioning` or
                :data:`None`.
        """
        resource = self._get_sub_prop("rangePartitioning")
        if resource is not None:
            return RangePartitioning(_properties=resource)

    @range_partitioning.setter
    def range_partitioning(self, value):
        resource = value
        if isinstance(value, RangePartitioning):
            resource = value._properties
        elif value is not None:
            raise ValueError(
                "Expected value to be RangePartitioning or None, got {}.".format(value)
            )
        self._set_sub_prop("rangePartitioning", resource)

    @property
    def udf_resources(self):
        """List[google.cloud.bigquery.query.UDFResource]: user
        defined function resources (empty by default)

        See:
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationQuery.FIELDS.user_defined_function_resources
        """
        prop = self._get_sub_prop("userDefinedFunctionResources", default=[])
        return _from_api_repr_udf_resources(prop)

    @udf_resources.setter
    def udf_resources(self, values):
        self._set_sub_prop(
            "userDefinedFunctionResources", _to_api_repr_udf_resources(values)
        )

    @property
    def use_legacy_sql(self):
        """bool: Use legacy SQL syntax.

        See
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationQuery.FIELDS.use_legacy_sql
        """
        return self._get_sub_prop("useLegacySql")

    @use_legacy_sql.setter
    def use_legacy_sql(self, value):
        self._set_sub_prop("useLegacySql", value)

    @property
    def use_query_cache(self):
        """bool: Look for the query result in the cache.

        See
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationQuery.FIELDS.use_query_cache
        """
        return self._get_sub_prop("useQueryCache")

    @use_query_cache.setter
    def use_query_cache(self, value):
        self._set_sub_prop("useQueryCache", value)

    @property
    def write_disposition(self):
        """google.cloud.bigquery.job.WriteDisposition: Action that occurs if
        the destination table already exists.

        See
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationQuery.FIELDS.write_disposition
        """
        return self._get_sub_prop("writeDisposition")

    @write_disposition.setter
    def write_disposition(self, value):
        self._set_sub_prop("writeDisposition", value)

    @property
    def table_definitions(self):
        """Dict[str, google.cloud.bigquery.external_config.ExternalConfig]:
        Definitions for external tables or :data:`None` if not set.

        See
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationQuery.FIELDS.external_table_definitions
        """
        prop = self._get_sub_prop("tableDefinitions")
        if prop is not None:
            prop = _from_api_repr_table_defs(prop)
        return prop

    @table_definitions.setter
    def table_definitions(self, values):
        self._set_sub_prop("tableDefinitions", _to_api_repr_table_defs(values))

    @property
    def time_partitioning(self):
        """Optional[google.cloud.bigquery.table.TimePartitioning]: Specifies
        time-based partitioning for the destination table.

        Only specify at most one of
        :attr:`~google.cloud.bigquery.job.LoadJobConfig.time_partitioning` or
        :attr:`~google.cloud.bigquery.job.LoadJobConfig.range_partitioning`.

        Raises:
            ValueError:
                If the value is not
                :class:`~google.cloud.bigquery.table.TimePartitioning` or
                :data:`None`.
        """
        prop = self._get_sub_prop("timePartitioning")
        if prop is not None:
            prop = TimePartitioning.from_api_repr(prop)
        return prop

    @time_partitioning.setter
    def time_partitioning(self, value):
        api_repr = value
        if value is not None:
            api_repr = value.to_api_repr()
        self._set_sub_prop("timePartitioning", api_repr)

    @property
    def clustering_fields(self):
        """Optional[List[str]]: Fields defining clustering for the table

        (Defaults to :data:`None`).

        Clustering fields are immutable after table creation.

        .. note::

           BigQuery supports clustering for both partitioned and
           non-partitioned tables.
        """
        prop = self._get_sub_prop("clustering")
        if prop is not None:
            return list(prop.get("fields", ()))

    @clustering_fields.setter
    def clustering_fields(self, value):
        """Optional[List[str]]: Fields defining clustering for the table

        (Defaults to :data:`None`).
        """
        if value is not None:
            self._set_sub_prop("clustering", {"fields": value})
        else:
            self._del_sub_prop("clustering")

    @property
    def schema_update_options(self):
        """List[google.cloud.bigquery.job.SchemaUpdateOption]: Specifies
        updates to the destination table schema to allow as a side effect of
        the query job.
        """
        return self._get_sub_prop("schemaUpdateOptions")

    @schema_update_options.setter
    def schema_update_options(self, values):
        self._set_sub_prop("schemaUpdateOptions", values)

    def to_api_repr(self):
        """Build an API representation of the query job config.

        Returns:
            Dict: A dictionary in the format used by the BigQuery API.
        """
        resource = copy.deepcopy(self._properties)

        # Query parameters have an addition property associated with them
        # to indicate if the query is using named or positional parameters.
        query_parameters = resource["query"].get("queryParameters")
        if query_parameters:
            if query_parameters[0].get("name") is None:
                resource["query"]["parameterMode"] = "POSITIONAL"
            else:
                resource["query"]["parameterMode"] = "NAMED"

        return resource


class QueryJob(_AsyncJob):
    """Asynchronous job: query tables.

    Args:
        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.
    """

    _JOB_TYPE = "query"
    _UDF_KEY = "userDefinedFunctionResources"

    def __init__(self, job_id, query, client, job_config=None):
        super(QueryJob, self).__init__(job_id, client)

        if job_config is None:
            job_config = QueryJobConfig()
        if job_config.use_legacy_sql is None:
            job_config.use_legacy_sql = False

        self._properties["configuration"] = job_config._properties
        self._configuration = job_config

        if query:
            _helpers._set_sub_prop(
                self._properties, ["configuration", "query", "query"], query
            )

        self._query_results = None
        self._done_timeout = None
        self._transport_timeout = None

    @property
    def allow_large_results(self):
        """See
        :attr:`google.cloud.bigquery.job.QueryJobConfig.allow_large_results`.
        """
        return self._configuration.allow_large_results

    @property
    def create_disposition(self):
        """See
        :attr:`google.cloud.bigquery.job.QueryJobConfig.create_disposition`.
        """
        return self._configuration.create_disposition

    @property
    def default_dataset(self):
        """See
        :attr:`google.cloud.bigquery.job.QueryJobConfig.default_dataset`.
        """
        return self._configuration.default_dataset

    @property
    def destination(self):
        """See
        :attr:`google.cloud.bigquery.job.QueryJobConfig.destination`.
        """
        return self._configuration.destination

    @property
    def destination_encryption_configuration(self):
        """google.cloud.bigquery.encryption_configuration.EncryptionConfiguration: Custom
        encryption configuration for the destination table.

        Custom encryption configuration (e.g., Cloud KMS keys) or :data:`None`
        if using default encryption.

        See
        :attr:`google.cloud.bigquery.job.QueryJobConfig.destination_encryption_configuration`.
        """
        return self._configuration.destination_encryption_configuration

    @property
    def dry_run(self):
        """See
        :attr:`google.cloud.bigquery.job.QueryJobConfig.dry_run`.
        """
        return self._configuration.dry_run

    @property
    def flatten_results(self):
        """See
        :attr:`google.cloud.bigquery.job.QueryJobConfig.flatten_results`.
        """
        return self._configuration.flatten_results

    @property
    def priority(self):
        """See
        :attr:`google.cloud.bigquery.job.QueryJobConfig.priority`.
        """
        return self._configuration.priority

    @property
    def query(self):
        """str: The query text used in this query job.

        See:
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationQuery.FIELDS.query
        """
        return _helpers._get_sub_prop(
            self._properties, ["configuration", "query", "query"]
        )

    @property
    def query_parameters(self):
        """See
        :attr:`google.cloud.bigquery.job.QueryJobConfig.query_parameters`.
        """
        return self._configuration.query_parameters

    @property
    def udf_resources(self):
        """See
        :attr:`google.cloud.bigquery.job.QueryJobConfig.udf_resources`.
        """
        return self._configuration.udf_resources

    @property
    def use_legacy_sql(self):
        """See
        :attr:`google.cloud.bigquery.job.QueryJobConfig.use_legacy_sql`.
        """
        return self._configuration.use_legacy_sql

    @property
    def use_query_cache(self):
        """See
        :attr:`google.cloud.bigquery.job.QueryJobConfig.use_query_cache`.
        """
        return self._configuration.use_query_cache

    @property
    def write_disposition(self):
        """See
        :attr:`google.cloud.bigquery.job.QueryJobConfig.write_disposition`.
        """
        return self._configuration.write_disposition

    @property
    def maximum_billing_tier(self):
        """See
        :attr:`google.cloud.bigquery.job.QueryJobConfig.maximum_billing_tier`.
        """
        return self._configuration.maximum_billing_tier

    @property
    def maximum_bytes_billed(self):
        """See
        :attr:`google.cloud.bigquery.job.QueryJobConfig.maximum_bytes_billed`.
        """
        return self._configuration.maximum_bytes_billed

    @property
    def range_partitioning(self):
        """See
        :attr:`google.cloud.bigquery.job.QueryJobConfig.range_partitioning`.
        """
        return self._configuration.range_partitioning

    @property
    def table_definitions(self):
        """See
        :attr:`google.cloud.bigquery.job.QueryJobConfig.table_definitions`.
        """
        return self._configuration.table_definitions

    @property
    def time_partitioning(self):
        """See
        :attr:`google.cloud.bigquery.job.QueryJobConfig.time_partitioning`.
        """
        return self._configuration.time_partitioning

    @property
    def clustering_fields(self):
        """See
        :attr:`google.cloud.bigquery.job.QueryJobConfig.clustering_fields`.
        """
        return self._configuration.clustering_fields

    @property
    def schema_update_options(self):
        """See
        :attr:`google.cloud.bigquery.job.QueryJobConfig.schema_update_options`.
        """
        return self._configuration.schema_update_options

    def to_api_repr(self):
        """Generate a resource for :meth:`_begin`."""
        # Use to_api_repr to allow for some configuration properties to be set
        # automatically.
        configuration = self._configuration.to_api_repr()
        return {
            "jobReference": self._properties["jobReference"],
            "configuration": configuration,
        }

    @classmethod
    def from_api_repr(cls, resource, client):
        """Factory:  construct a job given its API representation

        Args:
            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:
            google.cloud.bigquery.job.QueryJob: Job parsed from ``resource``.
        """
        cls._check_resource_config(resource)
        job_ref = _JobReference._from_api_repr(resource["jobReference"])
        job = cls(job_ref, None, client=client)
        job._set_properties(resource)
        return job

    @property
    def query_plan(self):
        """Return query plan from job statistics, if present.

        See:
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobStatistics2.FIELDS.query_plan

        Returns:
            List[google.cloud.bigquery.job.QueryPlanEntry]:
                mappings describing the query plan, or an empty list
                if the query has not yet completed.
        """
        plan_entries = self._job_statistics().get("queryPlan", ())
        return [QueryPlanEntry.from_api_repr(entry) for entry in plan_entries]

    @property
    def timeline(self):
        """List(TimelineEntry): Return the query execution timeline
        from job statistics.
        """
        raw = self._job_statistics().get("timeline", ())
        return [TimelineEntry.from_api_repr(entry) for entry in raw]

    @property
    def total_bytes_processed(self):
        """Return total bytes processed from job statistics, if present.

        See:
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobStatistics2.FIELDS.total_bytes_processed

        Returns:
            Optional[int]:
                Total bytes processed by the job, or None if job is not
                yet complete.
        """
        result = self._job_statistics().get("totalBytesProcessed")
        if result is not None:
            result = int(result)
        return result

    @property
    def total_bytes_billed(self):
        """Return total bytes billed from job statistics, if present.

        See:
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobStatistics2.FIELDS.total_bytes_billed

        Returns:
            Optional[int]:
                Total bytes processed by the job, or None if job is not
                yet complete.
        """
        result = self._job_statistics().get("totalBytesBilled")
        if result is not None:
            result = int(result)
        return result

    @property
    def billing_tier(self):
        """Return billing tier from job statistics, if present.

        See:
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobStatistics2.FIELDS.billing_tier

        Returns:
            Optional[int]:
                Billing tier used by the job, or None if job is not
                yet complete.
        """
        return self._job_statistics().get("billingTier")

    @property
    def cache_hit(self):
        """Return whether or not query results were served from cache.

        See:
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobStatistics2.FIELDS.cache_hit

        Returns:
            Optional[bool]:
                whether the query results were returned from cache, or None
                if job is not yet complete.
        """
        return self._job_statistics().get("cacheHit")

    @property
    def ddl_operation_performed(self):
        """Optional[str]: Return the DDL operation performed.

        See:
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobStatistics2.FIELDS.ddl_operation_performed

        """
        return self._job_statistics().get("ddlOperationPerformed")

    @property
    def ddl_target_routine(self):
        """Optional[google.cloud.bigquery.routine.RoutineReference]: Return the DDL target routine, present
            for CREATE/DROP FUNCTION/PROCEDURE  queries.

        See:
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobStatistics2.FIELDS.ddl_target_routine
        """
        prop = self._job_statistics().get("ddlTargetRoutine")
        if prop is not None:
            prop = RoutineReference.from_api_repr(prop)
        return prop

    @property
    def ddl_target_table(self):
        """Optional[google.cloud.bigquery.table.TableReference]: Return the DDL target table, present
            for CREATE/DROP TABLE/VIEW queries.

        See:
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobStatistics2.FIELDS.ddl_target_table
        """
        prop = self._job_statistics().get("ddlTargetTable")
        if prop is not None:
            prop = TableReference.from_api_repr(prop)
        return prop

    @property
    def num_dml_affected_rows(self):
        """Return the number of DML rows affected by the job.

        See:
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobStatistics2.FIELDS.num_dml_affected_rows

        Returns:
            Optional[int]:
                number of DML rows affected by the job, or None if job is not
                yet complete.
        """
        result = self._job_statistics().get("numDmlAffectedRows")
        if result is not None:
            result = int(result)
        return result

    @property
    def slot_millis(self):
        """Union[int, None]: Slot-milliseconds used by this query job."""
        return _helpers._int_or_none(self._job_statistics().get("totalSlotMs"))

    @property
    def statement_type(self):
        """Return statement type from job statistics, if present.

        See:
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobStatistics2.FIELDS.statement_type

        Returns:
            Optional[str]:
                type of statement used by the job, or None if job is not
                yet complete.
        """
        return self._job_statistics().get("statementType")

    @property
    def referenced_tables(self):
        """Return referenced tables from job statistics, if present.

        See:
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobStatistics2.FIELDS.referenced_tables

        Returns:
            List[Dict]:
                mappings describing the query plan, or an empty list
                if the query has not yet completed.
        """
        tables = []
        datasets_by_project_name = {}

        for table in self._job_statistics().get("referencedTables", ()):

            t_project = table["projectId"]

            ds_id = table["datasetId"]
            t_dataset = datasets_by_project_name.get((t_project, ds_id))
            if t_dataset is None:
                t_dataset = DatasetReference(t_project, ds_id)
                datasets_by_project_name[(t_project, ds_id)] = t_dataset

            t_name = table["tableId"]
            tables.append(t_dataset.table(t_name))

        return tables

    @property
    def undeclared_query_parameters(self):
        """Return undeclared query parameters from job statistics, if present.

        See:
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobStatistics2.FIELDS.undeclared_query_parameters

        Returns:
            List[Union[ \
                google.cloud.bigquery.query.ArrayQueryParameter, \
                google.cloud.bigquery.query.ScalarQueryParameter, \
                google.cloud.bigquery.query.StructQueryParameter \
            ]]:
                Undeclared parameters, or an empty list if the query has
                not yet completed.
        """
        parameters = []
        undeclared = self._job_statistics().get("undeclaredQueryParameters", ())

        for parameter in undeclared:
            p_type = parameter["parameterType"]

            if "arrayType" in p_type:
                klass = ArrayQueryParameter
            elif "structTypes" in p_type:
                klass = StructQueryParameter
            else:
                klass = ScalarQueryParameter

            parameters.append(klass.from_api_repr(parameter))

        return parameters

    @property
    def estimated_bytes_processed(self):
        """Return the estimated number of bytes processed by the query.

        See:
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobStatistics2.FIELDS.estimated_bytes_processed

        Returns:
            Optional[int]:
                number of DML rows affected by the job, or None if job is not
                yet complete.
        """
        result = self._job_statistics().get("estimatedBytesProcessed")
        if result is not None:
            result = int(result)
        return result

    def done(self, retry=DEFAULT_RETRY, timeout=None, reload=True):
        """Refresh the job and checks if it is complete.

        Args:
            retry (Optional[google.api_core.retry.Retry]):
                How to retry the call that retrieves query results.
            timeout (Optional[float]):
                The number of seconds to wait for the underlying HTTP transport
                before using ``retry``.
            reload (Optional[bool]):
                If ``True``, make an API call to refresh the job state of
                unfinished jobs before checking. Default ``True``.

        Returns:
            bool: True if the job is complete, False otherwise.
        """
        is_done = (
            # Only consider a QueryJob complete when we know we have the final
            # query results available.
            self._query_results is not None
            and self._query_results.complete
            and self.state == _DONE_STATE
        )
        # Do not refresh if the state is already done, as the job will not
        # change once complete.
        if not reload or is_done:
            return is_done

        # Since the API to getQueryResults can hang up to the timeout value
        # (default of 10 seconds), set the timeout parameter to ensure that
        # the timeout from the futures API is respected. See:
        # https://github.com/GoogleCloudPlatform/google-cloud-python/issues/4135
        timeout_ms = None
        if self._done_timeout is not None:
            # Subtract a buffer for context switching, network latency, etc.
            api_timeout = self._done_timeout - _TIMEOUT_BUFFER_SECS
            api_timeout = max(min(api_timeout, 10), 0)
            self._done_timeout -= api_timeout
            self._done_timeout = max(0, self._done_timeout)
            timeout_ms = int(api_timeout * 1000)

        # If an explicit timeout is not given, fall back to the transport timeout
        # stored in _blocking_poll() in the process of polling for job completion.
        transport_timeout = timeout if timeout is not None else self._transport_timeout

        self._query_results = self._client._get_query_results(
            self.job_id,
            retry,
            project=self.project,
            timeout_ms=timeout_ms,
            location=self.location,
            timeout=transport_timeout,
        )

        # Only reload the job once we know the query is complete.
        # This will ensure that fields such as the destination table are
        # correctly populated.
        if self._query_results.complete and self.state != _DONE_STATE:
            self.reload(retry=retry, timeout=transport_timeout)

        return self.state == _DONE_STATE

    def _blocking_poll(self, timeout=None):
        self._done_timeout = timeout
        self._transport_timeout = timeout
        super(QueryJob, self)._blocking_poll(timeout=timeout)

    @staticmethod
    def _format_for_exception(query, job_id):
        """Format a query for the output in exception message.

        Args:
            query (str): The SQL query to format.
            job_id (str): The ID of the job that ran the query.

        Returns:
            str: A formatted query text.
        """
        template = "\n\n(job ID: {job_id})\n\n{header}\n\n{ruler}\n{body}\n{ruler}"

        lines = query.splitlines()
        max_line_len = max(len(line) for line in lines)

        header = "-----Query Job SQL Follows-----"
        header = "{:^{total_width}}".format(header, total_width=max_line_len + 5)

        # Print out a "ruler" above and below the SQL so we can judge columns.
        # Left pad for the line numbers (4 digits plus ":").
        ruler = "    |" + "    .    |" * (max_line_len // 10)

        # Put line numbers next to the SQL.
        body = "\n".join(
            "{:4}:{}".format(n, line) for n, line in enumerate(lines, start=1)
        )

        return template.format(job_id=job_id, header=header, ruler=ruler, body=body)

    def _begin(self, client=None, retry=DEFAULT_RETRY, timeout=None):
        """API call:  begin the job via a POST request

        See
        https://cloud.google.com/bigquery/docs/reference/rest/v2/jobs/insert

        Args:
            client (Optional[google.cloud.bigquery.client.Client]):
                The client to use. If not passed, falls back to the ``client``
                associated with the job object or``NoneType``.
            retry (Optional[google.api_core.retry.Retry]):
                How to retry the RPC.
            timeout (Optional[float]):
                The number of seconds to wait for the underlying HTTP transport
                before using ``retry``.

        Raises:
            ValueError: If the job has already begun.
        """

        try:
            super(QueryJob, self)._begin(client=client, retry=retry, timeout=timeout)
        except exceptions.GoogleCloudError as exc:
            exc.message += self._format_for_exception(self.query, self.job_id)
            exc.query_job = self
            raise

    def result(
        self,
        page_size=None,
        max_results=None,
        retry=DEFAULT_RETRY,
        timeout=None,
        start_index=None,
    ):
        """Start the job and wait for it to complete and get the result.

        Args:
            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.
            timeout (Optional[float]):
                The number of seconds to wait for the underlying HTTP transport
                before using ``retry``.
                If multiple requests are made under the hood, ``timeout``
                applies to each individual request.
            start_index (Optional[int]):
                The zero-based index of the starting row to read.

        Returns:
            google.cloud.bigquery.table.RowIterator:
                Iterator of row data
                :class:`~google.cloud.bigquery.table.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.

        Raises:
            google.cloud.exceptions.GoogleCloudError:
                If the job failed.
            concurrent.futures.TimeoutError:
                If the job did not complete in the given timeout.
        """
        try:
            super(QueryJob, self).result(retry=retry, timeout=timeout)
        except exceptions.GoogleCloudError as exc:
            exc.message += self._format_for_exception(self.query, self.job_id)
            exc.query_job = self
            raise
        except requests.exceptions.Timeout as exc:
            six.raise_from(concurrent.futures.TimeoutError, exc)

        # If the query job is complete but there are no query results, this was
        # special job, such as a DDL query. Return an empty result set to
        # indicate success and avoid calling tabledata.list on a table which
        # can't be read (such as a view table).
        if self._query_results.total_rows is None:
            return _EmptyRowIterator()

        schema = self._query_results.schema
        dest_table_ref = self.destination
        dest_table = Table(dest_table_ref, schema=schema)
        dest_table._properties["numRows"] = self._query_results.total_rows
        rows = self._client.list_rows(
            dest_table,
            page_size=page_size,
            max_results=max_results,
            start_index=start_index,
            retry=retry,
            timeout=timeout,
        )
        rows._preserve_order = _contains_order_by(self.query)
        return rows

    # If changing the signature of this method, make sure to apply the same
    # changes to table.RowIterator.to_arrow()
    def to_arrow(
        self,
        progress_bar_type=None,
        bqstorage_client=None,
        create_bqstorage_client=True,
    ):
        """[Beta] Create a class:`pyarrow.Table` by loading all pages of a
        table or query.

        Args:
            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 :func:`tqdm.tqdm` function to print a progress bar
                  to :data:`sys.stderr`.
                ``'tqdm_notebook'``
                  Use the :func:`tqdm.tqdm_notebook` function to display a
                  progress bar as a Jupyter notebook widget.
                ``'tqdm_gui'``
                  Use the :func:`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 the ``pyarrow`` and
                ``google-cloud-bigquery-storage`` libraries.

                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

        Returns:
            pyarrow.Table
                A :class:`pyarrow.Table` populated with row data and column
                headers from the query results. The column headers are derived
                from the destination table's schema.

        Raises:
            ValueError:
                If the :mod:`pyarrow` library cannot be imported.

        ..versionadded:: 1.17.0
        """
        if self.query_plan and progress_bar_type:
            start_time = time.time()
            i = 0
            progress_bar = _get_progress_bar(
                progress_bar_type,
                "Query executing stage {}".format(self.query_plan[i].name),
                len(self.query_plan),
                "query",
            )
            while True:
                total = len(self.query_plan)
                self.reload()  # Refreshes the state via a GET request.

                current_stage = self.query_plan[i]
                progress_bar.set_description(
                    "Query executing stage {} and status {} : {:0.2f}s".format(
                        current_stage.name,
                        current_stage.status,
                        time.time() - start_time,
                    ),
                )

                try:
                    query_result = self.result(timeout=0.5)
                    progress_bar.update(total)
                    progress_bar.set_description(
                        "Query complete after {:0.2f}s".format(
                            time.time() - start_time
                        ),
                    )
                    break
                except concurrent.futures.TimeoutError:
                    if current_stage.status == "COMPLETE":
                        if i < total - 1:
                            progress_bar.update(i + 1)
                            i += 1
                    continue

            progress_bar.close()
        else:
            query_result = self.result()

        return query_result.to_arrow(
            progress_bar_type=progress_bar_type,
            bqstorage_client=bqstorage_client,
            create_bqstorage_client=create_bqstorage_client,
        )

    # If changing the signature of this method, make sure to apply the same
    # changes to table.RowIterator.to_dataframe()
    def to_dataframe(
        self,
        bqstorage_client=None,
        dtypes=None,
        progress_bar_type=None,
        create_bqstorage_client=True,
        date_as_object=True,
    ):
        """Return a pandas DataFrame from a QueryJob

        Args:
            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 ``dtype``s. 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
                :func:`~google.cloud.bigquery.table.RowIterator.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

            date_as_object (Optional[bool]):
                If ``True`` (default), cast dates to objects. If ``False``, convert
                to datetime64[ns] dtype.

                ..versionadded:: 1.26.0

        Returns:
            A :class:`~pandas.DataFrame` populated with row data and column
            headers from the query results. The column headers are derived
            from the destination table's schema.

        Raises:
            ValueError: If the `pandas` library cannot be imported.
        """
        query_plan = self.query_plan
        if query_plan and progress_bar_type:
            start_time = time.time()
            i = 0
            progress_bar = _get_progress_bar(
                progress_bar_type,
                "Query executing stage {}".format(query_plan[i].name),
                len(query_plan),
                "query",
            )
            while True:
                total = len(query_plan)
                self.reload()  # Refreshes the state via a GET request.

                current_stage = query_plan[i]
                progress_bar.set_description(
                    "Query executing stage {} and status {} : {:0.2f}s".format(
                        current_stage.name,
                        current_stage.status,
                        time.time() - start_time,
                    )
                )

                try:
                    query_result = self.result(timeout=0.5)
                    progress_bar.update(total)
                    progress_bar.set_description(
                        "Query complete after {:0.2f}s".format(time.time() - start_time)
                    )
                    break
                except concurrent.futures.TimeoutError:
                    if current_stage.status == "COMPLETE":
                        if i < total - 1:
                            progress_bar.update(i + 1)
                            i += 1
                    continue
            progress_bar.close()
        else:
            query_result = self.result()
        return query_result.to_dataframe(
            bqstorage_client=bqstorage_client,
            dtypes=dtypes,
            progress_bar_type=progress_bar_type,
            create_bqstorage_client=create_bqstorage_client,
            date_as_object=date_as_object,
        )

    def __iter__(self):
        return iter(self.result())


class QueryPlanEntryStep(object):
    """Map a single step in a query plan entry.

    Args:
        kind (str): step type.
        substeps (List): names of substeps.
    """

    def __init__(self, kind, substeps):
        self.kind = kind
        self.substeps = list(substeps)

    @classmethod
    def from_api_repr(cls, resource):
        """Factory: construct instance from the JSON repr.

        Args:
            resource (Dict): JSON representation of the entry.

        Returns:
            google.cloud.bigquery.job.QueryPlanEntryStep:
                New instance built from the resource.
        """
        return cls(kind=resource.get("kind"), substeps=resource.get("substeps", ()))

    def __eq__(self, other):
        if not isinstance(other, self.__class__):
            return NotImplemented
        return self.kind == other.kind and self.substeps == other.substeps


class QueryPlanEntry(object):
    """QueryPlanEntry represents a single stage of a query execution plan.

    See
    https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#ExplainQueryStage
    for the underlying API representation within query statistics.
    """

    def __init__(self):
        self._properties = {}

    @classmethod
    def from_api_repr(cls, resource):
        """Factory: construct instance from the JSON repr.

        Args:
            resource(Dict[str: object]):
                ExplainQueryStage representation returned from API.

        Returns:
            google.cloud.bigquery.job.QueryPlanEntry:
                Query plan entry parsed from ``resource``.
        """
        entry = cls()
        entry._properties = resource
        return entry

    @property
    def name(self):
        """Optional[str]: Human-readable name of the stage."""
        return self._properties.get("name")

    @property
    def entry_id(self):
        """Optional[str]: Unique ID for the stage within the plan."""
        return self._properties.get("id")

    @property
    def start(self):
        """Optional[Datetime]: Datetime when the stage started."""
        if self._properties.get("startMs") is None:
            return None
        return _helpers._datetime_from_microseconds(
            int(self._properties.get("startMs")) * 1000.0
        )

    @property
    def end(self):
        """Optional[Datetime]: Datetime when the stage ended."""
        if self._properties.get("endMs") is None:
            return None
        return _helpers._datetime_from_microseconds(
            int(self._properties.get("endMs")) * 1000.0
        )

    @property
    def input_stages(self):
        """List(int): Entry IDs for stages that were inputs for this stage."""
        if self._properties.get("inputStages") is None:
            return []
        return [
            _helpers._int_or_none(entry)
            for entry in self._properties.get("inputStages")
        ]

    @property
    def parallel_inputs(self):
        """Optional[int]: Number of parallel input segments within
        the stage.
        """
        return _helpers._int_or_none(self._properties.get("parallelInputs"))

    @property
    def completed_parallel_inputs(self):
        """Optional[int]: Number of parallel input segments completed."""
        return _helpers._int_or_none(self._properties.get("completedParallelInputs"))

    @property
    def wait_ms_avg(self):
        """Optional[int]: Milliseconds the average worker spent waiting to
        be scheduled.
        """
        return _helpers._int_or_none(self._properties.get("waitMsAvg"))

    @property
    def wait_ms_max(self):
        """Optional[int]: Milliseconds the slowest worker spent waiting to
        be scheduled.
        """
        return _helpers._int_or_none(self._properties.get("waitMsMax"))

    @property
    def wait_ratio_avg(self):
        """Optional[float]: Ratio of time the average worker spent waiting
        to be scheduled, relative to the longest time spent by any worker in
        any stage of the overall plan.
        """
        return self._properties.get("waitRatioAvg")

    @property
    def wait_ratio_max(self):
        """Optional[float]: Ratio of time the slowest worker spent waiting
        to be scheduled, relative to the longest time spent by any worker in
        any stage of the overall plan.
        """
        return self._properties.get("waitRatioMax")

    @property
    def read_ms_avg(self):
        """Optional[int]: Milliseconds the average worker spent reading
        input.
        """
        return _helpers._int_or_none(self._properties.get("readMsAvg"))

    @property
    def read_ms_max(self):
        """Optional[int]: Milliseconds the slowest worker spent reading
        input.
        """
        return _helpers._int_or_none(self._properties.get("readMsMax"))

    @property
    def read_ratio_avg(self):
        """Optional[float]: Ratio of time the average worker spent reading
        input, relative to the longest time spent by any worker in any stage
        of the overall plan.
        """
        return self._properties.get("readRatioAvg")

    @property
    def read_ratio_max(self):
        """Optional[float]: Ratio of time the slowest worker spent reading
        to be scheduled, relative to the longest time spent by any worker in
        any stage of the overall plan.
        """
        return self._properties.get("readRatioMax")

    @property
    def compute_ms_avg(self):
        """Optional[int]: Milliseconds the average worker spent on CPU-bound
        processing.
        """
        return _helpers._int_or_none(self._properties.get("computeMsAvg"))

    @property
    def compute_ms_max(self):
        """Optional[int]: Milliseconds the slowest worker spent on CPU-bound
        processing.
        """
        return _helpers._int_or_none(self._properties.get("computeMsMax"))

    @property
    def compute_ratio_avg(self):
        """Optional[float]: Ratio of time the average worker spent on
        CPU-bound processing, relative to the longest time spent by any
        worker in any stage of the overall plan.
        """
        return self._properties.get("computeRatioAvg")

    @property
    def compute_ratio_max(self):
        """Optional[float]: Ratio of time the slowest worker spent on
        CPU-bound processing, relative to the longest time spent by any
        worker in any stage of the overall plan.
        """
        return self._properties.get("computeRatioMax")

    @property
    def write_ms_avg(self):
        """Optional[int]: Milliseconds the average worker spent writing
        output data.
        """
        return _helpers._int_or_none(self._properties.get("writeMsAvg"))

    @property
    def write_ms_max(self):
        """Optional[int]: Milliseconds the slowest worker spent writing
        output data.
        """
        return _helpers._int_or_none(self._properties.get("writeMsMax"))

    @property
    def write_ratio_avg(self):
        """Optional[float]: Ratio of time the average worker spent writing
        output data, relative to the longest time spent by any worker in any
        stage of the overall plan.
        """
        return self._properties.get("writeRatioAvg")

    @property
    def write_ratio_max(self):
        """Optional[float]: Ratio of time the slowest worker spent writing
        output data, relative to the longest time spent by any worker in any
        stage of the overall plan.
        """
        return self._properties.get("writeRatioMax")

    @property
    def records_read(self):
        """Optional[int]: Number of records read by this stage."""
        return _helpers._int_or_none(self._properties.get("recordsRead"))

    @property
    def records_written(self):
        """Optional[int]: Number of records written by this stage."""
        return _helpers._int_or_none(self._properties.get("recordsWritten"))

    @property
    def status(self):
        """Optional[str]: status of this stage."""
        return self._properties.get("status")

    @property
    def shuffle_output_bytes(self):
        """Optional[int]: Number of bytes written by this stage to
        intermediate shuffle.
        """
        return _helpers._int_or_none(self._properties.get("shuffleOutputBytes"))

    @property
    def shuffle_output_bytes_spilled(self):
        """Optional[int]: Number of bytes written by this stage to
        intermediate shuffle and spilled to disk.
        """
        return _helpers._int_or_none(self._properties.get("shuffleOutputBytesSpilled"))

    @property
    def steps(self):
        """List(QueryPlanEntryStep): List of step operations performed by
        each worker in the stage.
        """
        return [
            QueryPlanEntryStep.from_api_repr(step)
            for step in self._properties.get("steps", [])
        ]


class TimelineEntry(object):
    """TimelineEntry represents progress of a query job at a particular
    point in time.

    See
    https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#querytimelinesample
    for the underlying API representation within query statistics.
    """

    def __init__(self):
        self._properties = {}

    @classmethod
    def from_api_repr(cls, resource):
        """Factory: construct instance from the JSON repr.

        Args:
            resource(Dict[str: object]):
                QueryTimelineSample representation returned from API.

        Returns:
            google.cloud.bigquery.TimelineEntry:
                Timeline sample parsed from ``resource``.
        """
        entry = cls()
        entry._properties = resource
        return entry

    @property
    def elapsed_ms(self):
        """Optional[int]: Milliseconds elapsed since start of query
        execution."""
        return _helpers._int_or_none(self._properties.get("elapsedMs"))

    @property
    def active_units(self):
        """Optional[int]: Current number of input units being processed
        by workers, reported as largest value since the last sample."""
        return _helpers._int_or_none(self._properties.get("activeUnits"))

    @property
    def pending_units(self):
        """Optional[int]: Current number of input units remaining for
        query stages active at this sample time."""
        return _helpers._int_or_none(self._properties.get("pendingUnits"))

    @property
    def completed_units(self):
        """Optional[int]: Current number of input units completed by
        this query."""
        return _helpers._int_or_none(self._properties.get("completedUnits"))

    @property
    def slot_millis(self):
        """Optional[int]: Cumulative slot-milliseconds consumed by
        this query."""
        return _helpers._int_or_none(self._properties.get("totalSlotMs"))


class UnknownJob(_AsyncJob):
    """A job whose type cannot be determined."""

    @classmethod
    def from_api_repr(cls, resource, client):
        """Construct an UnknownJob from the JSON representation.

        Args:
            resource (Dict): JSON representation of a job.
            client (google.cloud.bigquery.client.Client):
                Client connected to BigQuery API.

        Returns:
            UnknownJob: Job corresponding to the resource.
        """
        job_ref_properties = resource.get("jobReference", {"projectId": client.project})
        job_ref = _JobReference._from_api_repr(job_ref_properties)
        job = cls(job_ref, client)
        # Populate the job reference with the project, even if it has been
        # redacted, because we know it should equal that of the request.
        resource["jobReference"] = job_ref_properties
        job._properties = resource
        return job


class ScriptStackFrame(object):
    """Stack frame showing the line/column/procedure name where the current
    evaluation happened.

    Args:
        resource (Map[str, Any]): JSON representation of object.
    """

    def __init__(self, resource):
        self._properties = resource

    @property
    def procedure_id(self):
        """Optional[str]: Name of the active procedure.

        Omitted if in a top-level script.
        """
        return self._properties.get("procedureId")

    @property
    def text(self):
        """str: Text of the current statement/expression."""
        return self._properties.get("text")

    @property
    def start_line(self):
        """int: One-based start line."""
        return _helpers._int_or_none(self._properties.get("startLine"))

    @property
    def start_column(self):
        """int: One-based start column."""
        return _helpers._int_or_none(self._properties.get("startColumn"))

    @property
    def end_line(self):
        """int: One-based end line."""
        return _helpers._int_or_none(self._properties.get("endLine"))

    @property
    def end_column(self):
        """int: One-based end column."""
        return _helpers._int_or_none(self._properties.get("endColumn"))


class ScriptStatistics(object):
    """Statistics for a child job of a script.

    Args:
        resource (Map[str, Any]): JSON representation of object.
    """

    def __init__(self, resource):
        self._properties = resource

    @property
    def stack_frames(self):
        """List[ScriptStackFrame]: Stack trace where the current evaluation
        happened.

        Shows line/column/procedure name of each frame on the stack at the
        point where the current evaluation happened.

        The leaf frame is first, the primary script is last.
        """
        return [
            ScriptStackFrame(frame) for frame in self._properties.get("stackFrames", [])
        ]

    @property
    def evaluation_kind(self):
        """str: Indicates the type of child job.

        Possible values include ``STATEMENT`` and ``EXPRESSION``.
        """
        return self._properties.get("evaluationKind")