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Merge pull request googleapis#4245 from GoogleCloudPlatform/bigquery-b2
BigQuery Beta 2 Changes
2 parents e354310 + df016c2 commit 09cf23a

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‎bigquery/.coveragerc‎

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pragma: NO COVER
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# Ignore debug-only repr
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def __repr__
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# Ignore abstract methods
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raise NotImplementedError

‎bigquery/README.rst‎

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Querying massive datasets can be time consuming and expensive without the
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right hardware and infrastructure. Google `BigQuery`_ (`BigQuery API docs`_)
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solves this problem by enabling super-fast, SQL-like queries against
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append-only tables, using the processing power of Google's infrastructure.
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solves this problem by enabling super-fast, SQL queries against
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append-mostly tables, using the processing power of Google's infrastructure.
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.. _BigQuery: https://cloud.google.com/bigquery/what-is-bigquery
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.. _BigQuery API docs: https://cloud.google.com/bigquery/docs/reference/v2/
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Create a dataset
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~~~~~~~~~~~~~~~~
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.. code:: python
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from google.cloud import bigquery
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from google.cloud.bigquery import Dataset
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client = bigquery.Client()
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dataset_ref = client.dataset('dataset_name')
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dataset = Dataset(dataset_ref)
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dataset.description = 'my dataset'
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dataset = client.create_dataset(dataset) # API request
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Load data from CSV
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~~~~~~~~~~~~~~~~~~
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import csv
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from google.cloud import bigquery
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from google.cloud.bigquery import LoadJobConfig
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from google.cloud.bigquery import SchemaField
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client = bigquery.Client()
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dataset = client.dataset('dataset_name')
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dataset.create() # API request
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SCHEMA = [
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SchemaField('full_name', 'STRING', mode='required'),
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SchemaField('age', 'INTEGER', mode='required'),
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]
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table = dataset.table('table_name', SCHEMA)
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table.create()
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table_ref = client.dataset('dataset_name').table('table_name')
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load_config = LoadJobConfig()
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load_config.skip_leading_rows = 1
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load_config.schema = SCHEMA
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with open('csv_file', 'rb') as readable:
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table.upload_from_file(
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readable, source_format='CSV', skip_leading_rows=1)
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# Contents of csv_file.csv:
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# Name,Age
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# Tim,99
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with open('csv_file.csv', 'rb') as readable:
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client.load_table_from_file(
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readable, table_ref, job_config=load_config) # API request
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Perform a synchronous query
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~~~~~~~~~~~~~~~~~~~~~~~~~~~
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Perform a query
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~~~~~~~~~~~~~~~
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.. code:: python
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# Perform a synchronous query.
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# Perform a query.
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QUERY = (
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'SELECT name FROM [bigquery-public-data:usa_names.usa_1910_2013] '
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'WHERE state = "TX"')
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query = client.run_sync_query('%s LIMIT 100' % QUERY)
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query.timeout_ms = TIMEOUT_MS
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query.run()
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for row in query.rows:
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print(row)
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'SELECT name FROM `bigquery-public-data.usa_names.usa_1910_2013` '
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'WHERE state = "TX" '
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'LIMIT 100')
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query_job = client.query(QUERY) # API request
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rows = query_job.result() # Waits for query to finish
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for row in rows:
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print(row.name)
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See the ``google-cloud-python`` API `BigQuery documentation`_ to learn how

‎bigquery/google/cloud/bigquery/__init__.py‎

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from pkg_resources import get_distribution
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__version__ = get_distribution('google-cloud-bigquery').version
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from google.cloud.bigquery._helpers import ArrayQueryParameter
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from google.cloud.bigquery._helpers import ScalarQueryParameter
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from google.cloud.bigquery._helpers import StructQueryParameter
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from google.cloud.bigquery._helpers import DEFAULT_RETRY
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from google.cloud.bigquery.client import Client
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from google.cloud.bigquery.dataset import AccessGrant
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from google.cloud.bigquery.dataset import AccessEntry
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from google.cloud.bigquery.dataset import Dataset
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from google.cloud.bigquery.dataset import DatasetReference
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from google.cloud.bigquery.job import CopyJob
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from google.cloud.bigquery.job import CopyJobConfig
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from google.cloud.bigquery.job import ExtractJob
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from google.cloud.bigquery.job import ExtractJobConfig
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from google.cloud.bigquery.job import QueryJob
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from google.cloud.bigquery.job import QueryJobConfig
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from google.cloud.bigquery.job import LoadJob
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from google.cloud.bigquery.job import LoadJobConfig
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from google.cloud.bigquery.query import ArrayQueryParameter
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from google.cloud.bigquery.query import ScalarQueryParameter
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from google.cloud.bigquery.query import StructQueryParameter
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from google.cloud.bigquery.query import UDFResource
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from google.cloud.bigquery.schema import SchemaField
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from google.cloud.bigquery.table import Table
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from google.cloud.bigquery.table import TableReference
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from google.cloud.bigquery.external_config import ExternalConfig
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from google.cloud.bigquery.external_config import BigtableOptions
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from google.cloud.bigquery.external_config import BigtableColumnFamily
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from google.cloud.bigquery.external_config import BigtableColumn
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from google.cloud.bigquery.external_config import CSVOptions
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from google.cloud.bigquery.external_config import GoogleSheetsOptions
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__all__ = [
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'__version__', 'AccessGrant', 'ArrayQueryParameter', 'Client',
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'Dataset', 'ScalarQueryParameter', 'SchemaField', 'StructQueryParameter',
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'__version__',
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'Client',
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# Queries
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'QueryJob',
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'QueryJobConfig',
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'ArrayQueryParameter',
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'ScalarQueryParameter',
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'StructQueryParameter',
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# Datasets
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'Dataset',
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'DatasetReference',
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'AccessEntry',
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# Tables
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'Table',
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'TableReference',
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'CopyJob',
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'CopyJobConfig',
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'ExtractJob',
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'ExtractJobConfig',
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'LoadJob',
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'LoadJobConfig',
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# Shared helpers
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'SchemaField',
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'UDFResource',
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'ExternalConfig',
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'BigtableOptions',
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'BigtableColumnFamily',
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'BigtableColumn',
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'CSVOptions',
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'GoogleSheetsOptions',
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'DEFAULT_RETRY',
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]

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