Python Client for Google BigQuery

Querying massive datasets can be time consuming and expensive without the right hardware and infrastructure. Google BigQuery solves this problem by enabling super-fast, SQL queries against append-mostly tables, using the processing power of Google’s infrastructure.

Quick Start

In order to use this library, you first need to go through the following steps:

Installation

Install this library in a virtualenv using pip. virtualenv is a tool to create isolated Python environments. The basic problem it addresses is one of dependencies and versions, and indirectly permissions.

With virtualenv, it’s possible to install this library without needing system install permissions, and without clashing with the installed system dependencies.

Supported Python Versions

Python >= 3.7

Unsupported Python Versions

Python == 2.7, Python == 3.5, Python == 3.6.

The last version of this library compatible with Python 2.7 and 3.5 is google-cloud-bigquery==1.28.0.

Mac/Linux

pip install virtualenv
virtualenv <your-env>
source <your-env>/bin/activate
<your-env>/bin/pip install google-cloud-bigquery

Windows

pip install virtualenv
virtualenv <your-env>
<your-env>\Scripts\activate
<your-env>\Scripts\pip.exe install google-cloud-bigquery

Example Usage

Perform a query

from google.cloud import bigquery

client = bigquery.Client()

# Perform a query.
QUERY = (
    'SELECT name FROM `bigquery-public-data.usa_names.usa_1910_2013` '
    'WHERE state = "TX" '
    'LIMIT 100')
query_job = client.query(QUERY)  # API request
rows = query_job.result()  # Waits for query to finish

for row in rows:
    print(row.name)

Instrumenting With OpenTelemetry

This application uses OpenTelemetry to output tracing data from API calls to BigQuery. To enable OpenTelemetry tracing in the BigQuery client the following PyPI packages need to be installed:

pip install google-cloud-bigquery[opentelemetry] opentelemetry-exporter-gcp-trace

After installation, OpenTelemetry can be used in the BigQuery client and in BigQuery jobs. First, however, an exporter must be specified for where the trace data will be outputted to. An example of this can be found here:

from opentelemetry import trace
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.trace.export import BatchSpanProcessor
from opentelemetry.exporter.cloud_trace import CloudTraceSpanExporter
tracer_provider = TracerProvider()
tracer_provider = BatchSpanProcessor(CloudTraceSpanExporter())
trace.set_tracer_provider(TracerProvider())

In this example all tracing data will be published to the Google Cloud Trace console. For more information on OpenTelemetry, please consult the OpenTelemetry documentation.

Metadata

Release files for arrivy-google-cloud-bigquery 3.14.4

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Source distribution (sdist)

Source distribution for arrivy-google-cloud-bigquery 3.14.4
File	Size	Uploaded	Provenance
arrivy-google-cloud-bigquery-3.14.4.tar.gz	431.8 kB	Jan 4, 2024	Without provenance	Details

Release files / arrivy-google-cloud-bigquery-3.14.4.tar.gz

Download URL	arrivy-google-cloud-bigquery-3.14.4.tar.gz
Size	431.8 kB
Tags	Source
SHA-256 checksum How to use checksums	`ceca5269827f7f3e46ced0e4970f7a88f67f1aad5bcb88f50ec0dedb66797123`
BLAKE2b-256 checksum How to use checksums	`70195454653f726c2f0433479513dd9ed33b556ac0b41d92512a5bcc09097933`
Upload date	Jan 4, 2024
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/4.0.2 CPython/3.11.6`

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