Write to destination table

Run a query on the natality public dataset and write the results to a destination table.

Explore further

For detailed documentation that includes this code sample, see the following:

• Use Dataproc, BigQuery, and Apache Spark ML for Machine Learning

Code sample

Python

Before trying this sample, follow the Python setup instructions in the BigQuery quickstart using client libraries. For more information, see the BigQuery Python API reference documentation.

To authenticate to BigQuery, set up Application Default Credentials. For more information, see Set up authentication for client libraries.

"""Create a Google BigQuery linear regression input table.

In the code below, the following actions are taken:
* A new dataset is created "natality_regression."
* A query is run against the public dataset,
    bigquery-public-data.samples.natality, selecting only the data of
    interest to the regression, the output of which is stored in a new
    "regression_input" table.
* The output table is moved over the wire to the user's default project via
    the built-in BigQuery Connector for Spark that bridges BigQuery and
    Cloud Dataproc.
"""

from google.cloud import bigquery

# Create a new Google BigQuery client using Google Cloud Platform project
# defaults.
client = bigquery.Client()

# Prepare a reference to a new dataset for storing the query results.
dataset_id = "natality_regression"
dataset_id_full = f"{client.project}.{dataset_id}"

dataset = bigquery.Dataset(dataset_id_full)

# Create the new BigQuery dataset.
dataset = client.create_dataset(dataset)

# Configure the query job.
job_config = bigquery.QueryJobConfig()

# Set the destination table to where you want to store query results.
# As of google-cloud-bigquery 1.11.0, a fully qualified table ID can be
# used in place of a TableReference.
job_config.destination = f"{dataset_id_full}.regression_input"

# Set up a query in Standard SQL, which is the default for the BigQuery
# Python client library.
# The query selects the fields of interest.
query = """
    SELECT
        weight_pounds, mother_age, father_age, gestation_weeks,
        weight_gain_pounds, apgar_5min
    FROM
        `bigquery-public-data.samples.natality`
    WHERE
        weight_pounds IS NOT NULL
        AND mother_age IS NOT NULL
        AND father_age IS NOT NULL
        AND gestation_weeks IS NOT NULL
        AND weight_gain_pounds IS NOT NULL
        AND apgar_5min IS NOT NULL
"""

# Run the query.
client.query_and_wait(query, job_config=job_config)  # Waits for the query to finish

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