Secuencia de comandos de consulta

Ejecuta una secuencia de comandos de consulta

Muestra de código

Java

Antes de probar este ejemplo, sigue las instrucciones de configuración para Java incluidas en la guía de inicio rápido de BigQuery sobre cómo usar bibliotecas cliente. Para obtener más información, consulta la documentación de referencia de la API de BigQuery para Java.

Para autenticarte en BigQuery, configura las credenciales predeterminadas de la aplicación. Si deseas obtener más información, consulta Configura la autenticación para bibliotecas cliente.

import com.google.api.gax.paging.Page;
import com.google.cloud.bigquery.BigQuery;
import com.google.cloud.bigquery.BigQueryException;
import com.google.cloud.bigquery.BigQueryOptions;
import com.google.cloud.bigquery.Job;
import com.google.cloud.bigquery.JobInfo;
import com.google.cloud.bigquery.QueryJobConfiguration;

// Sample to run query script.
public class QueryScript {

  public static void main(String[] args) {
    String script =
        "-- Declare a variable to hold names as an array.\n"
            + "DECLARE top_names ARRAY<STRING>;\n"
            + "-- Build an array of the top 100 names from the year 2017.\n"
            + "SET top_names = (\n"
            + "  SELECT ARRAY_AGG(name ORDER BY number DESC LIMIT 100)\n"
            + "  FROM `bigquery-public-data`.usa_names.usa_1910_current\n"
            + "  WHERE year = 2017\n"
            + ");\n"
            + "-- Which names appear as words in Shakespeare's plays?\n"
            + "SELECT\n"
            + "  name AS shakespeare_name\n"
            + "FROM UNNEST(top_names) AS name\n"
            + "WHERE name IN (\n"
            + "  SELECT word\n"
            + "  FROM `bigquery-public-data`.samples.shakespeare\n"
            + ");";
    queryScript(script);
  }

  public static void queryScript(String script) {
    try {
      // Initialize client that will be used to send requests. This client only needs to be created
      // once, and can be reused for multiple requests.
      BigQuery bigquery = BigQueryOptions.getDefaultInstance().getService();

      QueryJobConfiguration queryConfig = QueryJobConfiguration.newBuilder(script).build();
      Job createJob = bigquery.create(JobInfo.of(queryConfig));
      // Wait for the whole script to finish.
      JobInfo jobInfo = createJob.waitFor();
      String parentJobId = jobInfo.getJobId().getJob();

      // Fetch jobs created by the SQL script.
      Page<Job> childJobs = bigquery.listJobs(BigQuery.JobListOption.parentJobId(parentJobId));
      childJobs
          .iterateAll()
          .forEach(job -> System.out.printf("Child Job Id: ", job.getJobId().getJob()));

      System.out.println("Query script performed successfully.");
    } catch (BigQueryException | InterruptedException e) {
      System.out.println("Query not performed \n" + e.toString());
    }
  }
}

Python

Antes de probar este ejemplo, sigue las instrucciones de configuración para Python incluidas en la guía de inicio rápido de BigQuery sobre cómo usar bibliotecas cliente. Para obtener más información, consulta la documentación de referencia de la API de BigQuery para Python.

Para autenticarte en BigQuery, configura las credenciales predeterminadas de la aplicación. Si deseas obtener más información, consulta Configura la autenticación para bibliotecas cliente.

from google.cloud import bigquery

# Construct a BigQuery client object.
client = bigquery.Client()

# Run a SQL script.
sql_script = """
-- Declare a variable to hold names as an array.
DECLARE top_names ARRAY<STRING>;

-- Build an array of the top 100 names from the year 2017.
SET top_names = (
SELECT ARRAY_AGG(name ORDER BY number DESC LIMIT 100)
FROM `bigquery-public-data.usa_names.usa_1910_2013`
WHERE year = 2000
);

-- Which names appear as words in Shakespeare's plays?
SELECT
name AS shakespeare_name
FROM UNNEST(top_names) AS name
WHERE name IN (
SELECT word
FROM `bigquery-public-data.samples.shakespeare`
);
"""
parent_job = client.query(sql_script)

# Wait for the whole script to finish.
rows_iterable = parent_job.result()
print("Script created {} child jobs.".format(parent_job.num_child_jobs))

# Fetch result rows for the final sub-job in the script.
rows = list(rows_iterable)
print(
    "{} of the top 100 names from year 2000 also appear in Shakespeare's works.".format(
        len(rows)
    )
)

# Fetch jobs created by the SQL script.
child_jobs_iterable = client.list_jobs(parent_job=parent_job)
for child_job in child_jobs_iterable:
    child_rows = list(child_job.result())
    print(
        "Child job with ID {} produced {} row(s).".format(
            child_job.job_id, len(child_rows)
        )
    )

¿Qué sigue?

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