DDL로 루틴 만들기

DDL 쿼리를 통해 루틴을 만듭니다.

코드 샘플

자바

이 샘플을 사용해 보기 전에 BigQuery 빠른 시작: 클라이언트 라이브러리 사용의 자바 설정 안내를 따르세요. 자세한 내용은 BigQuery 자바 API 참조 문서를 확인하세요.

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 create a routine using DDL
public class CreateRoutineDdl {

  public static void main(String[] args) {
    // TODO(developer): Replace these variables before running the sample.
    String projectId = "MY_PROJECT_ID";
    String datasetId = "MY_DATASET_ID";
    String routineId = "MY_ROUTINE_ID";
    String sql =
        "CREATE FUNCTION "
            + "`"
            + projectId
            + "."
            + datasetId
            + "."
            + routineId
            + "`"
            + "( arr ARRAY<STRUCT<name STRING, val INT64>>) AS "
            + "( (SELECT SUM(IF(elem.name = \"foo\",elem.val,null)) FROM UNNEST(arr) AS elem))";
    createRoutineDdl(sql);
  }

  public static void createRoutineDdl(String sql) {
    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 config = QueryJobConfiguration.newBuilder(sql).build();

      // create a routine using query and it will wait to complete job.
      Job job = bigquery.create(JobInfo.of(config));
      job = job.waitFor();
      if (job.isDone()) {
        System.out.println("Routine created successfully");
      } else {
        System.out.println("Routine was not created");
      }
    } catch (BigQueryException | InterruptedException e) {
      System.out.println("Routine was not created. \n" + e.toString());
    }
  }
}

Node.js

이 샘플을 사용해 보기 전에 BigQuery 빠른 시작: 클라이언트 라이브러리 사용의 Node.js 설정 안내를 따르세요. 자세한 내용은 BigQuery Node.js API 참조 문서를 확인하세요.

// Import the Google Cloud client library and create a client
const {BigQuery} = require('@google-cloud/bigquery');
const bigquery = new BigQuery();

async function createRoutineDDL() {
  // Creates a routine using DDL.

  /**
   * TODO(developer): Uncomment the following lines before running the sample.
   */
  // projectId = 'my_project';
  // const datasetId = 'my_dataset';
  // const routineId = 'my_routine';

  const query = `CREATE FUNCTION \`${projectId}.${datasetId}.${routineId}\`(
      arr ARRAY<STRUCT<name STRING, val INT64>>
  ) AS (
      (SELECT SUM(IF(elem.name = "foo",elem.val,null)) FROM UNNEST(arr) AS elem)
  )`;

  const options = {
    query: query,
  };

  // Run the query as a job
  const [job] = await bigquery.createQueryJob(options);
  console.log(`Job ${job.id} started.`);

  // Wait for the query to finish
  await job.getQueryResults();

  console.log(`Routine ${routineId} created.`);
}
createRoutineDDL();

Python

이 샘플을 사용해 보기 전에 BigQuery 빠른 시작: 클라이언트 라이브러리 사용의 Python 설정 안내를 따르세요. 자세한 내용은 BigQuery Python API 참조 문서를 확인하세요.


from google.cloud import bigquery

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

# TODO(developer): Choose a fully-qualified ID for the routine.
# routine_id = "my-project.my_dataset.my_routine"

sql = """
CREATE FUNCTION `{}`(
    arr ARRAY<STRUCT<name STRING, val INT64>>
) AS (
    (SELECT SUM(IF(elem.name = "foo",elem.val,null)) FROM UNNEST(arr) AS elem)
)
""".format(
    routine_id
)
query_job = client.query(sql)  # Make an API request.
query_job.result()  # Wait for the job to complete.

print("Created routine {}".format(query_job.ddl_target_routine))

다음 단계

다른 Google Cloud 제품의 코드 샘플을 검색하고 필터링하려면 Google Cloud 샘플 브라우저를 참조하세요.