Mettre à jour une table avec le langage LMD

Mettre à jour des données dans une table BigQuery à l'aide d'une requête LMD

Exemple de code

Java

Avant d'essayer cet exemple, suivez les instructions de configuration pour Java du guide de démarrage rapide de BigQuery : Utiliser les bibliothèques clientes. Pour en savoir plus, consultez la documentation de référence de l'API BigQuery pour Java.

Pour vous authentifier auprès de BigQuery, configurez le service Identifiants par défaut de l'application. Pour en savoir plus, consultez la page Configurer l'authentification pour les bibliothèques clientes.

import com.google.cloud.bigquery.BigQuery;
import com.google.cloud.bigquery.BigQueryException;
import com.google.cloud.bigquery.BigQueryOptions;
import com.google.cloud.bigquery.FormatOptions;
import com.google.cloud.bigquery.Job;
import com.google.cloud.bigquery.JobId;
import com.google.cloud.bigquery.QueryJobConfiguration;
import com.google.cloud.bigquery.TableDataWriteChannel;
import com.google.cloud.bigquery.TableId;
import com.google.cloud.bigquery.TableResult;
import com.google.cloud.bigquery.WriteChannelConfiguration;
import java.io.IOException;
import java.io.OutputStream;
import java.nio.channels.Channels;
import java.nio.file.FileSystems;
import java.nio.file.Files;
import java.nio.file.Path;
import java.util.UUID;

// Sample to update data in BigQuery tables using DML query
public class UpdateTableDml {

  public static void main(String[] args) throws IOException, InterruptedException {
    // TODO(developer): Replace these variables before running the sample.
    String datasetName = "MY_DATASET_NAME";
    String tableName = "MY_TABLE_NAME";
    updateTableDml(datasetName, tableName);
  }

  public static void updateTableDml(String datasetName, String tableName)
      throws IOException, InterruptedException {
    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();

      // Load JSON file into UserSessions table
      TableId tableId = TableId.of(datasetName, tableName);

      WriteChannelConfiguration writeChannelConfiguration =
          WriteChannelConfiguration.newBuilder(tableId)
              .setFormatOptions(FormatOptions.json())
              .build();

      // Imports a local JSON file into a table.
      Path jsonPath =
          FileSystems.getDefault().getPath("src/test/resources", "userSessionsData.json");

      // The location and JobName must be specified; other fields can be auto-detected.
      String jobName = "jobId_" + UUID.randomUUID().toString();
      JobId jobId = JobId.newBuilder().setLocation("us").setJob(jobName).build();

      try (TableDataWriteChannel writer = bigquery.writer(jobId, writeChannelConfiguration);
          OutputStream stream = Channels.newOutputStream(writer)) {
        Files.copy(jsonPath, stream);
      }

      // Get the Job created by the TableDataWriteChannel and wait for it to complete.
      Job job = bigquery.getJob(jobId);
      Job completedJob = job.waitFor();
      if (completedJob == null) {
        System.out.println("Job not executed since it no longer exists.");
        return;
      } else if (completedJob.getStatus().getError() != null) {
        System.out.println(
            "BigQuery was unable to load local file to the table due to an error: \n"
                + job.getStatus().getError());
        return;
      }

      System.out.println(
          job.getStatistics().toString() + " userSessionsData json uploaded successfully");

      // Write a DML query to modify UserSessions table
      // To create DML query job to mask the last octet in every row's ip_address column
      String dmlQuery =
          String.format(
              "UPDATE `%s.%s` \n"
                  + "SET ip_address = REGEXP_REPLACE(ip_address, r\"(\\.[0-9]+)$\", \".0\")\n"
                  + "WHERE TRUE",
              datasetName, tableName);

      QueryJobConfiguration dmlQueryConfig = QueryJobConfiguration.newBuilder(dmlQuery).build();

      // Execute the query.
      TableResult result = bigquery.query(dmlQueryConfig);

      // Print the results.
      result.iterateAll().forEach(rows -> rows.forEach(row -> System.out.println(row.getValue())));

      System.out.println("Table updated successfully using DML");
    } catch (BigQueryException e) {
      System.out.println("Table update failed \n" + e.toString());
    }
  }
}

Python

Avant d'essayer cet exemple, suivez les instructions de configuration pour Python du guide de démarrage rapide de BigQuery : Utiliser les bibliothèques clientes. Pour en savoir plus, consultez la documentation de référence de l'API BigQuery pour Python.

import pathlib
from typing import Dict, Optional

from google.cloud import bigquery
from google.cloud.bigquery import enums

def load_from_newline_delimited_json(
    client: bigquery.Client,
    filepath: pathlib.Path,
    project_id: str,
    dataset_id: str,
    table_id: str,
) -> None:
    full_table_id = f"{project_id}.{dataset_id}.{table_id}"
    job_config = bigquery.LoadJobConfig()
    job_config.source_format = enums.SourceFormat.NEWLINE_DELIMITED_JSON
    job_config.schema = [
        bigquery.SchemaField("id", enums.SqlTypeNames.STRING),
        bigquery.SchemaField("user_id", enums.SqlTypeNames.INTEGER),
        bigquery.SchemaField("login_time", enums.SqlTypeNames.TIMESTAMP),
        bigquery.SchemaField("logout_time", enums.SqlTypeNames.TIMESTAMP),
        bigquery.SchemaField("ip_address", enums.SqlTypeNames.STRING),
    ]

    with open(filepath, "rb") as json_file:
        load_job = client.load_table_from_file(
            json_file, full_table_id, job_config=job_config
        )

    # Wait for load job to finish.
    load_job.result()

def update_with_dml(
    client: bigquery.Client, project_id: str, dataset_id: str, table_id: str
) -> int:
    query_text = f"""
    UPDATE `{project_id}.{dataset_id}.{table_id}`
    SET ip_address = REGEXP_REPLACE(ip_address, r"(\\.[0-9]+)$", ".0")
    WHERE TRUE
    """
    query_job = client.query(query_text)

    # Wait for query job to finish.
    query_job.result()

    assert query_job.num_dml_affected_rows is not None

    print(f"DML query modified {query_job.num_dml_affected_rows} rows.")
    return query_job.num_dml_affected_rows

def run_sample(override_values: Optional[Dict[str, str]] = None) -> int:
    if override_values is None:
        override_values = {}

    client = bigquery.Client()
    filepath = pathlib.Path(__file__).parent / "user_sessions_data.json"
    project_id = client.project
    dataset_id = "sample_db"
    table_id = "UserSessions"
    load_from_newline_delimited_json(client, filepath, project_id, dataset_id, table_id)
    return update_with_dml(client, project_id, dataset_id, table_id)

Étapes suivantes

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