자동 감지된 스키마를 사용하여 Cloud Storage에서 CSV 파일을 로드합니다.
더 살펴보기
이 코드 샘플이 포함된 자세한 문서는 다음을 참조하세요.
코드 샘플
Go
이 샘플을 사용해 보기 전에 BigQuery 빠른 시작: 클라이언트 라이브러리 사용의 Go 설정 안내를 따르세요. 자세한 내용은 BigQuery Go API 참조 문서를 확인하세요.
import (
"context"
"fmt"
"cloud.google.com/go/bigquery"
)
// importCSVAutodetectSchema demonstrates loading data from CSV data in Cloud Storage
// and using schema autodetection to identify the available columns.
func importCSVAutodetectSchema(projectID, datasetID, tableID string) error {
// projectID := "my-project-id"
// datasetID := "mydataset"
// tableID := "mytable"
ctx := context.Background()
client, err := bigquery.NewClient(ctx, projectID)
if err != nil {
return fmt.Errorf("bigquery.NewClient: %v", err)
}
defer client.Close()
gcsRef := bigquery.NewGCSReference("gs://cloud-samples-data/bigquery/us-states/us-states.csv")
gcsRef.SourceFormat = bigquery.CSV
gcsRef.AutoDetect = true
gcsRef.SkipLeadingRows = 1
loader := client.Dataset(datasetID).Table(tableID).LoaderFrom(gcsRef)
job, err := loader.Run(ctx)
if err != nil {
return err
}
status, err := job.Wait(ctx)
if err != nil {
return err
}
if status.Err() != nil {
return fmt.Errorf("job completed with error: %v", status.Err())
}
return nil
}
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.CsvOptions;
import com.google.cloud.bigquery.Job;
import com.google.cloud.bigquery.JobInfo;
import com.google.cloud.bigquery.LoadJobConfiguration;
import com.google.cloud.bigquery.TableId;
// Sample to load CSV data with autodetect schema from Cloud Storage into a new BigQuery table
public class LoadCsvFromGcsAutodetect {
public static void main(String[] args) {
// TODO(developer): Replace these variables before running the sample.
String datasetName = "MY_DATASET_NAME";
String tableName = "MY_TABLE_NAME";
String sourceUri = "gs://cloud-samples-data/bigquery/us-states/us-states.csv";
loadCsvFromGcsAutodetect(datasetName, tableName, sourceUri);
}
public static void loadCsvFromGcsAutodetect(
String datasetName, String tableName, String sourceUri) {
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();
TableId tableId = TableId.of(datasetName, tableName);
// Skip header row in the file.
CsvOptions csvOptions = CsvOptions.newBuilder().setSkipLeadingRows(1).build();
LoadJobConfiguration loadConfig =
LoadJobConfiguration.newBuilder(tableId, sourceUri)
.setFormatOptions(csvOptions)
.setAutodetect(true)
.build();
// Load data from a GCS CSV file into the table
Job job = bigquery.create(JobInfo.of(loadConfig));
// Blocks until this load table job completes its execution, either failing or succeeding.
job = job.waitFor();
if (job.isDone() && job.getStatus().getError() == null) {
System.out.println("CSV Autodetect from GCS successfully loaded in a table");
} else {
System.out.println(
"BigQuery was unable to load into the table due to an error:"
+ job.getStatus().getError());
}
} catch (BigQueryException | InterruptedException e) {
System.out.println("Column not added during load append \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 libraries
const {BigQuery} = require('@google-cloud/bigquery');
const {Storage} = require('@google-cloud/storage');
// Instantiate clients
const bigquery = new BigQuery();
const storage = new Storage();
/**
* TODO(developer): Uncomment the following lines before running the sample
*/
// const datasetId = "my_dataset";
// const tableId = "my_table";
/**
* This sample loads the CSV file at
* https://storage.googleapis.com/cloud-samples-data/bigquery/us-states/us-states.csv
*
* TODO(developer): Replace the following lines with the path to your file
*/
const bucketName = 'cloud-samples-data';
const filename = 'bigquery/us-states/us-states.csv';
async function loadCSVFromGCSAutodetect() {
// Imports a GCS file into a table with autodetected schema.
// Configure the load job. For full list of options, see:
// https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationLoad
const metadata = {
sourceFormat: 'CSV',
skipLeadingRows: 1,
autodetect: true,
location: 'US',
};
// Load data from a Google Cloud Storage file into the table
const [job] = await bigquery
.dataset(datasetId)
.table(tableId)
.load(storage.bucket(bucketName).file(filename), metadata);
// load() waits for the job to finish
console.log(`Job ${job.id} completed.`);
}
PHP
이 샘플을 사용해 보기 전에 BigQuery 빠른 시작: 클라이언트 라이브러리 사용의 PHP 설정 안내를 따르세요. 자세한 내용은 BigQuery PHP API 참조 문서를 참조하세요.
use Google\Cloud\BigQuery\BigQueryClient;
use Google\Cloud\Core\ExponentialBackoff;
/** Uncomment and populate these variables in your code */
// $projectId = 'The Google project ID';
// $datasetId = 'The BigQuery dataset ID';
// $tableId = 'us_states';
// instantiate the bigquery table service
$bigQuery = new BigQueryClient([
'projectId' => $projectId,
]);
$dataset = $bigQuery->dataset($datasetId);
$table = $dataset->table($tableId);
// create the import job
$gcsUri = 'gs://cloud-samples-data/bigquery/us-states/us-states.csv';
$loadConfig = $table->loadFromStorage($gcsUri)->autodetect(true)->skipLeadingRows(1);
$job = $table->runJob($loadConfig);
// poll the job until it is complete
$backoff = new ExponentialBackoff(10);
$backoff->execute(function () use ($job) {
print('Waiting for job to complete' . PHP_EOL);
$job->reload();
if (!$job->isComplete()) {
throw new Exception('Job has not yet completed', 500);
}
});
// check if the job has errors
if (isset($job->info()['status']['errorResult'])) {
$error = $job->info()['status']['errorResult']['message'];
printf('Error running job: %s' . PHP_EOL, $error);
} else {
print('Data imported successfully' . PHP_EOL);
}
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): Set table_id to the ID of the table to create.
# table_id = "your-project.your_dataset.your_table_name
# Set the encryption key to use for the destination.
# TODO: Replace this key with a key you have created in KMS.
# kms_key_name = "projects/{}/locations/{}/keyRings/{}/cryptoKeys/{}".format(
# "cloud-samples-tests", "us", "test", "test"
# )
job_config = bigquery.LoadJobConfig(
autodetect=True,
skip_leading_rows=1,
# The source format defaults to CSV, so the line below is optional.
source_format=bigquery.SourceFormat.CSV,
)
uri = "gs://cloud-samples-data/bigquery/us-states/us-states.csv"
load_job = client.load_table_from_uri(
uri, table_id, job_config=job_config
) # Make an API request.
load_job.result() # Waits for the job to complete.
destination_table = client.get_table(table_id)
print("Loaded {} rows.".format(destination_table.num_rows))
다음 단계
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