使用批量优先级运行查询作业。
包含此代码示例的文档页面
如需查看上下文中使用的代码示例,请参阅以下文档:
代码示例
Go
在尝试此示例之前,请按照《BigQuery 快速入门:使用客户端库》中的 Go 设置说明进行操作。如需了解详情,请参阅 BigQuery Go API 参考文档。
import (
"context"
"fmt"
"io"
"time"
"cloud.google.com/go/bigquery"
)
// queryBatch demonstrates issuing a query job using batch priority.
func queryBatch(w io.Writer, projectID, dstDatasetID, dstTableID string) error {
// projectID := "my-project-id"
// dstDatasetID := "mydataset"
// dstTableID := "mytable"
ctx := context.Background()
client, err := bigquery.NewClient(ctx, projectID)
if err != nil {
return fmt.Errorf("bigquery.NewClient: %v", err)
}
defer client.Close()
// Build an aggregate table.
q := client.Query(`
SELECT
corpus,
SUM(word_count) as total_words,
COUNT(1) as unique_words
FROM ` + "`bigquery-public-data.samples.shakespeare`" + `
GROUP BY corpus;`)
q.Priority = bigquery.BatchPriority
q.QueryConfig.Dst = client.Dataset(dstDatasetID).Table(dstTableID)
// Start the job.
job, err := q.Run(ctx)
if err != nil {
return err
}
// Job is started and will progress without interaction.
// To simulate other work being done, sleep a few seconds.
time.Sleep(5 * time.Second)
status, err := job.Status(ctx)
if err != nil {
return err
}
state := "Unknown"
switch status.State {
case bigquery.Pending:
state = "Pending"
case bigquery.Running:
state = "Running"
case bigquery.Done:
state = "Done"
}
// You can continue to monitor job progress until it reaches
// the Done state by polling periodically. In this example,
// we print the latest status.
fmt.Fprintf(w, "Job %s in Location %s currently in state: %s\n", job.ID(), job.Location(), state)
return nil
}
Java
试用此示例之前,请按照《BigQuery 快速入门:使用客户端库》中的 Java 设置说明进行操作。 如需了解详情,请参阅 BigQuery Java API 参考文档。
import com.google.cloud.bigquery.BigQuery;
import com.google.cloud.bigquery.BigQueryException;
import com.google.cloud.bigquery.BigQueryOptions;
import com.google.cloud.bigquery.QueryJobConfiguration;
import com.google.cloud.bigquery.TableResult;
// Sample to query batch in a table
public class QueryBatch {
public static void main(String[] args) {
// TODO(developer): Replace these variables before running the sample.
String projectId = "MY_PROJECT_ID";
String datasetName = "MY_DATASET_NAME";
String tableName = "MY_TABLE_NAME";
String query =
"SELECT corpus"
+ " FROM `"
+ projectId
+ "."
+ datasetName
+ "."
+ tableName
+ " GROUP BY corpus;";
queryBatch(query);
}
public static void queryBatch(String query) {
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(query)
// Run at batch priority, which won't count toward concurrent rate limit.
.setPriority(QueryJobConfiguration.Priority.BATCH)
.build();
TableResult results = bigquery.query(queryConfig);
results
.iterateAll()
.forEach(row -> row.forEach(val -> System.out.printf("%s,", val.toString())));
System.out.println("Query batch performed successfully.");
} catch (BigQueryException | InterruptedException e) {
System.out.println("Query batch not performed \n" + e.toString());
}
}
}
Node.js
在尝试此示例之前,请按照《BigQuery 快速入门:使用客户端库》中的 Node.js 设置说明进行操作。如需了解详情,请参阅 BigQuery Node.js API 参考文档。
// Import the Google Cloud client library and create a client
const {BigQuery} = require('@google-cloud/bigquery');
const bigquery = new BigQuery();
async function queryBatch() {
// Runs a query at batch priority.
// Create query job configuration. For all options, see
// https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#jobconfigurationquery
const queryJobConfig = {
query: `SELECT corpus
FROM \`bigquery-public-data.samples.shakespeare\`
LIMIT 10`,
useLegacySql: false,
priority: 'BATCH',
};
// Create job configuration. For all options, see
// https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#jobconfiguration
const jobConfig = {
// Specify a job configuration to set optional job resource properties.
configuration: {
query: queryJobConfig,
},
};
// Make API request.
const [job] = await bigquery.createJob(jobConfig);
const jobId = job.metadata.id;
const state = job.metadata.status.state;
console.log(`Job ${jobId} is currently in state ${state}`);
}
Python
在尝试此示例之前,请按照《BigQuery 快速入门:使用客户端库》中的 Python 设置说明进行操作。如需了解详情,请参阅 BigQuery Python API 参考文档。
from google.cloud import bigquery
# Construct a BigQuery client object.
client = bigquery.Client()
job_config = bigquery.QueryJobConfig(
# Run at batch priority, which won't count toward concurrent rate limit.
priority=bigquery.QueryPriority.BATCH
)
sql = """
SELECT corpus
FROM `bigquery-public-data.samples.shakespeare`
GROUP BY corpus;
"""
# Start the query, passing in the extra configuration.
query_job = client.query(sql, job_config=job_config) # Make an API request.
# Check on the progress by getting the job's updated state. Once the state
# is `DONE`, the results are ready.
query_job = client.get_job(
query_job.job_id, location=query_job.location
) # Make an API request.
print("Job {} is currently in state {}".format(query_job.job_id, query_job.state))