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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"
)
// createTableRangeParitioned demonstrates creating a table and specifying a
// range partitioning configuration.
func createTableRangePartitioned(projectID, datasetID, tableID string) error {
// projectID := "my-project-id"
// datasetID := "mydatasetid"
// tableID := "mytableid"
ctx := context.Background()
client, err := bigquery.NewClient(ctx, projectID)
if err != nil {
return fmt.Errorf("bigquery.NewClient: %v", err)
}
defer client.Close()
sampleSchema := bigquery.Schema{
{Name: "full_name", Type: bigquery.StringFieldType},
{Name: "city", Type: bigquery.StringFieldType},
{Name: "zipcode", Type: bigquery.IntegerFieldType},
}
metadata := &bigquery.TableMetadata{
RangePartitioning: &bigquery.RangePartitioning{
Field: "zipcode",
Range: &bigquery.RangePartitioningRange{
Start: 0,
End: 100000,
Interval: 10,
},
},
Schema: sampleSchema,
}
tableRef := client.Dataset(datasetID).Table(tableID)
if err := tableRef.Create(ctx, metadata); err != nil {
return 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.Field;
import com.google.cloud.bigquery.RangePartitioning;
import com.google.cloud.bigquery.Schema;
import com.google.cloud.bigquery.StandardSQLTypeName;
import com.google.cloud.bigquery.StandardTableDefinition;
import com.google.cloud.bigquery.TableId;
import com.google.cloud.bigquery.TableInfo;
// Sample to create a range partitioned table
public class CreateRangePartitionedTable {
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";
Schema schema =
Schema.of(
Field.of("integerField", StandardSQLTypeName.INT64),
Field.of("stringField", StandardSQLTypeName.STRING),
Field.of("booleanField", StandardSQLTypeName.BOOL),
Field.of("dateField", StandardSQLTypeName.DATE));
createRangePartitionedTable(datasetName, tableName, schema);
}
public static void createRangePartitionedTable(
String datasetName, String tableName, Schema schema) {
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);
// Note: The field must be a top- level, NULLABLE/REQUIRED field.
// The only supported type is INTEGER/INT64
RangePartitioning partitioning =
RangePartitioning.newBuilder()
.setField("integerField")
.setRange(
RangePartitioning.Range.newBuilder()
.setStart(1L)
.setInterval(2L)
.setEnd(10L)
.build())
.build();
StandardTableDefinition tableDefinition =
StandardTableDefinition.newBuilder()
.setSchema(schema)
.setRangePartitioning(partitioning)
.build();
TableInfo tableInfo = TableInfo.newBuilder(tableId, tableDefinition).build();
bigquery.create(tableInfo);
System.out.println("Range partitioned table created successfully");
} catch (BigQueryException e) {
System.out.println("Range partitioned table 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
const {BigQuery} = require('@google-cloud/bigquery');
const bigquery = new BigQuery();
async function createTableRangePartitioned() {
// Creates a new integer range partitioned table named "my_table"
// in "my_dataset".
/**
* TODO(developer): Uncomment the following lines before running the sample.
*/
// const datasetId = "my_dataset";
// const tableId = "my_table";
const schema = [
{name: 'fullName', type: 'STRING'},
{name: 'city', type: 'STRING'},
{name: 'zipcode', type: 'INTEGER'},
];
// To use integer range partitioning, select a top-level REQUIRED or
// NULLABLE column with INTEGER / INT64 data type. Values that are
// outside of the range of the table will go into the UNPARTITIONED
// partition. Null values will be in the NULL partition.
const rangePartition = {
field: 'zipcode',
range: {
start: 0,
end: 100000,
interval: 10,
},
};
// For all options, see https://cloud.google.com/bigquery/docs/reference/v2/tables#resource
const options = {
schema: schema,
rangePartitioning: rangePartition,
};
// Create a new table in the dataset
const [table] = await bigquery
.dataset(datasetId)
.createTable(tableId, options);
console.log(`Table ${table.id} created with integer range partitioning: `);
console.log(table.metadata.rangePartitioning);
}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"
schema = [
bigquery.SchemaField("full_name", "STRING"),
bigquery.SchemaField("city", "STRING"),
bigquery.SchemaField("zipcode", "INTEGER"),
]
table = bigquery.Table(table_id, schema=schema)
table.range_partitioning = bigquery.RangePartitioning(
# To use integer range partitioning, select a top-level REQUIRED /
# NULLABLE column with INTEGER / INT64 data type.
field="zipcode",
range_=bigquery.PartitionRange(start=0, end=100000, interval=10),
)
table = client.create_table(table) # Make an API request.
print(
"Created table {}.{}.{}".format(table.project, table.dataset_id, table.table_id)
)다음 단계
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